（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
参考文献
[1] 张军六， 樊伟， 谭忠富， 等. 计及需求响应的气电互联虚拟电厂多目标调度优化模型[J] . 电力建设，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] 赵珍珍， 王维庆， 樊小朝， 等. 基于 NSGA-Ⅱ-PSO 算法的微电网多目标优化运行模式[J] . 电源学报，2023， 21(1) ：118-125.
[4] 黄淑媛， 肖健梅. 基于差分进化算法的微电网多目标优化调度[J]. 船电技术， 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] 王子龙， 于东立， 门向阳， 等. 含压缩空气储能的能源互联微网型系统优化配置[J] . 电力需求侧管理， 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] 李国庆， 翟晓娟， 李扬， 等. 基于改进蚁群算法的微电网多目标模糊优化运行[J] . 太阳能学报，2018， 39(8) ：2310-2317.
[9] 甘阳. 考虑需求响应的独立微电网多目标优化配置研究[D]. 郑州：郑州大学， 2018.
[10] 张娜， 赵泽丹， 包晓安， 等. 基于改进的 Tent 混沌万有引力搜索算法[J] . 控制与决策， 2020，35(4) ：893-900．
[11] 黄臻， 吴峻. 基于学生 t 分布的变分贝叶斯 UKF 算法在无人船对准中的应用[J] . 传感技术学报，2022， 35(10) ：1340-1347.
