Developing a holistic fuzzy hierarchy-cloud assessment model for the connection risk of renewable energy microgrid. (15th April 2022)
- Record Type:
- Journal Article
- Title:
- Developing a holistic fuzzy hierarchy-cloud assessment model for the connection risk of renewable energy microgrid. (15th April 2022)
- Main Title:
- Developing a holistic fuzzy hierarchy-cloud assessment model for the connection risk of renewable energy microgrid
- Authors:
- Wu, Zhongqun
Yang, Chan
Zheng, Ruijin - Abstract:
- Abstract: Grid-connection of renewable energy microgrids (GCREM) is an important form of promoting the use of clean and renewable energy (RE). However, GCREM will bring huge risks to the power grid. Accurate evaluation and control of risks are critical to the development of GCREM. The existing research is not deep and comprehensive enough to make a reliable evaluation on the risks. The current study proposes a new evaluation framework based on the unit decomposition of the system of GCREM, and then builds a holistic fuzzy hierarchy-cloud assessment model for the risks. The main contributions of this paper are as follows: (1) decomposes GCREM risks to each functional unit of the system, and clarifies the risk transmission between the units within the system; (2) improves the accuracy of weighting risk variables based on interval type-2 fuzzy method; (3) realizes the visibility of risk evaluation and a prior judgment on its effectiveness; (4) establishes a 5-dimensional risk evaluation system of GCREM for the first time, which achieved full coverage of risk variables without the overlap between dimensions. The empirical analyses show that our model can not only assess the overall risk level of GCREM, but also identify key risk sources. Highlights: Decomposed the risks of GCREM to each functional unit of the system. The interval type-2 fuzzy method is used to improve the accuracy of weighting risk variables. Realized the visible display of the risks and a prior judgment on theAbstract: Grid-connection of renewable energy microgrids (GCREM) is an important form of promoting the use of clean and renewable energy (RE). However, GCREM will bring huge risks to the power grid. Accurate evaluation and control of risks are critical to the development of GCREM. The existing research is not deep and comprehensive enough to make a reliable evaluation on the risks. The current study proposes a new evaluation framework based on the unit decomposition of the system of GCREM, and then builds a holistic fuzzy hierarchy-cloud assessment model for the risks. The main contributions of this paper are as follows: (1) decomposes GCREM risks to each functional unit of the system, and clarifies the risk transmission between the units within the system; (2) improves the accuracy of weighting risk variables based on interval type-2 fuzzy method; (3) realizes the visibility of risk evaluation and a prior judgment on its effectiveness; (4) establishes a 5-dimensional risk evaluation system of GCREM for the first time, which achieved full coverage of risk variables without the overlap between dimensions. The empirical analyses show that our model can not only assess the overall risk level of GCREM, but also identify key risk sources. Highlights: Decomposed the risks of GCREM to each functional unit of the system. The interval type-2 fuzzy method is used to improve the accuracy of weighting risk variables. Realized the visible display of the risks and a prior judgment on the effectiveness of the evaluation. A 5-dimensional risk evaluation system of GCREM is established for the first time. … (more)
- Is Part Of:
- Energy. Volume 245(2022)
- Journal:
- Energy
- Issue:
- Volume 245(2022)
- Issue Display:
- Volume 245, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 245
- Issue:
- 2022
- Issue Sort Value:
- 2022-0245-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-04-15
- Subjects:
- Renewable energy microgrid -- Grid-connected risk -- Risk assessment model
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2022.123235 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21072.xml