Learning the LMP-Load Coupling From Data: A Support Vector Machine Based Approach

This paper investigates the fundamental coupling between loads and locational marginal prices (LMPs) in security-constrained economic dispatch (SCED). Theoretical analysis based on multi-parametric programming theory points out the unique one-to-one mapping between load and LMP vectors. Such one-to-...

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Vydáno v:IEEE transactions on power systems Ročník 32; číslo 2; s. 1127 - 1138
Hlavní autoři: Geng, Xinbo, Xie, Le
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 01.03.2017
Témata:
Couplings
Economics
Generators
Locational marginal prices (LMPs)
Programming
security constrained economic dispatch (SCED)
support vector machine (SVM)
Support vector machines
system pattern region
Topology
Transmission line matrix methods
ISSN:0885-8950, 1558-0679
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Shrnutí:This paper investigates the fundamental coupling between loads and locational marginal prices (LMPs) in security-constrained economic dispatch (SCED). Theoretical analysis based on multi-parametric programming theory points out the unique one-to-one mapping between load and LMP vectors. Such one-to-one mapping is depicted by the concept of system pattern region (SPR) and identifying SPRs is the key to understanding the LMP-load coupling. Built upon the characteristics of SPRs, the SPR identification problem is modeled as a classification problem from a market participant's viewpoint, and a Support Vector Machine based data-driven approach is proposed. It is shown that even without the knowledge of system topology and parameters, the SPRs can be estimated by learning from historical load and price data. Visualization and illustration of the proposed data-driven approach are performed on a 3-bus system as well as the IEEE 118-bus system.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2016.2572138