Suzhou Electric Appliance Research Institute
期刊号: CN32-1800/TM| ISSN1007-3175

Article retrieval

文章检索

首页 >> 文章检索 >> 最新索引

多能互补的微电网经济运行优化

来源:电工电气发布时间:2020-11-19 15:19 浏览次数:519
多能互补的微电网经济运行优化
 
施爱文
(连云港三新供电服务有限公司灌南分公司,江苏 灌南 223500)
 
    摘 要:为降低微电网发电成本,考虑实际运行的约束条件,以调度周期内发电总成本最小为目标建立模型。为防止天牛须搜索算法( 简称天牛算法) 陷于局部最优,将Metropolis准则加入标准天牛算法中增加变异的概率,并将改进天牛算法与标准天牛算法分别求解微电网日前调度模型,仿真结果表明,利用改进算法求出的调度方案能够合理安排机组的出力,降低并网模式下微电网运行的总发电成本。
    关键词:微电网;经济调度;天牛须搜索算法;Metropolis准则
    中图分类号:TM714     文献标识码:A      文章编号:1007-3175(2020)11-0028-03
 
Economic Operation Optimization of Microgrid with Multiple Complementary Functions
 
SHI Ai-wen
(Guannan Branch of Lianyungang Sanxin Power Supply Service Co., Ltd, Guannan 223500, China)
 
    Abstract: In order to reduce the generation cost of micro-grid, considering the constraints of actual operation, the model is established with the goal of minimizing the total power generation cost in the dispatch period. In order to prevent the beetle antennae search algorithm from falling into the local optimum, the Metropolis criterion was added to the standard beetle antennae search algorithm to increase the probability of mutation, and the improved beetle antennae search algorithm and the standard beetle antennae search algorithm were separately solved for the day-ahead scheduling model of the micro-grid. The simulation results show that the dispatch plan obtained by the improved algorithm can reasonably arrange the output of the units and reduce the total power generation cost of the micro-grid operation in the gridconnected mode.
    Key words: micro-grid; economic dispatch; beetle antennae search algorithm; Metropolis criterion
 
参考文献
[1] 李佳华,马连博,王兴伟,等. 基于多目标蜂群进化优化的微电网能量调度方法[J]. 郑州大学学报( 工学版),2018,39(6):50-58.
[2] 宋学伟, 刘天羽, 刘玉瑶. 考虑环保性与自治性的主动配电网能量优化管理[J]. 电工电气,2019(6):58-62.
[3] 翟云峰,易国伟,王亦,等. 基于改进帝国竞争算法的微网动态经济调度[J]. 电力科学与工程,2015,31(5):34-41.
[4] 朱宗耀. 计及电动汽车充电负荷的微电网能量优化调度研究[D]. 西安:西安理工大学,2018.
[5] 高佳,肖迎群. 风、光、燃、储多源互补微电网的日优化运行[J]. 科学技术与工程,2019,19(15):136-142.
[6] 李正茂. 基于电热联合调度的微电网运行优化[D].济南:山东大学,2016.
[7] 周磊,董学育,孙飞. 基于改进人工鱼群算法的微电网经济调度[J]. 供用电,2019,36(12):62-68.
[8] 韩瑞达. 基于天牛须搜索和变异策略的花朵授粉算法研究[D]. 葫芦岛:辽宁工程技术大学,2018.
[9] 王甜甜,刘强. 基于BAS-BP模型的风暴潮灾害损失预测[J]. 海洋环境科学,2018,37(3):457-463.
[10] 何庆, 吴意乐, 徐同伟. 改进遗传模拟退火算法在TSP优化中的应用[J]. 控制与决策,2018,33(2):219-225.