考虑集中式与分布式新能源不确定性的输配协同负荷恢复方法OA

In recent years,low-probability but high-risk events including extreme weather,natural disasters,and cyberattacks have been occurring with increasing frequency.The large-scale blackouts triggered by these incidents not only pose a grave threat to the reliable supply of electricity but also inflict enormous economic losses,emerging as a major issue that demands urgent resolution in the context of the new electricity system.Furthermore,with the continuous growth in the proportion of renewable energy sources installed capacity,the scale and complexity of the transmission and distribution networks have significantly increased,which further exacerbates the operational risks of the system under extreme events.In the context of large-scale integration of renewable energy sources,its inherent uncertainty makes it difficult for traditional load restoration methods to meet actual demand.Conducting research on load restoration methods that take into account the uncertainties of renewable energy sources and formulating scientific and rational load restoration strategies are of significant theoretical importance and practical relevance. To address these issues,a coordinated load restoration method of transmission and distribution networks considering the uncertainties of centralized and distributed renewable energy sources is proposed.Firstly,taking into account the repair progress of transmission and distribution network lines,the flexible adjustment characteristics of soft open points and network reconfiguration strategies are considered to establish load restoration models for transmission and distribution networks.Secondly,the fuzzy chance constraint method is used to model the power output of renewable energy sources on both sides of the transmission and distribution networks,thereby constructing a coordinated load restoration model of transmission and distribution networks that accounts for uncertainties.On this basis,a Peaceman-Rachford splitting-embedded adaptive regularized alternating direction method of multipliers(PR-AR-ADMM)is proposed to decompose the proposed model into sub-optimization models for distributed solution of the transmission and distribution networks. Simulation analyses are conducted using the modified T30D2 and T118D30 transmission-distribution systems as case studies,drawing the following conclusions:(1)The uncertainties of renewable energy sources output on both sides of the transmission and distribution networks are simultaneously considered and modeled using the fuzzy chance constraint method.Through comparative analysis,it can be concluded that setting a reasonable confidence level can improve restoration performance while controlling restoration costs using renewable energy sources,achieving a balance between safety and economy,and providing scientific basis for optimized decision-making in load restoration.(2)By integrating soft open points with the tie switch-based network reconfiguration strategy,the interactive power at the transmission-distribution boundary is optimized,enhancing the mutual support capability between the transmission and distribution networks and improving the overall restoration performance of the system.Compared to the strategy that only considered the tie switch-based network reconfiguration,the proposed strategy reduces the total restoration cost by 65 630 CNY and advances the completion time of restoration by 15 min.(3)The proposed PR-AR-ADMM can efficiently solve the distributed optimization model for coordinated load restoration in transmission and distribution networks,demonstrating good computational efficiency and solution accuracy.Compared to the traditional alternating direction method of multipliers,the PR-AR-ADMM reduces the computation time by 63.04%,decreases the number of iterations by 19,and narrows the optimization gap to 0.48%.