Economic transmission planning model suitable for a regulated network service provider

Fonseka, P. A. J. and Shrestha, G. B. (2009) Economic transmission planning model suitable for a regulated network service provider. Journal of Energy Engineering, 135 3: 64-72. doi:10.1061/(ASCE)0733-9402(2009)135:3(64)


Author Fonseka, P. A. J.
Shrestha, G. B.
Title Economic transmission planning model suitable for a regulated network service provider
Journal name Journal of Energy Engineering   Check publisher's open access policy
ISSN 0733-9402
1943-7897
Publication date 2009-01-01
Year available 2009
Sub-type Article (original research)
DOI 10.1061/(ASCE)0733-9402(2009)135:3(64)
Open Access Status Not Open Access
Volume 135
Issue 3
Start page 64
End page 72
Total pages 9
Place of publication Reston, VA United States
Publisher American Society of Civil Engineer
Language eng
Subject 2102 Curatorial and Related Studies
2104 Nuclear Energy and Engineering
2105 Renewable Energy, Sustainability and the Environment
2205 Civil and Structural Engineering
2311 Waste Management and Disposal
Abstract Conventional transmission planning models are subject to constant debate in the context of competitive markets, due to the functional unbundling of transmission sector from generation and distribution sectors and due to the new environment regulations. A value-based transmission planning model is proposed, suitable for an unbundled transmission network service provider having no assets in the generation sector. The model minimizes the long-term transmission investment costs and the expected social costs incurred to its clients, energy producers, and consumers, in the power auctions due to transmission bottlenecks. The uncertainties involved when incorporating short-term market models into long-term planning models are modeled with probabilistic representations for the bid prices, the component availabilities, and the hourly load variations. These features make this model suitable in the new environment paradigm. Generalized Benders decomposition technique with nonsequential Monte Carlo technique is employed to solve the final stochastic mixed-integer optimization model. Case studies are given to illustrate the performance of this model by implementing it in the modified Garver's six-bus test system and the IEEE 24-bus reliability test system for a single planning year.
Keyword Electric transmission
Grid systems
Investments
Networks
Optimization
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Information Technology and Electrical Engineering Publications
 
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