Optimal Planning of PV and Battery Resources in Remote Microgrids Considering Degradation Costs: An Iterative Post-Optimization Correction-based Approach

The benefits of shifting to renewable energy sources have granted microgrids considerable attention, especially photovoltaic (PV) systems. However, given the inherent variable and intermittent nature of solar power, battery energy storage systems (BESS) are pivotal for a reliable and cost-effective microgrid. The optimal sizing and energy scheduling of PV and BESS pose significant importance for minimal investment and operational cost. The associated costs of degradation for both these sources further add complexity to the overall planning problem. This paper proposes a microgrid resource planning model for determining the optimal PV and BESS sizes in combination with natural gas generators, considering their technical and financial characteristics as well as the degradation costs of both PV and BESS. Its objective is to minimize the microgrid-wide total operational and capital cost. The optimization model is formulated using mixed-integer linear programming to ensure the resource sizing problem converges with a reasonably small optimality gap. In addition, an iterative post-optimization BESS degradation cost correction algorithm is proposed for enhanced accuracy. The results showcase the savings in the overall objective cost and reductions in solar energy curtailment upon BESS's inclusion.