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Local-Generator-Based Virtual Power Plant Operation Algorithm Considering Operation Time

Authors
Park, Sung-WonPark, Yong-GiSon, Sung-Yong
Issue Date
Nov-2017
Publisher
SPRINGER SINGAPORE PTE LTD
Keywords
Virtual Power Plant (VPP); Optimal operation algorithm; Equality operation; Operation time; Local generator
Citation
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, v.12, no.6, pp.2127 - 2137
Journal Title
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
Volume
12
Number
6
Start Page
2127
End Page
2137
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/5556
DOI
10.5370/JEET.2017.12.6.2127
ISSN
1975-0102
Abstract
A virtual power plant (VPP) is a system that virtually integrates power resources based on the VPP participating customer (VPC) unit and operates as a power plant. When VPP operators manage resources to maximize their benefits, load reduction instructions may focus on more responsive VPCs, or those producing high profitability, by using VPC resources with high operation efficiency. VPCs may thus encounter imbalance problems during operation. This imbalance in operation time would bring more participation for some VPCs, causing potential degradation of their resources. Such an operation strategy would be not preferable for VPP operators in managing the relationship with VPCs. This issue impedes both continual VPC participation and economical and reliable VPP operation in the long term. An operation algorithm is therefore proposed that considers the operation time of VPC generators for mandatory reduction of power resource consumption. The algorithm is based on constraints of daily and annual operation times when VPP operators of local generators perform capacity-market power transactions. The algorithm maximizes the operator benefit through VPP operations. The algorithm implements a penalty parameter for imbalances in operation times spent by VPC generators in fulfilling their obligations. An evaluation was conducted on VPP operational effects by applying the algorithm to the Korean power market.
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Graduate School (Dept. of Next Generation Smart Energy System Convergence)
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