Abstract
Hybrid renewable energy system (HRES), which combines several renewable power, including photovoltaics (PV) and wind power, and a small portion of power generated by conventional power generators as backups when the renewable power is insufficient, is gaining more popularity over the decades because it has minimal impact on environment and health. However, due to the uncertain amount of power generated by the HRES, the HRES-based power supply can be very unstable. In this paper, we propose a stochastic programming model and apply an analysis methodology to ensure the robust power supply and reduce the power shortage risk for HRES when the distribution of the amount of renewable power is ambiguous. In order to validate the performance of our methodology, we create some realistic-size scenarios to test the model and the proposed analysis methodology. Results show that the instances can be efficiently solved. Finally, we create a decision support system (DSS) that integrate the proposed model and the analysis methodology is developed as an efficient decision tool to enable effective and efficient energy management of HRES. The visualized outputs of DSS allow decision makers to gain better understanding about the management of HRES, facilitating the decision making process.