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Collaborative Planning of DERs and Intentional Islands in Distribution Network Considering Loss-of-Load Risk
Author(s) -
Wenxia Liu,
Zhengzhou Li,
Bo Zeng,
Mengyao Yang,
Hao Qin,
Xiaoxing Zheng,
Dongbo Zhao
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2864549
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
With the increasing use of distributed generations and distribution automation technologies in smart grid, the distribution system operator can alleviate the loss-of-load and improve the reliability of supply by forming intentional islands when emergency situations occur. Considering that the successful operation of the intentional island needs allocation of new circuit breakers (CBs), this paper proposes an integrated optimization method for simultaneous allocation of CBs and distributed energy resources (PV and battery energy storage, DERs) in distribution networks. The proposed approach is established on a multi-objective optimization framework, which determines the positions and sizes of CBs and DERs in order to minimize the total cost and the outage risk of the system, while subject to the voltage stability constraint. As distinct from the previous works, the loss-of-load risk and the effects of the intentional islands on system reliability are especially considered in our paper. To achieve this, an efficient technique to calculate the system risk index that converges with limited computation efforts is developed. The proposed model is solved by using the multi-objective evolutionary optimization algorithm—NSGA-II. Simulations based on RBTS-BUS6 verify the effectiveness of the proposed model and methods. Furthermore, the impacts of CB positions and load characteristics on the planning results are also analyzed.

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