In this investigation, nature-inspired heuristic strategy exploiting moth flame optimization (MFO) algorithm combined with active-set algorithm (ASA), interior point algorithm (IPA) and sequential quadratic programming (SQP) are presented to take care of the enhancement issues of economic load dispatch (ELD) problem involving valve point loading effect (VPLE) and stochastic wind (SW). The strength of MFO algorithm is used as a global search mechanism that explore and exploit the entire search space while ASA, IPA and SQP are responsible for refinement of local optimum. The performance of the design system is based on 40 generating units including 37 thermal and 3 wind power units and is evaluated to verify the effectiveness of the scheme. The worth of the design integrated heuristic of MFO algorithm is endorsed through outcomes of the state of the art counterpart solvers in case of ELD problems integrated with wind power units in terms of cost minimization and computational complexity parameters.

在这项研究中，提出了结合蛾类火焰优化（MFO）算法，活动集算法（ASA），内部点算法（IPA）和顺序二次规划（SQP）的自然启发式启发式策略，以解决以下问题：经济负荷分配（ELD）问题，涉及阀点负荷效应（VPLE）和随机风（SW）。MFO算法的优势被用作一种全局搜索机制，可以探索和利用整个搜索空间，而ASA，IPA和SQP则负责优化局部最优。设计系统的性能基于40个发电机组，包括37个火力和3个风力发电机组，并进行了评估以验证该方案的有效性。