Decomposition model and interior point methods for optimal spot pricing of electricity in deregulation environments

By K. Xie, Y. Song, J. Stonham, Erkeng Yu, Guangyi Liu. 2000

166 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8b58574f5c4597abb35ba62eca96ff7f3b55b571

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In Electrical and Electronic Engineering

Citations in the corpus

Network-Constrained Multiperiod Auction for a Pool-Based Electricity Market (2002, background): “URRENTLY, some pool-based electricity markets operate under a system-wide market price [1], [2], while others have elected the approach of nodal (or " locational " ) marginal prices [3].”
Probabilistic Optimal Power Flow in Electricity Markets Based on a Two-Point Estimate Method (2006, background): “In the context of electricity markets, the Lagrangian multipliers of the power flow equations are of special interest, since they can be directly associated with the system LMPs [16], [17].”
Development of a Hybrid Model for Electrical Power Spot Prices (2002, background): “data-driven approach of financial mathematicians, and not the “bottom-up" detail-driven approach typical of the engineering literature on this subject, such as found in [12] and [13].”
An open source power system analysis toolbox (2005, methodology): “The physical and security limits h included in PSAT are similar to what is used in [20], and take into account transmission line thermal limits, transmission line power ﬂ ow limits, generator reactive power limits, and voltage “security” limits.”
Probabilistic LMP Forecasting Considering Load Uncertainty (2009, background): “It is known that LMP can be decomposed into three components with each representing the marginal energy price, marginal loss price, and marginal congestion price, respectively [5]–[7].”
Multiobjective optimization for pricing system security in electricity markets (2003, background): “It is widely recognized that spot pricing through marginal costs can provide reliable pricing indicators [12].”