Optimal cost and feasible design for gridconnected microgrid on campus area using the robust-intelligence method

In this paper,a robust optimization and sustainable investigation are undertaken to find a feasible design for a microgrid in a campus area at minimum cost.The campus microgrid needs to be optimized with further investigation,especially to reduce the cost while considering feasibility in ensuring the continuity of energy supply.A modified combination of genetic algorithm and particle swarm optimization(MGAPSO)is applied to minimize the cost while considering the feasibility of a grid-connected photovoltaic/battery/diesel system.Then,a sustainable energy-management system is also defined to analyse the characteristics of the microgrid.The optimization results show that the MGAPSO method produces a better solution with better convergence and lower costs than conventional methods.The MGAPSO optimization reduces the system cost by up to 11.99%compared with the conventional methods.In the rest of the paper,the components that have been optimized are adjusted in a realistic scheme to discuss the energy profile and allocation characteristics.Further investigation has shown that MGAPSO can optimize the campus microgrid to be self-sustained by enhancing renewable-energy utilization.