A bilevel model for electricity retailers' participation in a demand response market environment

被引:235
作者
Zugno, Marco [1 ]
Morales, Juan Miguel [1 ]
Pinson, Pierre [1 ]
Madsen, Henrik [1 ]
机构
[1] Tech Univ Denmark, DTU Informat, DK-2800 Lyngby, Denmark
关键词
Demand response; Real-time pricing; Energy retail; Electricity markets; Stochastic programming; Bilevel programming;
D O I
10.1016/j.eneco.2012.12.010
中图分类号
F [经济];
学科分类号
02 ;
摘要
Demand response programmes are seen as one of the contributing solutions to the challenges posed to power systems by the large-scale integration of renewable power sources, mostly due to their intermittent and stochastic nature. Among demand response programmes, real-time pricing schemes for small consumers are believed to have significant potential for peak-shaving and load-shifting, thus relieving the power system while reducing costs and risk for energy retailers. This paper proposes a game theoretical model accounting for the Stackelberg relationship between retailers (leaders) and consumers (followers) in a dynamic price environment. Both players in the game solve an economic optimisation problem subject to stochasticity in prices, weather-related variables and must-serve load. The model allows the determination of the dynamic price-signal delivering maximum retailer profit, and the optimal load pattern for consumers under this pricing. The bilevel programme is reformulated as a single-level MILP, which can be solved using commercial off-the-shelf optimisation software. In an illustrative example, we simulate and compare the dynamic pricing scheme with fixed and time-of-use pricing. We find that the dynamic pricing scheme is the most effective in achieving load-shifting, thus reducing retailer costs for energy procurement and regulation in the wholesale market. Additionally, the redistribution of the saved costs between retailers and consumers is investigated, showing that real-time pricing is less convenient than fixed and time-of-use price for consumers. This implies that careful design of the retail market is needed. Finally, we carry out a sensitivity analysis to analyse the effect of different levels of consumer flexibility. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:182 / 197
页数:16
相关论文
共 35 条
[1]   A Generic Operations Framework for Discos in Retail Electricity Markets [J].
Algarni, Ayed A. S. ;
Bhattacharya, Kankar .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2009, 24 (01) :356-367
[2]  
[Anonymous], 1996, MATH PROGRAMS EQUILI, DOI DOI 10.1017/CBO9780511983658
[3]  
[Anonymous], 2006, Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach
[4]  
[Anonymous], 2015, Linear and Nonlinear Programming
[5]  
[Anonymous], 2011, MARKET STRUCTURE EQU
[6]   The trouble with electricity markets: Understanding California's restructuring disaster [J].
Borenstein, S .
JOURNAL OF ECONOMIC PERSPECTIVES, 2002, 16 (01) :191-211
[7]  
Carrion M., 2009, IEEE T POWER SYST, V24
[8]   Load pattern-based classification of electricity customers [J].
Chicco, G ;
Napoli, R ;
Piglione, F ;
Postolache, P ;
Scutariu, M ;
Toader, C .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2004, 19 (02) :1232-1239
[9]  
Conejo A.J, 2006, Decomposition Techniques in Mathematical Programming: Engineering and Science Applications
[10]   Real-Time Demand Response Model [J].
Conejo, Antonio J. ;
Morales, Juan M. ;
Baringo, Luis .
IEEE TRANSACTIONS ON SMART GRID, 2010, 1 (03) :236-242