Opposition-based gravitational search algorithm applied to economic power dispatch problems consisting of thermal units with emission constraints

Özyön, Serdar; Yaşar, Celal; Durmuş, Burhanettin; Temurtaş, Hasan

doi:10.3906/elk-1305-258

Cited by 14 publications

(5 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As is seen from Fig. 4, the best comprise solutions of NSGA- [17], FPA [5] are located above the Pareto-front clearly and the ones of MODE [22], PDE [22], SPEA2 [22], GSA [29] and v-MOGA [30] are also above the Pareto-front and locate near the solution of KSO when w = 0.5, which implies that the solution of KSO dominates the best comprise solutions of these algorithms. Meanwhile, the best comprise solutions of BSA [31], QOTLBO [16], TLBO [16], OGHS [32], NGPSO [27] are just on the Pareto-front which mean the competitive performance of KSO with them.…”

Section: Resultsmentioning

confidence: 84%

New Optimization Algorithm Inspired by Kernel Tricks for the Economic Emission Dispatch Problem With Valve Point

Dong

Wang

2020

IEEE Access

View full text Add to dashboard Cite

With the increasing concern over environment protection, Economic Emission Dispatch (EED) problem has received much attention. It is essentially a Multi-objective Optimization Problem, which minimizes both fuel cost and emission pollution simultaneously, as well as meets some system limits. This study transforms EED problem to a single-objective problem with weighted sum method, and then use Newton method to solve the equality constraint iteratively and introduce a common penalty function to deal with the inequality constraint. Moreover, this study tries to propose a new meta-heuristic algorithm inspired by kernel tricks to solve EED problem with no hyper parameters to be tuned. The new algorithm can map a non-linear objective function into a linear one with higher-dimension. Thus the optimization process could be transformed into a linear process, which is more likely to get the optimum solution. When applied in the 3 real-world EED cases with valve point, the new algorithm achieved a better performance compared with other algorithms in the literature. INDEX TERMS Economic emission dispatch, Kernel search optimization, meta-heuristic algorithm, swarm intelligence.

show abstract

Section: Resultsmentioning

confidence: 84%

New Optimization Algorithm Inspired by Kernel Tricks for the Economic Emission Dispatch Problem With Valve Point

Dong

Wang

2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Best fuel cost (w = 1.0) Best pollution emission (w = 0.0) which also illustrates the best comprising solutions obtained by some algorithms in the literature. As seen from Figure 5, the best comprising solutions of NSGA [21] and FPA [13] were located above the Pareto front clearly and those of MODE [23], PDE [23], SPEA2 [23], GSA [8], and ϵv-MOGA [29] were also above the Pareto front and located near the solution of FSO when w = 0.5, which implied that the solution of FSO dominated the best comprising solutions of these algorithms. Meanwhile, the best comprising solutions of BSA [30], QOTLBO [20], TLBO [20], OGHS [31], and NGPSO [27] were just on the Pareto front, which showed the competitive performance of FSO with them.…”

Section: Algorithmmentioning

confidence: 92%

“…In general, there are mainly two approaches. One is converting the multiobjective problem into a single objective optimization problem and solving it with metaheuristic algorithms, such as the genetic algorithm (GA) [5], particle swarm optimization algorithm (PSO) [6], differential evolution algorithm (DE) [7], opposition-based gravitational search algorithm (OGSA) [8], opposition-based harmony search algorithm (OHS) [9], spiral optimization algorithm (SOA) [10], virus optimization algorithm (VOA) [11], moth swarm algorithm (MSA) [12], flower pollination algorithm (FPA) [13], modified bacterial foraging algorithm (MBFA) [14], and charged system search algorithm (CSS) [15].…”

Section: Introductionmentioning

confidence: 99%

New optimization algorithm inspired by fluid mechanics for combined economic and emission dispatch problem

Dong¹,

Wang²

2018

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

With the increasing concern over environmental protection, the combined economic emission dispatch (CEED) problem has received much attention. It needs to minimize both fuel cost and emission pollution. This study aims to propose a new metaheuristic algorithm inspired by fluid mechanics to solve the CEED problem with the weighted sum method. The new algorithm simulates the inverse process of fluid flowing spontaneously from high pressure to low pressure, similar to the optimization process of the CEED problem. When applied in two real-world cases, the new algorithm achieves better performance compared with other algorithms in the literature.

show abstract

“…The process that GA undergoes until it comes to a solution can be described as coding the solution set, creating the initial population, assessing the compatibility of the solutions in the population, choosing the progenitor individuals according to the compatibility and creating new individuals through crossover and mutation processes. As for the control parameters of the GA, the crossover rate and the mutation rate are selected between 0.5-1.0 and 0.0001-0.05, respectively [20][21][22][23].…”

Section: Genetic Algorithmmentioning

confidence: 99%

Solving the economic dispatch by new hybrid algorithm

Naama

2024

ELECTROTECHNICAL REVIEW

View full text Add to dashboard Cite

The problem of economic dispatch is the minimization of the total cost of production by satisfying the demand of the load. The resolution of this problem is a way of managing an electricity production system taking into account the constraints of equalities and inequalities, in other words it is to find the optimal production for a given combination of units in operation. The appearance of meta-heuristic methods which are part of artificial intelligence, has effectively contributed to solving this problem. Bee colony optimization is a very recent family of meta-heuristics. Its principle is based on the behavior of real bees in life. Bees have properties that are quite different from those of other insect species. They live in colonies, building their nests in tree trunks or other similar enclosed spaces. In this paper, we will apply the optimization by colony of bees in test systems of different sizes with the aim of minimizing the cost of production of electrical energy by taking into account the effect of the valve points of the power plants. In order to see the effectiveness of the proposed algorithm, it has been compared with other algorithms in the literature.

show abstract

Opposition-based gravitational search algorithm applied to economic power dispatch problems consisting of thermal units with emission constraints

Cited by 14 publications

References 23 publications

New Optimization Algorithm Inspired by Kernel Tricks for the Economic Emission Dispatch Problem With Valve Point

New Optimization Algorithm Inspired by Kernel Tricks for the Economic Emission Dispatch Problem With Valve Point

New optimization algorithm inspired by fluid mechanics for combined economic and emission dispatch problem

Solving the economic dispatch by new hybrid algorithm

Contact Info

Product

Resources

About