Stochastic Expansion planning Model for a coordinated Natural gas and Electricity Networks Coupled with Gas-fired Generators, Power-to-Gas Facilities and Renewable Power

Abstract

This paper presents a stochastic expansion planning model for coordinated natural gas and electricity networks, incorporating gas-fired generators, Power-to-Gas facilities, and renewable power sources. The primary objective is to minimize the total cost over the planning horizon, addressing the significant interdependencies between these networks which, if planned independently, can lead to higher overall costs. The originality of this work lies in its comprehensive integration of both systems, leveraging their synergies to optimize infrastructure investment and operational efficiency. Methodologically, the model employs mixed integer linear programming (MILP) within the General Algebraic Modelling System (GAMS), using a Scenario Tree concept to account for the stochastic nature of renewable energy sources (RESs) and load variations. Data from an adapted twenty-node Belgium gas network and a sixteen-bus UK electricity distribution system were utilized. Results demonstrate substantial cost savings and improved system performance with the integrated approach, validating the model's effectiveness.