Optimal Bidding Strategy for a DER Aggregator in the Day-Ahead Market in the Presence of Demand Flexibility

被引:152
|
作者
Di Somma, Marialaura [1 ]
Graditi, Giorgio [1 ]
Siano, Pierluigi [2 ]
机构
[1] ENEA Agenzia Nazl Nuove Tecnol Energia & Sviluppo, Dept Energy Technol, I-80055 Portici, Italy
[2] Univ Salerno, Dept Ind Engn, I-84084 Fisciano, Italy
关键词
Aggregator distributed energy resources (DER); market bidding strategy; stochastic mixed integer linear programming; DISTRIBUTED ENERGY-RESOURCES; VIRTUAL POWER-PLANT; MICROGRIDS; OPERATION;
D O I
10.1109/TIE.2018.2829677
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The penetration of distributed energy resources (DER), including distributed generators, storage devices, and demand response (DR) is growing worldwide, encouraged by environmental policies and decreasing costs. To enable DER local integration, new energy players as aggregators appeared in the electricity markets. This player, acting toward the grid as one entity, can offer new services to the electricity market and the system operator by aggregating flexible DER involving both DR and generation resources. In this paper, an optimization model is provided for participation of a DER aggregator in the day-ahead market in the presence of demand flexibility. This player behaves as an energy aggregator, which manages energy and financial interactions between the market and DER organized in local energy systems (LES), which are in charge to satisfy the multienergy demand of a set of building clusters with flexible demand. A stochastic mixed-integer linear programming problem is formulated by considering uncertainties of intermittent DER facilities and day-ahead market price, to find the optimal bidding strategies while maximizing the expected aggregator's profit. Numerical results show that the method is efficient in finding the bidding curves in the day-ahead market through the optimal management of flexibility requests sent to clusters, as well as of DER in LES and interactions among LES.
引用
收藏
页码:1509 / 1519
页数:11
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