This article introduces a relatively current method named grasshopper optimization algorithm (GOA) for explaining power system based dynamic economic load dispatch (DELD) problem. However, like other optimization approaches, GOA suffers from premature convergence and a slow convergence rate. Thus, to boost the convergence mobility of GOA, oppositional based learning (OBL) is merged with the GOA approach. Moreover, another improvization, namely, chaotic concept, is also integrated with the GOA to improve its solution quality. The suggested oppositional based chaotic grasshopper optimization algorithm (OCGOA) method is applied to handle the DELD problem in the most efficient manner. Among the renewable energies, intermittent wind energy (WE) is the most sustainable one and remains technically and economically advantageous for electrical energy generation. The thermal and wind based power systems are hybridized, so that power generation is distributed among the operating units in an equivalent manner such that overall cost and loss part are optimized until all practical constraints are fulfilled. The production cost of the unpredictable wind generation power is further incorporated in the operational cost by employing a probability density function (PDF) formula. The precision and performance of the suggested GOA and OCGOA approaches are validated on 6-unit and 10-unit DELD systems for conventional and wind based energy systems. The efficacy and performance of the suggested OCGOA is judged by comparing it with conventional GOA and other presently developed meta-heuristic optimization techniques found in the literature.

中文翻译：

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基于对立混沌蚂蚱优化算法的混合风力发电系统动态经济调度问题

本文介绍了一种相对最新的方法，称为蚱grass优化算法（GOA），用于解释基于电力系统的动态经济负荷分配（DELD）问题。但是，像其他优化方法一样，GOA也存在过早收敛和收敛速度慢的问题。因此，为了提高GOA的收敛性，将基于对立的学习（OBL）与GOA方法合并。此外，GOA还集成了另一种即兴概念，即混沌概念，以提高其解决方案质量。提出了一种基于对立的混沌蚂蚱优化算法（OCGOA），以最有效的方式处理DELD问题。在可再生能源中，间歇风能（WE）是最可持续的一种，并且在发电方面在技术和经济上仍然具有优势。基于热力和风力的电力系统是混合的，因此发电以等效方式分配在各个操作单元之间，从而使总成本和损失部分得到优化，直到满足所有实际约束为止。通过采用概率密度函数（PDF）公式，将不可预测的风力发电的生产成本进一步纳入运营成本。建议的GOA和OCGOA方法的精度和性能在常规和基于风能的能源系统的6单元和10单元DELD系统上得到了验证。