Consensus‐based distributed scheduling for cooperative operation of distributed energy resources and storage devices in smart grids. Issue 5 (1st April 2016)

• Record Type: Journal Article
• Authors: Rahbari‐Asr, Navid; Zhang, Yuan; Chow, Mo‐Yuen
• Is Part Of: IET generation, transmission & distribution. Volume 10:Issue 5(2016)
• Page Start: 1268
• Page End: 1277
• Publication Date: 2016-04-01
• Subjects: smart power grids -- discrete time systems -- optimal control -- iterative methods -- Monte Carlo methods -- power generation scheduling -- distributed power generation -- power generation control; consensus‐based distributed scheduling -- cooperative operation -- distributed energy resources -- smart grids -- storage devices -- renewable production -- discrete‐time optimal control -- primal‐dual gradient descent -- consensus networks -- iterative coordination -- 5‐bus system -- Monte Carlo simulations; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2015.0159
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Optimal dispatch of storage devices is crucial for the economic operation of smart grids with distributed energy resources. Through appropriate scheduling, storage devices can store the energy when the renewable production is high or electricity price is low, and support the demand when electricity is expensive. Conventionally, this scheduling requires a control centre to gather information from the entire system and find the optimal schedule in the required horizon for the controllable devices. This study proposes a fully distributed scheduling methodology based on discrete‐time optimal control, primal‐dual gradient descent, and consensus networks. In the proposed approach, the requirement for the control centre is eliminated and the optimal schedule for all the devices is found solely through iterative coordination of each device with its neighbours. The application of the algorithm is demonstrated in a 5‐bus system and its convergence to the global optimum is validated through Monte Carlo simulations. Further, it is shown that the algorithm is robust against communication link failures provided that the communications topology remains connected or reconnects after being disconnected.