Zonotope‐based quantification of the impact of renewable power generation on hybrid AC/DC distribution system. Issue 16 (21st January 2019)

• Record Type: Journal Article
• Authors: Gao, Jianing; Han, Bei; Xu, Chenbo; Zhang, Lijun; Li, Guojie; Wang, Keyou
• Is Part Of: Journal of engineering. Volume 2019:Issue 16(2019)
• Page Start: 2493
• Page End: 2499
• Publication Date: 2019-01-21
• Subjects: set theory -- load flow -- hybrid power systems -- distributed power generation -- probability -- power convertors -- power distribution control -- power generation control; probabilistic method -- hybrid AC‐DC test system -- renewable energy resource integration -- hybrid AC‐DC distribution network -- multiple renewable energy resources -- generation uncertainty -- linearised power flow -- hybrid power systems -- system‐state variables -- renewable power fluctuations -- zonotope‐based set‐theoretic method -- system static performance -- renewable power generation -- zonotope‐based quantification; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2018.8520
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : Hybrid AC/DC distribution network has developed rapidly owing to its convenience for renewable energy integration, thus the authors are interested in quantifying the impact of uncertainty from renewable power on system static performance. This paper proposes a zonotope‐based set‐theoretic method for quantifying the impact of renewable power fluctuations on system‐state variables in hybrid AC/DC distribution network, both for the assessment of the capabilities for integrating renewable resources by hybrid AC/DC system, and for the appropriate selection of operating method in hybrid power systems. The authors bound the uncertain variations of generation by a zonotope and propagate it through a linearised power flow to get another zonotope, which captures all possible values of the system state variables. The zonotope‐based method is computationally tractable and takes less computation than probabilistic methods especially when considering the generation uncertainty of multiple renewable energy resources. The proposed method is applied to a hybrid AC/DC test system with different control strategies of converters. The results show that hybrid AC/DC system with proper control mode may help reduce the impact of generation uncertainty.