热电联产经济环保调度优化

为解决复杂的热电联产经济环保调度问题,提出了一种改进的多目标灰狼优化算法。标准灰狼算法只适用于处理单目标优化问题,而改进的算法也适用于多目标优化,并通过融入方向修正操作以修正狼群前进方向,并改善算法的全局搜索能力。其次,结合快速非劣解排序、拥挤距离计算等,在更新狼群位置时,采用"精英保留策略"淘汰弱势狼个体,进一步提高算法的收敛速度,并通过模糊决策理论获得最优折中解。最后,通过对某典型7机组热电联产系统的仿真,验证了所提出方法不仅能够有效地求取热电联产发电计划在经济性与环保性之间的最优折中,同时克服了标准灰狼算法的缺陷,且较其他群智能优化算法在求解质量、收敛性等方面具有明显优势。

Economic and Environmental Dispatch Optimization of Combined Heat and Power

In order to solve the economic and environmental emission dispatch problem of complex combined heat and power,this paper proposes an improved multi-objective gray wolf optimization algorithm.The standard grey wolf algorithm is only suitable for dealing with single objective optimization problems.However,the improved grey wolf algorithm is also suitable for the multi-objective optimization,which improves the global search ability of the algorithm by modifying the direction of the wolves.Secondly,with the combination of fast and elitist non-dominated sorting,crowded distance calculation,etc.,in the update wolves position,the algorithm uses 'elite retention strategy' to eliminate vulnerable wolves individual,further improves the convergence rate of the algorithm,and obtains the optimal solution by fuzzy decision theory.Finally,the simulation of a typical 7-unit combined heat and power system shows that the proposed method not only can effectively consider the optimal compromise between the economic and environmental protection of the cogeneration plan,but also overcome the defects of the standard gray wolf algorithm,and has obvious advantages in solving the quality and convergence compared with other swarm intelligence algorithms.