Market bidding strategy of the microgrids considering demand response and energy storage potential flexibilities

被引:19
|
作者
Nezamabadi, Hossein [1 ]
Vahidinasab, Vahid [1 ]
机构
[1] Shahid Beheshti Univ, Dept Elect Engn, Abbaspour Sch Engn, Tehran, Iran
关键词
pricing; renewable energy sources; power markets; distributed power generation; stochastic programming; energy storage; demand side management; market bidding strategy; microgrids; demand response; energy storage potential flexibilities; volatile impact; intermittent renewable energy sources; MGs; high-computational problem; bidding problem; three-stage hybrid stochastic; interval optimisation; volatilities; MG potential flexibilities resources; energy provision; real-time market; day-ahead market prices; cost-effective stochastic programming; day-ahead stage; RTM prices; flexibility scheme; real-time stages; computational complexity; HSIO model; cost-effective solution; computational simplicity; load uncertainties; RES production; market prices;
D O I
10.1049/iet-gtd.2018.6097
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Volatile impact of intermittent renewable energy sources (RESs) on the one hand and the uncertainties of loads and market prices, on the other hand, make the bidding strategy of microgrids (MGs) too risky and high-computational problem. To cope with these challenges, the bidding problem of MGs based on a three-stage hybrid stochastic/interval optimisation (HSIO) is devised in this study, which provides a trade-off between covering the volatilities by means of the MG potential flexibilities resources or by means of the energy provision from the real-time market (RTM). To tackle the uncertainties of the day-ahead market prices, the cost-effective stochastic programming (SP) is applied to maximise the profit of MG in the day-ahead stage of decision-making. In order to handle the volatilities of RESs production and uncertainties of RTM prices, a flexibility scheme based on the robust and low-computational interval optimisation (IO) approach is designed to minimise the balancing cost of MG in the real-time stages. Comprehensive numerical results are provided to compare the effectiveness, robustness, and computational complexity of the proposed model. Results show that the HSIO model takes advantage of the cost-effective solution from the SP model, and the robust solution with computational simplicity from the IO model.
引用
收藏
页码:1346 / 1357
页数:12
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