Volume 50

Power Generation Investment Portfolio Optimization under Output and Price Uncertainties Xianyang Zhou, Dequn Zhou, Hao Ding

Abstract

For power generation compony, decisions are made rely on regulation, policy, capacity factor and company’s financial situation. The coupled use of multiple energy sources can take advantage of the complementarity of multiple energy sources to improve energy efficiency. However, the increasing number of renewables and multi-energy loads entering the energy system increases the multiple uncertainties of energy system. These decision models must capture the challenge induced by the penetration of renewable energy (RE) and the role of energy storage. In this paper, we establish a two-stage stochastic optimization model and apply Latin hypercube sampling (LHS) to dealing with correlated random variables and study the investment portfolio among conventional power generators and renewable energy with different levels of volatility. Then, multi-dimensional correlation scenario set are generated to confirm the applicability of the model. The results shown that the volatility of renewable energy increases the proportion of flexible scheduling units in the system as well as the system cost in investment and operation. Energy storage capacity is being used to address intermittence of RE to make power system stable.

Keywords Renewable energy resources, expansion stochastic planning, capacity investment, uncertainty, representative day selection