Application of Modified Progressive Hedging for Stochastic Unit Commitment in Electricity-Gas Coupled Systems

The increasing number of gas-fired units has significantly intensified the coupling between electric and gas power networks.Traditionally,nonlinearity and nonconvexity in gas flow equations,together with renewable-induced stochasticity,resulted in a computationally expensive model for unit commitment in electricity-gas coupled integrated energy systems(IES).To accelerate stochastic day-ahead scheduling,we applied and modified Progressive Hedging(PH),a heuristic approach that can be computed in parallel to yield scenario-independent unit commitment.Through early termination and enumeration techniques,the modified PH algorithm saves considerable com,putational time for certain generation cost settings or when the scale of the IES is large.Moreover,an adapted second-order cone relaxation(SOCR)is utilized to tackle the nonconvex gas flow equation.Case studies were performed on the IEEE 24.bus system/Belgium 20-node gas system and the IEEE 118-bus system/Belgium 20-node gas system.The computational efficiency when employing PH is 188 times that of commercial software,and the algorithm even outperforms Benders Decomposition.At the same time,the gap between the PH algorithm and the benchmark is less than 0.01% in both IES systems,which proves that the solutions produced by PH reach acceptable optimality in this stochastic UC problem.

An operating state estimation model for integrated energy systems based on distributed solution

In view of the disadvantages of the traditional energy supply systems,such as separate planning,separate design,independent operating mode,and the increasingly prominent nonlinear coupling between various subsystems,the production,transmission,storage and corn sumption of multiple energy sources are coordinated and optimized by the integrated energy system,which improves energy and infrastructure utilization,promotes renewable energy consumption,and ensures reliability of energy supply.In this paper,the mathematical model of the electricity-gas interconnected integrated energy system and its state estimation method are studied.First,considering the nonlinearity between measurement equations and state variables,a performance simulation model is proposed.Then,the state consistency equations and constraints of the coupling nodes for multiple energy sub-systems are established,and constraints are relaxed into the objective function to decouple the integrated energy system.Finally,a distributed state estimation framework is formed by combining the synchronous alternating direction multiplier method to achieve an efficient estimation of the state of the integrated energy system.A simulation model of an electricity-gas interconnected integrated energy system verifies the efficiency and accuracy of the state estimation method proposed in this pape.The results show that the average relative errors of voltage amplitude and node pressure estimated by the proposed distributed state estimation method are only 0.0132%and 0.0864%,much lower than the estimation error by using the Lagrangian relaxation method.Besides,compared with the centralized estimation method,the proposed distributed method saves 5.42 s of computation time.The proposed method is more accurate and efficient in energy allocation and utilization.