Development of a stochastic simulation–optimization model for planning electric power systems – A case study of Shanghai, China

In this study, a stochastic simulation–optimization model (SSOM) is developed for planning electric power systems (EPS) under uncertainty. SSOM integrates techniques of support-vector-regression (SVR), Monte Carlo simulation, and inexact chance-constrained programming (ICP) into a general framework. SVR coupled Monte Carlo technique is used to predict the electricity consumption amount; ICP is effective for reflecting the reliability of …