Optimal Reactive Power Dispatch Incorporating Solar Power Using Jaya Algorithm

Das, Tanmay; Roy, Ranjit; Mandal, Kamal Krishna; Mondal, Shatanik; Mondal, Soumaymoy; Hait, Paresh; Das, Moloy Kumar

doi:10.1007/978-981-13-8687-9_4

Cited by 20 publications

(8 citation statements)

References 11 publications

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“…The forecast wind and solar photovoltaic are modeled using Weibull and lognormal probability distribution functions [4]. An optimal reactive power dispatch with solar photovoltaic power and its impact on minimizing real power losses is addressed using the Jaya algorithm to solve this issue [31]. A constrained multi-objective population external optimization method in [32] is presented to minimize the fuel cost and emission in the presence of renewable energy sources.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Equilibrium Optimizer Algorithm for Optimal Power Flow with High Penetration of Renewable Energy

Nusair

Alhmoud

2020

Energies

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In recent decades, the energy market around the world has been reshaped to accommodate 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 is 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 and provides the lowest optimization value in term of electric power generation, real power loss, emission index and voltage deviation.

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Section: Literature Reviewmentioning

confidence: 99%

Application of Equilibrium Optimizer Algorithm for Optimal Power Flow with High Penetration of Renewable Energy

Nusair

Alhmoud

2020

Energies

View full text Add to dashboard Cite

show abstract

“…The forecast wind and solar photovoltaic are modeled using Weibull and lognormal probability distribution functions [31]. An optimal reactive power dispatch with solar photovoltaic power and its impact on minimizing real power losses is addressed using the Jaya algorithm to solve this issue [32]. A constrained multi-objective population external optimization method in [33] is presented to minimize the fuel cost and emission in the presence of renewable energy sources.…”

Section: Literature Reviewmentioning

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 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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“…Abundant customary procedures [1][2][3][4][5][6] are betrothed nonetheless systematic hitches are set up with retrenchments. These eternities Evolutionary methods [7][8][9][10][11][12][13] are engaged. Choosing certain parameters to Modernize -Grounded Algorithm (CCM) is applied to solve the power loss lessening problem.…”

Section: Introductionmentioning

confidence: 99%

Real Power Loss Reduction by Choosing Certain Parameters to Modernize – Grounded Algorithm

Lenin

2022

Advances in Transdisciplinary Engineering

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In this paper choosing certain parameters to Modernize – Grounded Algorithm (CCM) is sculpted for untying loss descendant problem. The procedure of modernizing populace associates in the projected CCM observes to double values. The chief norm is that certain associates of the populace might be in a condition wherever if lone standards of certain parameters alter, they determined to be in an improved location as a substitute of altering all of the parameters. Consequently, in the projected CCM, the quantity of parameters nominated for the modernization procedure is fixed in iterations. The next standard is to stop the algorithm populace modernize procedure from depend on precise associates. Depend on procedure modernization to explicit associates of the populace influence the procedure to congregate in the direction of the local optimal solution and avert precise perusing of the examination region to achieve the universal optimal solution. Stoutness of the Choosing certain parameters to Modernize – Grounded Algorithm (CCM) corroborated in IEEE 30 bus test system. Diminution of loss has been accomplished.

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Optimal Reactive Power Dispatch Incorporating Solar Power Using Jaya Algorithm

Cited by 20 publications

References 11 publications

Application of Equilibrium Optimizer Algorithm for Optimal Power Flow with High Penetration of Renewable Energy

Application of Equilibrium Optimizer Algorithm for Optimal Power Flow with High Penetration of Renewable Energy

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

Real Power Loss Reduction by Choosing Certain Parameters to Modernize – Grounded Algorithm

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