Multi-time Collaborative Restoration for Integrated Electrical-gas Distribution Systems Based on Rolling Optimization

This paper proposes a multi-time collaborative restoration model for integrated electricity-gas distribution sys-tems(IEGDSs)considering multiple resources after extreme weather events.Based on the linearized power flow constraints of the unbalanced electrical distribution system(EDS)and gas distribution system(GDS),this problem can be formulated as a mixed-integer linear programming(MILP)model.To improve the efficiency and veracity of the solution,a rolling optimiza-tion based two-stage method is developed with the first stage solved by a linear approximation model,and the second stage solved by real-time updated rolling optimization.By solving the MILP problem using rolling optimization,the proposed model and solution method achieve efficient and reliable collaborative restoration of IEGDS considering multiple resources and unbal-anced operation characteristics of EDS.The effectiveness of the proposed model and method is validated by using an IEGDS made of a 37-bus unbalanced EDS and 11-node GDS.Index Terms-Electricity-gas system,mix-integer linear programming,power system restoration.

Fast Solution Method for the Large-scale Unit Commitment Problem with Long-term Storage

Long-term storage(LTS)can provide various services to address seasonal fluctuations in variable renewable energy by reducing energy curtailment.However,long-term unit commitment(UC)with LTS involves mixed-integer programming with large-scale coupling constraints between consecutive intervals(state-of-charge(SOC)constraint of LTS,ramping rate,and minimum up/down time constraints of thermal units),resulting in a significant computational burden.Herein,an iterative-based fast solution method is proposed to solve the long-term UC with LTS.First,the UC with coupling constraints is split into several sub problems that can be solved in parallel.Second,the solutions of the sub problems are adjusted to obtain a feasible solution that satisfies the coupling constraints.Third,a decoupling method for long-term time-series coupling constraints is proposed to determine the global optimization of the SOC of the LTS.The price-arbitrage model of the LTS determines the SOC boundary of the LTS for each sub problem.Finally,the sub problem with the SOC boundary of the LTS is iteratively solved independently.The proposed method was verified using a modified IEEE 24-bus system.The results showed that the computation time of the unit combination problem can be reduced by 97.8%,with a relative error of 3.62%.