基于多目标原子轨道搜索算法的风电场集群最优经济调度

Optimal economic dispatch of wind farm clusters based on multi-objective atomic orbital search

随着环保意识的增强以及风电渗透率的不断攀升,使得电力部门对含风电系统的经济调度提出了更高的要求。为了在降低污染物排放及促进风电消纳的同时将发电成本控制在最低,建立了考虑环境与经济指标的风-火多随机变量经济调度模型。该模型中的目标函数考虑了火力发电成本、风力发电成本、弃风惩罚成本及污染气体排放。采用多目标原子轨道搜索算法进行模型求解,该算法在传统原子轨道搜索算法的基础上添加了存档机制、网络机制以及领导者选择机制,具有较强的多目标优化执行能力。结合修改后的IEEE30节点算例进行仿真分析,结果验证了所提模型的可行性以及多目标原子轨道搜索算法求解此类问题的有效性。

The increasing awareness of environmental protection and the rising penetration rate of wind power have led the power sector to put forward higher requirements for the economic dispatch of wind power-containing systems.To reduce pollutant emission and promote wind power consumption while minimizing generation costs,this paper establishes a wind-fire multi-stochastic variable economic dispatch model considering environmental and economic indices,in which the objective function takes into account the costs of thermal and wind power generation,and of wind abandonment penalties,and pollutant gas emission.This paper adopts the multi-objective atomic orbital search algorithm(MOAOS)for model analysis.This adds archiving,grid and leader selection mechanisms on the basis of the traditional atomic orbital search algorithm(AOS),and has strong multi-objective optimization execution capability.The simulation results validate the feasibility of the proposed model and the effectiveness of the multi-objective stochastic painting optimization algorithm in solving such problems by combining the modified IEEE30-bus algorithm with simulation analysis.