Modelling of demand response in distribution systems

Transcription

1 Modelling of demand response in distribution systems Energy and Environment Chalmers University of Technology The work is financed by Chalmers Energy Initiative and Göteborg Energi Research Foundation Nordic cities workshop 1-2 th September of 15

2 HSB living lab Last week Yesterday Nordic cities workshop 1-2 th September of 15

3 Why demand response? Wind power Power system Solar PV Flexible loads Plug-in electric vehicle (PEV) Nordic cities workshop 1-2 th September of 15

4 Strategies to implement demand response Business as usual No demand response, use the electricity as today. Loss-optimal strategy The electricity consumption is shifted in time to minimize the losses in the power system. Price-optimal strategy The electricity consumption is shifted in time to minimize the electricity cost. Nordic cities workshop 1-2 th September of 15

5 Potential for demand response - Space-heating Nordic cities workshop 1-2 th September of 15

6 Potential for demand response - PEVs Residential Area Commercial Area Nordic cities workshop 1-2 th September of 15

7 Effects of network tariffs Energy based network tariff (EBT): Based on the electricity transferred over the grid. Monthly power based network tariff (MPT): Based on the monthly peak demand. Daily power based network tariff (DPT): Based on the daily peak demand. Nordic cities workshop 1-2 th September of 15

8 Effects of network tariff Customers benefit s Nordic cities workshop 1-2 th September of 15

9 Effects of network tariff Peak demand & losses Nordic cities workshop 1-2 th September of 15

10 DR & wind power Wind power penetration A future scenario with a high wind power share. Wind power placed in most profitable areas. Nordic cities workshop 1-2 th September of 15

11 DR & wind power Average area price (AAP) Average area price for the case with wind power compared to the reference case Average area price for the case with DR compared to the case without DR Nordic cities workshop 1-2 th September of 15

12 DR & wind power Revenue & cost reduction Revenue for wind power producers for the case with DR compared to the case without DR Rel. difference in heat cost [%] SE2 SE1 no WP with WP SE3 SE4 NO1 NO2 NO3 NO4 NO5 FI DK1 DK2 SYS Cost for heating for the case with DR compared to the case without DR Nordic cities workshop 1-2 th September of 15

13 Conclusions Increased electricity demand could result in overloading of components in distribution systems. Peak demand could be greatly reduced with demand response, however... its important how to implement demand response. Nordic cities workshop 1-2 th September of 15

14 Conclusions cont. Power based network tariffs would increase the benefit for customers with large variation in demand. Wind power producers would generally reduce their profits if customers would be responsive. Nordic cities workshop 1-2 th September of 15

15 Thank you for listening! Division of Department of Energy and Environment Chalmers University of Technology SE Göteborg, Sweden Mobile: +46(0) Nordic cities workshop 1-2 th September of 15