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The fluctuation of energy price and the expensive energy cost during the peak period will affect the living cost of users, and transmission congestion will also bring additional transmission costs. To solve this problem, this paper establishes the demand response model of energy users. Users can obtain a lower energy price by adjusting their replaceable load and price load. This paper uses cooperative game pricing method to solve the problem of congestion cost allocation. In order to ensure the privacy and independence of the energy system, the alternating direction method of multipliers is proposed to decouple the integrated energy system. The model is verified in the integrated energy system of IEEE 14-node electricity system and 14-node natural gas system. Simulation results show that the algorithm has convergence and can reduce the cost of user participation in demand response. • ADMM divides IES into two subsystems: electricity system and natural gas system. • Shapley value method is used to allocate congestion cost and improve social welfare. • Users participate in demand response to alleviate transmission congestion. • Consider the discomfort cost of energy use, making the user cost more accurate. [ABSTRACT FROM AUTHOR]

• A newly defined concept of predictive transmission security margin (PTSM) is presented accounting for the risk of uncertainty-induced congestion. • By incorporation of PTSM, the risk-averse UC and real-time thermal re-dispatch are formulated as a bi-level optimization model. • Quantification of PTSM can be exactly characterized given the impacts of thermal re-dispatch on the ex-post line flows in a probabilistic manner. • Transmission flexibility is gained economically by procuring PTSM for the alleviation of congestion and reserve undeliverability. Optimal scheduling of generation and transmission resources in the day-ahead market is vital for the assurance of operational reliability in the case of with high wind penetration. To mitigate the ramifications of wind power uncertainty, this paper presents a risk-averse approach for the unit commitment (UC) model in a two-settlement market. A newly defined concept of predictive transmission security margin (PTSM) is formulated in the UC, which provides a measure for the risk margin of transmission congestion while accounting for wind power forecast error and contingencies. These procured PTSMs on each line are dynamically characterized based on the statistics of ex-post line flows in the real-time re-dispatch. The proposed framework is formed as a bi-level optimization problem, and is transformed into a mixed integer programming formulation using Karush–Kuhn–Tucher (KKT) optimality conditions for computational tractability. The effectiveness of the proposed method is tested using various case scenarios on a modified IEEE RTS 24-bus and a 118-bus system in terms of key performance metrics, including the total operation cost, congestion hours, and required and undelivered generation reserves. The results show that the proposed method can effectively reduce the total operation costs by suppressing congestion risk and improving reserve deliverability. [ABSTRACT FROM AUTHOR]