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作 者:王隔霞 王军平 孙明杨 张启航 WANG Gexia;WANG Junping;SUN Mingyang;ZHANG Qihang(College of Mathematics and Physics,Shanghai University of Electic Power,Shanghai 201306,China)
出 处:《上海电机学院学报》2024年第4期219-223,236,共6页Journal of Shanghai Dianji University
摘 要:节能减排是降低环境污染、能源可持续发展的必由之路,因此微电网的多目标经济调度问题受到广泛关注。考虑阀点效应、出力约束、网络损耗、电力平衡等多种约束的经济调度问题是一类非凸优化问题,在数学上很难处理。基于蚱蜢算法,考虑了一类包含阀点效应在内的多约束多目标经济调度问题。为防止蚱蜢算法陷入局部最优及提高搜索能力,提出了弦函数的方法。同时,为解决非线性的电力平衡约束,采用解方程组的方法处理此约束。选出一组10个发电机的案例验证了改进的蚱蜢算法的有效性,并与其他算法进行了比较。结果表明:在满足各种约束下,改进的蚱蜢算法可以取得更优的燃料成本和排放量。To reduce environment pollution,energy saving and emission reduction are necessary for sustainable development.Therefore,the multi-objective economic environment dispatch problem of microgrids has mainly been focused on.However,it is hard to solve in mathematics for the economic dispatch problem with multi-constraints,including power operating limits,valve point effect,network loss,and power balance,due to the complexity of the non-convex optimization.The multi-objective economic environment dispatch problem including valve point effect is considered based on the grasshopper algorithm.To avoid getting stuck in a local optimum of the grasshopper algorithm and improve the search ability,the sine function is introduced into the algorithm.In addition,the method of solving the algebra equation is used to handle the nonlinear power balance constraint.A 10-unit test system is selected to verify the effectiveness of the improved grasshopper algorithm,which is compared with other algorithms.The results show that the improved grasshopper algorithm can achieve better fuel cost and emissions if the various constraints are satisfied.
分 类 号:TM863[电气工程—高电压与绝缘技术]
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