Modified Artificial Bee Colony Optimization Technique with Different Objective Function of Constraints Optimal Power Flow

Al-Kaabi, Murtadha; Al-Bahrani, Layth Tawfeeq

doi:10.22266/ijies2020.0831.33

Cited by 17 publications

(9 citation statements)

References 23 publications

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“…3" with the main characteristics specified in "Table 2." 6-10, 4-12,6-9, 28-27 Reactive power compensator on the buses 10,12,15,17,20,21,23,24,29 A code is written in MATLAB environment to simulate the proposed algorithm. The execution is carried out on a laptop with an Intel (R) Core (TM) i7-6700QM CPU running at 2.60 GHz (8 CPUs), 8.192 GB of RAM, and a 64-bit operating system.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

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Security Constrained Optimal Power Flow Based on an Artificial Intelligence Technique

Almansory,

Al-Anbarri

2023

J. eng. sustain. dev.

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In the past, artificial intelligence techniques were successfully adopted for obtaining optimal power flow in a power system. However, this optimality is limited to the economic aspects of the system's operating conditions. The other aspects of the operation, like security conditions, have been given limited attention. Hence, this paper presents an attempt to dispatch the power generation in electrical power systems optimally by taking into consideration both economic and secure operations, so that modern power systems can operate reliably and effectively. Security-constrained optimal power flow is addressed in this paper as a multi-objective optimization problem, consisting of four objective functions: minimizing power generation costs; minimizing voltage deviation; minimizing power losses; and alleviating the overloading on transmission lines. A detailed steady-state generator model is adopted in the present formulation. A metaheuristic optimization technique, namely, differential evolution, is used to obtain the security constraint optimal power dispatch. Additionally, the operating states of a power system have been addressed in this paper. The identification of the operating states is vital to the assessment of the security of the EPS. Improvements and appropriate security assessments have been made in some cases. The proposed algorithm is applied to a typical power system with different operating strategies. The obtained results are compared to those obtained from previous studies in the literature to demonstrate the suggested method's validity and effectiveness.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

“…SI quantifies the severity of OLTL, which describes the power system's post-contingency state as follows [24].…”

Section: Severity Index (Si)mentioning

confidence: 99%

Security Constrained Optimal Power Flow Based on an Artificial Intelligence Technique

Almansory,

Al-Anbarri

2023

J. eng. sustain. dev.

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“…The BCS of E and VD for the proposed techniques are the following: PFNDSs obtained by the proposed techniques MOGWO and MOHHO for this case are shown in Figure 12f. The BCS and OFs for Bi OFs on the IEEE 57 bus system obtained by MOGWO and MOHHO for Cases (11)(12)(13)(14)(15)(16) are illustrated in Tables 7 and 8. From Figure 12a-f, it can be observed that the PFNDSs obtained by MOGWO are better distributed than the PFNDSs obtained by MOHHO.…”

Section: Case #16: Minimization Of E and Vdmentioning

confidence: 99%

“…From Figure 12a-f, it can be observed that the PFNDSs obtained by MOGWO are better distributed than the PFNDSs obtained by MOHHO. Figure 13a-f shows the VD of the Bi OFs on the IEEE 57-bus system obtained by MOGWO and MOHHO for Cases (11)(12)(13)(14)(15)(16). This figure proves that the solutions obtained by MOGWO and MOHHO are effective in cases 14-16 (when VD is OFs) and infeasible in cases 11-13 (when VD is not OFs), as shown in Figure 8a-e.…”

Section: Case #16: Minimization Of E and Vdmentioning

confidence: 99%

“…Lately, many research papers have been published on applications of meta-heuristic optimization methods such as the salp swarm algorithm (SSA) [10], the black widow optimization (BWO) [11], the manta ray foraging optimization (MRFO) [12], Henry gas solubility optimization (HGSO) [13], etc. In power systems, metaheuristic optimization algorithms were proposed to solve OPF problems such as Modified Artificial Bee Colony (MABC) [14], Spatio-temporal distribution (STD) [15], differential evolution (DE) [16], enhanced Particle Swarm optimization (EPSO) and Ant Lion optimization (ALO) [17], improved differential evolution (IDE) [18,19], Harris Hawks Optimization (HHO) [20,21], and Grey Wolf Optimizer (GWO) [22]. The previous methods dealt with the problems of single-objective optimal power flow (SOOPF).…”

Section: Introductionmentioning

confidence: 99%

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Multi Criteria Frameworks Using New Meta-Heuristic Optimization Techniques for Solving Multi-Objective Optimal Power Flow Problems

Al-Kaabi,

Dumbrava,

Eremia

2024

Energies

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This article develops two metaheuristics optimization techniques, Grey Wolf Optimizer (GWO) and Harris Hawks Optimization (HHO), to handle multi-objective optimal power flow (MOOPF) issues. Multi Objective GWO (MOGWO) and Multi Objective HHO (MOHHO) are the names of the developed techniques. By combining these optimization techniques with Pareto techniques, the non-dominated solution set can be obtained. These developed approaches are characterized by simplicity and have few control parameters. Fuel cost, emissions, real power losses, and voltage deviation were the four objective functions considered. The theories used to determine the best compromise solution and organize the Pareto front options are the fuzzy membership equation and the crowding distance approach, respectively. To validate and evaluate the performance of the presented techniques, two standard IEEE bus systems—30-bus and 57-bus power systems—were proposed. Bi, Tri, and Quad objective functions with 21 case studies are the types of objective functions and the scenarios that were applied in this paper. As compared to the results of the most recent optimization techniques documented in the literature, the comparative analysis results for the proposed methodologies demonstrated the superiority and robustness of MOGWO and MOHHO.

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An Overview of the Smart Grid Attributes, Architecture and Components

Al-Kaabi¹,

Igeb

Ali

2023

Lecture Notes in Networks and Systems

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Modified Artificial Bee Colony Optimization Technique with Different Objective Function of Constraints Optimal Power Flow

Cited by 17 publications

References 23 publications

Security Constrained Optimal Power Flow Based on an Artificial Intelligence Technique

Security Constrained Optimal Power Flow Based on an Artificial Intelligence Technique

Multi Criteria Frameworks Using New Meta-Heuristic Optimization Techniques for Solving Multi-Objective Optimal Power Flow Problems

An Overview of the Smart Grid Attributes, Architecture and Components

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