Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage

The integration of high-proportion renewable power generation has brought great challenges to the efficiency of distribution network planning methods and the economy of planning results. In order to solve the problem of coordination between the massive operation data of renewable power generation an...

Full description

Saved in:
Bibliographic Details
Main Authors: Jinsen LIU, Ning LUO, Jie WANG, Chang XU, Yi Cao, Zhiwen Liu
Format: Article
Language:zho
Published: State Grid Energy Research Institute 2022-12-01
Series:Zhongguo dianli
Subjects:
Online Access:https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202208020
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850069062174900224
author Jinsen LIU
Ning LUO
Jie WANG
Chang XU
Yi Cao
Zhiwen Liu
author_facet Jinsen LIU
Ning LUO
Jie WANG
Chang XU
Yi Cao
Zhiwen Liu
author_sort Jinsen LIU
collection DOAJ
description The integration of high-proportion renewable power generation has brought great challenges to the efficiency of distribution network planning methods and the economy of planning results. In order to solve the problem of coordination between the massive operation data of renewable power generation and the coordinated planning of the source-network-load-storage, this paper proposes a coordinated planning method of the source-network-load-storage based on the massive scenario dimension reduction. Firstly, the dimensionality reduction clustering is carried out on the wind-light-load mass high-dimensional scenarios by the principal component Gaussian mixture clustering algorithm, and the typical scenario set of wind and power loads is obtained; then, a source-network-load-storage coordination planning model of distribution network for massive scenarios is constructed, and the second-order cone relaxation technique is adopted to convert the non-convex constraints to convex ones; finally, the effectiveness of the proposed massive scenario dimension reduction clustering method and distribution network planning model is verified on the Portugal 54-node distribution network.
format Article
id doaj-art-c5b2e17252be4bf2a8559b3e26bc9cee
institution DOAJ
issn 1004-9649
language zho
publishDate 2022-12-01
publisher State Grid Energy Research Institute
record_format Article
series Zhongguo dianli
spelling doaj-art-c5b2e17252be4bf2a8559b3e26bc9cee2025-08-20T02:47:52ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492022-12-015512788510.11930/j.issn.1004-9649.202208020zgdl-55-12-liujinsenMassive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and StorageJinsen LIU0Ning LUO1Jie WANG2Chang XU3Yi Cao4Zhiwen Liu5Power Grid Planning and Research Center, Guizhou Power Grid Co., Ltd., Guiyang 550003, ChinaPower Grid Planning and Research Center, Guizhou Power Grid Co., Ltd., Guiyang 550003, ChinaPower Grid Planning and Research Center, Guizhou Power Grid Co., Ltd., Guiyang 550003, ChinaPower Grid Planning and Research Center, Guizhou Power Grid Co., Ltd., Guiyang 550003, ChinaEnergy Research Institute of China Southern Power Grid Co., Ltd., Guangzhou 510663, ChinaEnergy Research Institute of China Southern Power Grid Co., Ltd., Guangzhou 510663, ChinaThe integration of high-proportion renewable power generation has brought great challenges to the efficiency of distribution network planning methods and the economy of planning results. In order to solve the problem of coordination between the massive operation data of renewable power generation and the coordinated planning of the source-network-load-storage, this paper proposes a coordinated planning method of the source-network-load-storage based on the massive scenario dimension reduction. Firstly, the dimensionality reduction clustering is carried out on the wind-light-load mass high-dimensional scenarios by the principal component Gaussian mixture clustering algorithm, and the typical scenario set of wind and power loads is obtained; then, a source-network-load-storage coordination planning model of distribution network for massive scenarios is constructed, and the second-order cone relaxation technique is adopted to convert the non-convex constraints to convex ones; finally, the effectiveness of the proposed massive scenario dimension reduction clustering method and distribution network planning model is verified on the Portugal 54-node distribution network.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202208020distribution networkprincipal component analysis methodgaussian mixed clusteringsource-network-load-storagecoordinated planning
spellingShingle Jinsen LIU
Ning LUO
Jie WANG
Chang XU
Yi Cao
Zhiwen Liu
Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage
Zhongguo dianli
distribution network
principal component analysis method
gaussian mixed clustering
source-network-load-storage
coordinated planning
title Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage
title_full Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage
title_fullStr Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage
title_full_unstemmed Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage
title_short Massive Scenario Reduction Based Distribution-Level Power System Planning Considering the Coordination of Source, Network, Load and Storage
title_sort massive scenario reduction based distribution level power system planning considering the coordination of source network load and storage
topic distribution network
principal component analysis method
gaussian mixed clustering
source-network-load-storage
coordinated planning
url https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202208020
work_keys_str_mv AT jinsenliu massivescenarioreductionbaseddistributionlevelpowersystemplanningconsideringthecoordinationofsourcenetworkloadandstorage
AT ningluo massivescenarioreductionbaseddistributionlevelpowersystemplanningconsideringthecoordinationofsourcenetworkloadandstorage
AT jiewang massivescenarioreductionbaseddistributionlevelpowersystemplanningconsideringthecoordinationofsourcenetworkloadandstorage
AT changxu massivescenarioreductionbaseddistributionlevelpowersystemplanningconsideringthecoordinationofsourcenetworkloadandstorage
AT yicao massivescenarioreductionbaseddistributionlevelpowersystemplanningconsideringthecoordinationofsourcenetworkloadandstorage
AT zhiwenliu massivescenarioreductionbaseddistributionlevelpowersystemplanningconsideringthecoordinationofsourcenetworkloadandstorage