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

Mondal, Soumitra; Bhattacharya, Aniruddha; Dey, Soumyajit

doi:10.1016/j.ijepes.2012.06.049

Cited by 162 publications

(81 citation statements)

References 39 publications

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“…These two conflicting objectives give a set of possible optimal solutions instead of one optimal solution. Therefore, this problem can be solved by transforming the multiobjective optimization problem into a single-objective function by using the appropriate PPF [14]. The PPF is used to blend the emission level into cost level as described in [28].…”

Section: Economic-emission Load Dispatch Problemmentioning

confidence: 99%

“…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%

“…total fuel cost and emission amount). In [14,16,17], the best compromise solution (in the set Pareto front solution) was obtained by implementing fuzzy set theory. It can help the system operator choose the best compromise solution among multiple solutions obtained by the multiobjective optimization method.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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Section: Economic-emission Load Dispatch Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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

View full text Add to dashboard Cite

show abstract

“…In the next we will explain just genetic algorithm as the most popular evolutionary algorithm and its application in GrSC activities. Recently Mondal et al [62] used GSA to minimize the emission of nitrogen oxides and fuel consumption. Although this paper is in the field of load dispatch, but the same idea can be used to minimize fuel consumption and carbon emission in logistics network in GrSC.…”

Section: Evolutionary Algorithmsmentioning

confidence: 99%

A Review of Nature-Based Algorithms Applications in Green Supply Chain Problems

Sadrnia¹,

Soltani²,

Zulkifli³

et al. 2014

IJET

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Abstract-In the recent years, there is a significant attention among researchers and practitioners to environmental issues and green supply chain (GrSC) because of legislations and profit oriented motivations.Because of considering environmental issues GrSC besides the economic variables, the models are very difficult to find optimal. Hence, complicated green problems call for development of modern optimization methods and algorithms to solve optimization models by efficient techniques. In recent decades, meta-heuristic algorithms have been developed to overcome the problem that most of them are inspired from nature. Some of the algorithms have been inspired from natural generation, some of them inspired from swarm behavior, and others simulate natural processes. In this research we summarize the recent advance evolutionary optimization algorithms and swarm intelligence algorithms which are applied to GrSC and green logistics. Literature reviewed in this paper shows the current state of the art and discusses the potential future research trends.Index Terms-Evolutionary algorithms, green supply chain, meta-heuristic, swarm intelligence algorithms.

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“…Due to the broad scope and limits of the ELD problem, there have been a lot of extensions in ELD to effectively address different issues. Some of these issues are minimising total emissions to acceptable limits brought about by state regulations (Mondal et al, 2013;Singh and Kumar, 2015), incorporating renewable energy sources (RES) (Alham et al, in press; Velamuri et al, in press), creating demand response models to balance out demand against supply (O'Connell et al, 2016), and distributed generation which allocates power to those who are far from the power grids (Govardhan and Roy, 2016). The complex behaviour of ELD has challenged many domain scholars in solving the required optimisation problem.…”

Section: Introductionmentioning

confidence: 99%

Policy-based unit commitment problem: a case in a peaking power generation plant

Wamilda

Santillan

Senen

et al. 2017

IJADS

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Unit commitment (UC) along with economic load dispatch (ELD) is an integral optimisation problem in the power generation industry. In this paper, policy-based algorithms are developed to address dispatch problems under different system configurations with the benefit of providing flexibility in addressing several desired policies of decision-makers. A case study is conducted in a diesel-fired, power plant in central Philippines to elucidate the proposed approach. Three policies were created to effectively address the optimisation problem: 1) classic UC model; 2) buying and selling strategy; 3) continuous loading strategy with various issues being considered. Results show that the strategies exhibit a significant decrease in total costs and ease of implementation with respect to the current production schedule of the case firm. Furthermore, the second policy provides the least generated cost which implies that generating firms must consider the option to sell power when market prices reach desired levels.

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

Cited by 162 publications

References 39 publications

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

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

A Review of Nature-Based Algorithms Applications in Green Supply Chain Problems

Policy-based unit commitment problem: a case in a peaking power generation plant

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