Multi-level interactive unit commitment of regional power system

被引:14
|
作者
Ji, Xingquan [1 ]
Zhang, Yumin [1 ]
Han, Xueshan [2 ]
Ye, Pingfeng [2 ]
Xu, Bo [3 ]
Yu, Yongjin [1 ]
机构
[1] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Peoples R China
[2] Shandong Univ, Minist Educ, Key Lab Power Syst Intelligent Dispatch & Control, Jinan 250061, Peoples R China
[3] State Grid Energy Res Inst Co, Beijing 102209, Peoples R China
基金
美国国家科学基金会;
关键词
Analytical target cascading algorithm; Distributed parallel computing; Primary and secondary frequency regulation; Unit commitment;
D O I
10.1016/j.ijepes.2020.106464
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
Distributed energy resource (DER) including wind power, solar energy and energy storage system (ESS) are connected to the active distribution network (ADN) in various combination ways, which makes the distribution network have interaction. As a bridge connecting the transmission grid (TG) and micro grid (MG), ADN breaks the traditional operation pattern of TG + ADN + MG. Considering the physical connections and shared information among TG, ADN and MG, this paper proposes a decentralized and parallel analytical target cascading (ATC) algorithm for interactive unit commitment (UC) implementation in regional power systems. To explore the synergistic ability of the TG + ADN + MG coping with uncertainties of DER, i.e., wind power, the primary and secondary frequency regulation of TG are implemented to cope with uncertainties. Furthermore, the distributional uncertainty of wind power is well modeled by data driven, which is proposed in our previous work (Zhang et al., 2019) [1]. Both the startup/shutdown variables of the thermal units and the variables in TG + ADN + MG are integrated into the multi-level interactive UC model to optimize simultaneously, thus realizing the optimal goal of the whole network, resources complementary and optimal allocation of power system. An improved 6-bus system is used to test the proposed model, the numerical results show that the proposed decentralized algorithm is a fully parallelized procedure. And it also demonstrates the parallel implementation significantly enhances computations efficiency of the ATC algorithm.
引用
收藏
页数:15
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