DEPLOYMENT OF HALF-HOURLY SCHEDULES ON A DNO-OWNED ENERGY STORAGE: FIELD TRIALS

Transcription

1 Energy Research lab, TSBE centre School of Built Environment DEPLOYMENT OF HALF-HOURLY SCHEDULES ON A DNO-OWNED ENERGY STORAGE: FIELD TRIALS Dr Timur Yunusov a Dr Maciej Fila b, Prof William Holderbaum a, Dr Ben Potter a New Thames Valley Vision, LCNF project 1 st December 2016 UK Energy Storage Conference, Birmingham. Copyright University of Reading a University of Reading b Scottish and Southern Energy Networks 1

2 PROJECT OVERVIEW Understanding demand and networks LV network monitoring ~300 substations ~250 domestic end point monitoring Anticipating Clustering and buddying network impact studies Demand forecasts short energy storage control (day to a week) medium - assessment for smart reinforcement (1-2 years) long planning and investment (2-8 years) Supporting networks Energy storage and demand management 2

3 PROBLEM DEFINITION Change in customer behaviour Uptake of Low Carbon Technologies (LCT) on Low Voltage feeders Electrification of heat Electrification of transport Increased demand Lower voltage Embedded generation Increase in nodal voltage Predominantly single-phase connections high neutral current 3

4 ENERGY STORAGE Energy Storage and Management Units (ESMU) 12 kva per phase Modular Lithium-Ion storage units 12.5kWh each 25 units in Bracknell, Berkshire 11 kv 400 V Battery Power Electronics 4

5 OBJECTIVE Control system for Energy Storage and Management units To address: Thermal constraints Phase imbalance Voltage constraints Voltage imbalance Input data: Substation monitoring - 5 second intervals Demand forecast 30 minute resolution > kw at feeder level per phase > Day to a week duration Integration into existing distribution management system Centralised location SCADA over GPRS control and feedback link 5

6 CONTROL ARCHITECTURE 6

7 CONTROL ARCHITECTURE EPM and Substation monitoring Forecasts Day ahead planning Real Time Control 7

8 CONTROL ALGORITHM Offline phase balancing and peak reduction No correction - can we rely on forecasts only? Half-hourly kw schedule per phase for next 24 hours Minimising F (P) where Forecast per phase Schedule per phase Difference in kw between phases End at 50% SoC Maximum demand on all phases Constraints: Power electronics rating, Energy storage rating and capacity 8

9 ANTICIPATED RESULTS S. Haben, J. A. Ward, D. V. Greetham, P. Grindrod and C. Singleton, A New Error Measure for Forecasts of Household-level, High Resolution Electrical Energy Consumption, International Journal of Forecasting, 30, pp ,

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14 FIELD TRIALS Change in storage capacity cell balancing 14

15 LESSONS LEARNED Offline control with Forecast only has some benefit Higher peaks at sub-half-hourly resolution Bad forecast is not always a bad result Reliability of Energy Storage Units Cell balancing could limit available capacity and charge Alternative to traditional reinforcement More trials underway with a range of forecasts and control techniques 15

16 FUTURE WORK Deployment of Online control As near as real-time as possible Dedicated voltage support Model predictive control Peak reduction Valley filling 16

17 THANK YOU Any questions?? 17

18 THANK YOU Any questions?? 4 th LV workshop, 1-2 nd of March 2017 at University of Reading Topics: Demand analytics Control methods for distribution networks Reasons to attend Participants include DNO and Energy Storage industry representatives Thames Valley Chamber of Commerce Energy Storage Seminar 18