Optimal reactive power resources sizing for power system operations enhancement based on improved grey wolf optimiser

Taha, Ibrahim B. M.; Elattar, Ehab E.

doi:10.1049/iet-gtd.2018.0053

Cited by 39 publications

(45 citation statements)

References 38 publications

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“…The number of iteration, population size ,testing ranges and other parameters of the optimization methods are given in Table 3. The IEEE 30-bus system consists of six thermal power generators, as presented in Figure 1.The data about transmission lines, tap changing transformers, AVR compensators, limitations on generators and load voltages, active and reactive power demand are given in [46][47][48]. The general specifications of this system are described in Table 4.…”

Section: Resultsmentioning

confidence: 99%

Optimal Operation of Conventional Power Generation with High Penetration of Renewable Energy using Equilibrium Optimizer Technique

Nusair¹,

Alhmoud²

2020

Preprint

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Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of simulation and statistical results of EO with other optimization techniques showed that EO is more effective and superior.

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Section: Resultsmentioning

confidence: 99%

Optimal Operation of Conventional Power Generation with High Penetration of Renewable Energy using Equilibrium Optimizer Technique

Nusair¹,

Alhmoud²

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…The number of iteration, population size ,testing ranges and other parameters of the optimization methods are given in Table 3. Figure 1.The data about transmission lines, tap changing transformers, AVR compensators, limitations on generators and load voltages, active and reactive power demand are given in [46][47][48]. The general specifications of this system are described in Table 4.…”

Section: Resultsmentioning

confidence: 99%

“…(b) Create the two random vector (λ and r). (c) Construct F, GCP, G 0 and G according to the equation (36), equation (46), equation (45) and equation (44), respectively [35].…”

Section: Implementation Of Eo To Solve the Opf Problemmentioning

confidence: 99%

Optimal Operation of Conventional Power Generation with High Penetration of Renewable Energy using Equilibrium Optimizer Technique

Nusair¹,

Alhmoud²

2020

Preprint

View full text Add to dashboard Cite

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus 13 voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ 14 constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources 15 on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar 16 PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed 17 using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of 18 simulation and statistical results of EO with other optimization techniques showed that EO is more effective 19 and superior.

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“…However, these techniques have some drawbacks in resolving the complex optimization problem of ORPD such as; trapping in local minima, untimely convergence and algorithmic intricacy. To resolved these cited issues and overwhelmed the weakness these approaches, the scholars/researchers have implemented meta-heuristic and evolutionary techniques such as; evolutionary programming [9], differential evolution algorithm [10], genetic algorithm [11], moth-flame algorithm [12], whale optimization algorithm [13], binary bat algorithm [14], seeker optimization algorithm [15], firefly algorithm [16], chaotic krill herd algorithm [17], jaya algorithm [18], backtracking search algorithm [19], gravitational search algorithm [20], particle swarm optimization [21], invasive weed optimization [22], imperialist competitive algorithm [23], cuckoo search algorithm [24], improved GWO optimizer [25] and other hybrid solution mechanisms by relating these concepts are studied in [26][27][28][29][30][31][32][33]. While, some hybrid techniques are used to solve the optimal reactive power dispatch problems such as; PSOGSA algorithm [34], HGAPSO [35], SOA-FS [36].…”

Section: Introductionmentioning

confidence: 99%

A Novel Nature Inspired Meta-Heuristic Optimization Approach of GWO Optimizer for Optimal Reactive Power Dispatch Problems

2020

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In this paper, a novel nature inspired meta heuristic optimization approach of Grey Wolf Optimization (GWO) algorithm is employed to solved the optimal reactive power dispatch (ORPD) problems. Essentially, it is the sub and non-linear optimization problem of optimal power flow (OPF) in which the control parameters of the power networks are optimized. The Grey wolf optimizer (GWO) which is inspired from grey wolves' leadership and hunting behaviors to solve the ORPD problems. For which, the optimizer is tested on two test cases of IEEE30 standards specially, for 13 and 19 variables in order to get three fitness objectives for instance; transmission line losses (Plosses, MW), voltage deviation (VD), voltage stability index (VSI) and cost of energy in ($). During computing all fitness objectives, the minimum fitness values are possibly achieved by the finest settings of control variables. The simulation results are compared with other artificial intelligence methods in previous literature to ensure the superior performance of the GWO for ORPD problem. The consistency of GWO will further be validated through detailed statistical analysis including histogram illustrations, boxplots, empirical CDF plot, probability plot and plot of minimum fitness during each independent trial.

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Optimal reactive power resources sizing for power system operations enhancement based on improved grey wolf optimiser

Cited by 39 publications

References 38 publications

Optimal Operation of Conventional Power Generation with High Penetration of Renewable Energy using Equilibrium Optimizer Technique

Optimal Operation of Conventional Power Generation with High Penetration of Renewable Energy using Equilibrium Optimizer Technique

Optimal Operation of Conventional Power Generation with High Penetration of Renewable Energy using Equilibrium Optimizer Technique

A Novel Nature Inspired Meta-Heuristic Optimization Approach of GWO Optimizer for Optimal Reactive Power Dispatch Problems

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