Smart- Grid Ready PV Inverter
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1 Smart- Grid Ready PV Inverter Tom Key, Technical Execu2ve EPRI IEEE PES Innova5ve Smart Grid Technologies Conference ISGT 2014, Washington, DC February 19, 2014
2 Smart Grid Ready Inverter: Objec2ves 1. Make Inverter Ready and Demo in Field Develop, test, field demo at u2lity sites Define and incorporate standard grid support func2ons (500 kva level)* Use feeder/pv modeling for scale up * 2. Revisit Feeder Level An5- Islanding Iden2fy u2lity- controlled trip op2ons Conduct laboratory side- by- side tests 3. Model DMS- DERMS Level Integra5on Characterize and model support func2ons Evaluate voltage control strategies and coordina2on with tradi2onal devices DMS Success depends on utility engagement and site learning
3 Who are Project Partners? Hydro One GRE Xcel Energy SDG&E DOE Project EPRI Cost Share DTE Energy National Grid AEP Pepco KCP&L Southern Co.
4 Demonstra2on Sites 1.7MW (DC) PV 18 95kW Inverters Cedarville, NJ 605kW (DC) PV 330kW & 250kW Inverters Everett, MA 225kW(DC) PV 300kVA Inverters Ann Arbor, MI 1MW (DC) PV 2 500kW Inverters Haverhill, MA
5 What is a Smart- Grid Ready Inverter? Link to distributed PV and Storage Systems that become Beneficial distribution system assets Enabling Higher Penetration of Renewables Improving Efficiency Improving Power Quality Reliability Deferred Costs Asset Life
6 1. Make Inverter Ready Big Challenges Utility resource or customer owned? Markets-drive or grid-code required? Standards and testing? Performance and reliability? What functions and how to initiate them?
7 Monitoring PV Output Variability F e e d er s Monitoring solar variability and power quality events throughout the feeder Regulator Tap Counts by Week and Average of Daily Variability Index (by Week) Fri 2 9 Sat /16 01/17 Date (Local Time) 01/18 01/19 0 Apr '12 May '12 Jun '12 Jul '12 Aug '12 Sep '12 Oct '12 Nov '12 Dec '12 Jan '13 Feb '13 Using the high resolu2on data for modeling and impact analysis /15 Average Variability Index (by week) /14 14 Reg Tap Counts (total by week) /13/ Regulator Total Tap Counts by Week Thu Reactive Power (kvar) Wed Variability Index (Avg by Week) ystem Power
8 Categories for Daily Variability Condi2ons Sandia s variability index (VI) and clearness index (CI) to classify days VI > 10 Clear Sky POA Irradiance Measured POA Irradiance High VI < 2 CI 0.5 Clear Moderate 5 VI < 10 VI < 2 CI 0.5 Overcast Mild 2 VI < 5
9 Geographical and Seasonal PV Variability Percentage of Days (%) Variability Condi2ons: NM Q Q Q Q Season Percentage of Days (%) Variability Condi2ons: NJ Q Q Q Q Season Variability Condi2ons: TN Percentage of Days (%) Variability Condi2ons: AZ Q Q Q Q Season Percentage of Days (%) Q Q Q Q Season
10 Applying Measured PV Data to Feeder Model Solar Data Collect high- res 1 sec solar data to use in model simula2ons Feeder Modeling Develop feeder models with input from u2li2es Power Production (W) Birmingham, AL (May 14, 2010) 0 8am 9am 10am 11am 12pm 1pm 2pm 3pm 4pm 5pm Local Time (h)
11 Sample Analysis Spa2al &Time Based 3D Visualiza2on of PV Measurement Feeder Voltage Profile PV Produc2on Time Series Regulator/Capacitor Opera2ons
12 Inverter Grid Support can Increase Hos2ng Capacity Minimum Hosting Capacity Maximum Hosting Capacity PV at Unity Power Factor Minimum Hosting Capacity Max Hosting Capacity PV with Volt/var Control Maximum Feeder Voltages (pu) 2500 cases shown Each point = highest primary voltage ANSI voltage limit Maximum Feeder Voltage (pu) ANSI voltage limit Increasing penetration (kw) No observable viola5ons regardless of PV size/loca5on Possible viola5ons based upon PV size/loca5on Observable viola5ons occur regardless of size/loca5on Increasing penetration (kw) For voltage-constrained feeders, results indicate use of smart inverters can increase feeder hosting capacity for PV
13 13 Impact of Smart Inverter Func2ons and Set Points at Different Feeders Reactive Power Active Power Volt- Watt 2 Volt- Watt 1 % Available Vars % 1.0V 1.05 % voltage 95% pf 98% pf Volt- Var 2 Volt- Var 1 Baseline - 100% Increasing PV Penetration > % Available Vars Unity Power Factor % voltage All penetrations in this region are acceptable, regardless of location Some penetrations in this region are acceptable, site specific No penetrations in this region are acceptable, regardless of location
14 Benefits Demonstrated at Different Sites
15 Benefits Derived from Func2ons
16 Tes2ng at ESIF - NREL s Energy System Integra2on Facility
17 2. Revisit An2- Islanding Big Challenges Enabling Voltage Sag Ride-Through Impacts on DER Hosting Capacity Update standards for anti-islanding Compare different methods in laboratory Need for feeder level antiislanding solutions
18 Side by Side comparisons of different technologies Direct transfer trip (DTT) via radio, cell or wire Power line carrier communica2ons (PLCC) low or high frequency Shor2ng switch Integra2on of DG into the u2lity SCADA Synchrophasor- based methods Research Prior Art Develop Func2onal Requirements Select Suitable Technology for Evalua2on Evaluate Technologies in Lab and Field
19 Power- Line Carrier Signal for DER Concept Grid Substation Power Line Tone Generator DX3 Pulsar Transmitter Island Controller Island X X X X
20 3. Model DMS- Level Integra2on Big Challenges Define functional requirements for DMS-DERMS Address gaps in feeder operational control New Types of DER autonomous or controllable Coordinating with traditional voltage control devices Managing grid control at the edge of the grid
21 DER Enterprise Integra2on MDMS OMS GIS DER representation in system model DMS Enterprise Integra2on DERMS Creation of groups and sharing of group definitions Monitoring of group status Sensors, Switches, Capacitors, Regulators SOLAR BATTERY PEV Dispatch of real and reactive power Forecasting of group capabilities
22 Conclusions 1. Smart inverter functions are defined and commercially available. 2. Demonstration in various system feeders, and geographic locations needed. 3. There are many lessons to learn and share. 4. Two known challenges: feeder anti-islanding and integration with utility Demand Management Systems. Thank you!
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