Optimal reactive power dispatch for real power loss minimization and voltage stability enhancement using Artificial Bee Colony Algorithm

Ettappan, M.; Vimala, V.; Ramesh, S.; Kesavan, V. Thiruppathy

doi:10.1016/j.micpro.2020.103085

Cited by 93 publications

(47 citation statements)

References 15 publications

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“…Review of various optimization approaches developed for the solution and analysis of ORPD with the main goal of enhancing efficiency, performance and security of power system is presented in [3]. The author in [4] solves the ORPD problem with voltage stability enhancement, and power loss, voltage deviation minimizations using the evolutionary based Artificial Bee Colony (ABC) algorithm. The author in [5] solves the ORPD problem using meta-heuristic based Crow Search Algorithm (CSA) and finds the optimal control variables settings.…”

Section: A Literature Reviewmentioning

confidence: 99%

Solving Reactive Power Scheduling Problem using Multi-objective Crow Search Algorithm

Salkuti¹

2021

IJACSA

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This paper presents the solution of multi-objective based optimal reactive power dispatch (MO-ORPD) problem by optimizing the system power losses and voltage stability enhancement index (VSEI)/L-index objectives. ORPD problem is considered as an important issue from system security and operational point of view for optimal steady-state operation of power system. Here, single-objective based ORPD problem is solved using Crow Search Algorithm (CSA) and multi-objective based ORPD problem is solved using multi-objective CSA (MO-CSA). The CSA is considered as an efficient and robust algorithm which determines the global optimal solution for solving the non-linear and discontinuous objective functions. Two standard test systems, i.e., IEEE 30 and 57 bus systems are considered to show the effectiveness, suitability and robustness of CSA and MO-CSA for solving the ORPD problem.

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Section: A Literature Reviewmentioning

confidence: 99%

Solving Reactive Power Scheduling Problem using Multi-objective Crow Search Algorithm

Salkuti¹

2021

IJACSA

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“…In 2014, Mojtaba et al [1] established an effectual and consistent approach that depends upon ABC approach for resolving the ORPD issues. Accordingly, ABC approach is exploited for attaining "generator voltage magnitude, tap position of tap changing transformer and reactive power output of the compensation devices".…”

Section: Related Workmentioning

confidence: 99%

“…The most important task of such ORPD issue is to discover optimal settings of the entire controlling factors such as "reactive power output of generators, on-load tap changer of transformers, and shunt capacitor power outputs" [3]. In an electrical system, the ORPD is said to be a major factor for reducing losses and cost, for improving the stability of voltage and so on [1] [2].…”

Section: Introductionmentioning

confidence: 99%

Optimal Reactive Power Dispatch for Voltage Stability Improvement using Enhanced Whale Optimization Algorithm

Devi¹

2020

JCMPS

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In recent days, the ORPD topic has attained significant consideration, since it enhances the economy and security of a power system. It includes discrete and continuous controlling parameters and thus it is considered as a complicated nonlinear issue. Thereby, this paper focuses on foremost objectives such as, diminution of loss and variations in voltage, which assists in resolving the ORPD problem under unbalanced states. For attaining these objectives, "Whale Optimization Algorithm based Parameter Optimization (WOAPO) approach" is exploited. This algorithm makes an impact on the controlling constraints that are adjusted to accomplish the optimal outcome. Finally, the superiority of the presented work is proved other other existing schemes. On observing the outcomes, the values attained under best case scenario using WOAPO scheme is 0.57%, 0.5% and 0.92% better than GA, FF and ABC. In addition, the worst case scenario of WOAPO approach is 1.16% superior to PSO model.

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“…To eliminate the RPD problems, various optimization algorithms have been implemented over a period of time to achieve the optimal results. Some of the known stochastic methods implemented for solution of RPD problem includes the linear programming (LP) [ 7 ], interior point method (IPM) [ 8 ], quadratic programming (QP) [ 9 ], genetic algorithm (GA) [ 10 ], particle swarm optimization (PSO) [ 11 , 12 ], multi-objective optimization particle swarm optimization (MOPSO) algorithm [ 13 ], fractional Order PSO (FO-PSO) [ 6 ], harmony search algorithm (HSA) [ 14 ], gaussian bare-bones water cycle algorithm (NGBWCA) [ 15 ], tabu search (TS) [ 16 ], comprehensive learning particle swarm optimization [ 17 ], teaching learning based optimization (TLBO) [ 18 ], adaptive GA (AGA) [ 19 ], seeker optimization algorithm (SOA) [ 20 ], jaya algorithm [ 21 ], differential evolution (DE) [ 2 , 3 , 5 , 22 , 23 , 24 , 25 ], Artificial Bee Colony Algorithm [ 26 ], Hybrid Artificial Physics PSO [ 27 ], improved antlion optimization algorithm [ 28 ], Chaotic Bat Algorithm [ 29 ], classification-based Multi-objective evolutionary algorithm [ 30 ], evolution strategies (ES) [ 31 ], evolutionary programming (EP) [ 32 ], firefly algorithm (FA) [ 33 ], gravitation search optimization algorithm (GSA) [ 34 , 35 ], bacteria foraging optimization (BFO) [ 36 ], bio-geography-based optimization algorithm (BBO) [ 37 ] and grey wolf based optimizer algorithm (GWO) [ 38 ]. In 2017, another advanced optimizer has also been applied to the problems RPD known as gradient-based WCA (GWCA) [ 39 , 40 ] and results demonstrate the relevance and pr...…”

Section: Introductionmentioning

confidence: 99%

A New Fractional Particle Swarm Optimization with Entropy Diversity Based Velocity for Reactive Power Planning

Waleed

Yasir

Raja

et al. 2020

Entropy

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Optimal Reactive Power Dispatch (ORPD) is the vital concern of network operators in the planning and management of electrical systems to reduce the real and reactive losses of the transmission and distribution system in order to augment the overall efficiency of the electrical network. The principle objective of the ORPD problem is to explore the best setting of decision variables such as rating of the shunt capacitors, output voltage of the generators and tap setting of the transformers in order to diminish the line loss, and improve the voltage profile index (VPI) and operating cost minimization of standard electrical systems while keeping the variables within the allowable limits. This research study demonstrates a compelling transformative approach for resolving ORPD problems faced by the operators through exploiting the strength of the meta-heuristic optimization model based on a new fractional swarming strategy, namely fractional order (FO)–particle swarm optimization (PSO), with consideration of the entropy metric in the velocity update mechanism. To perceive ORPD for standard 30 and 57-bus networks, the complex nonlinear objective functions, including minimization of the system, VPI improvement and operating cost minimization, are constructed with emphasis on efficacy enhancement of the overall electrical system. Assessment of the results show that the proposed FO-PSO with entropy metric performs better than the other state of the art algorithms by means of improvement in VPI, operating cost and line loss minimization. The statistical outcomes in terms of quantile–quantile illustrations, probability plots, cumulative distribution function, box plots, histograms and minimum fitness evaluation in a set of autonomous trials validate the capability of the proposed optimization scheme and exhibit sufficiency and also vigor in resolving ORPD problems.

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Optimal reactive power dispatch for real power loss minimization and voltage stability enhancement using Artificial Bee Colony Algorithm

Cited by 93 publications

References 15 publications

Solving Reactive Power Scheduling Problem using Multi-objective Crow Search Algorithm

Solving Reactive Power Scheduling Problem using Multi-objective Crow Search Algorithm

Optimal Reactive Power Dispatch for Voltage Stability Improvement using Enhanced Whale Optimization Algorithm

A New Fractional Particle Swarm Optimization with Entropy Diversity Based Velocity for Reactive Power Planning

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