Integrating genetic algorithms and tabu search for combined heat and power economic dispatch

Sudhakaran, M.; Slochanal, S. Mary Raja

doi:10.1109/tencon.2003.1273225

Cited by 28 publications

(29 citation statements)

References 4 publications

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“…The solution by the ACSA [6] is $9452.20/hr. This solution is much higher than that obtained by many conventional and non-conventional algorithms reported in [4][5][6]. The results obtained by various evolutionary computing techniques and conventional methods are compared in Table 2.…”

Section: Resultsmentioning

confidence: 75%

“…The solution of simple GA (SGA) [4] violates the power demand constraint. Similarly, the solution obtained in [5] using the combined GA and tabu search algorithm is not feasible, as the computed OEP 3 H 3 is outside the specified region.…”

Section: Resultsmentioning

confidence: 99%

“…The analysis and interpretation of the connection have led to the development of the two-layer algorithm. Evolutionary computing techniques, such as genetic algorithms (GAs) and tabu search [3][4][5], were proposed for finding the solution of CHP dispatch problems. An improved ant colony search algorithm (ACSA) was used in [6].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Selective Particle Swarm Optimization Approach for Combined Heat and Power Economic Dispatch

Ramesh

Jayabarathi

Shrivastava

et al. 2009

Electric Power Components and Systems

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This article presents a new, improved particle swarm optimization algorithm with a selection operator for the solution of the combined heat and power economic dispatch problem. In this technique, starting with a large swarm of particles, only those particles whose fitness is above the scaled average fitness are selected in successive iterations, using a selection factor that is adjustable depending on the nature of the problem. The method is illustrated using a test case. The result compares favorably with other particle swarm optimization variants and other existing non-conventional methods.

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Section: Resultsmentioning

confidence: 75%

Section: Resultsmentioning

confidence: 99%

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A Novel Selective Particle Swarm Optimization Approach for Combined Heat and Power Economic Dispatch

Ramesh

Jayabarathi

Shrivastava

et al. 2009

Electric Power Components and Systems

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show abstract

“…In the past, most work in optimization of CCHP and CHP operation tended to focus only on energy cost [12][13][14][15][16][17][18][19][20]. A significant amount of effort has been made by the several researchers in the field of combined heat and power economic dispatch (CHPED) to develop a better algorithm to attain optimal utilization of CHP units by minimizing the energy cost in CHP operation [14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

“…A significant amount of effort has been made by the several researchers in the field of combined heat and power economic dispatch (CHPED) to develop a better algorithm to attain optimal utilization of CHP units by minimizing the energy cost in CHP operation [14][15][16][17][18][19][20][21]. However, Mago et al [22] introduced different perspectives for evaluating CCHP systems operation.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of CCHP systems performance based on operational cost, primary energy consumption, and carbon dioxide emission by utilizing an optimal operation scheme

et al. 2009

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Social cognitive optimization with tent map for combined heat and power economic dispatch

Sun

2018

Int Trans Electr Energ Syst

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Summary Combined heat and power economic dispatch (CHPED) problem is a sophisticated constrained nonlinear optimization problem in a heat and power production system for assigning heat and power production to minimize the production costs. To address this challenging problem, a novel social cognitive optimization algorithm with tent map (TSCO) is presented for solving the CHPED problem. To handle the equality constraints in heat and power balance constraints, adaptive constraints relaxing rule is adopted in constraint processing. The novelty of our work lies in the introduction of a new powerful TSCO algorithm to solve the CHPED issue. The effectiveness and superiority of the presented algorithm is validated by conducting 2 typical CHPED cases. The numerical results show that the proposed approach has better convergence speed and solution quality than all other existing state‐of‐the‐art algorithms.

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Integrating genetic algorithms and tabu search for combined heat and power economic dispatch

Cited by 28 publications

References 4 publications

A Novel Selective Particle Swarm Optimization Approach for Combined Heat and Power Economic Dispatch

A Novel Selective Particle Swarm Optimization Approach for Combined Heat and Power Economic Dispatch

Evaluation of CCHP systems performance based on operational cost, primary energy consumption, and carbon dioxide emission by utilizing an optimal operation scheme

Social cognitive optimization with tent map for combined heat and power economic dispatch

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