An adaptive Marine Predators Algorithm for optimizing a hybrid PV/DG/Battery System for a remote area in China

Abstract

Lack of electricity networks in remote areas and also the high cost of connecting these areas to national networks due to the unfavorable geographical situation of the region leads to the use of other energy sources independent of the network in these areas. Today, the use of distributed generation sources is increasing due to the reduction of fossil fuel sources and heat problems. The output power of distributed generation sources, especially renewable energy sources, fluctuates under the influence of atmospheric conditions. The main purpose of the present study is to present a new optimal configuration for a hybrid photovoltaic/diesel generator/battery system to refine the load demand of a rural area in Hoxtolgay, China. The idea is to minimize the CO2 emissions value, the annualized cost, and the loss of load probability of the system. To simplify this system, ɛ-constraint method is performed. The problem has been solved by an adaptive version of Marine Predators Algorithm (AMPA) to improve the optimization results. The total ACS for the optimal system is achieved 8224.15 $. Also, an optimal value of 451.30 kW for diesel generator, 4266$ for battery storage, and 2670.53 $ for PV generator are achieved. The initial capital cost of the system is achieved 47940 $ that is less than the NPC. In this case, the maximum cost of the system with 43.12% belongs to the PV system of total cost of the system. Finally, CO2 emission by the suggested AMPA with 1624 kg/year shows the minimum value with cleanest result among the others. Final results of the proposed technique are compared with PSO method and HOMER-based optimization to indicate its effectiveness. Sensitivity analysis has been also performed to determine the system efficiency.

Keywords

• Hoxtolgay
• Hybrid renewable energy system
• Multi-objective optimization
• Battery energy storage system
• Photovoltaic
• Diesel generator