Optimization of a stand-alone photovoltaic–wind–diesel–battery system with multi-layered demand scheduling

Abstract

Abstract Operational and financial optimization of a renewable energy-based stand-alone electricity micro-grid is described. Due to the large problem size in time-series models, we construct the model using mixed integer linear programming (MILP). As the constraints required in this model generally have modest complexity, we were able to perform piece-wise linearization on any non-linear variable relationship. Additionally, controls have also be applied on the demand side. Here, a two stage MILP model has been developed to minimize the overall levelized electricity cost for a micro-grid containing a photovoltaic power source, wind turbine, diesel generator, and an energy storage system. The model aimed to converge on a balance of decision accuracy and computational efficiency. Model outputs were capable of defining both the optimal system sizing and scheduling for each system component, with additional demand management control levers on the loss of power supply probability and load deferring allowance. We believe that this model is one of the first to explore the possibilities of the influences of potential demand management strategies in overall system cost reduction, while presenting a relatively efficient first-pass component sizing for stand-alone micro-grids.