（1 Jiangsu Acrel Microgrid Research Institute Co., Ltd, Jiangyin 214432, China;
Abstract: The optimal dispatch of microgrid is an indispensable part of smart grid optimization, which is of great significance to reduce electricity costs of enterprises, energy consumption and environmental pollution. In this paper, the distributed power supply covering photovoltaic,wind power, energy storage, gas turbine and diesel generator is studied. In the case of grid-connected operation of microgrid, in order to coordinate the output of various micro power sources in the system, the photovoltaic power generation, wind power generation and electricity load power are predicted, and the objective function with the lowest operating cost and pollution control cost is established. The Improved Aquila Optimizer (IAO) algorithm is used to solve the problem to obtain the output of different distributed generators and large power grids. The simulation results show that the model can effectively reduce the electricity cost and pollutant emission of enterprise users to a certain extent under the condition of ensuring continuous power supply for users, and provide guidance for the power allocation of microgrid in actual operation.
Key words: microgrid; multi-objective; improved aquila optimizer algorithm; optimal dispatch
參考文獻
[1] 張軍六， 樊偉， 譚忠富， 等. 計及需求響應的氣電互聯虛擬電廠多目標調度優化模型[J] . 電力建設，2020， 41(2) ：1-10.
[2] HOU Hui， XUE Mengya， XU Yan， et al.Multiobjective economic dispatch of a microgrid considering electric vehicle and transferable load[J].Applied Energy， 2020， 262(6) ：114489.
[3] 趙珍珍， 王維慶， 樊小朝， 等. 基于 NSGA-Ⅱ-PSO 算法的微電網多目標優化運行模式[J] . 電源學報，2023， 21(1) ：118-125.
[4] 黃淑媛， 肖健梅. 基于差分進化算法的微電網多目標優化調度[J]. 船電技術， 2018， 38(7) ：57-61.
[5] ABUALIGAH L， YOUSRI D， ABD E M， et al.Aquila Optimizer:A Novel Meta-Heuristic Optimization Algorithm [J] . Computers & Industrial Engineering， 2021， 157 ：107250.
[6] 王子龍， 于東立， 門向陽， 等. 含壓縮空氣儲能的能源互聯微網型系統優化配置[J] . 電力需求側管理， 2018， 20(6) ：40-45.
[7] LACAL-ARANTEGUI R.Materials use in electricity generators in wind turbines-state-of-theart and future specifications[J].Journal of Cleaner Production， 2015，87(1) ：275-283.
[8] 李國慶， 翟曉娟， 李揚， 等. 基于改進蟻群算法的微電網多目標模糊優化運行[J] . 太陽能學報，2018， 39(8) ：2310-2317.
[9] 甘陽. 考慮需求響應的獨立微電網多目標優化配置研究[D]. 鄭州：鄭州大學， 2018.
[10] 張娜， 趙澤丹， 包曉安， 等. 基于改進的 Tent 混沌萬有引力搜索算法[J] . 控制與決策， 2020，35(4) ：893-900．
[11] 黃臻， 吳峻. 基于學生 t 分布的變分貝葉斯 UKF 算法在無人船對準中的應用[J] . 傳感技術學報，2022， 35(10) ：1340-1347.
