An optimal pricing scheme in electricity markets by parallelizing security constrained optimal power flow based market-clearing model
- Authors
- Kim, M. K.; Hur, D.
- Issue Date
- Jun-2013
- Publisher
- ELSEVIER SCI LTD
- Keywords
- Benders decomposition; Bilateral transaction; Locational marginal price (LMP); Market-clearing model; Nodal congestion price (NCP); Security constrained optimal power flow
- Citation
- INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, v.48, pp 161 - 171
- Pages
- 11
- Journal Title
- INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Volume
- 48
- Start Page
- 161
- End Page
- 171
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/61055
- DOI
- 10.1016/j.ijepes.2012.05.047
- ISSN
- 0142-0615
1879-3517
- Abstract
- To improve economic efficiency of electricity markets, the market-clearing model must be designed to give transparent information for pricing system security and to quantify the correlation between the market operations and the power systems operations, which is an immensely provocative and challenging issue in electricity markets. This paper sets out to propose a novel approach to pricing the system security by parallelizing the security constrained optimal power flow (SCOPF) based market-clearing model, while providing market solutions as a function of complying with the required voltage security margin and N-1 contingency criteria. The proposed SCOPF based market-clearing framework also takes into consideration the bilateral transaction information and, at the same time, optimal pricing expressions through computing locational marginal prices (LMPs) and nodal congestion prices (NCPs) for ensuring voltage security are derived. The results from a 129-bus model of the Italian HV transmission system turn out to be the validity of the proposed market-clearing model for managing and pricing the system security. (c) 2012 Elsevier Ltd. All rights reserved.
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Collections - College of Engineering > School of Energy System Engineering > 1. Journal Articles
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