热液发电调度的改进粒子群算法

Deepika Yadav, R. Naresh, Veena Sharma
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引用次数: 1

摘要

短期热液调度问题是一个复杂的非线性动态约束优化问题,对电力系统的经济运行起着重要的作用。水热发电调度的目标是在给定的电力负荷和有限的水资源条件下,通过优化调度所有水热机组的输出功率,使总体运行成本最小化,并满足给定的约束条件。提出了一种改进的粒子群优化算法(IPSO),用于求解固定水头热水系统中考虑阀点负荷的STHTS问题。其他各种启发式算法,如基本粒子群算法、改进粒子群算法、差分进化算法、实变量遗传算法(RVGA)等,也在同一问题上实现。在Matlab软件中编写了这些算法的程序。仿真结果表明,基于IPSO的方法能够以较小的计算量提供更好的解决方案。DOI: http://dx.doi.org/10.3126/hn.v15i0.11298 HYDRO Nepal Journal Journal of Water, Energy and Environment卷:15,2014年7月页:65-72
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Particle Swarm Optimization Algorithm for Hydrothermal Generation Scheduling
The short term hydrothermal scheduling (STHTS) problem is a complicated nonlinear dynamic constrained optimization problem, which plays an important role in the economic operation of electric power systems. The objective of hydro thermal generation scheduling is to minimize the overall operation cost and to satisfy the given constraints by scheduling optimally the power outputs of all hydro and thermal units under study periods, given electrical load and limited water resource. This paper presents an improved particle swarm optimization (IPSO) algorithm for solving the STHTS problem considering valve point loading for fixed head hydro-thermal system. Various other heuristic algorithms such as basic PSO, modified PSO, differential evolution, real variable genetic algorithm (RVGA) are also implemented on the same problem. The programs for these algorithms have been developed in Matlab software. From the simulation results, it is found that the IPSO based approach is able to provide a better solution at a lesser computational effort. DOI: http://dx.doi.org/10.3126/hn.v15i0.11298 HYDRO Nepal Journal Journal of Water, Energy and Environment Volume: 15, 2014, July Page: 65-72
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