A Improved Archimedes Optimization Algorithm for multi/single-objective Optimal Power Flow

•Proposed a novel Improved Archimedes Optimization Algorithm•A statistical performance-evaluation proved the validity and effectiveness of the IAOA method•Reducing fossil-based thermal power generation capacity in the region (in the current power system) with OPF by incorporating renewable energy so...

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Vydáno v:Electric power systems research Ročník 206; s. 107796
Hlavní autor: Akdag, Ozan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 01.05.2022
Elsevier Science Ltd
Témata:
Algorithms
Electricity distribution
Fuel emissions
Green energy
Improved Archimedes optimization algorithm
Offshore energy sources
OPF
Optimization
Optimization algorithms
Power flow
Simulation
System effectiveness
Wind power
Green energy
Fuel emissions
OPF
Improved Archimedes optimization algorithm
ISSN:0378-7796, 1873-2046
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Shrnutí:•Proposed a novel Improved Archimedes Optimization Algorithm•A statistical performance-evaluation proved the validity and effectiveness of the IAOA method•Reducing fossil-based thermal power generation capacity in the region (in the current power system) with OPF by incorporating renewable energy sources to reduce fuel emissions In this paper, an Improved Archimedes Optimization Algorithm (IAOA) is proposed to solve the Optimal Power Flow problem (OPF). The purpose of improving this IAOA algorithm is to increase population diversity in AOA, further improve the balance between the exploitation and exploration of AOA, and avoid premature convergence problems. The IAOA strategy uses a different approach to build a neighborhood for each object in which neighbor data can be transferred between objects. Dimension learning-based strategy is used for this process. The IAOA and AOA have been examined on the IEEE 30-bus, IEEE 57-bus and 16-bus South Marmara regional transmission systems. The effectiveness of the proposed IAOA and AOA are tested with the standard IEEE 30-bus and IEEE 57-bus system and the simulation results are compared with different techniques as available published in the literature in recent years. In addition, in this study, an Offshore Wind Farm (OWF) and 16-bus South Marmara transmission system is modeled, and later OWF is integrated into a 16-bus South Marmara transmission system. Afterward, IAOA and other algorithms have tested for minimization of fuel emissions in this transmission system. The obtained simulation results and the comparison with different techniques show that the IAOA provides robustness. Graphical Abstract [Display omitted] .
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ISSN:0378-7796
1873-2046
DOI:10.1016/j.epsr.2022.107796