储能
交流电源
光伏系统
工程类
谐波
逆变器
功率因数
最大功率点跟踪
风力发电
控制理论(社会学)
计算机科学
电气工程
汽车工程
功率(物理)
电压
量子力学
物理
人工智能
控制(管理)
作者
Papumoni Saikia,Niloy Kumar Das,Mrinal Buragohain
标识
DOI:10.1016/j.rser.2023.114079
摘要
Energy storage systems (ESS) have become a conspicuous research hotspot since they store power and supply it during peak hours. Existing storage systems must be replaced by advanced energy storage with improved performance, energy management, and a control interface due to issues with size, dependability, and charging/discharging. The suggested robust energy retention system uses a battery and a super-capacitor to generate power from wind and solar energy. A Multiport DC converter with a buck-boost capacitor is used to properly discharge the stored energy to DC loads via a DC bus. The inverter is then delivered to a Power Flow Controller (PFC) and a Voltage Source Inverter (VSI). The Gravitational Search Algorithm (GSA) method optimizes the power controller settings based on the fluctuation of the system's active and reactive power. The optimization method ensures improved power flow while dealing with the least amount of power variance in imbalanced load situations. Based on the power variation, the proposed method generates appropriate control signals for the inverter system. The covers convert the inverter and reduce harmonics with a controller. Furthermore, the inverter AC supplied to the AC bus is converted into reactive power by an inductive load, and unwanted signals and harmonics are extracted using a Cascaded C-type filter. As a result, the described method has preserved total harmonic distortion, electrical efficiency, and finer transient stability.
科研通智能强力驱动
Strongly Powered by AbleSci AI