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Optimization of automatic regulator settings of the distributed generation plants on the basis of genetic algorithm

机译:基于遗传算法的分布式发电厂自动调节器设置优化

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The smart grid concept envisages the creation of a developed automatic control system of the electric power system operation that involves a wide application of distributed generation plants integrated into the energy clusters. These technologies are fully applicable to the railway electricity supply systems (RESS) which are mainly intended for the reliable high quality electricity supply of the traction consumers (trains) as well as non-traction and non-transport ones. For effective operation of the distributed generation plants, it is necessary to solve the problem of the optimal tuning automatic excitation regulators (AER) and automatic speed regulators (ASR), taking into account the specific features of RESS. The paper presents a description of an adaptive genetic algorithm for solving the problems of settings optimization for AER and ASR of the distributed plant turbine generators operating in RESS. The studies of computer models of electric power systems with distributed generation plants in MATLAB show that the AER and ASR tuning coefficients calculated with the proposed adaptive genetic algorithm provide the required stability margin, good damping electromechanical oscillations and standard power quality values in the power supply system of non-traction consumers.
机译:智能电网概念设想了电力系统运行的开发自动控制系统的创建,该系统涉及集成到能源集群中的分布式发电厂的广泛应用。这些技术完全适用于铁路供电系统(RESS),该系统主要用于为牵引用户(火车)以及非牵引和非运输用户提供可靠的高质量电力供应。为了使分布式发电站有效运行,有必要考虑RESS的特定功能来解决优化调谐自动励磁调节器(AER)和自动速度调节器(ASR)的问题。本文介绍了一种自适应遗传算法,用于解决在RESS中运行的分布式植物涡轮发电机的AER和ASR设置优化的问题。在MATLAB中对具有分布式发电装置的电力系统的计算机模型进行的研究表明,通过提出的自适应遗传算法计算出的AER和ASR调整系数提供了供电系统所需的稳定性裕度,良好的机电振动阻尼和标准电能质量值非牵引式消费者。

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