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Teaching-Learning-Based Optimization Algorithm for the Combined Dynamic Economic Environmental Dispatch Problem

机译：基于教学的动态经济环境派出问题的教学优化算法

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摘要

The Dynamic Economic Environmental Dispatch Problem (DEEDP) is a major issue in power system control. It aims to find the optimum schedule of the power output of thermal units in order to meet the required load at the lowest cost and emission of harmful gases. Several constraints, such as generation limits, valve point loading effects, prohibited operating zones, and ramp rate limits, can be considered. In this paper, a method based on Teaching-Learning-Based Optimization (TLBO) is proposed for dealing with the DEEDP problem where all aforementioned constraints are considered. To investigate the effectiveness of the proposed method for solving this discontinuous and nonlinear problem, the ten-unit system under four cases is used. The obtained results are compared with those obtained by other metaheuristic techniques. The comparison of the simulation results shows that the proposed technique has good performance.
机译：动态经济环境调度问题（DEEDP）是电力系统控制的主要问题。它旨在找到热部件的功率输出的最佳时间表，以满足最低成本和有害气体排放的所需负载。可以考虑几个约束，例如生成限制，阀点加载效果，禁止的操作区域和斜率限制。在本文中，提出了一种基于教学的优化（TLBO）的方法，用于处理所有上述约束的DEEDP问题。为了研究求解这种不连续和非线性问题的提出方法的有效性，使用了四种情况下的十单位系统。将得到的结果与其他成式技术获得的结果进行比较。仿真结果的比较表明，所提出的技术具有良好的性能。

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