Optimal utilization of interconnected RESs to microgrid: a hybrid AWO-ANFIS technique

This dissertation proposes an elite converter for the optimal utilization of hybrid renewable energy sources in the microgrid-associated systems using hybrid technique. Microgrid (MG)-associated systems are photovoltaic, wind turbine and battery. The proposed elite converter is the high conversion ratio (HCR) DC–DC converter with a maximum power point tracking (MPPT) controller. The main advantage of the converter is to eliminate the problem of high switch voltage stress. The proposed hybrid technique is the joint execution of both the adaptive whale optimization algorithm (AWOA) and adaptive neuro-fuzzy interference system (ANFIS), and hence, it is named as AWO-ANFIS technique. Here, AWOA technique is utilized to establish the exact control signals based on the power variation between the source side (renewable energy sources and battery) and load side. ANFIS technique is utilized for error minimization by using the achieved dataset from AWOA technique. Here, the reference currents of the controller are managed in view of the MPPT for solar and wind energy. In the proposed technique, the objective function is defined by the system data subject to equality and inequality constraints. Finally, the proposed technique is executed in the MATLAB/Simulink working platform and the execution is compared with the existing techniques. To test the performance of the proposed method, different case studies are conducted such as variation of irradiance under constant wind speed, variation of PV power under constant irradiance and load variation under constant irradiance and wind speed. For all the cases, the response of current, voltage and power of all the sources is analyzed and compared with that of the existing techniques such as GA, PSO and WOA. The statistical analysis of the proposed technique is also analyzed. Likewise, the computation time using various trails such as 100, 250, 500 and 1000 is also analyzed. The comparison results affirm that the proposed technique has less computational time than the exiting techniques. Moreover, the proposed method is cost-effective power production of MG and effective utilization of renewable energy source without wasting the available energy.