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Journal ArticleDOI

Implementation of a Lagrangian relaxation based unit commitment problem

TLDR
The Lagrangian relaxation methodology has been used for solving the unit commitment problem as discussed by the authors, which is a class of complex combinatorial optimization problems in the power system, where the objective is to obtain an overall least-cost solution for operating the system over the scheduling horizon.
Abstract
The unit commitment problem in a power system involves determining a start-up and shut-down schedule of units to be used to meet the forecasted demand, over a future short term (24-168 hour) period. In solving the unit commitment problem, generally two basic decisions are involved. The "unit commitment" decision involves determining which generating units are to be running during each hour of the planning horizon, considering system capacity requirements including reserve, and the constraints on the start up and shut down of units. The related "economic dispatch" decision involves the allocation of system demand and spinning reserve capacity among the operating units during each specific hour of operation. As these two decisions are interrelated, the unit commitment problem generally embraces both these decisions, and the objective is to obtain an overall least cost solution for operating the power system over the scheduling horizon. The unit commitment problem belongs to the class of complex combinatorial optimization problems. During the past decade a new approach named "Lagrangian Relaxation" has been evolving for generating efficient solutions for this class of problems. It derives its name from the well-known mathematical technique of using Lagrange multipliers for solving constrained optimization problems, but is really a decomposition technique for the solution of large scale mathematical programming problems. The Lagrangian relaxation methodology generates easy subproblems for deciding commitment and generation schedules for single units over the planning horizon, independent of the commitment of other units.

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Citations
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Journal ArticleDOI

Solving unit commitment problem using a novel version of harmony search algorithm

TL;DR: In this article, a novel structure was proposed for improving harmony search (HS) algorithm to solve the unit comment (UC) problem, which obtained optimal solution for defined objective function by improvising, updating and checking operators.
Proceedings ArticleDOI

Latest experiences in improving convergence of dual optimization in LR method

Xiaoming Feng, +1 more
TL;DR: Encouraging experiences in achieving speedy convergence by judicious determination of the step size scaling factor based on simple rules that can be easily codified are presented.
Journal ArticleDOI

A novel approach for solving multi-objective unit commitment based on decompositioncoordination

TL;DR: A novel model for MOUC is proposed, and a decomposition coordination approach is presented to solve the model, which considers environmental objective by introducing a novel penalty term, and it's a quantized term for preference of environmental objective, which could be a basis for carbon tax makers.
Proceedings ArticleDOI

Direct Model Predictive Control: A Theoretical and Numerical Analysis

TL;DR: It is proved that Direct Model Predictive Control reaches an optimal policy for a wider class of decision processes than those solved by Modelpredictive Control, Stochastic Dynamic Programming or Stochastics Dual Dynamic Programming.
References
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Journal ArticleDOI

The Lagrangian Relaxation Method for Solving Integer Programming Problems

TL;DR: This paper is a review of Lagrangian relaxation based on what has been learned in the last decade and has led to dramatically improved algorithms for a number of important problems in the areas of routing, location, scheduling, assignment and set covering.
Journal ArticleDOI

Validation of subgradient optimization

TL;DR: It is concluded that the “relaxation” procedure for approximately solving a large linear programming problem related to the traveling-salesman problem shows promise for large-scale linear programming.
Journal ArticleDOI

A dual-based procedure for uncapacitated facility location

TL;DR: This approach has obtained and verified optimal solutions to all the Kuehn-Hamburger location problems in well under 0.1 seconds each on an IBM 360/91 computer, with no branching required.
Journal ArticleDOI

An Applications Oriented Guide to Lagrangian Relaxation

Marshall L. Fisher
- 01 Apr 1985 - 
TL;DR: This tutorial provides a practical guide to the use of Lagrangian relaxation and an on-line computerized routing and scheduling optimizer.
Journal ArticleDOI

Towards a more rigorous and practical unit commitment by Lagrangian relaxation

TL;DR: A mathematically based, systematic and generally applicable procedure to search for a reserve-feasible dual solution for power system generator unit commitment, giving reliable performance and low execution times.
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