A Chance-Constrained Interval-Inexact Energy Systems Planning Model (CCIESM) for City B Based on Power Demand Probabilistic Forecasting

Abstract

Energy management systems (EMS) are fraught with uncertainties, while current EMS models always deal with deterministic factors. The uncertainties in EMS could be expressed as interval values and probabilistic distributions. To tackle these uncertainties within EMS, a chance-constrained interval-inexact energy system planning model (CCIESM) was developed in this study, and the probability distribution of power demand was addressed with CCP, and …