Unit commitment of integrated energy system considering conditional value-at-risk and P2G.

• Quantifying the uncertainty of wind power through the use of CVaR and its admissible range, which allows for the direct consideration of wind power uncertainty within the IES UC model. • Developing an IES UC model that accounts for the CVaR of wind power, with the objective of minimizing the sum of the total system operating cost and the CVaR of wind power. • Solving the nonlinear components of CVaR through piecewise linear approximation and handling the flow constraints of the natural gas pipeline using an incremental linearization method, resulting in the transformation of the proposed model into a MILP problem. To address the formidable challenges posed by wind power grid connection and minimize the operational risks arising from wind power fluctuations, this paper proposes an IES-UC optimization model that incorporates power-to-Gas (P2G) and wind power conditional value at risk (CVaR). To start, the uncertainty of wind power is analyzed through the application of CVaR theory, while P2G methods are employed to reduce wind power curtailment and power storage devices are utilized to mitigate the operational risks due to wind power fluctuations. Next, to adequately exploit the flexibility inherent in the gas-thermal dynamic process and enhance the system's flexibility and wind power accommodation capacity, the dynamic transmission equations of the gas and thermal networks are derived through a thorough examination of the dynamics of the gas-thermal network. Finally, to increase computational efficiency, the nonlinear integral term of the CVaR model is linearized via piecewise linearization, transforming the model into a mixed integer linear programming (MILP) problem. The validity and feasibility of the proposed model have been demonstrated through simulations on 6–6–8 and 118–20–16 test systems. [ABSTRACT FROM AUTHOR]