Aggregator-based demand response mechanism for electric vehicles participating in peak regulation in valley time of receiving-end power grid

With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this problem while considering the potential of the large-scale charge load of electric vehicles(EVs), an aggregator-based demand response(DR) mechanism for EVs that are participating in the peak regulation in valley time is proposed in this study. In this aggregator-based DR mechanism, the profits for the power grid’s operation and the participation willingness of the EV owners are considered. Based on the characteristics of the EV charging process and the day-ahead unit generation scheduling, a rolling unit commitment model with the DR is established to maximize the social welfare. In addition, to improve the efficiency of the optimization problem solving process and to achieve communication between the independent system operator(ISO) and the aggregators, the clustering algorithm is utilized to extract typical EV charging patterns. Finally, the feasibility and benefits of the aggregator-based DR mechanism for saving the costs and reducing the peak-valley difference of the receiving-end power grid are verified through case studies.

Multi-agent-based Rolling Optimization Method for Restoration Scheduling of Distribution Systems with Distributed Generation

Resilience against major disasters is the most essential characteristic of future electrical distribution systems(EDSs).A multi-agent-based rolling optimization method for EDS restoration scheduling is proposed in this paper.When a blackout occurs,considering the risk of losing the centralized authority due to the failure of the common core communication network,the available agents after disasters or cyber-attacks identify the communication-connected parts(CCPs)in the EDS with distributed communication.A multi-time interval optimization model is formulated and solved by the agents for the restoration scheduling of a CCP.A rolling optimization process for the entire EDS restoration is proposed.During the scheduling/rescheduling in the rolling process,CCPs in EDS are re-identified and the restoration schedules for CCPs are updated.Through decentralized decision-making and rolling optimization,EDS restoration scheduling can automatically start and periodically update itself,providing an effective solution for EDS restoration scheduling in a blackout event.A modified IEEE123-bus EDS is utilized to demonstrate the effectiveness of the proposed method.