Risk assessment of park-level integrated energy system considering uncertainty and dynamic correlation of energy prices

Abstract

The planning of the park-level integrated energy system (PIES) is a long-term process, it faces risk caused by the volatility of energy prices including the natural gas price (NGP) and the electricity price (EP). The uncertainties of them are complex and have time-varying correlation, which influence the results of risk losses evaluation. To resist the future risk and guide the planning of PIES, a risk assessment method considering the uncertainty and dynamic correlation of energy prices is proposed in this paper. Considering the heteroscedasticity effect of NGP and EP, the time-varying marginal distribution models of them are established using the generalized autoregressive conditional heteroscedasticity (GARCH) model. Subsequently, resorting to the dynamic Copula function and dynamic conditional correlation (DCC) model, the dynamic joint distribution of NGP and EP is established, which describes the dynamic correlation of NGP and EP. On this basis, the Monte Carlo method is adopted to generate scenarios of NGP and EP to simulate possible situations. Then, the conditional value at risk (CVaR) is introduced as the risk measure to quantify the risk losses for the PIES planning schemes. Simulation results verified the effectiveness of the proposed method, which can present different correlation features of energy prices in different time periods and beneficial to evaluate the risk losses. And the utilization of multi-energy complementary supply and distributed renewable energy can improve the risk-resistant ability of the PIES.

Keywords

• Park-level integrated energy system
• Risk assessment
• Uncertainty
• Generalized autoregressive conditional heteroscedasticity (GARCH)
• Copula function
• Conditional value at risk (CVaR)