Optimal design of a university campus micro-grid operating under unreliable grid considering PV and battery storage

Abstract

This paper proposes a novel methodology for redesigning a micro-grid characterized by a heavy reliance on diesel generators due to receiving power supply from an unreliable grid. The new design aims at phasing out the diesel generators and replacing them with a hybrid energy system composed of photovoltaics and a battery storage system. Two optimization approaches are adopted, a heuristic genetic algorithm approach is used to achieve sub-optimal sizing of the hybrid system sources and a rules-based dynamic programming approach to ensure optimal power flow. In order to reduce the computation time, a novel combinational approach employing genetic algorithm, dynamic programming and rules-based algorithm is proposed. The intervention of the dynamic programming for optimal power flow is restricted to certain active hours within a given day, while the rules-based power flow algorithm runs only outside those hours. The study demonstrates that the application of the hybrid system yields minimal operational cost by almost entirely phasing out the diesel generators and significantly reducing the energy purchased from the grid during peak hours. The micro-grid of a university campus is used as a case study where energy and economic indicators are derived to prove the superiority of the proposed techniques.