A hybrid Hopfield neural network-quadratic programming approach for dynamic economic dispatch problem

A. Abdelaziz, S. Mekhamer, M. Kamh, M. Badr
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引用次数: 16

Abstract

This paper introduces a solution of the dynamic economic dispatch (DED) problem using a hybrid approach of Hopfield neural network (HNN) and quadratic programming (QP). The hybrid algorithm is based on using enhanced HNN; to solve the static part of the problem; and the QP algorithm for solving the dynamic part of the DED. This technique guarantees the global optimality of the solution due to its look-ahead capability. The new algorithm is applied and tested to an example from the literature and the solution is then compared with that obtained by some other techniques to prove the superiority and effectiveness of the proposed algorithm.
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动态经济调度问题的混合Hopfield神经网络二次规划方法
采用Hopfield神经网络(HNN)和二次规划(QP)的混合方法求解动态经济调度(DED)问题。该混合算法基于增强的HNN;解决了静态部分的问题;以及求解动态部分的QP算法。由于具有前瞻性,该技术保证了解决方案的全局最优性。将新算法应用于文献中的一个算例进行了测试,并与其他方法的解进行了比较,证明了该算法的优越性和有效性。
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