Study of Economic Load Dispatch by Various Hybrid Optimization Techniques

Santra, Dipankar; Mondal, Arindam; Mukherjee, Anirban

doi:10.1007/978-81-322-2544-7_2

Cited by 8 publications

(5 citation statements)

References 49 publications

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“…Economic Load Dispatch (ELD) problems can be solved by using traditional as well as advanced optimization techniques such as robust and heuristic optimizations [35,36], where minimization of the cost function is one of the major objectives in all techniques [37]. In conventional approaches, cost function can also be transformed as a fuel-cost curve depending upon a total number of energy generation units.…”

Section: Related Workmentioning

confidence: 99%

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

et al. 2018

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This paper proposes a system model for optimal dispatch of the energy and reserve capacity considering uncertain load demand and unsteady power generation. This implicates uncertainty in managing the power demand along with the consideration of utility, user and environmental objectives. The model takes into consideration a day-ahead electricity market that involves the varying power demand bids and generates a required amount of energy in addition with reserve capacity. The lost opportunity cost is also considered and incorporated within the context of expected load not served. Then, the effects of combined and separate dispatching the energy and reserve are investigated. The nonlinear cost curves have been addressed by optimizing the objective function using robust optimization technique. Finally, various cases in accordance with underlying parameters have been considered in order to conduct and evaluate numerical results. Simulation results show the effectiveness of proposed scheduling model in terms of reduced cost and system stability.

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Section: Related Workmentioning

confidence: 99%

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

et al. 2018

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“…In [37] different techniques and their hybrid combination based on different has been reviewed and addressed the complexity related to every computational techniques. A review of different hybrid approaches developed for the solution combined economic emission dispatch problem [38].…”

Section: Related Workmentioning

confidence: 99%

Economic Dispatch Solution for Generating Units through Optimization

Nazeer¹,

Jamil²,

Mohsin³

et al. 2020

IJEW

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The complex nature of the modern power system is because of the interconnection of the generating units and day by day increased load demand. The main purpose of the power system is to tantalize the load needs and generate reliable and cheap energy i.e. cost of generation should be optimum i.e. operating every generating unit in such a way to optimize the cost. The cost function of every generating unit is different from other generating unit, so load has to be divided among various generating units to obtain optimum generation. The optimization of power system is done by Economic load dispatch (ELD). ELD is of immense importance in power system operation and planning (PSOP). The primary purpose of ELD is to pacify the load needs at lowest cost while satiating all kind of equality and inequality constraints. Power system has highly non-linear input output characteristics because of different generation constraints. In ELD cost function of each and every generating unit is equated as quadratic function. Numerous methods have been devised to figure out ELD problem incorporating conventional methods like Lambda iteration method and Gradient method, and artificial intelligent method like Particle Swarm Optimization, Generic Algorithms etc. In this thesis optimization of generating units is done through General Algebraic Modelling System (GAMS). GAMS is a modelling system used for mathematical programming and optimization on a large scale. It helps to develop a mathematical model similar to their corresponding mathematical expression and gives more accurate results.

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“…Te ELD problem has previously been solved using numerical approaches such as gradient and Lambda iteration methods. Recently, metaheuristic optimization algorithms are utilized in many felds [22,23]. Te optimization problem, however, potentially adds extra complications to nonlinear control variables attributable to the penetration of renewable energy sources [9,[24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Metaheuristic Model for Optimal Economic Load Dispatch in Renewable Hybrid Energy System

Miracle

Viral

Tiwari

et al. 2023

International Transactions on Electrical Energy Systems

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Hybrid generating systems in power networks have emerged as a result of the rapid growth of renewable infrastructure and widespread support for green energy. One of the most significant problems in designing and operating an electric power generation system is the efficient scheduling of all power generation facilities to meet the rising power demand. Economic load dispatch (ELD) is a generic procedure in the electrical power system, and the ELD in power system problems involves scheduling the power generating units to reduce cost and satisfy system constraints. Metaheuristic algorithms are gaining popularity for solving constrained ELD issues because of their larger global solution capacity, flexibility, and derivative-free construction. In this research, the ELD problem of integrated renewable resources is solved using a unique solution model based on hybrid optimization. Furthermore, this work considers multiobjectives such as total wind generation cost, total cost function of thermal units, and penalty cost function. The hybrid optimization model optimizes the power generation of thermal power plants within the maximum and minimum limitations. Additionally, the turbines are selected optimally by the hybrid optimization model to ensure the power generation of wind turbines based on the demands. The proposed hybrid optimization is a combination of particle swarm optimization (PSO) and cat swarm optimization (CSO), and the new algorithm is referred to as the particle oriented cat swarm optimization model (POCSO). Finally, the performance of the proposed work is compared to other conventional models. In particular, the cost function of POCSO is 6.25%, 6%, 11.7%, 36%, 27%, and 46.42% better than the cost function of whale optimization algorithm (WOA), elephant herd optimization (EHO), moth-flame optimization (MFO), dragonfly algorithm (DA), sealion optimization (SLnO), CSO, and PSO methods, respectively. Also, for IEEE-30 bus system, the best value of the proposed work is 7.46%, 5.41%, 16.30%, 14.88%, 17.60%, 13.86%, 15.21%, 17.49%, and 4.27% better than that of the PSO, CSO, SLnO, DA, MFO, EHO, WOA, multiagent glowworm swarm optimization (MAGSO), and Harris hawks optimization-based feed-forward neural network (HHO-FNN) methods, respectively.

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Study of Economic Load Dispatch by Various Hybrid Optimization Techniques

Cited by 8 publications

References 49 publications

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

Economic Dispatch Solution for Generating Units through Optimization

Hybrid Metaheuristic Model for Optimal Economic Load Dispatch in Renewable Hybrid Energy System

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