Two-stage energy generation schedule market rolling optimisation of highly wind power penetrated microgrids

被引:31
作者
Cao, Zhiao [1 ]
Han, Yinghua [2 ]
Wang, Jinkuan [1 ]
Zhao, Qiang [3 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, 11 Third Lane,Cultural Rd, Shenyang, Liaoning, Peoples R China
[2] Northeastern Univ Qinhuangdao, Sch Comp & Commun Engn, 143 Taishan Rd, Qinhuangdao, Hebei, Peoples R China
[3] Northeastern Univ Qinhuangdao, Sch Control Engn, 143 Taishan Rd, Qinhuangdao, Hebei, Peoples R China
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
Wind power; Battery energy storage system; Rolling optimisation; Intraday energy market; Mutation-based artificial bee colony algorithm; DEMAND-RESPONSE; MANAGEMENT; STORAGE; UNCERTAINTY; FRAMEWORK; SYSTEMS;
D O I
10.1016/j.ijepes.2019.04.037
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
Considering increasingly scale of renewable energy resources penetration in modern power system, especially the wind power generation, this paper constructs a joint operation system which combined the wind turbine with the battery energy storage system (BESS) in a highly wind power penetrated microgrid, in order to weaken the impact of wind power uncertainty. Simultaneously, the demand response (DR) is optimally incorporated into system operation as flexible resources to adjust the imbalance of supply-demand in the microgrid. The battery investment capital and operation maintenance cost are also modeled as components of the optimisation. A novel two-stage energy generation schedule market rolling optimisation framework, which consists of the day-ahead energy generation schedule market and intraday energy generation reschedule market, is presented to pursue the best energy profits for the microgrid. A mutation-based artificial bee colony (MABC) algorithm is designed for the day-ahead market optimisation due to the nonlinear of battery operation model in this stage, while without considering the dispatch of battery, the intraday market rolling optimisation is solved as a mixed integer programming. Simulations are carried out on a small-scale microgrid with high penetration of wind power, the results show that the constructed joint operation system can effectively reduce the effect of wind power uncertainty and the proposed two-stage energy generation schedule market rolling optimisation framework can adjust the generation schedule along with the updated wind power predicted data, and thus increase the total energy profits for the joint operation system prominently.
引用
收藏
页码:12 / 27
页数:16
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