Solution to scalarized environmental economic power dispatch problem by using genetic algorithm

Yaşar, Celal; Özyön, Serdar

doi:10.1016/j.ijepes.2011.12.020

Cited by 57 publications

(20 citation statements)

References 17 publications

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“…Several methods have been reported in the literature concerning the environmental/economic dispatch problem such as Genetic Algorithms [10][11][12], Differential Evolution Algorithms [13,14], Harmony Search Algorithms [15], Gravitational Search Algorithms [16], Particle Swarm Optimization Algorithms [17][18][19], and Bacterial Foraging Algorithms [20]. Several MOEAs like Niched Pareto Genetic Algorithm (NPGA) [23], Strength Pareto Evolutionary Algorithm (SPEA) [24] and Non-dominated Sorting Genetic Algorithm (NSGA) [25,26] have been applied to multi-objective problems.…”

Section: The Unit Commitment Problem With Environmental Concernsmentioning

confidence: 99%

“…A recent review on the use of multi-objective optimization (MOO) in the energy sector, namely in the electricity sector, can be found in [9]. Several methods have been reported in the literature concerning the environmental/economic dispatch problem such as Genetic Algorithms [10][11][12], Differential Evolution Algorithms [13,14], Harmony Search Algorithms [15], Gravitational Search Algorithms [16], Particle Swarm Optimization Algorithms [17][18][19], and Bacterial Foraging Algorithms [20]. These methods fall into the category of metaheuristics, which are optimization methods known to be able to provide good quality solutions within a reasonable computational time (see e.g., [21,22]).…”

Section: Introductionmentioning

confidence: 99%

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A Metaheuristic Approach to the Multi-Objective Unit Commitment Problem Combining Economic and Environmental Criteria

Roque

Fontes

2017

Energies

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Abstract:We consider a Unit Commitment Problem (UCP) addressing not only the economic objective of minimizing the total production costs-as is done in the standard UCP-but also addressing environmental concerns. Our approach utilizes a multi-objective formulation and includes in the objective function a criterion to minimize the emission of pollutants. Environmental concerns are having a significant impact on the operation of power systems related to the emissions from fossil-fuelled power plants. However, the standard UCP, which minimizes just the total production costs, is inadequate to address environmental concerns. We propose to address the UCP with environmental concerns as a multi-objective problem and use a metaheuristic approach combined with a non-dominated sorting procedure to solve it. The metaheuristic developed is a variant of an evolutionary algorithm, known as Biased Random Key Genetic Algorithm. Computational experiments have been carried out on benchmark problems with up to 100 generation units for a 24 h scheduling horizon. The performance of the method, as well as the quality, diversity and the distribution characteristics of the solutions obtained are analysed. It is shown that the method proposed compares favourably against alternative approaches in most cases analysed.

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Section: The Unit Commitment Problem With Environmental Concernsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Metaheuristic Approach to the Multi-Objective Unit Commitment Problem Combining Economic and Environmental Criteria

Roque

Fontes

2017

Energies

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“…In this approach, the weighted sum method (WSM) is commonly applied to obtain a Pareto optimal solution [10]. The modified bacterial foraging algorithm (MBFA) [11], charged system search algorithm (CSS) [12], genetic algorithm (GA) [13], and gravitational search algorithm (GSA) [14] have been used to solve EELD problems based on this approach. In addition, the conic scalarization method (CSW) was first implemented in [15] for EELD problems and can be an alternative approach to the WSM.…”

Section: Introductionmentioning

confidence: 99%

Modified particle swarm optimization for economic-emission load dispatch of power system operation

Abdullah

Bakar²,

Rahim³

et al. 2015

Turk J Elec Eng & Comp Sci

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This paper proposes a modified particle swarm optimization considering time-varying acceleration coefficients for the economic-emission load dispatch (EELD) problem. The new adaptive parameter is introduced to update the particle movements through the modification of the velocity equation of the classical particle swarm optimization (PSO) algorithm. The idea is to enhance the performance and robustness of classical PSO. The price penalty factor method is used to transform the multiobjective EELD problem into a single-objective problem. Then the weighted sum method is applied for finding the Pareto front solution. The best compromise solution for this problem is determined based on the fuzzy ranking approach. The IEEE 30-bus system has been used to validate the effectiveness of the proposed algorithm.It was found that the proposed algorithm can provide better results in terms of best fuel cost, best emissions, convergence characteristics, and robustness compared to the reported results using other optimization algorithms.

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“…Niknam et al used an efficient evolutionary method known as new adaptive particle swarm optimization [23] and Modified Shuffle Frog Leaping Algorithm with Chaotic Local Search [24] to solve constrained economic dispatch problem. Yasar et al [25] applied genetic algorithm along with conic scalarization method to convert multi-objective problem into single objective problem and solved the environmental emission dispatch problem of power system. Same authors applied combined modified subgradient technique along with harmony search [26] to solve emission dispatch problems.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective economic emission load dispatch solution using gravitational search algorithm and considering wind power penetration

Mondal

Bhattacharya²,

Dey

2013

International Journal of Electrical Power & Energy Systems

165

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Solution to scalarized environmental economic power dispatch problem by using genetic algorithm

Cited by 57 publications

References 17 publications

A Metaheuristic Approach to the Multi-Objective Unit Commitment Problem Combining Economic and Environmental Criteria

A Metaheuristic Approach to the Multi-Objective Unit Commitment Problem Combining Economic and Environmental Criteria

Modified particle swarm optimization for economic-emission load dispatch of power system operation

Multi-objective economic emission load dispatch solution using gravitational search algorithm and considering wind power penetration

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