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.read more
Citations
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Journal ArticleDOI
Operational flexibility and economics of power plants in future low-carbon power systems
Anne Sjoerd Brouwer,Anne Sjoerd Brouwer,Machteld van den Broek,A.J. Seebregts,André Faaij,André Faaij +5 more
TL;DR: In this paper, the authors investigated the operation of future power plants by composing a comprehensive overview of the operational flexibility of current and future coal-powered power plants and performed a combined long-term optimization and hourly simulation with the soft-linked Markal-NL-UU and REPOWERS models for The Netherlands in 2030 and 2050.
Journal ArticleDOI
Optimal thermal generating unit commitment: a review
Subir Sen,D.P. Kothari +1 more
TL;DR: The purpose of economic thermal unit commitment scheduling is to minimize the cost of operation subject to attainment of a certain level of security and reliability as mentioned in this paper, however, owing to environmental considerations, operation at absolute minimum cost cannot be the only objective/basis of optimal thermal unit commitments.
Journal ArticleDOI
Economic dispatch in view of the Clean Air Act of 1990
A.A. El-Keib,H. Ma,J.L. Hart +2 more
TL;DR: In this paper, the impact of the Clean Air Act of 1990 on the current industry practices as related to the economic dispatch problem was investigated in view of the new SO/sub 2/ emissions and underutilization constraints.
Journal ArticleDOI
Review on methods of generation scheduling in electric power systems
TL;DR: In this article, a review on methods of generation scheduling in both regulated and deregulated power markets since 1951 is presented, covering a wide span of deterministic, meta-heuristic, and hybrid approaches.
Proceedings ArticleDOI
Genetic algorithm solution to unit commitment problem
TL;DR: In this paper, a GA is used to solve the unit commitment problem with consideration of up & down time, startup cost (Hot & Cold start), and production cost, and the GA is tested on two IEEE test systems, one of 5 units, 14 bus and another of 7 units, 56 bus respectively.
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
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
F. Zhuang,Francisco D. Galiana +1 more
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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