A Mixed-Integer Linear Optimization Model for Local Energy System Planning Based on Simplex and Branch-and-Bound Algorithms

Abstract

A Mixed-integer linear optimization model is developed to support the decision making for the sustainable use of energy in the local area. It details exploitation of primary energy sources, electrical and thermal generation, enduse sectors and emissions. The model covers both the energy demand and energy supply sides, and can provide valuable information both on the technical options, and on the possible policy measures. By aiming to realize a low-carbon energy system, the proposed optimization process provides feasible generation settlements between utility grid and distributed generations, as well as optimal diffusion of energy efficiency technologies. Moreover, the mathematical methods for solving the developed model are discussed. The focus is paid on the general solution method for mixed-integer linear optimization model including simplex algorithm and branch-and-bound algorithm. By using the suggested solution methods, the local energy system optimization problem is expected to be resolved in a reasonable time with enough precision.