A simulated annealing-based goal-attainment method for economic emission load dispatch of fixed head hydrothermal power systems

Basu, Mousumi

doi:10.1016/j.ijepes.2004.09.004

Cited by 172 publications

(71 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…1th iteration are updated using Eqs. (10) and (11). For detailed information, readers are referred to [16].…”

Section: Mopso Algorithmmentioning

confidence: 99%

“…Analytical methods [6], a Lagrangian method [7], and the Newton-Raphson method [8] have all been employed as initial approaches. Evolutionary methods have also been employed for this purpose, such as a genetic algorithm [9], particle swarm optimization (PSO) [10], simulated annealing [11], artificial immune system [12], differential evolution [13], and the frog algorithm [14]. In [15], the PSO-SIL algorithm was used to obtain an economical power flow with the optimum costs.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Economic dispatch in a power system considering environmental pollution using a multi-objective particle swarm optimization algorithm based on the Pareto criterion and fuzzy logic

Taheri

Aghajani

Sedaghat

2017

Int J Energy Environ Eng

View full text Add to dashboard Cite

In recent years, many studies have studied economic dispatch problem in power systems. However, most of them have not considered the environmental pollution caused by fossil fuels. In this study, the use of an evolutionary search algorithm called multi-objective particle swarm optimization algorithm is proposed to solve the economic dispatch problem in power systems while considering environmental pollution. The proposed method is validated in terms of its accuracy and convergence speed based on comparisons with the results obtained using the classic nonlinear programming method. The proposed strategy is applied to a realistic power system under various conditions. Overall, six generating units are investigated along the corresponding constraints. The results obtained reveal that costs of operation and pollution with/ without power loss are reduced significantly by the proposed approach. Obtained results show a good compromise can be established between two contradicting functions of exploitation cost and pollution by optimizing them simultaneously.

show abstract

“…1th iteration are updated using Eqs. (10) and (11). For detailed information, readers are referred to [16].…”

Section: Mopso Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Economic dispatch in a power system considering environmental pollution using a multi-objective particle swarm optimization algorithm based on the Pareto criterion and fuzzy logic

Taheri

Aghajani

Sedaghat

2017

Int J Energy Environ Eng

View full text Add to dashboard Cite

show abstract

“…Combined Economic Emission Dispatch (CEED) issue is to schedule the committed generating unit outputs to satisfy the needed load demand at minimum operating cost with minimum emission simultaneously. This multi-objective CEED problem [24,25] is changed into a single objective function with the help of a price penalty factor. Ugur Guvenc et al, [3] proposed a novel Genetic Algorithm technique based on similarity crossover for solving CEED problem in power systems.…”

Section: Related Workmentioning

confidence: 99%

An Advanced Genetic Optimization Algorithm to Solve Combined Economic and Emission Dispatch Problem

Gopalakrishnan¹

2012

BIJMMI

View full text Add to dashboard Cite

show abstract

“…Thereafter many researchers have proposed various methods to solve the combined economic and emission problem. In a research direction, the multi-objective CEED problem was converted into a single objective problem by linear combination of different objectives as a weighted sum [12][13][14]. Farag et al [15] has proposed a linear programming based optimization method in which the objectives are considered separately one at a time.…”

Section: Combined Economic Emissions Dispatchmentioning

confidence: 99%

Combined Economic Emission Dispatch Pareto Optimal Front Approach

Kumar¹,

Phani²

2011

IJCA

View full text Add to dashboard Cite

Recent advancements in artificial intelligence especially in evolutionary algorithms have enabled much efficient way to solve the constrained optimization problems in various fields of engineering. In this paper we explain the development of the optimization techniques from single criterion to multi criterion. We also address the Combined Economic and Emissions Dispatch (CEED) problem in thermal power stations. We use the aggregate objective function approach to solve the multiobjective CEEED problem using firefly optimization technique. Then we simulate the proposed approach on a test system and formulate the pareto optimal front for three different load demands. This proves that the algorithm can be effectively used to solve such multiobjective problems.

show abstract

A simulated annealing-based goal-attainment method for economic emission load dispatch of fixed head hydrothermal power systems

Cited by 172 publications

References 3 publications

Economic dispatch in a power system considering environmental pollution using a multi-objective particle swarm optimization algorithm based on the Pareto criterion and fuzzy logic

Economic dispatch in a power system considering environmental pollution using a multi-objective particle swarm optimization algorithm based on the Pareto criterion and fuzzy logic

An Advanced Genetic Optimization Algorithm to Solve Combined Economic and Emission Dispatch Problem

Combined Economic Emission Dispatch Pareto Optimal Front Approach

Contact Info

Product

Resources

About