Reduce Power Generation Cost by Using Load Dispatch Schedule

This paper addresses the preliminary new development results of the evolutionary algorithm technique to optimize the formulated problems incorporating the generation cost with emission gas as objective function or constraints. The power generation cost with emission gas are a complex problem which also the major concerns in electric power generation systems in the Environmental or Economic Dispatch Problems (EDP). Thus, due to environmental concern the electrical utilities required to minimize the emission level while optimizing the thermal generating units at a minimum generating cost and hence, satisfying the load demand and the emissions. In this work the electromagnetism-Like algorithm (EML) has been employed for optimizing generation cost and emission constraints economic dispatch problem. The proposed decision analysis tool software in this work will optimize the generation cost with emission gas objective function. The best generation cost with emission gas solution are obtained from different fuel technology via the developed software.

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Framework for evaluating the generation cost and wind power generation capacity constrained by operating reserve

2012 IEEE International Conference on Power System Technology (POWERCON) ◽

10.1109/powercon.2012.6401326 ◽

2012 ◽

Cited By ~ 1

Author(s):

K. Furusawa ◽

K. Okada

Keyword(s):

Power Generation ◽

Wind Power ◽

Wind Power Generation ◽

Generation Cost ◽

Generation Capacity ◽

Capacity Constrained

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Optimal economic dispatch of power generation solution using lightning search algorithm

IAES International Journal of Artificial Intelligence (IJ-AI) ◽

10.11591/ijai.v9.i3.pp371-378 ◽

2020 ◽

Vol 9 (3) ◽

pp. 371

Author(s):

Murad Yahya Nassar ◽

Mohd Noor Abdullah ◽

Asif Ahmed Rahimoon

Keyword(s):

Power Generation ◽

Power System ◽

Optimization Problems ◽

Search Algorithm ◽

Thermal Power ◽

Economic Dispatch ◽

Optimal Solution ◽

Fuel Price ◽

Solution Quality ◽

Generation Cost

Economic dispatch (ED) is the power demand allocating process for the committed units at minimum generation cost while satisfying system and operational constraints. Increasing cost of fuel price and electricity demand can increase the cost of thermal power generation. Therefore, robust and efficient optimization algorithm is required to determine the optimal solution for ED problem in power system operation and planning. In this paper the lightning search algorithm (LSA) is proposed to solve the ED problem. The system constraints such as power balance, generator limits, system transmission losses and valve-points effects (VPE) are considered in this paper. To verify the effectiveness of LSA in terms of convergence characteristic, robustness, simulation time and solution quality, the two case studies consists of 6 and 13 units have been tested. The simulation results show that the LSA can provide optimal cost than many methods reported in literature. Therefore, it has potential to solve many optimization problems in power dispatch and power system applications.

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Economic load dispatch solutions considering multiple fuels for thermal units and generation cost of wind turbines

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v11i5.pp3718-3726 ◽

2021 ◽

Vol 11 (5) ◽

pp. 3718

Author(s):

Anh Tuan Doan ◽

Dinh Thanh Viet ◽

Minh Quan Duong

Keyword(s):

Power Generation ◽

Particle Swarm Optimization ◽

Wind Farm ◽

Particle Swarm ◽

Wind Farms ◽

Total Power ◽

Economic Load Dispatch ◽

Swarm Optimization ◽

Generation Cost ◽

Constriction Factor

In this paper, economic load dispatch (ELD) problem is solved by applying a suggested improved particle swarm optimization (IPSO) for reaching the lowest total power generation cost from wind farms (WFs) and thermal units (TUs). The suggested IPSO is the modified version of Particle swarm optimization (PSO) by changing velocity and position updates. The five best solutions are employed to replace the so-far best position of each particle in velocity update mechanism and the five best solutions are used to replace previous position of each particle in position update. In addition, constriction factor is also used in the suggested IPSO. PSO, constriction factor-based PSO (CFPSO) and bat optimization algorithm (BOA) are also run for comparisons. Two systems are used to run the four methods. The first system is comprised of nine TUs with multiple fuels and one wind farm. The second system is comprised of eight TUs with multiple fuels and two WFs. From the comparisons of results, IPSO is much more powerful than three others and it can find optimal power generation with the lowest total power generation cost.

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