用改进Hopfield神经网络求解经济负荷调度组合优化问题

D. Gupta, S.K. Jain
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引用次数: 4

摘要

求解经济负荷调度的组合问题,在满足电力平衡方程的情况下,找出成本最小或排放水平最小的发电水平。将环境排放水平作为成本优化问题的约束条件。本文尝试使用改进的Hopfield神经网络(MHNN)来解决上述问题,该网络具有将目标函数和约束分开处理的灵活性,并以能量函数最小为原则,从而保证了收敛性。以SOx和NOx排放为约束,对成本优化、NOx排放优化、SOx排放优化和成本优化进行了研究。给出了考虑损耗和忽略损耗的标准3-发电机数据的仿真结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Solving Combinatorial Optimization Problem of Economic Load Dispatch Using Modified Hopfield Neural Network
The combinatorial problem of the economic load dispatch is solved to find the generation levels that minimize the cost or minimize the emission level while satisfying the power balance equation. The environmental emission levels are also taken as the constraints in cost optimization problem. The solutions to the above problems is attempted using modified Hopfield neural network (MHNN), which has the flexibility of handling objective function and the constraints separately and works on the principal of minimizing the energy function and therefore ensure convergence. The study is carried out for cost optimization, NOx emission optimization, SOx emission optimization and cost optimization with SOx and NOx emissions as constraint. The simulation results are presented for standard 3-generator data while considering the losses and neglecting them.
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