Techno-Economic Optimization of a Stand-alone PV/PHS/Battery systems for very low load situation

In much of the sizing problems of hybrid renewable energy system addressed so far, the emphasis has mostly been on optimizing the cost of energy and finding capacity of the feasible components. However there is hardly any literature on the optimal sizing of renewable energy system (RES) for very low load situation. The objective of this paper is to study the feasibility of pumped hydro storage (PHS) based photovoltaic (PV) RES for a very low load (maximum demand less than 30 kW) and also to study the integration of battery storage into the PV/PHS system, only to optimise and make the whole system cost effective and storage practically realizable. The modelling for components sizing of the RES is first discussed. Then the individual RESs are techno-economically optimized taking levelized cost of energy (COE) as the objective function at 100% reliability, i.e. 0% unmeet energy (UE) condition. In this, three optimization algorithms, namely genetic algorithm (GA), Firefly Algorithm (FA), and Grey Wolf Optimization (GWO) are implemented for optimal sizing of the PV and the storage units , and their performances are compared by applying them to an institutional academic block in India. It is shown that combined PV, PHS, and battery based RES is the optimal solution for the given low load situation. And GWO is the best optimization algorithm in terms of convergence rate as well as the COE and reliability. The results also demonstrate that utilizing a small battery bank with the PHS greatly reduces the upper reservoir capacity , with least generation of excess energy . Further, the optimal solution has also improved the low load factor of the academic block. Thus the present research contributes as a useful reference to the sizing problem of RES for a very low load situation by solving using a single resource PV based RES with two different reliable storage systems .