A new multiobjective evolutionary algorithm for environmental/economic power dispatch
A new multiobjective evolutionary algorithm for environmental/economic power dispatch
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DOI：
10.1109/pess.2001.970254
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发表时间：
2001-07
期刊：
影响因子：
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通讯作者：
A.A. Abido
中科院分区：
文献类型：
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作者：
A.A. Abido
提出了一种新的多目标进化算法求解环境/经济电力调度优化问题。EED问题是一个非线性约束多目标优化问题，等式和不等式约束。提出了一种新的基于非支配排序遗传算法（NSGA）的方法来处理这个问题作为一个真正的多目标优化问题的竞争和不可分割的目标。该方法采用了多样性保持技术，以克服早熟收敛和搜索偏差的问题，并产生一个分布良好的帕累托最优的非支配解决方案。一个层次聚类技术也施加到决策者提供一个具有代表性的和可管理的帕累托最优集。所提出的方法进行了几个优化运行的标准IEEE测试系统。结果表明，建议的NSGA为基础的方法，以产生真正的帕累托最优集的非支配解决方案的多目标EED问题在一个单一的运行的能力。所提出的方法的仿真结果进行了比较，在文献中报道的。比较表明，建议的NSGA为基础的方法的优越性，并确认其潜在的解决多目标EED问题。
In this paper, a new multiobjective evolutionary algorithm for environmental/economic power dispatch (EED) optimization problem is presented. The EED problem is formulated as a nonlinear constrained multiobjective optimization problem with both equality and inequality constraints. A new nondominated sorting genetic algorithm (NSGA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. The proposed approach employs a diversity-preserving technique to overcome the premature convergence and search bias problems and produce a well-distributed Pareto-optimal set of nondominated solutions. A hierarchical clustering technique is also imposed to provide the decision maker with a representative and manageable Pareto-optimal set. Several optimization runs of the proposed approach are carried out on a standard IEEE test system. The results demonstrate the capabilities of the proposed NSGA based approach to generate the true Pareto-optimal set of nondominated solutions of the multiobjective EED problem in one single run. Simulation results with the proposed approach have been compared to those reported in the literature. The comparison shows the superiority of the proposed NSGA based approach and confirms its potential to solve the multiobjective EED problem.