A Multi- Objective Stochastic Programming Model for Power Capacity Planning with Sample Average Approximation Approach and Quantile Method

Abstract

This paper, develop a linear stochastic programming model. The objective of model is planning for power energy capacity for facing with demand. In this model, capacity decisions are made to select the time, the location and the type of equipment for power transmission and generation expansion and also try to demand side management. The purpose of model is making decision for construction and expansion of region’s capacity by an incorporated pattern. In this study, planning horizon is 10 years. Demand and outage are considered as an uncertain factor. Attention to different way of facing with demand, demand side management and outage together are the innovations of this research. Designed model centralize in economic, environmental and sociable factors. The results are anticipation of needed capacity, planning for making power plant, providing transmission base and development of demand side management in order to increase social satisfaction. However the remaining sections described the review of capacity planning and assigned the affecting factors on it. Then formulated a linear multi-objective stochastic optimization model and optimal solutions are founded base on sample average approximation.

Keywords

• capacity planning
• multi-objective stochastic model
• sample average approximation method
• quantile method