Development of a Load Management Algorithm Using Nonlinear Programming (NLP) for Optimum Integration of Electric-Mobility Solutions into Rural Off-Grid PV Systems

Abstract:
The electric output and efficiency of the Photovoltaic (PV) devices are strongly dependent on metrological variables such as solar irradiation, wind speed and ambient temperature. It is therefore important to optimise the size and electrical loads of an off-grid PV system to meet the required load demands at least cost. However, sizing results dependent on the energy management techniques used for operating the system, especially when considering components with different dynamics. This paper presents an off-grid PV system modelling and simulation approach using MATLAB / Simulink CARNOT 7.0 toolbox including a load management methodology using nonlinear programming (NLP). For a better integration of electric mobility into the off-grid PV system with battery storage operation, an optimisation problem was formulated which resulted in a nonlinear programming problem. The optimisation model was developed to solve the NLP problem and to optimise electric loads including electric mobility and battery storages in order to properly utilise the PV generation, thereby reducing energy deficit and cost. Metrological hourly dataset for a complete year was used for successful simulation of the PV system. A sensitivity analysis of the NLP optimisation model was carried out to evaluate the impact of the electric loads (kWh) on the objective function.