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Serdar Ozyon - One of the best experts on this subject based on the ideXlab platform.

  • artificial bee colony algorithm with dynamic population size to combined economic and emission dispatch Problem
    International Journal of Electrical Power & Energy Systems, 2014
    Co-Authors: Dogan Aydin, Serdar Ozyon, Celal Yasar, Tianjun Liao
    Abstract:

    Abstract Incremental Artificial Bee Colony algorithm with Local Search (IABC-LS) is one of efficient variant of artificial bee colony Optimization which was successfully applied to economic power dispatch Problems before. However IABC-LS algorithm has some tunable parameters which are directly affecting the algorithm behavior. In this study, we have introduced a new algorithm namely Artificial Bee Colony with Dynamic Population size (ABCDP) which is using similar mechanisms defined in IABC-LS without using many parameters to be tuned. To prove the efficiency and robustness of algorithm in power dispatch, the algorithm is used for the combined economic and emission dispatch Problem which is converted into single objective Optimization Problem. For fair comparison, the parameters of both IABC and ABCDP algorithms are determined via automatic parameter configuration tool, Iterated F-Race. IEEE 30 bus test system and 40-generator units Problem are used as the Problem instances. The results of the algorithms indicate that ABCDP is giving good results in both systems and very competitive with the state-of-the-art.

  • charged system search algorithm for emission constrained economic power dispatch Problem
    Energy, 2012
    Co-Authors: Serdar Ozyon, Hasan Temurtas, Burhanettin Durmus, Gultekin Kuvat
    Abstract:

    Today it is very important to consider environmental effects in economic power dispatch Problems as well. These kinds of Problems, which are called environmental economic power dispatch Problems, are multi-objective Optimization Problems. In the present study, in order to find the pareto-optimal results, the Problem has been transformed into Single-Objective Optimization Problem by using weighted sum method. Charged system search algorithm (CSS) has been used for the solution of the transformed Problem. CSS algorithm has been applied to the 30 bus 6 generator (IEEE) test system by including transmission line losses. Also, economic power dispatch Problem with prohibited operating zone which considers ramp rate limit, has been solved by CSS. B loss matrix has been used for the computation of the transmission line losses. In the study, the pareto-optimal solutions obtained for different weight values (w) have been compared with the solution values obtained by the other methods in literature.

  • solution to scalarized environmental economic power dispatch Problem by using genetic algorithm
    International Journal of Electrical Power & Energy Systems, 2012
    Co-Authors: Celal Yasar, Serdar Ozyon
    Abstract:

    Abstract Nowadays, the widespread use of fossil based fuels in power generation units requires the consideration of the environmental pollution. Therefore, in this study, the solution of scalarized environmental economic power dispatch Problem in which the environmental pollution has been taken into consideration has been analyzed by using genetic algorithm (GA). In order to turn the environmental economic power dispatch Problem into the single objective Optimization Problem, the conic scalarization method (CSM) has been used. Also, weighted sum method (WSM) has been utilized in the scalarization of the same Problem for comparison with CSM. The solution algorithm is tested for the electric power system of thermal units which has been solved by different methods in the literature. The best solution values that give minimum total fuel cost and minimum total emission values have been obtained (Pareto optimal values) for different weight values under electric constraints via CSM and WSM. The obtained Pareto optimal values for different scalarization methods have been compared with each other.

Celal Yasar - One of the best experts on this subject based on the ideXlab platform.

  • artificial bee colony algorithm with dynamic population size to combined economic and emission dispatch Problem
    International Journal of Electrical Power & Energy Systems, 2014
    Co-Authors: Dogan Aydin, Serdar Ozyon, Celal Yasar, Tianjun Liao
    Abstract:

    Abstract Incremental Artificial Bee Colony algorithm with Local Search (IABC-LS) is one of efficient variant of artificial bee colony Optimization which was successfully applied to economic power dispatch Problems before. However IABC-LS algorithm has some tunable parameters which are directly affecting the algorithm behavior. In this study, we have introduced a new algorithm namely Artificial Bee Colony with Dynamic Population size (ABCDP) which is using similar mechanisms defined in IABC-LS without using many parameters to be tuned. To prove the efficiency and robustness of algorithm in power dispatch, the algorithm is used for the combined economic and emission dispatch Problem which is converted into single objective Optimization Problem. For fair comparison, the parameters of both IABC and ABCDP algorithms are determined via automatic parameter configuration tool, Iterated F-Race. IEEE 30 bus test system and 40-generator units Problem are used as the Problem instances. The results of the algorithms indicate that ABCDP is giving good results in both systems and very competitive with the state-of-the-art.

  • solution to scalarized environmental economic power dispatch Problem by using genetic algorithm
    International Journal of Electrical Power & Energy Systems, 2012
    Co-Authors: Celal Yasar, Serdar Ozyon
    Abstract:

    Abstract Nowadays, the widespread use of fossil based fuels in power generation units requires the consideration of the environmental pollution. Therefore, in this study, the solution of scalarized environmental economic power dispatch Problem in which the environmental pollution has been taken into consideration has been analyzed by using genetic algorithm (GA). In order to turn the environmental economic power dispatch Problem into the single objective Optimization Problem, the conic scalarization method (CSM) has been used. Also, weighted sum method (WSM) has been utilized in the scalarization of the same Problem for comparison with CSM. The solution algorithm is tested for the electric power system of thermal units which has been solved by different methods in the literature. The best solution values that give minimum total fuel cost and minimum total emission values have been obtained (Pareto optimal values) for different weight values under electric constraints via CSM and WSM. The obtained Pareto optimal values for different scalarization methods have been compared with each other.

Tianjun Liao - One of the best experts on this subject based on the ideXlab platform.

  • artificial bee colony algorithm with dynamic population size to combined economic and emission dispatch Problem
    International Journal of Electrical Power & Energy Systems, 2014
    Co-Authors: Dogan Aydin, Serdar Ozyon, Celal Yasar, Tianjun Liao
    Abstract:

    Abstract Incremental Artificial Bee Colony algorithm with Local Search (IABC-LS) is one of efficient variant of artificial bee colony Optimization which was successfully applied to economic power dispatch Problems before. However IABC-LS algorithm has some tunable parameters which are directly affecting the algorithm behavior. In this study, we have introduced a new algorithm namely Artificial Bee Colony with Dynamic Population size (ABCDP) which is using similar mechanisms defined in IABC-LS without using many parameters to be tuned. To prove the efficiency and robustness of algorithm in power dispatch, the algorithm is used for the combined economic and emission dispatch Problem which is converted into single objective Optimization Problem. For fair comparison, the parameters of both IABC and ABCDP algorithms are determined via automatic parameter configuration tool, Iterated F-Race. IEEE 30 bus test system and 40-generator units Problem are used as the Problem instances. The results of the algorithms indicate that ABCDP is giving good results in both systems and very competitive with the state-of-the-art.

Dogan Aydin - One of the best experts on this subject based on the ideXlab platform.

  • artificial bee colony algorithm with dynamic population size to combined economic and emission dispatch Problem
    International Journal of Electrical Power & Energy Systems, 2014
    Co-Authors: Dogan Aydin, Serdar Ozyon, Celal Yasar, Tianjun Liao
    Abstract:

    Abstract Incremental Artificial Bee Colony algorithm with Local Search (IABC-LS) is one of efficient variant of artificial bee colony Optimization which was successfully applied to economic power dispatch Problems before. However IABC-LS algorithm has some tunable parameters which are directly affecting the algorithm behavior. In this study, we have introduced a new algorithm namely Artificial Bee Colony with Dynamic Population size (ABCDP) which is using similar mechanisms defined in IABC-LS without using many parameters to be tuned. To prove the efficiency and robustness of algorithm in power dispatch, the algorithm is used for the combined economic and emission dispatch Problem which is converted into single objective Optimization Problem. For fair comparison, the parameters of both IABC and ABCDP algorithms are determined via automatic parameter configuration tool, Iterated F-Race. IEEE 30 bus test system and 40-generator units Problem are used as the Problem instances. The results of the algorithms indicate that ABCDP is giving good results in both systems and very competitive with the state-of-the-art.

Raphael T Haftka - One of the best experts on this subject based on the ideXlab platform.

  • constrained particle swarm Optimization using a bi objective formulation
    Structural and Multidisciplinary Optimization, 2010
    Co-Authors: Gerhard Venter, Raphael T Haftka
    Abstract:

    This paper introduces an approach for dealing with constraints when using particle swarm Optimization. The constrained, single objective Optimization Problem is converted into an unconstrained, bi-objective Optimization Problem that is solved using a multi-objective implementation of the particle swarm Optimization algorithm. A specialized bi-objective particle swarm Optimization algorithm is presented and an engineering example Problem is used to illustrate the performance of the algorithm. An additional set of 13 test Problems from the literature is used to further validate the performance of the newly proposed algorithm. For the example Problems considered here, the proposed algorithm produced promising results, indicating that it is an approach that deserves further consideration. The newly proposed algorithm provides performance similar to that of a tuned penalty function approach, without having to tune any penalty parameters.