An interactive operation management of a micro-grid with multiple distributed generations using multi-objective uniform water cycle algorithm

被引:50
|
作者
Deihimi, Ali [1 ]
Zahed, Babak Keshavarz [1 ]
Iravani, Reza [2 ]
机构
[1] Bu Ali Sina Univ, Dept Elect Engn, Shahid Fahmideh St, Hamadan 6517838683, Iran
[2] Univ Toronto, Dept Elect & Comp Engn, Toronto, ON M5S 3G4, Canada
关键词
Micro-grid; Multi-objective optimization; Operation management; Pareto-optimal front; Renewable energy sources; Water cycle algorithm; INTELLIGENT ENERGY MANAGEMENT; CHP (COMBINED HEAT; STORAGE-SYSTEMS; OPTIMIZATION; WIND; DISPATCH; BATTERY; DESIGN;
D O I
10.1016/j.energy.2016.03.048
中图分类号
O414.1 [热力学];
学科分类号
摘要
Accommodation of DGs (distributed generations) close to loads has led to the concept of MG (micro-grid) for better reliability and quality of energy supply. MG as a clump of consumers and DGs can operate in stand-alone and grid-connected modes, and often needs ESS (energy storage system) to handle generation surplus/shortage. Variations of renewable sources and consumptions along with economical and environmental issues necessitate an efficient OM (operation management) of MG for short-term scheduling of energy outputs of DGs, ESS and exchange route to upstream macro-grid. This paper presents MOUWCA (multi-objective uniform water cycle algorithm) for optimal OM of MG considering operation cost and emission as objectives. The problem is casted to find 24 POFs (pareto-optimal fronts) corresponding to 24 h of the day (unlike previous studies giving one POF per day) to provide more flexibility for selecting hourly compromise solutions. Through an interactive process, charging/discharging of ESS is balanced over a day based on the desired order of hours for discharging ESS. MOUWCA is examined on some benchmark problems and compared with NSGA-II (non-dominated GA-II), MOPSO (multi-objective particle swarm optimization) and NCA (normal constraint algorithm) to verify its effectiveness. MOUWCA is then applied to a typical MG where its superiority is confirmed in comparison to other previously used algorithms. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:482 / 509
页数:28
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