Constrained Elitist Genetic Algorithm for Economic Load Dispatch: Case Study on Nigerian Power System

Orike, Sunny; Corne, David

doi:10.5120/13245-0706

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…Rahul M, et al propose genetic algorithm to improve the direct torque control errors of the inductor, turbine compressor system, and servo dc drive, demonstrating the superiority of the genetic algorithm of independent soft-control controllers and conventional controllers [45]. The authors in [5, 46,47,48,49,50] propose genetic algorithms as a solution to the problem of economic dispatch. They agreed in technique procedures and differed in the case study.…”

Section: Volume (2) Issue (2)mentioning

confidence: 99%

Optimization techniques for economic load dispatch problem in power plant

2021

SUDORJ

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This paper presents survey of optimization techniques used to solve the problem of economic load dispatch in power stations. Since there is no single method available for solving all economic dispatch problems efficiently, thus a number of different optimization methods have been developed to solve this problem. These techniques were divided into three types depending on the efficiency of the solution: stochastic process techniques, statistical methods, and mathematical programming techniques which divided to local optimization, and global optimization. It is found that is better to use hybrid techniques to overcome load dispatch problems so as to achieve significant improvements in computation time, convergence properties, solution quality, or parameter robustness.

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Section: Volume (2) Issue (2)mentioning

confidence: 99%

Optimization techniques for economic load dispatch problem in power plant

2021

SUDORJ

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“…Limited ELD-oriented optimization-based study has been done, addressing only the SELD or close variants thereof. Related aspects of the Nigerian system have been studied [36]. Power transmission and contingency analysis were carried out to compute bus voltages, bus powers and transmission losses in a section of the Nigerian transmission network in [37,38].…”

Section: A Review Of Related Workmentioning

confidence: 99%

Evolutionary algorithms for bid-based dynamic economic load dispatch: A large-scale test case

Orike

Corne

2014

2014 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE)

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The bid-based dynamic economic load dispatch problem (BBDELD) is an optimization problem that arises in the modern context of a de-regulated national energy market, and involves matching bids from competing generating companies to the demands of consumers (regions) so as to maximize a measure of 'social profit'. We present a novel approach to solving the BBDELD, and introduce a large-scale test-case designed to reflect the deregulated Nigerian electricity industry. We build on previous work on smart evolutionary algorithm approaches to the static economic load dispatch (SELD) and dynamic economic load dispatch (DELD) problems, and also the BBELD (the nondynamic form). We evaluate the performance of two evolutionary algorithm, previously reported on small-scale test cases of the BBELD, on dynamic extensions of those test cases (with demand profiles varied over 24 periods), and we introduce a new large-scale test case based on Nigerian sector data, involving 40 generators, 11 customers in 24 dispatch periods. The results demonstrate that the two approaches reported seem more effective than previous approaches on the previously reported cases (when tested on the non-dynamic versions for which prior results are available), and are capable of dealing successfully with the country's large-scale test case.

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“…Heuristic methods, like Genetic Algorithm, Evolutionary algorithm, Fuzzy logic and neural networks, have evolved to evade the above difficulties (Wei-Tzer et-al. 2018) and are known as complete and effective tools in power system optimization (Orike and Corne 2013).…”

Section: Introductionmentioning

confidence: 99%

Lambda Iteration and Genetic Algorithms Application to solve the Economic Load Dispatch Problem of Seven Nigerian Thermal Power Plants

2021

JETP

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Economic load dispatch (ELD) is a method of earmarking the required load demand between the existing generations in power system and principally determining allocation of generators to each generation for various systems load levels. ELD is an essential component in power system planning and operation. ELD solutions are found by solving the conventional load flow equations, while at the same time ensuring that fuel costs are minimized. There are many methods developed for solving ELD problems, but this work is restricted to two, which are the Lambda Iteration Method (LIM) and the Genetic Algorithm (GA) modified with sorting algorithm. The main objective is to apply the two methods to solve ELD problems in power system networks by comparing the performance of GA method with that of LIM in terms of fuel cost efficiency. The usefulness of LIM and GA to solving economic dispatch problem is emphasized. Simulation results obtained on this network using GA and LIM verify their effectiveness in solving ELD problems. Lastly, GA and LIM approaches have been effectively applied to the harmonization of the Nigerian 32-bus system powered by seven thermal and three hydro generating units. The study shows that GA exhibits better results than LIM from both best possible generation allocations. The results obtained demonstrate that GA based method gave better solution in terms of fuel cost reduction, when compared with those obtained using LIM. By blending the probabilities of crossover and mutation, and the application of sorting techniques, computer usage time can be significantly reduced in the system with better fuel cost reduction.

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Constrained Elitist Genetic Algorithm for Economic Load Dispatch: Case Study on Nigerian Power System

Cited by 5 publications

References 15 publications

Optimization techniques for economic load dispatch problem in power plant

Optimization techniques for economic load dispatch problem in power plant

Evolutionary algorithms for bid-based dynamic economic load dispatch: A large-scale test case

Lambda Iteration and Genetic Algorithms Application to solve the Economic Load Dispatch Problem of Seven Nigerian Thermal Power Plants

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