Influencing the Portfolio through the Distribution System Case Study- Pullman, WA

Transcription

1 July 27, Presented by: Curtis Kirkeby, P.E. Fellow Engineer Avista Utilities Influencing the Portfolio through the Distribution System Case Study- Pullman, WA

2 ARRA Grant Projects Smart Grid Workforce Training Grant Smart Grid Demonstration Project Smart Grid Investment Grant Pullman Energy Storage Project

3 Smart Grid Infrastructure HAN Neighborhood Area Network Distribution Area Network Core Network Demand Response/IHD Data Analytics CIS/WMS DR To Tstat Cloud GIS/OMS Homeowner Wi-fi Tstat Cloud AMI Network 900Mhz Distribution Area Network b Fiber Utility Core Systems Internet using Cell or WiFi Customer Mobile Device Capacitor Banks Smart Transformer s Power Quality Sensors Distribution Automation Smart Fault Indication Voltage Regulation MDM /CE Field Data Applications IA Apps PI Battelle Ops Center DMS Blue Fin Transactive Signal System

4 Energy Efficiency - Voltage Optimization Power Factor Correction to Near Unity (fixed and switched capacitor banks) Voltage Regulation on Each Phase at Head End of Feeder Measures at Each Switch, Cap Bank, Voltage Regulator, Smart Transformer, and AMI Meter Automated Optimization via Distribution Management System Substation Existing Feeder W/Voltage Optimization End of Line

5 Distribution Energy Efficiency Reduction of Loads and Losses: 42,300 MWh per Year (2014) 4.9MW Average

6 How Big Is The Opportunity? 326 Feeders 1072 Average MW 1529 Winter Peak MW 1638 Summer Peak MW 8,603,000 MWh Retail Sales

7 How Big Is The Opportunity?

8 Distributed Resources in Pullman, WA HVAC Air Handlers HVAC Chillers Natural Gas Generator Natural Gas Generator XFMR Loading Diesel Generator Normal After Smoothing

9 Dispatching for Optimal Value Prediction of Load 3 Days Forward (time variable, 5minute at t0) Constraints Quantified (customer and utility) System State Awareness. Day Ahead Pricing Considered Weather Considered T=0 Recalibration of Prediction Schedule Based on Optimization Objectives

10 Energy Storage 1.2MW, 3.2MWh Vanadium Flow Battery

11 Turner Energy Storage (TES)

12 Stacked Values for Energy Storage Stacked Values in $/Year 500, , , , ,000 0 Resiliency Reliability Energy Risk Energy O&M Operations Negative Pricing Flex Market CVR Off-Peak CVR On-Peak Ancillary Services Avoided Cost Capacity

13 Findings Thus Far... Energy Storage, Size, Cycle Life and Duration Matter Output Is Variable Based on State of Charge Duration is Dependent on Discharge Rate and State of Charge Efficiency is Variable based on Charge/Discharge Rate and State of Charge Extremely Fast Response 4 Quadrant Capability Allows for Multiple Use Case Realization Reliability and Resiliency May Be High Value Targets Optimization is Essential to Maximize Benefits The Perfect Feeder is Possible

14 Distribution Resource Planning - Impedance

15 Distribution Resource Planning Load

16 Pullman Area - Large Loads Pullman

17 Pullman Area - Natural MicroGrid

18 South Pullman Feeder Load Profile

19 SPU Feeder Load Profile (1MW, 3.2MWh ESS)

20 SPU Feeder MicroGrid

21 SPU MicroGrid Largest Load)

22 How Big Might The Opportunity Need to Be?

23 Load Defection Projections - Rocky Mountain Institute Detailed Study

24 Solar Is Cost Competitive for Avista Commercial Customers

25 Grid Defection Projections - Utility Options

26 MicroGrid Customer & Utility Optimization Prediction

27 U-District Micro-Grid Opportunity (pending) How Might We - Increase the utilization of renewable energy (e.g. Solar) - While providing additional resilience to grid loss Future: Pipeline or Platform?? (see: Uber, AirBNB, etc.) Economies of Scale + Economies of Scope 1.0 MW / 3.2 MWh Vanadium Flow Battery 1) 2) 3) 4) 5) 6) 7) 8) New: 1) Sharing / Coordination 2) Load Shifting 3) Resilience Capacity Transmission Balancing CVR / PF Correction Ramping / Flex Rate Market Negative Pricing Less Swing of generators Avoided cost of Energy Large UPS

28 Questions? Contact Information: Curtis Kirkeby, P.E. Fellow Engineer telephone: (509) website: