A Novel Energy Management Scheme using ANFIS for Independent Microgrid

Abstract

In this paper an energy management technique for Hybrid Renewable Energy System (HRES) connected with AC load using Adaptive Neuro Fuzzy Interference System (ANFIS) is proposed. This algorithm is developed with an aim of increasing the power transfer capability between the source side and load side and it offers several benefits like the enhanced predicting capability, degradation in complexity as well as the randomization and so forth. In this work, photovoltaic (PV) system, Wind Generating System (WGS), Fuel Cell (FC), Ultra Capacitor (UC) and the battery are considered as the energy sources. The ANFIS technique is trained with the inputs such as the previous instant energy of the available sources and the required load demand of the current time and the corresponding target reference power of the sources. According to the load variation, the proposed method makes the appropriate control signals at the testing time to manage the energy of the HRES. A STATCOM based voltage regulation and harmonic mitigation is introduced. The implementation of the system elements and control method has been done in MATLAB/Simulink and the performance of the proposed method is analysed by using different environmental and load test conditions. The results of the test cases confirms that the control technique proposed is effectual in prediction of energy required for the next instant and manages the energy flow among HRES power sources and energy storage devices. In this paper an energy management technique for Hybrid Renewable Energy System (HRES) connected with AC load using Adaptive Neuro Fuzzy Interference System (ANFIS) is proposed. This algorithm is developed with an aim of increasing the power transfer capability between the source side and load side and it offers several benefits like the enhanced predicting capability, degradation in complexity as well as the randomization and so forth. In this work, photovoltaic (PV) system, Wind Generating System (WGS), Fuel Cell (FC), Ultra Capacitor (UC) and the battery are considered as the energy sources. The ANFIS technique is trained with the inputs such as the previous instant energy of the available sources and the required load demand of the current time and the corresponding target reference power of the sources. According to the load variation, the proposed method makes the appropriate control signals at the testing time to manage the energy of the HRES. A STATCOM based voltage regulation and harmonic mitigation is introduced. The implementation of the system elements and control method has been done in MATLAB/Simulink and the performance of the proposed method is analysed by using different environmental and load test conditions. The results of the test cases confirms that the control technique proposed is effectual in prediction of energy required for the next instant and manages the energy flow among HRES power sources and energy storage devices.