A coupled gradient network for the solution of the temporal unit commitment problem in power systems planning

1994 ◽  
Author(s):  
P.B. Watta ◽  
M.H. Hassoun
Keyword(s):  
Power Systems ◽  
Unit Commitment ◽  
Unit Commitment Problem ◽  
Systems Planning ◽  
Commitment Problem

scholarly journals Fat Tail Model for Simulating Test Systems in Multiperiod Unit Commitment

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
J. A. Marmolejo ◽  
R. Rodriguez
Keyword(s):  
Power Systems ◽  
Unit Commitment ◽  
Electrical Power ◽  
Random Variables ◽  
Production Costs ◽  
Unit Commitment Problem ◽  
Test Systems ◽  
Fat Tail ◽  
Commitment Problem ◽  
Stable Random Variables

This paper describes the use of Chambers-Mallows-Stuck method for simulating stable random variables in the generation of test systems for economic analysis in power systems. A study that focused on generating test electrical systems through fat tail model for unit commitment problem in electrical power systems is presented. Usually, the instances of test systems in Unit Commitment are generated using normal distribution, but in this work, simulations data are based on a new method. For simulating, we used three original systems to obtain the demand behavior and thermal production costs. The estimation of stable parameters for the simulation of stable random variables was based on three generally accepted methods: (a) regression, (b) quantiles, and (c) maximum likelihood, choosing one that has the best fit of the tails of the distribution. Numerical results illustrate the applicability of the proposed method by solving several unit commitment problems.

An Application of Alpha-Stable Distributions for the Economic Analysis of Unit Commitment

2016 ◽  
pp. 160-184
Author(s):  
Jose Antonio Marmolejo ◽  
Román Rodríguez
Keyword(s):  
Economic Analysis ◽  
Power Systems ◽  
Unit Commitment ◽  
Electrical Power ◽  
Random Variables ◽  
Unit Commitment Problem ◽  
Solution Quality ◽  
Test Systems ◽  
Commitment Problem ◽  
Stable Random Variables

In power systems, we still lack the existence of standardized test systems that can be used to benchmark the performance and solution quality of proposed optimization techniques. It is therefore necessary to develop new methods for design of test cases for economic analysis in power systems. We compared two methods to generate test systems: time series and a method for simulating stable random variables that can be used to multiperiod unit commitment based on the use of Chambers-Mallows-Stuck. Hence, after comparing both methods, we describe the method for simulating stable random variables in the generation of test systems for economic analysis in power systems. A study focused on generating test electrical systems through fat tail model for unit commitment problem in electrical power systems is presented. Usually, the instances of test systems in Unit Commitment are generated using normal distribution, but in this work, simulations data are based on alpha-stable distribution. Numerical results illustrate the applicability of the proposed method.

A MIQCP formulation to solve the unit commitment problem for large-scale power systems

2012 ◽  
Vol 36 (1) ◽  
pp. 68-75 ◽  
Author(s):  
Juan Álvarez López ◽  
José L. Ceciliano-Meza ◽  
Isaías Guillén Moya ◽  
Rolando Nieva Gómez
Keyword(s):  
Power Systems ◽  
Large Scale ◽  
Unit Commitment ◽  
Unit Commitment Problem ◽  
Commitment Problem

scholarly journals A New Affinely Adjustable Robust Model for Security Constrained Unit Commitment under Uncertainty

2021 ◽  
Vol 11 (9) ◽  
pp. 3987
Author(s):  
Juan Esteban Sierra-Aguilar ◽  
Cristian Camilo Marín-Cano ◽  
Jesús M. López-Lezama ◽  
Álvaro Jaramillo-Duque ◽  
Juan G. Villegas
Keyword(s):  
Power Systems ◽  
Unit Commitment ◽  
Decision Rules ◽  
Forecast Errors ◽  
Unit Commitment Problem ◽  
Sources Of Uncertainty ◽  
Robust Model ◽  
Proposed Model ◽  
Commitment Problem ◽  
Linear Decision Rules

Currently, optimization models for the safe and reliable operation of power systems deal with two major challenges: the first one is the reduction of the computational load when considering N−1 contingencies; the second one is the adequate modeling of the uncertainty of intermittent generation and demand. This paper proposes a new affinely adjustable robust model to solve the security constrained unit commitment problem considering these sources of uncertainty. Linear decision rules, which take into account the forecasts and forecast errors of the different sources of uncertainty, are used for the affine formulation of the dispatch variables, thus allowing the tractability of the model. Another major novelty is that the evaluation of the N−1 security constraints is performed by incorporating a novel method, proposed in the literature, based on the user-cuts concept. This method efficiently and dynamically adds only the binding N−1 security constraints, increasing the computational efficiency of the model when transmission line contingencies are considered. Finally, Monte Carlo simulations on the post-optimization results were run to demonstrate the effectiveness, feasibility and robustness of the solutions provided by the proposed model.

scholarly journals The optimal solution for unit commitment problem using binary hybrid grey wolf optimizer

2022 ◽  
Vol 12 (1) ◽  
pp. 122
Author(s):  
Ali Iqbal Abbas ◽  
Afaneen Anwer
Keyword(s):  
Power Systems ◽  
Production Cost ◽  
Unit Commitment ◽  
Optimal Solution ◽  
Suggested Method ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Unit Commitment Problem ◽  
Commitment Problem ◽  
Quadratic Programming Method

The aim of this work is to solve the unit commitment (UC) problem in power systems by calculating minimum production cost for the power generation and finding the best distribution of the generation among the units (units scheduling) using binary grey wolf optimizer based on particle swarm optimization (BGWOPSO) algorithm. The minimum production cost calculating is based on using the quadratic programming method and represents the global solution that must be arriving by the BGWOPSO algorithm then appearing units status (on or off). The suggested method was applied on “39 bus IEEE test systems”, the simulation results show the effectiveness of the suggested method over other algorithms in terms of minimizing of production cost and suggesting excellent scheduling of units.

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