Economic load dispatch problems are most important in operation and management of the electric power systems which are formulated as optimization problems. Modern deterministic and stochastic optimization techniques are efficient in solving economic load dispatch problems without any limitation because of their capability to seek the global optimal solution. Economic load dispatch problems involve linear equality constraints which are difficult to handle along with discontinuous, non-differentiable and highly non-linear objective functions. The problem becomes challenging for optimization techniques, especially for deterministic methods. This study presents a new approach based on a hybrid algorithm consisting of Genetic algorithm and modified Hooke and Jeeves method to solve the economic load dispatch problems with equality constraints. The performance of proposed Algorithm is tested on five generating systems with valve-point effects. Test results of proposed technique are quite promising and effective, with good convergence property and generation cost to produce better quality solution compared with several state-of-the-art methods.

经济负荷分配问题在电力系统的运营和管理中最为重要，这些问题被表述为优化问题。现代的确定性和随机性优化技术可以有效地解决经济负荷分配问题，因为它们具有寻求全局最优解的能力，因此没有任何限制。经济负荷分配问题涉及难以处理的线性等式约束以及不连续，不可微和高度非线性的目标函数。对于优化技术，尤其对于确定性方法，该问题变得具有挑战性。该研究提出了一种基于混合算法的新方法，该方法由遗传算法和改进的Hooke and Jeeves方法组成，用于解决具有等式约束的经济负荷分配问题。在具有阀点效应的五个发电系统上测试了所提出算法的性能。与几种最新方法相比，所提出技术的测试结果很有希望且有效，具有良好的收敛性和生成成本，可以产生质量更高的解决方案。