Microgrid operation and management using probabilistic reconfiguration and unit commitment

被引:90
作者
Jabbari-Sabet, Reza [1 ]
Moghaddas-Tafreshi, Seyed-Masoud [2 ]
Mirhoseini, Seyed-Sattar [3 ]
机构
[1] KN Toosi Univ Technol, Fac Elect Engn, Tehran, Iran
[2] Univ Guilan, Fac Engn, Power Engn Grp, Guilan, Iran
[3] IUST, Dept Elect Engn, Tehran, Iran
关键词
Reconfiguration; Unit commitment; Micro-grid; Uncertainty; Wind power generation; NETWORK RECONFIGURATION; ENERGY-STORAGE; FUEL-CELL; OPTIMIZATION;
D O I
10.1016/j.ijepes.2015.09.012
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
A stochastic model for day-ahead Micro-Grid (MG) management is proposed in this paper. The presented model uses probabilistic reconfiguration and Unit Commitment (UC) simultaneously to achieve the optimal set points of the MG's units besides the MG optimal topology for day-ahead power market. The proposed operation method is employed to maximize MG's benefit considering load demand and wind power generation uncertainty. MG's day-ahead benefit is considered as the Objective Function (OF) and Particle Swarm Optimization (PSO) algorithm is used to solve the problem. For modeling uncertainties, some scenarios are generated according to Monte Carlo Simulation (MCS), and MG optimal operation is analyzed under these scenarios. The case study is a typical 10-bus MG, including Wind Turbine (WT), battery, Micro-Turbines (MTs), vital and non-vital loads. This MG is connected to the upstream network in one bus. Finally, the optimal set points of dispatchable units and best topology of MG are determined by scenario aggregation, and these amounts are proposed for the day-ahead operation. In fact, the proposed model is able to minimize the undesirable impact of uncertainties on MG's benefit by creating different scenarios. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:328 / 336
页数:9
相关论文
共 28 条
  • [1] [Anonymous], 2012, MATH PROBL ENG, DOI DOI 10.1155/2012/829451
  • [2] [Anonymous], P INT C SUPERGEN SUP
  • [3] Bagherian A, 2009, 2009 IEEE BUCHAREST POWERTECH, VOLS 1-5, P1756
  • [4] Billinton R., 1996, RELIABILITY EVALUATI, P114
  • [5] Optimal placement of line switches for distribution automation systems using immune algorithm
    Chen, Chao-Shun
    Lin, Chia-Hung
    Chuang, Hui-Jen
    Li, Chung-Sheng
    Huang, Ming-Yang
    Huang, Chia-Wen
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2006, 21 (03) : 1209 - 1217
  • [6] Distribution system optimisation with intra-day network reconfiguration and demand reduction procurement
    Coroama, Iulia
    Chicco, Gianfranco
    Gavrilas, Mihai
    Russo, Angela
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2013, 98 : 29 - 38
  • [7] Feinberg E. A., 2011, 2011 IEEE Second International Conference on Smart Grid Communications (SmartGridComm 2011), P339, DOI 10.1109/SmartGridComm.2011.6102344
  • [8] Ghiani E., P 2005 INT C FUTURE, DOI DOI 10.1109/FPS.2005.204290
  • [9] Govardhan M. D., 2012, 2012 11th International Conference on Environment and Electrical Engineering, P334, DOI 10.1109/EEEIC.2012.6221398
  • [10] Hui R., 2012, Power and Energy Society General Meeting, 2012 IEEE, P1