Hierarchical energy management scheme for residential communities under grid outage event. Issue 2 (6th April 2020)

• Record Type: Journal Article
• Authors: Zhang, Fangfei; Luo, Fengji; Dong, Zhaoyang; Liu, Yanli; Ranzi, Gianluca
• Is Part Of: IET smart grid. Volume 3:Issue 2(2020)
• Page Start: 174
• Page End: 181
• Publication Date: 2020-04-06
• Subjects: distributed power generation -- domestic appliances -- smart power grids -- energy management systems -- battery management systems -- building management systems -- renewable energy sources -- scheduling -- optimisation -- power distribution reliability; hierarchical energy management scheme -- residential communities -- grid outage event -- energy demand -- extreme weather days -- frequent power outage events -- distributed renewable energy sources -- residential buildings -- energy sharing -- multiple houses -- home energy management system -- community energy management system -- CEMS -- planned outage -- community battery energy storage system -- load re‐shaping instructions -- appliance‐level autonomous scheduling -- residential energy resources scheduling; B0170N Reliability -- B0260 Optimisation techniques -- B8110B Power system management, operation and economics -- B8120K Distributed power generation; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/iet-stg.2019.0150
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract : The ever‐increasing energy demand and extreme weather days lead to more frequent power outage events. This paper proposes a hierarchical energy management scheme for residential communities, aiming to facilitate energy sharing among houses and minimize the impact on the grid outage on the whole community. In the proposed model, the complexity of scheduling residential energy resources of multiple houses is decomposed into a bi‐level structure, in which the Home Energy Management System (HEMS) of each house iteratively interacts with the Community Energy Management System (CEMS). In the upper layer, the CEMS receives the information of the planned outage; it then solves a social warfare optimization model to determine: (1) charging/discharging power of a community battery energy storage system, and (2) load re‐shaping instructions of each house. In the lower layer, the HEMS of each house performs appliance‐level autonomous scheduling to try to satisfy the load re‐shaping instructions received from the CEMS. The autonomous scheduling result of individual HEMSs are sent back to the CEMS, and the latter updates the upper‐layer result based on the received result. This process continues until the convergence criteria is achieved. Extensive simulations are conducted to validate the proposed solution