Optimization Portfolio Allocation For Generation Companies Based On Worst-case Conditional Value-at-risk

Electric power market practice "power station and grid apart and bidding for access" reform, electricity will serve as commodity into the market. Meanwhile, power market reform make the members such as generation companies to become the main part of market. The generation companies in the free market can trade independently, so power transactions are diversified way development. There are multiple markets existing in the power market with different price fluctuation and yields random variation characteristics. How generation companies will be limiting power distribution to each market is becoming a hot issue.Gradually open power market will bring high profits but also high risk challenge to generation companies. The generation companies need to establish a suitable bidding strategy to maximize profit at the lowest risk realization. This involves the generation companies’bidding strategy and risk assessment problem, and also is the key and central issue of this paper.Choose a reasonable risk metric factor is the key fact for the generation companies to bid successfully. Worst-case Conditional Value-at-Risk (WCVaR) is selected in this paper, which is better than the traditional mean-variance analysis method and Conditional Value-at-Risk.Based on Worst-case Conditional Value-at-Risk, considering the generation companies’ expected return and risk level, setting up the minimum WCVaR expected yields constrined model, which can make the generation companies minimum risk as while as in guarantee of expectations. Based on this model, the electricity capacities are distributed in time balancing market, spot market, medium-term contract market and forward contracts market, and make the model into linear programming problem, then every market distribution ratio and effective frontier is simulated. The results show that the model is reasonable and effective, and can reflect the generation companies’essential character facing in the market risk, so it can provide bidding decision-making and risk assessment for generation companies.