Solving constrained optimal power flow with renewables using hybrid modified imperialist competitive algorithm and sequential quadratic programming

•Proposed a novel Hybrid Modified Imperialist Competitive Algorithm and Sequential Quadratic Programming.•Studied the uncertainties of solar power and wind energy.•Solved different OPF problems including wind and solar generators.•A comparative study proved the effectiveness of the HMICA-SQP in prov...

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Veröffentlicht in:Electric power systems research Jg. 177; S. 105989
Hauptverfasser: Ben Hmida, Jalel, Chambers, Terrence, Lee, Jim
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 01.12.2019
Elsevier Science Ltd
Schlagworte:
Algorithms
Alternative energy sources
Computer simulation
Constraints
Electric power
Electric power systems
Electric power transmission
Evolutionary algorithms
Heuristic methods
Hybrid systems
Mica
Multiobjective optimization
Optimal power flow
Optimization
Power flow
Quadratic programming
Renewable energy sources
Security constraints
Solar energy
Solar power
Wind energy
Wind power
Solar power
Security constraints
Wind energy
Optimal power flow
Multiobjective optimization
ISSN:0378-7796, 1873-2046
Online-Zugang:Volltext
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Zusammenfassung:•Proposed a novel Hybrid Modified Imperialist Competitive Algorithm and Sequential Quadratic Programming.•Studied the uncertainties of solar power and wind energy.•Solved different OPF problems including wind and solar generators.•A comparative study proved the effectiveness of the HMICA-SQP in providing better solutions.•A statistical performance evaluation proved the validity and robustness of the proposed method. The objective of this paper was to develop and solve different constrained optimal power flow (OPF) problems for hybrid power systems containing renewable energy sources like wind energy and solar power. OPF seeks to optimize the transmission of electric power by finding a steady state operating point that minimizes gas emission and cost of generated electric power without disturbing network power flow, operating limits and system constraints. The OPF problem was solved using a hybrid modified imperialist competitive algorithm and sequential quadratic programming, (HMICA-SQP). Efficacy of the modified imperialist competitive algorithm (MICA) is further enhanced by the process of hybridization with the sequential quadratic programming (SQP) for rapid local refinement and improved precision of the solution. The potential and effectiveness of the proposed metaheuristic were presented and assessed using three benchmark test systems IEEE 30, IEEE 57 and IEEE 118-bus power systems that incorporates several solar and wind energy sources. Comparison of simulation results with recently published optimization approaches solutions showed that the suggested paradigm is more efficient, robust and provides the lowest cost of generated electric power while keeping low emissions.
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ISSN:0378-7796
1873-2046
DOI:10.1016/j.epsr.2019.105989