Risk Dispatch for a Combined Electricity and Heating System with Unimodal Distribution

Considering the uncertainty of renewable energy sources (RESs) integrated into sustainability-driven combined heat and power systems (CEHS), the stochastic forecast error of wind power can produce an overlimit operational risk. An appropriately quantified risk is the key to achieving controllable risk and economic dispatch. This study proposes a risk dispatch model for CEHS to determine the optimal dispatch with uncertain RES. Firstly, moment-based ambiguity can be constructed with unimodal information, which is estimated from historical data. The ambiguity underscores the inherent uncertainty associated with wind power. The DRCC is present to show the operational risk induced by uncertain wind power. Linear decision rules are utilized to improve the computational efficiency of the proposed method. Secondly, risk indices are proposed to quantify the risk level. We used the probability of chance constraint violation to describe the mean risk probability. The mean cost of risk dispatch for the CEHS can reflect the risk dispatch cost. Finally, numerical results derived from the real-world Barry Island system illustrate the influence of the risk coefficient on the risk indices. Selecting ε=0.2 can bridge the gap between risk control and economic dispatch.