A Two-Stage Chance-Constrained Stochastic Programming Model for Electricity Supply Chain Network Design: a Case Study

Development of every society is dependent on the technological and economic effectiveness of energy sector. The electricity industry is growing and needs to have a better performance to cover the demand effectively. This industry is required to make a balance between cost and efficiency through careful design and planning. In this paper, a two-stage stochastic programming model is presented for the design of the electricity supply chain network. The proposed network consists of power stations, transmission lines, substations, and demand points. While minimizing costs and maximizing the grid effectiveness, this paper seeks to determine time and location of establishing new facilities as well as capacity planning for facilities. The chanceconstrained optimization method is used to satisfy the uncertain demand with high probability. The proposed model is validated through a case study on Southern Khorasan Province’s power grid network; the computational results show that the reliability rate is a crucial factor that greatly affects costs and demand coverage.