Stochastic expansion planning of integrated energy system: A benders-based decomposition approach

Abstract

This paper introduces a two-stage stochastic optimization model for the renewables-transmission expansion planning (RTEP) problem to obtain the optimal size and site of the renewable energy generating unit, as well as the investment decisions related to transmission lines and gas pipelines. The uncertainties associated with demand growth and stochastic renewable sources production levels are considered via a series of scenarios, and then, the scenario-reduction approach, i.e., the k-medoids method, is applied to reduce the computation burden. In addition, the gas flow-pressure difference steady-state formulations in the expansion planning model are reconstructed convexly using second-order cone constraints. A Benders-based decomposition method is adopted as a solution methodology in the co-planning problem. The proposed model was simulated on a modified IEEE 39-bus and Belgian gas-20 energy test network, and the simulation results validate the correctness and applicability of the presented approaches.