ABSTRACT

This paper proposes an optimal fuzzy-based coordination approach for thermal generator and solar photovoltaic (PV) plant in a two-area power system. The proposed intelligent coordinator is designed for valid adjustment of integral gain of secondary control loop in thermal generator and the proportional gain in PV plant. The classic controllers are generally applied with a constant gain for nominal operation state of the system. However, the proposed fuzzy method illustrates a favorable performance in load perturbations by fine tuning of classic conventional controllers’ gains. In this study, particle swarm optimization algorithm is used to optimize the fuzzy controller’s scaling factors. To demonstrate the effectiveness of the proposed optimal fuzzy controller, it is applied on a two-area power system with different generation unit in each area. Three scenarios of variations in load and solar radiation are implemented to illustrate the adequate performance of the controller in disturbances. A comparison with two optimization methods, known as firefly algorithm and genetic algorithm, is presented to approve the superiority of the controller.

摘要

本文提出了一种基于模糊的优化协调方法，用于两区域电力系统中的热力发电机和太阳能光伏 (PV) 电厂。所提出的智能协调器设计用于有效调整火力发电机二次控制回路的积分增益和光伏电站的比例增益。经典控制器通常以恒定增益用于系统的标称运行状态。然而，所提出的模糊方法通过微调经典传统控制器的增益来说明负载扰动的良好性能。在这项研究中，粒子群优化算法被用来优化模糊控制器的比例因子。为了证明所提出的最优模糊控制器的有效性，它被应用于一个两区域电力系统，每个区域都有不同的发电机组。实施了负载和太阳辐射变化的三种场景，以说明控制器在干扰中的适当性能。通过与萤火虫算法和遗传算法两种优化方法的比较，验证了控制器的优越性。