A Framework for Stacked-Benefit Analysis of Distribution-Level Energy Storage Deployment

Transcription

1 inventions Article A Framework Stacked-Benefit Analysis Distribution-Level Energy Srage Deployment Anamika Dubey 1, *, Pisitpol Chirapongsananurak 2 Surya Sanso 3 1 School Electrical Engineering Computer Science, Washingn State University, Pullman, WA 99163, USA 2 Department Electrical Engineering, Chulalongkorn University, Bangkok 10330, Thail; pisitpol.c@chula.ac.th 3 Department Electrical Computer Engineering, The University Texas at Austin, Austin, TX 78712, USA; ssanso@mail.utexas.edu * Correspondence: anamika.dubey@wsu.edu; Tel.: Academic Edir: Josep M. Guerrero Received: 25 February 2017; Accepted: 23 March 2017; Published: 28 March 2017 Abstract: This paper presents a planning framework integrating energy srage () systems in distribution system. An system is deployed simultaneously provide multiple benefits, also known as stacked-benefits, feeder. The primary secondary application scenarios feeder are identified. The proposed deployment approach includes following steps: (1) size system primary application; (2) identify optimal locations based on both primary secondary application scenarios; (3) calculate accommodation capacity each potential location; (4) develop control methods units conduct grid impact analysis demonstrate applications. For selected feeder, primary application deployment is provide N-1 contingency requirement. During normal operating conditions, is programmed multiple secondary applications: voltage management ancillary services by frequency regulation. A probabilistic approach is presented obtain optimal size providing N-1 contingency requirement. Optimal locations are obtained based on secondary application scenarios. Real reactive power control methods are developed demonstrate viability deploying an system simultaneously providing multiple applications. The simulation results show that can successfully provide stacked-benefits distribution circuit. The proposed framework is generic can be employed integration analysis any feeder, with different sets primary secondary applications. Keywords: smart grid; power distribution system; distributed energy resources (DERs); energy srage (); phovoltaic system (PV) 1. Introduction With advances in smart-grid technologies integration distributed energy resources (DERs), electric distribution system has been changing rapidly [1 5]. These infrastructural changes pose multiple challenges electric distribution service providers. The inherent variability renewable generation vulnerability traditional power systems dem load schasticity, can potentially result in poor service reliability quality [6 9]. Energy srage () systems have been identified as a potential solution maintain strict power quality reliability stards, by both utilities researchers [10 12]. Including technology in distribution plans can enable utilities, system operars, end users increase power reliability reduce cost electricity [12 14]. Additionally, systems aid distribution grid flexibility, as y can help integrate variable generation resources such as wind solar [15 18]. Given various applications systems, Inventions 2017, 2, 6; doi: /inventions

2 Inventions 2017, 2, a distribution system planning framework is called that incorporates potential impacts benefits deployments. Several studies have assessed values integrating systems in distribution circuits. To reduce impacts renewable energy resources, has been used multiple grid support applications, such as load management, voltage regulation, frequency support [15 18]. References [18 20] describe benefit in providing a phovoltaic (PV) smoothing service by reducing PV generation variability. can also be employed provide peak load shaving [21] support grid during outages [22]. According [18,21,23], is efficient at providing voltage regulation in distribution circuits with a high penetration PV. The application in providing frequency regulation is presented in [18,24,25]. So far, however, se technical studies have not quantified benefits deployment in simultaneously providing multiple grid benefits. With ongoing efts make systems cost-competitive [26] an increasing number successful demonstration studies [27], a systematic approach evaluate grid impacts benefits systems is called. Grid integration ols should be able identify suitable applications, sizes, deployment locations, by using domain-specific knowledge. The objective this study is develop a systematic approach integrating an system in a given distribution grid. This paper presents an approach deploy an system, provide multiple grid benefits, also termed stacked-benefits, feeder. The optimal size locations are obtained based on stacked-benefit application scenario distribution system grid impact analysis. This paper also shows that can simultaneously provide multiple benefits distribution feeder. For this study, system is expected provide following stacked benefits: (1) primary application N-1 contingency requirements; (2) secondary applications voltage management frequency support applications. Note that, although proposed framework is applicable any technology capable providing active reactive power support, presented framework mostly focusses on battery systems Distribution-Level Energy Srage Deployment A brief review use cases distribution-level deployment is presented in this section. Broadly, systems can be deployed provide system-level benefits cusmer-level benefits. When deployed system-level benefits, systems are programmed provide operational benefits utility companies in m grid services. When deployed cusmer-level benefits, systems are programmed meet specific service quality reliability requirements individual cusmers System-Level Benefits Defer Distribution System Upgrades With an increase in yearly peak load dem, substation distribution lines may require expensive upgrades. If cost-benefits analysis allows, an system may be deployed decrease peak load dem defer any immediate distribution system upgrades. Support DER Integration As stated previously, integrating a large percentage DERs can result in multiple grid issues requiring grid upgrades. has been shown be beneficial in mitigating impacts DERs by supporting applications such as load shifting mitigate f-peak generation, voltage management mitigate overvoltage concerns, voltage control mitigate DER variability. Support Energy Arbitrage/Electricity Price Shift can help distribution utilities in decreasing yearly cost electricity by participating in electricity market. can be programmed charge discharge as electricity rates fluctuate, thus decreasing yearly electricity costs. Provide Ancillary Services can be programmed provide ancillary services frequency regulation based on feeder s open access transmission tariff.

3 Inventions 2017, 2, Cusmer-Level Benefits Voltage Management Traditionally, voltage management is pursued using load-tap changers capacir banks. For a feeder with high DER penetrations, voltage management will require new methods using faster voltage control devices. In such cases, inverters can provide voltage regulation services mitigate overvoltage voltage variation concerns. Provide Reliability Benefits When deployed providing reliability benefits, will discharge support connected loads during an outage, thus decreasing both Cusmer Average Interruption Frequency Index (CAIFI) Cusmer Average Interruption Duration Index (CAIDI). Dem Charge Management The dem charge is a billing mechanism used recover cost providing a transmission distribution service commercial cusmers. The dem charge a month is calculated based on largest peak dem recorded over month. systems are deployed decrease monthly peak load dem decrease tal cusmer dem charge Objectives Assumptions The objective this paper is present a systematic approach planning deployment units a distribution system. For deployment be economical, should be integrated provide multiple grid benefits, also known as stacked benefits. Depending upon feeder, planner first needs identify primary or secondary benefits deployment. The primary application is one that is eir most critical or will generate most revenue distribution system. The secondary applications correspond additional grid benefits that can provide, in addition primary application. Multiple secondary benefits should be identified, depending upon feeder use case. Next, a systematic approach should be developed evaluate efficacy deployment in providing multiple/stacked grid services. In this paper, we present a step-by-step approach integration analysis, starting with assessment requirements grid, method used calculate system size, identification optimal locations while accounting grid impacts deployment, finally, verification benefits through simulation. We identify three important aspects deployment: (1) deployment should be economical; (2) deployment should not result in any operational concern grid; (3) must provide intended grid benefits. In this regard, we demonstrate a stacked application case deployment. The is sized primary application scenario. To ensure that deployment does not cause additional operational concerns, largest allowable limits capacity each potential location are determined. Next, a grid impact analysis is completed verify demonstrate that an can provide intended grid benefits. In this study, system is sized deployed following stacked benefit application scenario: (1) Primary application provide N-1 contingency substation transmer; (2) Secondary applications frequency regulation voltage management services. The distribution circuit selected this analysis is adapted from EPRI s 34.5-kV test circuit [26]. We also include data modeling requirement enable proposed integration analysis framework (see Section 2). The proposed framework integration analysis is detailed in Section 3, followed by verification method results in Section 4. Finally, conclusions are presented Section Contributions This paper provides a systematic approach evaluating grid impacts benefits deployment a multiple/stacked application scenario. The system is planned simultaneously provide multiple grid benefits. A primary grid benefit, potentially most critical application, is identified. The is programmed provide secondary benefits, when not required primary application. We develop a control method program system voltage management

4 Inventions 2017, 2, frequency regulation support. Voltage management is achieved using Volt-VAR control, while frequency regulation is provided by charging discharging, based on frequency control signal. We also present an approach size, based on primary benefit i.e., N-1 contingency requirement using a percentile analysis. Next, optimal locations systems are identified, while including ir impacts on feeder. Finally, using simulations, we demonstrate proposed approach selected feeder. The purpose this paper is provide a methodology that can essentially help include in distribution planning framework. In this regard, proposed approach is generic applicable a different set primary secondary application cases. We also provide details on data model requirements proposed study. Theree, proposed framework can be easily used by utility providers assess applicability deployment ir feeder. 2. Analysis Tools Test Circuit The analysis ols test circuit used study are detailed in this section. We simulate proposed integration framework using OpenDSS [28] MATLAB. The analysis is conducted using a test circuit adapted from a 34.5-kV EPRI test feeder [29] available from an open-source distribution system analysis Analysis Tools The proposed application framework requires a detailed distribution system feeder model an interface simulate analyze multiple case studies. This paper uses OpenDSS, an open-source distribution system simular, simulate distribution circuit model [28]. We have used MATLAB as an interface OpenDSS, conveniently simulate multiple case studies, project load generation scenarios. A detailed feeder model starting from substation down individual cusmer locations is simulated in OpenDSS. Additionally, representative models cusmer loads are also developed using substation load data cusmer load characteristics. The units are modeled using equipment model available in OpenDSS Distribution Circuit Simular OpenDSS OpenDSS [28] is a comprehensive electrical system simulation ol electric utility distribution systems, supporting all frequency domain analyses. It supports quasi-static unbalanced three-phase power flow analysis radial looped networks, while including user-defined control algorithms shunt capacirs, voltage regulars, on-load tap changers, smart-inverters. The simular also facilitates DER integration analysis provides pre-defined models DERs ir control blocks. OpenDSS can be implemented as both a st-alone executable program an in-process Component Object Model (COM) server DLL, designed be driven by a variety existing stware platms. In this study, OpenDSS is executed using MATLAB program Energy Srage Model The srage element is modeled as a generar is dispatched eir generate power by discharging, or consume power by charging, within its power rating its sred energy capacity. In OpenDSS, is modeled as a generar (Figure 1). The srage element can also produce or absorb reactive power within kva rating its inverter. The model supports power flow analysis in multiple time-scales, including Snapshot, Daily, Yearly, Duty cycle modes [28]. In addition equipment model solution interfaces, OpenDSS also provides several control models systems. The control modes are required simulating cases demonstrate that utility is providing grid benefits.

5 Inventions 2017, 2, Inventions 2017, 2, Figure Figure Simplified Simplified block block diagram diagram OpenDSS OpenDSS model model an an system system [28]. [28] Required Circuit Data Required Circuit Data The data requirement proposed analysis framework is detailed in this section. Note that The data requirement proposed analysis framework is detailed in this section. Note that a a detailed feeder model, including circuit data, load data, DER data, is required conduct a detailed feeder model, including circuit data, load data, DER data, is required conduct a realistic realistic distribution planning analysis (see Table 1). There are three categories required data: distribution planning analysis (see Table 1). There are three categories required data: Circuit data Includes one-line diagram feeder, substation model, distribution line characteristics Circuit data Includes including impedance, one-line diagram ampacity, voltage feeder, levels, substation connections, model, distribution details line regarding characteristics distribution including transmers impedance, ampacity, capacir voltage banks. levels, connections, details Load regarding data Includes distribution transmers hourly load dem capacir data banks. measured at substation one year or more, Load as data Includes well as characteristics hourly load individual dem data cusmer measured loads at distributed substation across one feeder. year or DER more, data Details as well as characteristics existing future individual DER integration cusmeris loads required distributed across planning analysis. feeder. For DERexample, data Details existing existing PV systems, future necessary DER integration data include is required PV panels location, planningsize, analysis. characteristics. For example, Additionally, existing PVhigh-resolution systems, necessary data (typically data include 1 s) on PV PV panels generation location, an size, entire year characteristics. a few selected Additionally, representative high-resolution days should data (typically be provided. 1 s) on PV generation an entire year a few selected representative days should be provided. Table 1. Required circuit data integration analysis. Table 1. Required circuit Circuit datadata integration analysis. Line line voltage (kv) at source bus, short-circuit MVA at high-side bus Source each substation Circuit Data (three-phase line-ground) Transmer connections, Line line voltage high- (kv) at low-side source bus, voltages, short-circuit transmer MVA at high-side size, X/R bus ratio, each Source Substation leakage impedance (% on substation substation MVA), (three-phase substation line-ground) bus configuration number Transmer feeders served connections, from high- each bus, low-side substation voltages, LTC transmer regular size, X/R settings ratio, Substation leakage impedance (% on substation MVA), substation bus configuration number Bus connections, conducr size, type, length, construction, Distribution lines feeders served from each bus, substation LTC or regular settings Bus emergency connections, ampacity, conducr size, phase type, length, sequence construction, impedance emergency ampacity, phase Distribution lines Distribution Primary secondary buses connected sequence transmer, impedance transmer MVA rating, transmer high Primary low-side secondary voltages, buses size connected (kva), X/R ratio, transmer, leakage transmer impedance MVA rating, Distribution transmer high low-side voltages, size (kva), X/R ratio, leakage impedance Bus connection connection type, size, control mechanism Capacir banks Bus connection connection type, size, control mechanism (fixed, voltage, current, kvar, Capacir banks (fixed, voltage, current, kvar, time, etc.), control settings (on/f settings) time, etc.), control settings (on/f settings) Load Data Load Data 1-year data with appropriate granularity (at least in hourly intervals) real energy Metered Load 1-year data with appropriate granularity (at least in hourly intervals) real energy (MWh) Metered Load Data at Substation (MWh) reactive reactive energy (Mvarh) in in out out substation, substation, real (MW) real reactive (MW) (Mvar) Data at Substation reactive (Mvar) power dem at at substation. Rated load dem Rated loadat dem individual at individual cusmer cusmer locations (kw, power facr, allocation facr), Cusmer Loads load duration curves (15-min interval) aggregated circuit individual Cusmer Loads facr), load duration curves (15-min interval) aggregated circuit cusmers, if available. individual cusmers, if available. DER Data DER Data Existing DER locations size along feeder DER control mechanism. DER Existing DER generation locations data provided size along in 1 sec resolution feeder - DER entire control year or mechanism. longer (if available) DER or Existing DERs generation priles generation data generation provided priles in 1 representing sec resolution typical - days, example, entire year a clear or day, longer mild, (if moderate, available) generation high variability, an overcast day should be provided. or generation priles representing typical days, example, a clear day, mild, priles moderate, high variability, an overcast day should be provided.

6 Inventions 2017, 2, Inventions 2017, 2, Selected Distribution Circuit Inventions 2.2. Selected 2017, Distribution 2, 6 Circuit 6 20 The one-line diagram test circuit is shown in Figure 2. In this study, we simulate two identical The substation one-line transmers diagram supplying test circuit two is shown distribution in Figure feeders 2. In this with study, identical we simulate load dem two 2.2. Selected Distribution Circuit characteristics identical substation peaktransmers load dems. supplying Note two that distribution under feeders N-1with contingency identical load case, dem one transmers characteristics The one-line out--service diagram peak load dems. test circuit or Note is shown transmer that under in Figure supplies N-1 2. In contingency this study, we both feeders. case, simulate The one distribution two identical transmers substation is out--service transmers supplying or two transmer distribution supplies feeders both with feeders. identical The load distribution dem feeder supplied by Transmer T1, i.e., Feeder 1, is adapted from 34.5-kV EPRI test feeder [29]. characteristics feeder supplied by Transmer peak load dems. T1, i.e., Feeder Note 1, that is adapted under from N-1 contingency 34.5-kV EPRI case, test feeder one [29]. The feeder transmers supplied by Transmer T2 is represented as an equivalent load with an identical load The feeder supplied is out--service by Transmer T2 or is represented transmer as an supplies equivalent both load feeders. with The an identical distribution load prile feeder prile load supplied load dem by dem Transmer characteristics characteristics T1, i.e., as as Feeder Feeder 1, is Both Both adapted substation substation from transmers transmers 34.5-kV EPRI are are test rated rated feeder as having as[29]. having a normal The a normal MVA feeder rating MVA supplied rating 45by MVA Transmer 45 MVA emergency T2 emergency is represented rating rating 75 as MVA. an 75 equivalent MVA. The three-phase The load three-phase with short-circuit an identical short-circuit load capacity at prile capacity secondary at load secondary eir dem substation characteristics eir substation transmer as Feeder transmer is Both MVA. substation is 422 MVA. transmers are rated as having a normal MVA rating 45 MVA emergency rating 75 MVA. The three-phase short-circuit capacity at secondary eir substation transmer is 422 MVA. Figure 2. One line diagram substation configuration. Figure 2. One line diagram substation configuration. The one-line diagram Figure Feeder 2. One line 1 is diagram shown in Figure substation 3 [30]. configuration. In Figure 3, colors represent The distance one-line diagram feeder from Feeder substation. 1 is shown The indistance Figure(in 3 [30]. km) associated In Figure 3, with each colors color represent is also distance shown The in one-line feeder figure. diagram fromthe detailed substation. Feeder circuit 1 is The shown characteristics distance in Figure (in km) 3 [30]. Feeder associated In Figure 1, including 3, with each colors bus color represent connections, is also shown in distance primary-feeder figure. The detailed feeder characteristics, circuit from characteristics substation. service transmer The distance Feeder data, 1, (in including km) secondary-feeder associated bus connections, with characteristics, each color primary-feeder also shown cusmer in load figure. data, are The available. detailed Also, circuit yearly characteristics load prile measured Feeder 1, at including substation bus connections, characteristics, service transmer data, secondary-feeder characteristics, cusmer transmer load data, are primary-feeder is available one characteristics, year, at a 1-h service resolution. transmer This circuit data, has three secondary-feeder capacirs 0.9, characteristics, Mvar. available. Also, yearly load prile measured at substation transmer is available one year, cusmer These capacirs load data, are are fixed available. always Also, online. yearly The load substation prile transmer measured at is equipped substation with transmer a load tap at a 1-h resolution. This circuit has three capacirs 0.9, Mvar. These capacirs are fixed is changer available (LTC). one Five year, PV at systems a 1-h resolution. are installed This at circuit a 34.5 has kv three voltage capacirs level Feeder 0.9, Each 1.2 Mvar. PV is always These online. The substation transmer is equipped with a load tap changer (LTC). Five PV connected capacirs are feeder fixed via a 1.2-MVA always online. 34.5/0.48-kV The substation service transmer is equipped has a capacity with a load 1 MW, tap systems changer with are a tal installed (LTC). installed Five at acapacity PV 34.5 systems kv voltage 5 are MW. installed level at Feeder a 34.5 kv 1. Each voltage PVlevel is connected Feeder 1. Each feeder PV is via a 1.2-MVA connected 34.5/0.48-kV feeder service via a transmer 1.2-MVA 34.5/0.48-kV has aservice capacity transmer 1 MW, with has aa tal capacity installed 1 MW, capacity 5 MW. with a tal installed capacity 5 MW. Figure 3. Detailed one-line diagram Feeder 1. Figure 3. Detailed one-line diagram Feeder 1. Figure 3. Detailed one-line diagram Feeder 1.

7 Inventions 2017, 2, Inventions 2017, 2, Using available load dem data circuit characteristics, a power flow analysis is conducted Using one available year. load The dem load dem data recorded circuitat characteristics, secondary a power one flow substation analysis is transmers conducted one year. given Theyear, loadis dem shown recorded in Figure at 4. Note secondary that recorded one load substation dem transmers does not take PV given generation year, is in shown account. in Figure The peak 4. Note load that dem recorded when load existing dem PV does systems not are takenot PV generating generation in account. given year Theis peak equal load dem MVA. when The peak existing load dem PV systems without are PV notgeneration generating is reported, givenbecause year is equal PV is a variable MVA. The peak uncertain load dem resource without should PV generation not be included is reported, contingency because PV is peak a variable load management uncertain analysis. resource The PV should prile not be impacts included will be contingency included when studying peak loadvoltage management support analysis. frequency The PV prile regulation impacts applications. will be In included this study, when studying primary voltage application support i.e., frequency meet regulation N-1 contingency applications. criteria, In this planned study, a primary duration application five years, i.e., starting meet from N-1 contingency base year criteria, (Year 1). A is load planned growth arate duration 1% per five year years, is assumed starting from project base yearly (Year load 1). dem A load growth rate next five 1% years. per year is assumed project yearly load dem next five years. Substation Load Dem (MW) Figure 4. Yearly load dem recorded at secondary one substation transmers Figure 4. Yearly load dem recorded at secondary one substation transmers base year Year (PV systems are assumed be not generating). base year Year 1 (PV systems are assumed be not generating). 3. Proposed Analysis Framework 3. Proposed Analysis Framework In this paper, we present a planning approach stacked benefits application an In this paper, we present a planning approach stacked benefits application an simultaneously providing: N-1 contingency, voltage management, frequency regulation services. simultaneously providing: N-1 contingency, voltage management, frequency regulation services. The primary application is providing N-1 contingency support. Theree, when feeder The primary application is providing N-1 contingency support. Theree, when feeder requires contingency support, 100% is deployed mitigate substation transmer requires contingency support, 100% is deployed mitigate substation transmer overloading. When contingency support is not required, is committed providing secondary overloading. When contingency support is not required, is committed providing secondary benefits, i.e., voltage support frequency regulation. The energy srage commitment both benefits, i.e., voltage support frequency regulation. The energy srage commitment both voltage management frequency regulation support is assumed be 50%. voltage management frequency regulation support is assumed be 50% Define/Identify Define/Identify Application Application Scenario Scenario In In this this section, section, details details both both primary primary secondary secondary application application cases cases are are presented, presented, along along with with an an control control scheme scheme used used provide provide stacked stacked grid grid benefits. benefits Primary Application Scenario N-1 Contingency The systemis is primarily deployed provide N-1 contingency requirement substation transmer. The one-line diagram distribution circuit under analysisis is shownin in Figure2. 2. Two identical transmers witha a nominal rating MVA an an emergency rating MVA are connected substation. Each transmer serves a distribution feeder with a peak load dem MW, measured during base year (Year 1). It Itis is assumed that, under normal conditions, both transmers are in service. The N-1 contingency condition is is simulated by by applying a a fault fault at at secondary transmer T1. T1. In this In this case, case, or or transmer, transmer, T2, ist2, required is required serve serve both feeders both feeders (see Figure (see Figure 5). Based 5). Based on on peak load peak dems load dems both feeders, both feeders, worst-case worst-case dem dem transmer transmer T2 during T2 during base year base is year MW. is The MW. N-1The contingency N-1 contingency requirement requirement is not satisfied not satisfied base year, base year, worst-case worst-case load dem load dem exceeds exceeds transmer s transmer s emergency emergency rating. rating.

8 Inventions 2017, 2, Inventions 2017, 2, Figure 5. Simulated N-1 contingency case. Figure 5. Simulated N-1 contingency case. The following assumptions are made deployment provide N-1 contingency support: The following assumptions are made deployment provide N-1 contingency support: 1. The is planned five years, since N-1 contingency requirement is not met The The isyearly planned load prile fiveat years, a 1-h since resolution N-1 is available contingency requirement base year. A is 1% not load met. growth per 2. The yearly is assumed load prile project at a 1-h yearly resolution load dem is available future base years. year. A 1% load growth per 3. yearthe is assumed system size project is determined yearlybased loadon dem a percentile analysis futureon years. five-year load dem 3. The data, system including size available is determined measurements based on a percentile base year analysis projected on five-year measurements load dem data, future years. including available measurements base year projected measurements future years Secondary Application Scenarios Voltage Management Frequency Regulation Secondary Application Scenarios Voltage Management Frequency Regulation As mentioned bee, in this study is deployed provide following secondary As benefits: mentioned (1) voltage bee, management; in this study (2) frequency is deployed regulation provide or ancillary following services by secondary participating benefits: (1) voltage in management; ISO market. An (2) participates frequencyin regulation ancillary service/frequency or ancillary services regulation by participating by generating or ISO market. absorbing An real participates power based in ancillary on frequency service/frequency regulation signal regulation [31]. Voltage by generating management oris absorbing achieved real power using based Volt-VAR on frequency control regulation smart inverter signal connected [31]. Voltage management system. Since is achieved feeder using contains Volt-VAR control PV systems, smart inverter is deployed connected mitigate voltage system. variations Since resulting feeder from contains PV variability. PV systems, Note that is deployed feeder voltages mitigatewill voltage also fluctuate variations due resulting participation from PV variability. system Notein that providing feeder ancillary voltages will also services. fluctuate Thus, due needs participation mitigate voltage variation system due in providing both PV variability ancillary services. Thus, charge/discharge frequency regulation schedule. The system is committed providing 50% needs mitigate voltage variation due both PV variability charge/discharge voltage support anor 50% frequency regulation service. frequency regulation schedule. The system is committed providing 50% voltage support anor Voltage 50% Management frequency regulation service. Voltage Management For voltage management service, control objective is mitigate voltage variations due both PV variability charge/discharge frequency regulation schedule. The feeder For voltages voltage can be regulated management using service, real reactive control power objective control, is although mitigate a reactive voltage power variations control due both mode PV may variability incur an additional charge/discharge cost smart inverter. frequency Additionally, regulationthis schedule. control The method, feeder unlike voltages can be real regulated power control, using real does not reactive deteriorate power battery control, life-cycle. althoughalso, a reactive when it power is in reactive control power mode may incurcontrol an additional mode, cost is not generating smarr inverter. absorbing Additionally, any real power, this so control it need not method, be oversized unlike real meet power control, multiple does not objectives. deteriorate battery life-cycle. Also, when it is in reactive power control mode, In this paper, reactive power control mode is implemented voltage management. The is not generating or absorbing any real power, so it need not be oversized meet multiple objectives. inverter is controlled generate or absorb reactive power, mitigate voltage variations In this paper, reactive power control mode is implemented voltage management. due both PV variability charge/discharge frequency regulation schedule. The reactive The inverter power supplied is or controlled consumed by generate inverter or absorb is calculated reactive from both power, change mitigate in PV generation voltage variations due change both in PVcharge/discharge variability (1). charge/discharge frequency regulation schedule. The reactive power supplied or consumed by inverter R is calculated from both change in PV th generation change in charge/discharge Q PPV (1). P (1) X th Q = ( P PV + P ) R th X th (1) where, Q is change in reactive power supplied or absorbed by inverter, P PV is change in PV generation power, P is change in charge or discharge power in

9 There are two regulation signals calculated from area control error signal (ACE): RegA RegD. Both RegA RegD signals are in per-unit with 2-s resolution. RegA Signal: This signal is generated by passing ACE signal through a low pass filter. The RegA signal is used traditional regulating resources. Inventions 2017, RegD 2, 6Signal: This signal is generated by passing ACE signal through a high pass filter. The 9 20 RegD signal is used dynamic or fast response resources. response This paper frequency uses a regulation 2-s resolution schedule, RegD frequency R th is regulation real part signal short-circuit generated impedance one day, as at location, shown in Figure X th is 6b [32]. imaginary For frequency part regulation short-circuit service, impedance positive at value signal location. instructs Note that discharge (acting as a generar), while negative signal instructs charge (acting as P PV P are measured as difference between present PV real power, a load). The signal (in per unit) is multiplied by power rating commitment level min moving average PV real power, respectively. The PV generation follows (50%), obtain charge discharge schedule (in MW). Note that schedule is also solar a irradiance 2-sec resolution. prile The curve charge recorded on discharge a high schedule variability fluctuates day with over a one-second simulation resolution, period. This shown in Figure fluctuation 6a. results in variations in feeder voltages. Solar Irradiance (pu) Time (hour) (a) Frequency Regulation Signal (pu) Time (hour) (b) Figure 6. Assumptions analysis: (a) PV generation prile; (b) Frequency regulation signal. Figure 6. Assumptions analysis: (a) PV generation prile; (b) Frequency regulation signal Energy Srage Deployment Methodology Frequency Regulation The proposed deployment method is detailed in this section. First, energy srage size is For determined frequency based regulation N-1 contingency service, criteria. control It objective is assumed is that consume is deployed or produce provide real power N-1 participate contingency ancillary benefits service/frequency five years. A statistical regulation analysis in is ISOcompleted market. In this present paper, isprojected programmed charge load or dem discharge, data. according A 1% load growth frequency is assumed. regulation Based on signal statistical providedanalysis, by [32]. There typical are two regulation substation signals load calculated dem from overload area duration control are error obtained, signal which (ACE): are RegA used calculate RegD. Both RegA size. Next, best locations deploying along feeder are determined. Note that a few grid RegD signals are in per-unit with 2-s resolution. applications, example, voltage management reliability services, are sensitive RegA Signal: This signal is generated by passing ACE signal through a low pass filter. The RegA signal is used traditional regulating resources. RegD Signal: This signal is generated by passing ACE signal through a high pass filter. The RegD signal is used dynamic or fast response resources. This paper uses a 2-s resolution RegD frequency regulation signal generated one day, as shown in Figure 6b [32]. For frequency regulation service, positive value signal instructs discharge (acting as a generar), while negative signal instructs charge (acting as a load). The signal (in per unit) is multiplied by power rating commitment level (50%), obtain charge discharge schedule (in MW). Note that schedule is also a 2-sec resolution. The charge discharge schedule fluctuates over simulation period. This fluctuation results in variations in feeder voltages Energy Srage Deployment Methodology The proposed deployment method is detailed in this section. First, energy srage size is determined based on N-1 contingency criteria. It is assumed that is deployed provide N-1 contingency benefits five years. A statistical analysis is completed present projected load dem data. A 1% load growth is assumed. Based on statistical analysis, typical substation load dem overload duration are obtained, which are used calculate size. Next, best locations deploying along feeder are determined. Note that a few grid applications, example, voltage management reliability services, are sensitive deployment locations, while ors, including frequency regulation peak-load shaving, are not. Theree, in this paper,

10 Inventions 2017, 2, systems are collocated with PV systems feeder voltage management, mitigate impacts a variable PV generation prile. Since deployment should not result in any additional integrational challenges, accommodation limit is calculated at each PV location. Based on accommodation limit, is sized each location. Finally, a grid impact analysis is simulated verify demonstrate Inventions 2017, 2, that is successfully able provide intended grid benefits. deployment locations, while ors, including frequency regulation peak-load shaving, are not Calculate Theree, Energy in this Srage paper, Size systems are collocated with PV systems feeder voltage management, mitigate impacts a variable PV generation prile. Since deployment should not result in needs any additional be sized integrational challenges, power subsystem accommodation (MW) limit is energy calculated subsystem at each PV location. (MWh) ratings. The powerbased subsystem on accommodation rating defines limit, largest is sized capacity each location. that Finally, can supply. a grid impact The energy analysis is subsystem simulated verify demonstrate that is successfully able provide intended grid benefits. rating defines tal energy that an can provide without recharging. is sized meet N-1 contingency Calculate requirement Energy Srage asize duration five years, including base year, selected distribution system. The N-1 contingency requirement is satisfied if transmer can supply both needs be sized power subsystem (MW) energy subsystem (MWh) ratings. The feeders without power subsystem recordingrating anydefines overloading largest incapacity an emergency that can situation supply. The i.e., energy when subsystem or rating transmer is out--service. defines Given tal energy uncertainty that an can in provide loadwithout dem, recharging. sizing is sized worst meet case N-1 peak load dem recorded contingency over requirement five years a isduration not advisable. five years, In this including study, base year, size is determined selected using distribution system. The N-1 contingency requirement is satisfied if transmer can supply both a statistical analysis on five-year substation load dem data under an N-1 contingency scenario. feeders without recording any overloading in an emergency situation i.e., when or transmer The statistically out--service. representative Given peak uncertainty load dem in load dem, energysizing supplied above worst case transmer s peak load rating are obtained dem usingrecorded a percentile over five analysis years on not advisable. base In this projected study, year size load is determined dem data. using The a energy srage is sized statistical analysis typical on five-year peak load substation (MW) load dem typical data under energy an N-1 supplied contingency above scenario. transmer s The statistically representative peak load dem energy supplied above transmer s rating are emergency rating (MWh). obtained using a percentile analysis on base projected year load dem data. The energy srage is sized typical peak load (MW) typical energy supplied above Percentile transmer s Analysis onemergency Load Data rating (MWh). The yearly Percentile load Analysis dem on Load is available Data base year at an hourly interval. The base year load dem is projected next four years, assuming a load growth 1% per year. This results in a The yearly load dem is available base year at an hourly interval. The base year load tal 43,800 dem data is projected points, with 8760 next four each years, year. assuming A percentile a load growth analysis 1% per is completed year. This results in a obtained data set. Figure tal 743,800 shows data points, percentile with 8760 plot each year. A five-year percentile load analysis dem is completed data. Here, obtained load dem corresponding data set. Figure x7 percentile, shows percentile say P x plot, means that five-year x% load hourly dem load data. Here, dems load will dem fall below P x. corresponding x percentile, say Px, means that x% hourly load dems will fall below Px. By this definition, 98% load dem, recorded projected over five-years, will fall below By this definition, 98% load dem, recorded projected over five-years, will fall below 98-percentile 98-percentile load dem load value. dem value. Net Load Dem Feeder 1 + Feeder 2 (MW) Figure 7. Percentage prile five-year load data. Figure 7. Percentage prile obtained five-year load data. Since needs be sized cases substation overloading, a percentile analysis is only Sincecompleted needs those be sized hours when cases load dem substation is greater overloading, than substation a percentile transmer analysis rating is only (see Figure 8). In Figure 8, load dem ( ) corresponding -percentile denotes that, if a completed those hours when load dem is greater than substation transmer rating transmer overloading is recorded, it will be less than, with a % probability. Theree, (see Figureload 8). dem In Figure corresponding 8, load dem 95th-percentile (P x ) corresponding ( = MW) indicates x-percentile that transmer denotes that, if a transmer overloading is recorded, it will be less than P x, with a x% probability. Theree, load dem corresponding 95th-percentile (P 95 = MW) indicates that transmer overloading recorded (in five years) will be less than MW, with a 0.95 probability. Note that representative peak load dem decreases significantly in 75th-percentile, MW.

11 Inventions 2017, 2, Inventions overloading 2017, 2, 6 recorded (in five years) will be less than MW, with a 0.95 probability. Note that Inventions 2017, 2, representative peak load dem decreases significantly in 75th-percentile, MW. overloading recorded (in five years) will be less than MW, with a 0.95 probability. Note that representative peak load dem decreases significantly in 75th-percentile, Percentile Peak MW. Load (MW) Percentile 100 Peak Load 99 (MW) (median) Figure 8. Percentile prile overload dem (dem > 75 MW) selected 75 percentile values Figure 8. Percentile prile overload dem (dem > 75 MW) 50 (median) selected percentile values. Figure A similar 8. Percentile analysis prile is conducted overload dem MWh served (dem above > 75 MW) transmer s selected percentile emergency values. rating (75 A similar MVA) over analysis span is conducted five years. The percentile MWh served plot above representative transmer s percentile emergency MWh above rating (75 MVA) transmer A over similar analysis span rating are is five conducted shown years. in The Figure percentile 9. MWh The served 75th-percentile plot above representative value transmer s percentile MWh emergency served MWh above rating above transmer rating implies that, under N-1 contingency, transmer will be serving an overload transmer (75 MVA) rating over arespan shown five in Figure years. The 9. The percentile 75th-percentile plot representative value percentile MWh served MWh above energy transmer less than or rating equal are shown MWh, in Figure with 9. a probability The 75th-percentile 0.75 in value five-year planning MWh served period. above transmer rating implies that, under N-1 contingency, transmer will be serving an overload transmer rating implies that, under N-1 contingency, transmer will be serving an overload energy less 140 than or equal MWh, with a probability 0.75 in five-year MWh Served planning above period. energy less than or equal MWh, with a probability 0.75 in Percentile five-year planning period. 120 Transmer Rating Significant decrease from 100 MWh Served above percentile Percentile Transmer Rating 100 Significant decrease from percentile Percentile Figure 0 9. Percentile prile energy dem above transmer rating selected percentile values Load Dem Load above Dem transmer above transmer rating (MW) rating (MW) Energy served Energy above served transmer above rating transmer (MWh) rating (MWh) Percentile Energy Figure 9. Srage Percentile Size prile energy dem above transmer rating selected percentile values. Figure 9. Percentile prile energy dem above transmer rating selected percentile The values. size both MW MWh ratings are determined based on results obtained from Energy Srage percentile Size analysis five-year load dem data. For worst-case scenario avoid any capacity violation, rating should be at least equal maximum load dem Energy Srage The Size size both MW MWh ratings are determined based on results obtained from maximum percentile energy analysis supplied above five-year substation load dem transmer data. For rating worst-case in five-year scenario planning period avoid The any i.e., size capacity 100th both violation, percentile MW value. MWh rating Instead ratings should are be worst-case at determined least equal rating, based however, on maximum results a representative load obtained dem from percentile rating maximum is selected, analysis energy based supplied on five-year statistical above load analysis dem substation data. transmer load Fordem worst-case rating prile. in scenario five-year planning avoid any capacity period violation, The i.e., required 100th MW percentile rating capacity should value. beinstead at is least determined equal worst-case by subtracting maximum rating, however, load substation dem a representative transmer maximum emergency rating (75 MVA) from percentile overload dem. The MW capacity obtained energy rating supplied is selected, above based substation statistical transmer analysis rating load in dem five-year prile. planning period i.e., 100th meet The a few required percentile MW overloading capacity conditions is determined are shown in by Table subtracting 2. Similarly, substation MWh rating transmer percentile value. Instead worst-case rating, however, a representative rating is selected, based is emergency obtained using rating (75 percentile MVA) from analysis percentile results on overload MWh supplied dem. above The MW transmer capacity obtained rating. The on MWh statistical ratings analysis meet a few percentile, corresponding load dem overloading conditions several prile. percentiles, are shown in are Table shown 2. Similarly, in Table 2. The MWh capacity rating (both MW The is obtained required MWh) MW using decreases capacity percentile significantly analysis from is determined results on 100th-percentile by subtracting MWh supplied above 75th-percentile. substation transmer When transmer rating. sizing The emergency MWh ratings rating 75th-percentile (75, MVA) corresponding value, from under percentile several worst-case percentiles, overload scenario, are dem. shown re in is The Table a probability MW The capacity capacity that obtained (both meetwill MW a few be unable percentile MWh) decreases mitigate overloadinga significantly transmer conditions overload. from are shown 100th-percentile The 0.25 inprobability Table 2. Similarly, 75th-percentile. not meeting MWh When contingency rating sizing is obtained requirement using 75th-percentile occurs when value, analysis transmer under results overloading worst-case on MWh supplied scenario, occurs with above re a probability is a 0.25 transmer probability 1. To rating. realistically that The MWh ratings estimate will be, unable corresponding risk mitigate a five-year transmer severalplanning percentiles, overload. horizon, The are 0.25 shown probability in Table 2. not The observing meeting capacity a contingency transmer (both MW MWh) overload requirement decreases should occurs significantly be when included from in transmer risk 100th-percentile calculation overloading (Table occurs 2). with For 75th-percentile. a probability given circuit, When 1. in To five sizing realistically years, an 75th-percentile estimate value, risk under five-year worst-case planning scenario, horizon, re is aprobability 0.25 probability observing that a transmer will be unable overload should be included in risk calculation (Table 2). For given circuit, in five years, an mitigate a transmer overload. The 0.25 probability not meeting contingency requirement occurs when transmer overloading occurs with a probability 1. To realistically estimate risk five-year planning horizon, probability observing a transmer overload should be included in risk calculation (Table 2). For given circuit, in five years, an overloading under an N-1 contingency scenario was recorded a tal 641 h. Thus, probability overloading under an

12 Inventions 2017, 2, Inventions 2017, 2, N-1 contingency scenario is equal If is sized 75th-percentiles peak load, N-1 overloading under an N-1 contingency scenario was recorded a tal 641 h. Thus, contingency transmer will not be met with a probability p f ail = = , probability overloading under an N-1 contingency scenario is equal If is sized assuming that a failure in T1 is a certain event. The risk will furr decrease when including actual 75th-percentiles peak load, N-1 contingency transmer will not be met with a probability probability observing a failure substation transmer. = = , assuming that a failure in T1 is a certain event. The risk will furr decrease when including actual probability observing a failure substation transmer. Table 2. Percentile-based size (kw). In this study, 75th-percetile value is selected sizing energy srage unit. Based on Representative Size analysis, Probability that N-1 Contingency not Met (Assuming Percentile tal system deployed in feeder has a capacity 6 MW/30 MWh. Note that a riskaverse deployment may select size based on a 95th- or 97th-percentile calculation. However, MW MWh that Fault Happens with Probability 1) corresponding 100 size 11.73may not be viable deployment, given exorbitant 0 cost Table Percentile-based size (kw) Representative Size Probability that N-1 Contingency not Met (Assuming Percentile MW MWh that Fault Happens with 50 (median) Probability 1) In this study, 75th-percetile value is selected sizing energy srage unit. Based on analysis, tal system deployed in feeder has a capacity 6 MW/30 MWh. Note that a risk-averse deployment may select size based on a 95th- or 97th-percentile calculation. However, corresponding size may not be viable deployment, given exorbitant cost (median) Identify Energy Srage Location For N-1 Identify contingency Energy Srage support, Location system can be located anywhere, along eir distribution For feeders. N-1 contingency Similarly, support, frequency system regulation can be application, located anywhere, can be along deployed eir anywhere alongdistribution feederfeeders. dispatched Similarly, using frequency communication regulation application, network in response can be deployed frequency anywhere signal. However, along feeder location dispatched important using voltage communication management network application. in response In order frequency mitigate voltage signal. variations However, due PVlocation variability, is important must bevoltage locatedmanagement close application. PV systems. In Theree, order in this paper, mitigate is voltage integrated variations co-located due PV at variability, 480-V level must with be located each PV close system. PV Thesystems. circuit is supplied Theree, by a 1.2 in this MVA paper, 34.5/0.48 is integrated kv service transmer. co-located at The 480-V pology level with each secondary PV system. distribution The circuit at circuit is location supplied is by shown a 1.2 MVA in Figure 34.5/ kv The service tal transmer. capacity based The pology on N-1 contingency secondary analysis distribution circuit at location is shown in Figure 10. The tal capacity based on N-1 is 6 MW/30 MWh. This capacity is distributed at following five PV locations. Since all contingency analysis is 6 MW/30 MWh. This capacity is distributed at following five PV locations. PV systems are same capacity, we should ideally deploy a 1.2 MW/6 MWh system at each Since all PV systems are same capacity, we should ideally deploy a 1.2 MW/6 MWh location. system However, at each location. bee deploying However, bee at each deploying PV location, at each PV largest location, capacity largest that capacity can be integrated that at can selected be integrated locations need selected be locations calculated. need This be calculated. is called This is accommodation called accommodation capacity feeder capacity given feeder location. given location. Figure 10. Topology secondary distribution circuit at location. Figure 10. Topology secondary distribution circuit at location.

13 Inventions 2017, 2, Calculate Energy Srage Accommodation Limit may affect normal operating conditions test feeder. Theree, largest capacity that can be installed at selected location must be determined bee integrating in feeder. In this paper, obtained capacity is referred as accommodation capacity. Since one stacked-benefits is provide a voltage management service, voltage selected feeder must be kept within acceptable limit, i.e., between pu [33]. Hence, size must be less than largest capacity that can be installed without resulting in a steady-state voltage limit violation, overvoltage (V > 1.05 pu), or undervoltage (V < 0.95 pu), at bus connected system (480-V level). In order obtain capacity limit, this paper determines largest size resulting in an overvoltage ( capacity limit overvoltage condition) largest size resulting in an undervoltage ( capacity limit undervoltage condition), using a simulation approach permed in OpenDSS. For overvoltage case, analysis aims at determining largest generation without causing overvoltage at selected location. The simulation conditions assumed analysis are detailed as follows. The test feeder is assumed be operating at minimum load condition, thus resulting in a high voltage condition. The is set discharge at its full rated output (acting as a generar) with a unity power facr, thus, causing voltage rise. The power rating is increased from 0 5 MVA, at an increment 1 kva. Since is discharging, all PVs in circuit are assumed be not generating. The phase voltages at location (480-V level) are recorded each capacity (0 5 MVA). The accommodation capacity circuit at selected location overvoltage is equal minimum rating, resulting in a phase voltage greater than A similar simulation approach is used determine largest capacity, resulting in an undervoltage violation (V < 0.95 pu). The obtained capacity is referred as accommodation capacity undervoltage limit violation. The simulation conditions methodology are detailed as follows. For worst-case scenario, selected distribution circuit is assumed be operating at peak load condition is programmed charge. The power rating is increased from 0 10 MVA, with an increment 1 kva. Since is assumed be charging, all PVs are assumed be generating at ir rated power with a unity power facr. The phase voltages at location are recorded each capacity (0 10 MVA). The capacity limit undervoltage condition is equal minimum rating, resulting in a phase voltage less than 0.95 pu at each location. The phase voltages corresponding capacity one PV bus locations are shown in Figure 11. Based on results, overvoltage violation (V > 1.05 pu) is recorded when adding 3 MVA, while undervoltage violation (V < 0.95 pu) is recorded when adding 9.1 MVA. Thus, accommodation capacity overvoltage condition is 3 MVA, is 9.1 MVA undervoltage condition. Since integration must not cause eir overvoltage or undervoltage limit violations in circuit, overall capacity limit this circuit at selected location is equal 3 MVA ( lesser value). The same analysis is repeated each PV location, accommodation capacities are obtained (please see Table 3). Based on analysis, an system with a capacity 1.2 MW/6 MWh can be deployed at each PV location, amounting a tal capacity 6 MW/30 MWh.

14 Inventions 2017, 2, Inventions 2017, 2, Voltage (pu) Voltage (pu) (a) (b) Figure Figure accommodation accommodation limit limit obtained obtained (a) (a) overvoltage overvoltage concern; concern; (b) (b) undervoltage undervoltage concern. concern. Table 3. accommodation capacity at difference PV bus locations. Table 3. accommodation capacity at difference PV bus locations. Accommodation Capacity PV Location Accommodation Capacity PV Location Overvoltage Limit Undervoltage Limit Overvoltage Limit Undervoltage Limit PV PV PV PV PV 3 PV PV 4 PV PV PV Grid Grid Impact Impact Analysis Analysis The The final final task task is is conduct conduct a grid grid impact impact analysis analysis demonstrate demonstrate that that an an application application can can provide provide required required stacked-benefits. stacked-benefits. First, First, application application meeting meeting N-1 N-1 contingency contingency requirements requirements is is demonstrated. demonstrated. Since Since size size is is selected selected based based on on 75th 75th percentile percentile value value overload overload dem dem energy, energy, deployed deployed will will not not be be able able eliminate eliminate each each possible possible case case overloading overloading over over course course five five years. years. However, However, we we should should expect expect a decrease decrease in in overload overload dem dem overloading overloading duration duration after after deploying deploying system. system. Next, Next, application application in in meeting meeting secondary secondary grid grid benefits benefits i.e., i.e., voltage voltage management management frequency frequency regulation, regulation, are are discussed. discussed. 4. Results Discussion 4. Results Discussion Based on analysis presented in Section 3, five systems, each with a rating 1.2 MW/6 MWh, Based on analysis presented in Section 3, five systems, each with a rating are collocated with PV systems in Feeder 1. The systems are programmed 100% commitment 1.2 MW/6 MWh, are collocated with PV systems in Feeder 1. The systems are programmed when N-1 contingency is not met. For rest time, is programmed provide voltage 100% commitment when N-1 contingency is not met. For rest time, is programmed management frequency regulation services, each with 50% commitment. The utility above provide voltage management frequency regulation services, each with 50% commitment. The deployment method in providing stacked-benefits is detailed in this section. utility above deployment method in providing stacked-benefits is detailed in this section Primary Application Scenario N-1 Contingency Analysis 4.1. Primary Application Scenario N-1 Contingency Analysis The utility deploying a 75th-percentile capacity, which corresponds 6MW/30MWh, meeting The utility N-1 contingency deploying requirement, a 75th-percentile is demonstrated capacity, which in this section. corresponds The 6MW/30MWh, is programmed discharge, meeting N-1 keep contingency substation requirement, load dem is demonstrated less than 75 MW. in this The section. begins The charging is programmed at 2 am every day. discharge, Figure 12 keep shows substation reduction load in dem overload less dem than 75 recorded MW. The during begins five-year charging planning at 2 am horizon. every day. It can Figure be seen 12 shows that deployed reduction can in provide overload contingency dem recorded requirement during most five-year time. planning However, horizon. at It can 75th-percentile, be seen that N-1 deployed contingency can requirement provide is contingency not met requirement a few hours, as shown most in Figure time. 12. However, at 75th-percentile, N-1 contingency requirement is not met a few hours, as shown in Figure 12.

15 Inventions 2017, 2, Inventions 2017, 2, Inventions 2017, 2, Substation load dem (MW) Substation load dem (MW) Figure 12. Application energy srage in mitigating substation transmer overloading during an N-1 contingency scenario. Figure 12. Application energy srage in mitigating substation transmer overloading during an N-1 contingency scenario. Figure 13 compares utility system providing N-1 contingency support base year Figure (Year 1) 13 compares Year 5. For utility this study, system load priles providing three N-1 contingency consecutive support days overloading transmer base year (Year under 1) N-1 Year N-1 contingency 5. For this study, event event are load are compared priles with three with consecutive without without an days an overloading system. system. For For selected selected days transmer days in in base under base year an N-1 year (Year contingency (Year 1), 1), energy event energy supplied are compared supplied above with above transmer without transmer rating system. rating is 28.2 For is MWh, MWh, MWh, selected MWh, days 28.6 in MWh base In MWh. year this (Year case, In this 1), case, 30energy MWh 30 supplied energy MWh srage energy above srage istransmer successfully successfully rating ableis 28.2 supply able supply MWh, load dem load MWh, dem above above 28.6 MWh. substation substation In this case, transmer transmer 30 MWh rating. rating. energy The analysis The srage analysis successfully repeated is repeated able same supply load dem above substation transmer rating. The analysis is repeated days same during days during Year-5 Year-5 (see Figure (see Figure 13b). 13b). On On selected selected days days in Year-5, in Year-5, energy energy supplied supplied above above same days during Year-5 (see Figure 13b). On selected days in Year-5, energy supplied above transmer transmer rating rating is 55.36, is 55.36, MWh. MWh. In this In this case, case, 30 MWh 30 MWh system system is not is not able able transmer rating is 55.36, MWh. In this case, 30 MWh system is not able successfully mitigate overload concerns. As As sized 75th-percentile successfully mitigate overload concerns. As expected, system sized 75th-percentile value value is not is able not able supply supply required energy dem a few a fewdays days during during planning planning duration. duration Combined Combined feeder feeder peak peak load load dem (Feeder (Feeder Feeder 2) 2) Without energy srage With energy srage 20 Without energy srage 20 With energy srage Base Year (a) Base Year 100 Combined feeder feeder peak peak load load dem dem (Feeder Feeder + Feeder 2) 2) Without Energy Srage With Energy Srage 30 Without Energy Srage With Energy Srage Year 5 (b) Year 5 Figure 13. Application (a) energy srage in mitigating substation transmer (b) overloading under an Figure 13. Application energy srage in mitigating substation transmer overloading under an N-1 contingency scenario a few selected days during: (a) Base year (Year-1), (b) Year-5. N-1 Figure contingency 13. Application scenario energy a fewsrage selected in days mitigating during: substation (a) Base year transmer (Year-1), overloading (b) Year-5. under an N Secondary contingency Application scenario Scenario Stacked-Benefit a few selected days during: Analysis (a) Base year (Year-1), (b) Year Secondary Application Scenario Stacked-Benefit Analysis 4.2. Secondary For Application stacked-benefit Scenario Stacked-Benefit application, system Analysis deployed with 50% commitment voltage For management stacked-benefit 50% commitment application, frequency systemregulation. is deployedthe with simulation 50% commitment is permed voltage in management For OpenDSS stacked-benefit 50% one hour, commitment from application, 12 1 frequency pm, with system regulation. a time is resolution deployed The simulation with one 50% second. iscommitment permed Note that in OpenDSS voltage management one selected hour, PV from prile 12 50% (see commitment 1 pm, Figure with 6a), a time largest frequency resolution PV variability regulation. oneis second. observed The Note simulation around thatnoon. is In permed order selected PV in OpenDSS better underst one hour, from stacked 12 benefits, 1 pm, four with application a time scenarios resolution are simulated: prile (see Figure 6a), largest PV variability is observed around noon. one In order second. better Note that underst selected stacked PV benefits, prile (see fourfigure application 6a), scenarios largest are PV simulated: variability is observed around noon. In order better underst stacked benefits, four application scenarios are simulated:

16 Inventions 2017, 2, Inventions 2017, 2, Case 1 is not operating, i.e., real reactive power are zero Case 2 50% 1 is not operating, capacity i.e., provides real voltage reactive management power service are due zero PV variability only. Case is not 2 50% providing anycapacity frequency provides regulation voltage support. management service due PV variability only. Case Inventions is 3 not 2017, providing 2, simultaneously 6 any frequency provides regulation following support. services: Case 3 simultaneously provides following services: Case Voltage 1 management 50% is not operating, i.e., real capacity reactive power provides voltage are zero management service due o Case Voltage 2 50% management 50% PV variability only capacity provides voltage capacity management provides service voltage due management PV variability service only. due is PV not variability providing only any frequency regulation support. Frequency regulation 50% capacity provides frequency regulation service o Case Frequency 3 simultaneously regulation 50% provides following capacity services: provides frequency regulation service Case 4 simultaneously provides following services: Case o 4 Voltage simultaneously management 50% provides following capacity services: provides voltage management service due PV variability only o Voltage management 50% capacity provides voltage o Voltage Frequency management 50% regulation 50% capacity provides provides frequency voltage regulation management service service due both both PV PVvariability charge/discharge charge/discharge frequency frequency regulation regulation schedule schedule Case 4 simultaneously provides o Frequency regulation 50% following capacity services: is isdeployed provide frequency regulation o Voltage management 50% capacity provides voltage management service due The effectiveness both PV variability in providing voltage charge/discharge management frequency frequency regulation schedule regulation services is is demonstrated o Frequency using using regulation 50% real real reactive power capacity output is deployed provide three-phase frequency average regulation voltage priles recorded at location. The prile real power generated by all PV panels is presented The effectiveness in providing voltage management frequency regulation services is in Figure 14. Recall that tal installed PV capacity is 5 MW. Figure 15a,b show real demonstrated using real reactive power output three-phase average voltage reactive priles power recorded when at is location. employed The prile provide real frequency power generated regulation by all PV panels voltage is presented management services, in Figure respectively. 14. Recall that tal installed PV capacity is 5 MW. Figure 15a,b show real reactive power when is employed provide frequency regulation voltage management 5 services, respectively. PV Generation (MW) PV Generation (MW) Time 30(min) Time (min) Figure Figure Total Total real real power power generated generated by by PV PV panels panels from from p.m. p.m. 1 p.m. p.m. Figure 14. Total real power generated by PV panels from 12 p.m. 1 p.m. Real Power Generation (MW) Real Power Generation (MW) Cases 2, 3 Case 4 Cases 2, Case Time (min) (a) (b) Time (min) (a) (b) Figure 15. Application stacked-benefits: (a) Real power generated by one units Figure 15. Application stacked-benefits: (a) Real power generated by one units frequency Figure frequency 15. Application regulation service; stacked-benefits: (b) Reactive power (a) Real produced power by generated when by providing one voltage units regulation service; (b) Reactive power produced by when providing voltage management service. frequency management regulation service. service; (b) Reactive power produced by when providing voltage management service. Reactive Reactive Power Power Generation (Mvar) (Mvar)

17 Inventions 2017, 2, Inventions 2017, 2, The voltage priles each case recorded at one locations (34.5-kV level) are shown in FigureThe 16. voltage In Case priles 2, voltage each case variability recorded significantly at one reduces locations when (34.5-kV is level) providing are shown voltage management in Figure 16. duein Case PV 2, variability. voltage However, variability significantly voltage variability reduces when significantly is providing increases voltage Case 3. Recall management that in Case due 3, PV 50% variability. However, capacity is deployed voltage variability provide significantly frequency increases regulation Case services, 3. Recall that in Case 3, 50% capacity is deployed provide frequency regulation services, while remaining 50% is committed voltage management voltage variability resulting only while remaining 50% is committed voltage management voltage variability resulting only from PV systems. Due frequency regulation services, systems also result in voltage variability, from PV systems. Due frequency regulation services, systems also result in voltage variability, which which needs needs be be accounted accounted during during voltage voltage management. management. In Case In Case 4, when 4, when is providing is providing a a voltage voltage management service due both PV PVvariability charge/discharge charge/discharge frequency frequency regulation regulation schedule, schedule, voltage variability decreases significantly. Voltage (pu) (a) (b) Figure 16. Voltage priles at system location different case studies: (a) selected test Figure 16. Voltage priles at system location different case studies: (a) selected test distribution circuit locations; (b) voltage priles at one system location. distribution circuit locations; (b) voltage priles at one system location. For ease comparison, voltage variability is quantified using voltage variability index For (VVI) easequantified comparison, using voltage stard variability deviation is quantified voltage using variability voltage recorded variability over index (VVI) simulation quantified period. usingthe voltage stard variability deviation is calculated voltage as difference variability between recorded present over voltage simulation voltage recorded during previous time step. VVI is calculated using 1-min average data period. The voltage variability is calculated as difference between present voltage voltage priles. The VVI each case is summarized in Table 4. voltage recorded during previous time step. VVI is calculated using 1-min average data voltage priles. The VVI eachtable case 4. isvoltage summarized Variability in Index Table(VVI) 4. Various Cases. Table VVI 4. Voltage PV Variability 1 PV 2Index PV (VVI) 3 PV 4Various PV Cases. 5 Case VVI Case PV PV PV PV PV 5 Case Case Case Case Case During Case 4 simulation 1.91 period, a large 1.87 variation in 2.64 PV generation 1.86 is recorded, 2.16 as shown in Figure 14. When is not operating in Case 1, fluctuation PV generation results in significant voltage variability, as shown in Figure 16 Table 4. After deploying voltage management due During PV variability simulationin period, Case 2, a large adjusts variation in reactive PV generation power ismitigate recorded, voltage as shown variations. in Figure 14. When According is not operating Table 4, involtage Case variability 1, fluctuation decreases at PV each generation location. results Thus, incan significant successfully voltage variability, mitigate ashort-term shown involtage Figurevariations 16 Table due 4. PV After generation. deploying voltage management due PV variability On inemploying Case 2, adjusts frequency reactive regulation power in mitigate addition voltage voltage variations. management According due PV Table 4, voltage variability variability (Case 3), decreases real power at each follows location. frequency Thus, regulation can successfully schedule, mitigate as presented short-term in Figure 15a. Theree, is successfully able charge discharge provide a frequency voltage variations due PV generation. regulation service. However, Figure 16 shows that voltage prile this case fluctuates On employing frequency regulation in addition voltage management due PV significantly, due variation real power. From Table 4, voltage variability significantly variability (Case 3), real power follows frequency regulation schedule, as presented in Figure 15a. Theree, is successfully able charge discharge provide a frequency regulation service. However, Figure 16 shows that voltage prile this case fluctuates significantly, due variation real power. From Table 4, voltage variability significantly increases when is

18 Inventions 2017, 2, deployed providing frequency regulation services. Theree, should be deployed manage voltage variability due both PV real power variations. When is also used provide voltage management due frequency regulation schedule in Case 4, Figure 15b shows that provides reactive power support based on both PV variability frequency regulation schedule. Hence, voltage variability due frequency regulation schedule is reduced, as illustrated in Figure 16. From Table 4, Case 4, voltage variability decreases at each location. 5. Conclusions This paper presents a planning framework integrating energy srage systems in distribution system. The objective is deploy system providing stacked-benefits grid. We present a systematic approach, starting by identifying application scenario feeder n presenting an deployment framework. For given feeder, depending upon load dem data current future service requirements, primary secondary applications deployment are identified. For selected feeder, is primarily deployed provide N-1 contingency requirement feeder. For stacked-benefit application, system is deployed provide voltage management frequency regulation services. The presented deployment framework is based on following four steps: (1) calculate system size based on primary application scenario; (2) determine optimal locations based on both primary secondary application scenarios; (3) calculate accommodation capacity at each potential location (4) deploy system develop a methodology grid impact analysis validate if intended benefits are provided by systems. Furrmore, paper also develops power control methods demonstrates stacked-benefit applications deploying in simultaneously providing multiple services. For primary applications, 100% capacity would be deployed provide N-1 contingency requirement i.e., when one substation transmers is at fault, net load dem exceeds or transmer s emergency rating. However, when circuit is in a normal operating condition, 100% capacity would be used provide or secondary services, such as voltage management frequency regulation. In providing frequency regulation services, employs a real power control mode. In this control mode, charges discharges in accordance with frequency regulation schedule. The simulation results show that while can successfully provide frequency regulation by charging discharging, frequency regulation signal may suddenly ramp up or down, thus resulting in voltage variations. Theree, along with variability PV generation, should also be employed provide voltage management voltage variations due frequency regulation schedule. In this paper, we develop control in order provide reactive power support decreasing voltage variability resulting from sudden ramps in PV generation in frequency regulation schedule. The simulation results validate that systems are able successfully mitigate voltage variation concerns due both variability PV generation frequency regulation schedule. The proposed deployment framework is generic can be easily adapted or feeders, with a different set primary secondary application scenarios. The paper also outlines characteristics modeling framework with required dataset, thus presenting an important guideline integration analysis. Finally, by demonstrating application in providing stacked grid benefits, this paper provides a successful use case deployment in smart distribution systems. It should be noted that rapid charging discharging battery may deteriorate its overall lifetime. In this framework, provide frequency regulation services, is generating/absorbing active power by rapidly charging/discharging every 2 s. Usually, battery technologies are rated several deep charge or discharge cycles, after which deterioration is expected. Fortunately, when participating in frequency regulation, energy srage does not undergo deep charge or discharge every 2 s.

19 Inventions 2017, 2, Instead, a few cycles deep charge or discharge are observed over an entire day (Figure 15). Theree, framework may be feasible existing battery systems if benefit providing frequency regulation fsets cost battery deterioration. However, an actual analysis on lifetime deterioration will depend upon depth charge/discharge in each cycle type battery technology. In this paper, we do not model battery lifetime deterioration due charging/discharging a potential pic future research. Author Contributions: Anamika Dubey, Pisitpol Chirapongsananurak, Surya Sanso collaboratively developed idea, problem mulation, test framework. Anamika Dubey conducted simulations, permed data analysis, wrote paper; Pisitpol Chirapongsananurak helped with simulations, analysis, paper writing; Surya Sanso helped with analysis interpretation results. Conflicts Interest: The authors declare no conflict interest. References 1. Ipakchi, A.; Albuyeh, F. Grid future. IEEE Power Energy Mag. 2009, 7, [CrossRef] 2. Peças Lopesa, J.A.; Hatziargyrioub, N.; Mutalec, J.; Djapicc, P.; Jenkinsc, N. Integrating distributed generation in electric power systems: A review drivers, challenges opportunities. Electr. Power Syst. Res. (Elsevier) 2007, 77, [CrossRef] 3. Executive Office President. National Science Technology Council. In A Policy Framework 21st Century Grid: A Progress Report. Available online: files/microsites/ostp/2013_nstc_grid.pdf (accessed on 24th February 2017). 4. U.S. Department Energy. The American Recovery Reinvestment Act Smart Grid Highlights. Available online: pdf (accessed on 24th February 2017). 5. U.S. Department Energy, Office Energy Efficiency & Renewable Energy. Vehicle Technologies Program Multi-Year Program Plan ( ). Available online: zhong1/docs/vt_mypp_ pdf (accessed on 24th February 2017). 6. Katiraei, F.; Aguero, J.R. Solar PV integration challenges. IEEE Power Energy Mag. 2011, 9, [CrossRef] 7. Erdman, W. Secondary Network Distribution Systems Background Issues Related Interconnection Distributed Resources; National Renewable Energy Laborary: Golden, CO, USA, Dubey, A.; Sanso, S. Electric vehicle charging on residential distribution systems: Impacts mitigations. IEEE Access 2015, 3, [CrossRef] 9. Brown, R.E. Impact smart grid on distribution system design. In Proceedings IEEE Power Energy Society General Meeting Conversion Delivery Electrical Energy in 21st Century, Pittsburgh, PA, USA, July Calinia Energy Commission KEMA Inc. Research Evaluation Wind Generation, Solar Generation, Srage Impact on Calinia Grid. CEC PIER Final Project Report, CEC Available online: (accessed on 24th February 2017). 11. Rittershausen, J.; McDonagh, M. Moving Energy Srage from Concept Reality; Sourn Calinia Edison: Rosemead, CA, USA, Eyer, J.; Corey, G. Energy Srage Electricity Grid: Benefits Market Potential Assessment Guide; SAND ; Sia National Laboraries: Albuquerqu, NM, USA, Abrams, A.; Fioravanti, R.; Harrison, J.; Katzenstein, W.; Kleinberg, M.; Lahiri, S.; Vartanian, C. Energy Srage Cost Effectiveness Methodology Preliminary Results; Calinia Energy Commission: Sacramen, CA, USA, Chen, C.; Duan, S.; Cai, T.; Liu, B. Optimal allocation economic analysis energy srage system in microgrids. IEEE Trans. Power Electron. 2011, 26, [CrossRef] 15. Xu, X.; Bishop, M.; Oikarinen, D.G.; Hao, C. Application modeling battery energy srage in power systems. CSEE J. Power Energy Syst. 2016, 2, [CrossRef] 16. Atwa, Y.M.; El-Saadany, E.F. Optimal allocation S in distribution systems with a high penetration wind energy. IEEE Trans. Power Syst. 2010, 25, [CrossRef]

20 Inventions 2017, 2, Barn, J.P.; Infield, D.G. Energy srage its use with intermittent renewable energy. IEEE Trans. Energy Convers. 2004, 19, [CrossRef] 18. Hill, C.A.; Such, M.C.; Chen, D.; Gonzalez, J.; Grady, W.M. Battery energy srage enabling integration distributed solar power generation. IEEE Trans. Smart Grid 2012, 3, [CrossRef] 19. Wang, G.; Ciobotaru, M.; Agelidis, V.G. Power management improved dispatch utility-scale PV plants. IEEE Trans. Power Syst. 2016, 31, [CrossRef] 20. Bass, R.B.; Carr, J.; Aguilar, J.; Whitener, K. Determining power energy capacities a battery energy srage system accommodate high phovoltaic penetration on a distribution feeder. IEEE Power Energy Technol. Syst. J. 2016, 3, [CrossRef] 21. Yang, Y.; Li, H.; Aichhorn, A.; Zheng, J.; Greenleaf, M. Sizing strategy distributed battery srage system with high penetration phovoltaic voltage regulation peak load shaving. IEEE Trans. Smart Grid 2014, 5, [CrossRef] 22. Gantz, J.M.; Amin, S.M.; Giacomoni, A.M. Optimal mix placement energy srage systems in power distribution networks reduced outage costs. In Proceedings IEEE Energy Conversion Congress Exposition, Raleigh, NC, USA, September 2012; pp Wang, Y.; Tan, K.T.; Peng, X.Y.; So, P.L. Coordinated control distributed energy-srage systems voltage regulation in distribution networks. IEEE Trans. Power Deliv. 2016, 31, [CrossRef] 24. Han, Y.; Young, P.M.; Jain, A.; Zimmerle, D. Robust control microgrid frequency deviation reduction with attached srage system. IEEE Trans. Smart Grid 2015, 6, [CrossRef] 25. Kim, Y.; Del-Rosario-Calaf, G.; Nord, L.K. Analysis experimental implementation grid frequency regulation using behind--meter batteries compensating fast load dem variations. IEEE Trans. Power Syst. 2017, 32, [CrossRef] 26. U.S. Department Energy. Grid Energy Srage. Available online: Grid_Energy_Srage_Dec_2013.pdf (accessed on 24th February 2017). 27. Bender, D.; Byrne, R.; Borneo, D. ARRA Energy Srage Demonstration Projects: Lessons Learned Recommendations; SAND ; Sia National Laboraries: Albuquerque, NM, USA, Dugan, R.C. The Open Distribution System Simular (OpenDSS), Reference Guide; Electric Power Research Institute, Inc.: Palo Al, CA, USA, Smart Grid Resource Center. Electric Power Research Institute. Available online: com/simulationtool.aspx (accessed on 24th February 2017). 30. Reno, M.J.; Coogan, K. Grid Integrated Distributed PV (GridPV) Version 2; SAND ; Sia National Laboraries: Albuquerque, NM, USA, Chirapongsananurak, P.; Dubey, A.; Jothibasu, S.; Sanso, S.; Maitra, A. Stacked benefit applications energy srage systems in distribution circuits. In Proceedings IEEE P General Meeting, Chicago, IL, USA, July accepted. 32. Ancillary Services. PJM. Available online: (accessed on 24th February 2017). 33. American National Stard Electric Power Systems Equipment Voltage Ratings (60 Hz); ANSI C ; National Electrical Manufacturers Association: Rosslyn, VA, USA, by authors. Licensee MDPI, Basel, Switzerl. This article is an open access article distributed under terms conditions Creative Commons Attribution (CC BY) license (