An MILP Model for the Optimization of Hybrid Renewable Energy System

This paper explores the possibility of utilizing a region's renewable resources to satisfy its energy demand. The proposed approach uses bi-objective optimization to estimate both the economic and environmental impacts of a hybrid renewable energy system. The considered renewable energy resources are lignocellulosic biomass, solar and wind energy. The approach uses a mixed-integer linear programming (MILP) model which enables selection of technology, capacity and location of the facilities for production of renewable energy. It determines the capacity of storage facilities for both biomass and fuel products and the capacity of the transportation links. The economic criterion used is the total cost of the hybrid renewable energy system (HRES) which includes the installation, operation and maintenance cost of the conversion facilities and total transportation cost. To measure the environmental impacts, the total annual CO2-equivalent GHG emission is used. The Pareto front was generated by epsilon-constraint method. The proposed approach was applied for County of Surrey in the South East of England.