Optimal Scheduling Strategies of Distributed Energy Storage Aggregator in Energy and Reserve Markets Considering Wind Power Uncertainties

Zengqiang Mi, Yulong Jia, Junjie Wang and Xiaoming Zheng
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Zengqiang Mi: School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
Yulong Jia: School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
Junjie Wang: School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
Xiaoming Zheng: School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China

Energies, 2018, vol. 11, issue 5, 1-17

Abstract: With continuous technological improvement and economic development of energy storage, distributed energy storage (DES) will be widely connected to the distribution network. If fragmented DES systems are aggregated to form a distributed energy storage aggregator (DESA), the DESA will have great potential to participate in the day-ahead energy and reserve market and the balancing market. The DESA could act as a mediator between the market and DES consumers, enabling beneficial coordination for DES owners and power systems. This paper presents a bilevel optimization model for DESAs in the energy and reserve market under wind power uncertainties. In the lower-level problem, generating companies, wind power plants (WPP), and DESAs are optimized for scheduling day-ahead (DA) energy and the reserve market. In the upper-level problem, operational strategies for DES systems and DESAs are designed to deal with wind power uncertainties in the balancing market. The DESA splits its resources between the energy and reserve markets so that it can reduce total power system consumption, and mutual profit for the system and end customers is achieved. This model is formulated as a mixed-integer linear programming (MILP) program, which can be solved with commercial software. The validity of the bilevel optimization model is verified by the eight-node test transmission system and IEEE-33 bus distribution system.

Keywords: distributed energy storage aggregator (DESA); day-ahead energy and reserve markets; balancing market; bilevel optimization model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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