Sizing and Optimization of Solar PV and Wind Power with Energy Storage Systems

The ever-increasing trend in installing renewable energy sources (RESs)-based assets like solar photovoltaic (PV) and wind turbines (WTs) has started changing the power system nature and also bringing new challenges in the planning and operation of such systems. Residential PV units, WTs, and battery energy storage systems (BESSs) have been introduced as crucial components of modern power systems. Such generation and storage technologies are being utilized to maximize local power generation and mitigate the dependency on electrical grids to supply the required electrical power. Nevertheless, the economic viability of such systems has remained controversial mainly because of substantial capital costs, system degradation, and also fluctuating energy tariffs. Accordingly, this master’s thesis proposes a comprehensive tool for optimally sizing small-scale PV, BESSs, and WTs by taking into consideration different energy tariffs, degradation of the BESSs, and intermittent renewable power generation. This thesis is primarily aimed at optimally determining the size of PV, wind turbine, and BESS, so that the net present value (NPV) of the system is maximized. The mentioned framework is coded in MATLAB, and an advanced optimization technique, e.g. NOMAD solver in the OPTI toolbox in MATLAB has been employed to provide a robust techno-economic analysis for residential and small commercial applications. It is worth mentioning that this thesis has further developed the open-source optimization tool to also account for small-scale WTs and different cases. In this respect, the obtained simulation results indicate that by optimally sizing the PV, BESSs, and WTs, and by taking into account the local market conditions, the economic return on such systems can be remarkably enhanced. Moreover, the simulation results show the profitability of these systems in the long term. This master’s thesis contributes to the body of research in this field by investigating a practical solution for maximizing the economic and technical performance of small-scale PV, WT, and BEESs. The obtained results give meaningful perspectives for the residential sector, policymakers, and energy system planners, to make more informed decisions on RESs.