摘要
为降低发电成本,提高电力系统经济性,以发电机组的燃料成本最小化为目标函数,引入功率平衡约束、发电机输出功率约束等限制条件,建立了电力负荷经济调度的动态模型。提出改进的樽海鞘群算法(ISSA)求解该模型,引入Levy飞行策略提升算法的寻优能力,加入非线性收敛因子提升算法的收敛能力;以六台发电机组和十五台发电机组的电力系统为测试案例,来验证改进算法对负荷调度问题的优化效果。结果表明:与传统算法相比,改进的樽海鞘群算法能够更快更有效地求解两个测试系统的电力负荷经济调度问题,优化效果最好,寻优能力最强,所获得的燃料成本比粒子群算法分别降低了0.14%和1.33%,且有更好的运行稳定性。
In order to reduce the cost of power generation and improve the economy of the power system,the minimum fuel cost of the generator units is taken as an indicator,the constraints such as power balance constraints and generator output power constraints are introduced,thereby a dynamic model of power load economic dispatch is established.An improved salp swarm algorithm(ISSA)is proposed to solve the model.Levy flight strategy is introduced to improve the optimization ability of algorithm,and the nonlinear convergence factors is added to improve the convergence ability of algorithm.Six generator units system and fifteen generator units system are used to verify the optimization effect of the improved algorithm on the load dispatch problem.The results show that,compared with the traditional algorithm,the improved salp swarm algorithm can faster and more effectively solve the power load economic dispatch problem of the two test systems,with the best optimization effect and the strongest optimization ability.The fuel cost obtained is reduced by 0.14%and 1.33%respectively compared with particle swarm algorithm,and it has better operational stability.
作者
李玲玲
陈文泉
冯欢
LI Ling-ling;CHEN Wen-quan;FENG Huan(State Key Laboratory of Reliability and Intelligence of Electrical Equipment,Hebei University of Technology,Tianjin 300130,China;Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province,Hebei University of Technology,Tianjin 300130,China)
出处
《天津工业大学学报》
CAS
北大核心
2022年第2期67-73,共7页
Journal of Tiangong University
基金
天津市自然科学基金重点资助项目(19JCZDJC32100)
河北省自然科学基金资助项目(E2018202282)。
