Electricity Retailer Trading Portfolio Optimization Considering Risk Assessment in Chinese Electricity Market

Abstract The Chinese electricity market underwent a significant reform in 2015 resulting in its complete liberalization on the sell-side. Electricity retailers now seeking to adapt to the electricity market are focused on trading portfolio optimization based on risk assessment, which can be performed by classifying and combining possible electricity purchases and sales on mid-long-term and spot markets. The scenario method is used in this study to simulate random risk variables (the real-time price and user demand), then a comprehensive decision-making/risk assessment model for electricity trading portfolio optimization is established with the goal of profit maximization. The conditional value-at-risk (CVaR) serves as the risk assessment index for electricity purchases and sales. Four combinations of electricity trading modes are assessed as a case study. The most basic trading mode is significantly affected by the risk aversion factor in regards to purchases scale and expected profit, which validates the proposed model. The time-of-use (TOU) price and real-time price guaranteeing the bottom and top price as a transaction mode are found to affect the scale of electricity purchases and the expected profit of the electricity retailer. Proportional distribution plans for three respective retail transactions are determined according to electricity retailers’ different attitudes toward risk.