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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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Proceedings ArticleDOI

Hybrid immune genetic algorithm approach for short-term unit commitment problem

TL;DR: In this paper, a hybrid immune algorithm (IA)/genetic algorithm (GA) and fuzzy system (FS) method (IGAFS) was used for solving short-term thermal generating unit commitment (UC) problems.
Journal ArticleDOI

Implementation of Genetic Algorithm Based Additive and Divisive Clustering Techniques for Unit Commitment

TL;DR: A novel technique to solve the problem of unit commitment through sorting of units into different clusters based on Genetic Algorithm is presented in order to decrease the overall operating cost and to assure the various constraints that involve minimum up/down.
Journal ArticleDOI

A Solution to Unit Commitment Problem withV2G Using Harmony Search Algorithm

TL;DR: A new solution to the UC problem based on Harmony Search Algorithm (HSA) is proposed and an intelligent UC with V2G for cost optimization is presented.
Journal ArticleDOI

Mixed integer programming approach to optimal short-term unit commitment for hydropower systems

TL;DR: In this paper, a Mixed Integer Programming (MIP) model is developed to solve the unit commitment problem, which is a nonlinear, nonconvex, high dimensional, and large-scale optimization problem over mixed integer variables.

Unit commitment by a fast and new analytical non-iterative method using IPPD table and “λ-logic” algorithm

TL;DR: In large scale systems, the proposed method achieves minimum operational cost within minimum computational time and results in simplification of the UC problem solution.
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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