Optimal economic designing of grid-connected photovoltaic systems with multiple inverters using linear and nonlinear module models based on Genetic Algorithm

Nowadays installed power capacity of grid-connected photovoltaic (GCPV) systems has an exponential increase around the world. Since these systems are more expensive than other conventional electricity resources, optimal economic designing is much necessary. In this paper, a new intelligent-based approach is proposed to design GCPV systems using Genetic Algorithm (GA). By defining the net present value (NPV) of system as the objective function and considering electrical constraints, the optimal value for sizing factor and also system configuration are determined. In order to calculate the annual produced energy of system with high accuracy, the accurate efficiency model and power equations are used for inverter and PV module, respectively. Also, five-parameter, i.e. linear and five-point, i.e. nonlinear, models of PV module are used to evaluate the behavior of PV array in different temperature and solar radiation conditions. This approach is presented for GCPV systems in all sizes including two or more inverters even with different topologies. The proposed method is applied for designing of a power plant system with multiple inverters.