• Unit commitment problem: A new...

Result: Unit commitment problem: A new formulation and solution method

Title:
Unit commitment problem: A new formulation and solution method
Authors:
VAMSI KRISHNA TUMULURU, ZHE HUANG, TSANG, Danny H. K
Source:
Electrical power & energy systems. 57:222-231
Publisher Information:
Oxford: Elsevier, 2014.
Publication Year:
2014
Physical Description:
print, 33 ref
Original Material:
INIST-CNRS
Subject Terms:
Electrical engineering, Electrotechnique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Electrotechnique. Electroenergetique, Electrical engineering. Electrical power engineering, Electroénergétique, Electrical power engineering, Réseaux et lignes électriques, Power networks and lines, Exploitation. Commande de charge. Fiabilité, Operation. Load control. Reliability, Divers, Miscellaneous, Planification réseau électrique, Power system planning, Coût, Costs, Coste, Dépendance du temps, Time dependence, Dependencia del tiempo, Economie réseau électrique, Power system economics, Effet on off, On off effect, Efecto on off, Espace état, State space, Espacio estado, Etude comparative, Comparative study, Estudio comparativo, Fonction coût, Cost function, Función coste, Fonction exponentielle, Exponential function, Función exponencial, Fonction non linéaire, Non linear function, Función no lineal, Gestion prévisionnelle, Forecasting management, Gestión provisional, Marché électricité, Power markets, Méthode Lagrange, Lagrangian method, Método Lagrange, Méthode combinatoire, Combinatorial method, Método combinatorio, Méthode relaxation, Relaxation method, Método relajación, Ordonnancement, Scheduling, Reglamento, Planification distribution énergie électrique, Power distribution planning, Problème livraison, Dispatching problem, Problema reparto, Programmation partiellement en nombres entiers, Mixed integer programming, Programación mixta entera, Réseau électrique, Electrical network, Red eléctrica, Solution optimale, Optimal solution, Solución óptima, Temps minimal, Minimum time, Tiempo mínimo, Lagrangian relaxation, Power scheduling, Thermal generators, Unit commitment problem
Subject Geographic:
Amérique du Nord, North America, America del norte, Amérique, America, Etats-Unis, United States, Estados Unidos
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Department of Electronics and Computer Engineering, Hong Kong University of Science and Technology, Hong-Kong
ISSN:
0142-0615
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28307092
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Electrical engineering. Electroenergetics
Accession Number:
edscal.28307092
Database:
PASCAL Archive

Further Information

In this paper, we present a new formulation and solution method for the well known unit commitment problem (UCP) for scheduling the thermal generators in a day-ahead electricity market. Compared to the traditional approach, our approach has several advantages such as: (a) reducing the combinatorial complexity (i.e., the size of the binary state space) significantly, (b) eliminating the need for linearizing the constraints associated with the minimum ON time and minimum OFF time for any thermal generator, (c) eliminating the need for defining new binary decision variables to represent the startup and shutdown decisions for any thermal generator in each hour and (d) eliminating the need to linearize the non-linear cost functions associated with any thermal generator (e.g., time dependent exponential startup cost function). According to our formulation, the UCP can be stated as finding a feasible path of ON-OFF states for each generator (i.e., a sequence of unit commitment states that satisfy the corresponding minimum ON time and minimum OFF time constraints over the scheduling horizon) such that the total generation cost is minimized while meeting the demand and reserve requirement in each hour for the next day. We show how a near optimal solution for the UCP can be constructed using our solution method which is based on the Lagrangian relaxation (LR) method. Although only a near optimal solution is found, we show that our solution is comparable to that obtained when the UCP is modeled as a mixed integer linear program (MILP).