TY - JOUR
T1 - Upgrading Conventional Distribution Networks by Actively Planning Distributed Generation Based on Virtual Microgrids
AU - Xu, Xiaotong
AU - Xue, Fei
AU - Wang, Xiaoliang
AU - Lu, Shaofeng
AU - Jiang, Lin
AU - Gao, Ciwei
N1 - Publisher Copyright:
© 2007-2012 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - In addition to active energy management, this article proposes active planning as another critical feature of active distribution networks (ADNs). To develop this set of tasks, this article introduces a three-layer active planning framework consisting of a physical layer, cyber layer, and socioeconomic layer. Furthermore, a three-step developing strategy for ADNs based on a virtual microgrid (VM) is put forward. Then, according to this framework, this article focuses on a specific and fundamental issue that often arises: The optimal allocation of distributed generation (DG). A two-stage scheme based on VMs is a proposed solution. In the first stage, VM boundaries are determined based on the characteristics of a network structure. Using the identified VM boundaries as constraints, a bilevel hierarchical optimization method is applied to determine the optimal DG allocation in the second stage. The proposed method is verified in the popular PGandE 69-bus distribution network.
AB - In addition to active energy management, this article proposes active planning as another critical feature of active distribution networks (ADNs). To develop this set of tasks, this article introduces a three-layer active planning framework consisting of a physical layer, cyber layer, and socioeconomic layer. Furthermore, a three-step developing strategy for ADNs based on a virtual microgrid (VM) is put forward. Then, according to this framework, this article focuses on a specific and fundamental issue that often arises: The optimal allocation of distributed generation (DG). A two-stage scheme based on VMs is a proposed solution. In the first stage, VM boundaries are determined based on the characteristics of a network structure. Using the identified VM boundaries as constraints, a bilevel hierarchical optimization method is applied to determine the optimal DG allocation in the second stage. The proposed method is verified in the popular PGandE 69-bus distribution network.
KW - Active planning
KW - distributed generation (DG)
KW - electrical coupling strength (ECS)
KW - genetic algorithm (GA)
KW - virtual microgrids (VMs)
UR - http://www.scopus.com/inward/record.url?scp=85110927374&partnerID=8YFLogxK
U2 - 10.1109/JSYST.2020.2999560
DO - 10.1109/JSYST.2020.2999560
M3 - Article
AN - SCOPUS:85110927374
SN - 1932-8184
VL - 15
SP - 2607
EP - 2618
JO - IEEE Systems Journal
JF - IEEE Systems Journal
IS - 2
M1 - 9119110
ER -