Risk-constrained multi-period planning for park-level integrated energy system based on CVaR method

Abstract

The planning of park-level integrated energy system (PIES) is a long-term process, which needs to meet the increasing growth loads and faces the planning cost risk caused by energy price fluctuation during the planning period. It needs to be gradually implemented in multiple periods. Therefore, this paper proposes a risk-constrained multi-period planning model of PIES considering the uncertainties of natural gas price (NGP) and electricity price (EP). The marginal probability distribution model of NGP and EP is established, respectively. On this basis, Monte Carlo simulation (MCS) is used to generate a number of scenarios of NGP and EP to characterize their uncertainties. Conditional value at risk (CVaR) is adopted as the risk measure, and risk-constrained multi-period planning mode of PIES is established. The generated price scenarios are brought into the multi-period planning model, and the equipment capacity allocation of each planning period is obtained by optimizing the expectation of the total cost of investment cost and operational cost. Case study verifies the effectiveness of the proposed method.