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A Memory Simulated Annealing Method to the Unit Commitment Problem with Ramp Constraints

  • Research Article - Electrical Engineering
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Abstract

This paper proposes an improved local search metaheuristic using simulated annealing method with memory component (MSA) for solving the unit commitment problem (UCP) with ramp constraints. The proposed method benefits simultaneously from the advantages of a two metaheuristics: acceptance of “bad” solutions in order to escape from local optimal configurations (SA), and prohibition for a time period of certain areas already been searched (Tabu list) as used in Tabu search method. The proposed effective MSA method is tested on several systems as the conventional ten unit test system and its multiples with 24-h scheduling horizon and the IEEE 118-bus system with 54 units. To justify the success of the MSA method, a comparison of results with those of other metaheuristic methods and hybrid methods treated by recent references is made. The results show that the proposed method obtains less total operation costs than the others with an acceptable time computing and indicate its potential for solving the UCP.

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Abbreviations

MSA:

Memory simulated annealing

TS:

Tabu search

GRASP:

Greedy randomized adaptive search procedure

EP:

Evolutionary programming

GA:

Genetic algorithm

GAUC:

Genetic algorithm based on unit characteristic classification

IPSO:

Improved particle swarm optimization

MA:

Memetic algorithm

BCGA:

Binary coded genetic algorithm

ICGA:

Integer coded genetic algorithm

LRGA:

Lagrangian relaxation-genetic algorithm

SFA:

Straightforward algorithm

F T :

Total operation cost ($)

P i (t):

Generation output of unit i at hour t (MW)

N :

Set of indexes of the generating units

I :

Index of units

N t :

Set of indexes of the time periods (h)

t :

Index of time periods

U i (t):

Status of unit i at hour t (on = 1, off = 0)

a i , b i , c i :

Coefficients of quadratic fuel cost function of unit i

S i (t):

Start up cost of unit i at hour t ($)

P D (t):

System load demand at hour t (MW)

\({P_i^{\max}}\) :

Maximum output power of unit i (MW)

\({P_i^{\min}}\) :

Minimum output power of unit i (MW)

P R(t):

System spinning reserve at hour t (MW)

ST i (t):

Start-up cost of unit i ($)

CSC i :

Cold start up cost of unit i ($)

HSC i :

Hot start up cost of unit i ($)

SC i :

Cold start up time of unit i (h)

DC i (t):

Shut-down cost of unit i ($)

\({X_i^{\rm ON}}\) :

Continuous on time of unit i (h)

\({X_i^{\rm OFF}}\) :

Continuous off time of unit i (h)

UR i :

Ramp-up rate limit of unit i (MW/h)

DR i :

Ramp-down rate limit of unit i (MW/h)

MDT i :

Minimum down time of unit i (h)

MUT i :

Minimum up time of unit i (h)

T 0,T min :

Initial and minimal temperature

α :

Temperature reduction factor

TL:

Tabu list

itrmax :

Maximum number of iterations

PL:

Priority list of units

P load :

Priority list of loads

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Authors and Affiliations

  1. Laboratoire d’Analyse et de Commande des Systèmes d’Energie et Réseaux Electriques (LACoSERE), University of Laghouat, Laghouat, Algeria

    S. Arif, A. Hellal & A. Choucha

  2. Electrical Engineering Department, University of Djelfa, Djelfa, Algeria

    R. D. Mohammedi

Authors
  1. S. Arif
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  2. R. D. Mohammedi
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  3. A. Hellal
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  4. A. Choucha
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Correspondence to S. Arif.

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Arif, S., Mohammedi, R.D., Hellal, A. et al. A Memory Simulated Annealing Method to the Unit Commitment Problem with Ramp Constraints. Arab J Sci Eng 37, 1021–1031 (2012). https://doi.org/10.1007/s13369-012-0217-2

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  • DOI: https://doi.org/10.1007/s13369-012-0217-2

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