Planning and Dispatching of Hybrid Renewable Power System Based on Portfolio Theory

Renewable energies are growing fast and have occupied great percentage in power generation. However, one major drawback of most renewable energies is the variability due to the stochastic nature of wind speed, solar irradiation, and etc. It is important to integrate the risk of wind power's uncertainty into profitability assessments for investors. In this paper, certain effective ideas from portfolio theory in financial engineering field are exploited to deal with renewable energies as risky assets to be invested. It's a systematic way to neutralize risks as well as maximize return values. To adjust these financial tools used to solve renewable energy's problem, some other financial models and concepts are introduced. Time Series models, ARMA (autoregressive moving average), GARCH (generalized autoregressive conditional heteroscedasticity) and PSO (particle swarm optimization) algorithm are utilized to modify data to be real-time effective. Utility function is introduced to evaluate different energy resources. This paper is abundant with interdisciplinary ideas using advanced risk management methods on renewable energy issues. The proposed approach is also applied in real world problem to provide consulting evidence for power system planning and dispatching in Gansu province, northwest of China.