2011•IEEE Transactions on Power SystemsRequires access

Optimal LMP Decomposition for the ACOPF Calculation

Vaskar Sarkar, Shrikrishna A. Khaparde

Open publisher page 42 citations

Abstract

The objective of this work is to design a suitable rule for the energy reference selection in the AC optimal power flow (ACOPF)-based locational marginal price (LMP) calculation. In the case of the ACOPF model, the congestion component of the LMP vector exhibits strong dependence on the energy reference. This in turn makes the hourly values of financial transmission rights (FTRs) to be reference dependent, and, thus, is a source of dispute. In order to resolve this dispute, a direct optimization framework is developed in this work exploring the interrelationship between the congestion components of locational marginal prices at individual buses. The objective function and the constraints of this optimization model are carefully designed looking at the true motive of the LMP decomposition. At the same time, necessary attention is paid so as to ensure revenue adequacy in the FTR settlement. The optimization problem that is ultimately to be solved is a simple quadratic programming problem with only one variable and two constraints. The effectiveness of the proposed methodology is verified through a case study on a modified IEEE 30-bus system. The framework developed also unveils several interesting features of the LMP components that were under cover until now.

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What this paper is about

The objective of this work is to design a suitable rule for the energy reference selection in the AC optimal power flow (ACOPF)-based locational marginal price (LMP) calculation. In the case of the ACOPF model, the congestion component of the LMP vector exhibits strong dependence on the energy reference. This in turn makes the hourly values of financial transmission rights (FTRs) to be reference dependent, and, thus, is a source of dispute. In order to resolve this dispute, a direct optimization framework is developed in this work exploring the interrelationship between the congestion components of locational marginal prices at individual buses. The objective function and the constraints of this optimization model are carefully designed looking at the true motive of the LMP decomposition. At the same time, necessary attention is paid so as to ensure revenue adequacy in the FTR settlement. The optimization problem that is ultimately to be solved is a simple quadratic programming problem with only one variable and two constraints. The effectiveness of the proposed methodology is verified through a case study on a modified IEEE 30-bus system. The framework developed also unveils several interesting features of the LMP components that were under cover until now.

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Available abstract

The objective of this work is to design a suitable rule for the energy reference selection in the AC optimal power flow (ACOPF)-based locational marginal price (LMP) calculation. In the case of the ACOPF model, the congestion component of the LMP vector exhibits strong dependence on the energy reference. This in turn makes the hourly values of financial transmission rights (FTRs) to be reference dependent, and, thus, is a source of dispute. In order to resolve this dispute, a direct optimization framework is developed in this work exploring the interrelationship between the congestion components of locational marginal prices at individual buses. The objective function and the constraints of this optimization model are carefully designed looking at the true motive of the LMP decomposition. At the same time, necessary attention is paid so as to ensure revenue adequacy in the FTR settlement. The optimization problem that is ultimately to be solved is a simple quadratic programming problem with only one variable and two constraints. The effectiveness of the proposed methodology is verified through a case study on a modified IEEE 30-bus system. The framework developed also unveils several interesting features of the LMP components that were under cover until now.

Key concepts: Mathematical optimization, Computer science, Decomposition, Revenue, Component (thermodynamics), Optimization problem, Decomposition method (queueing theory), Electric power system

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