A Novel Algorithm to Improve the Power Quality for the Smart Grid and Integration with the Optimization Framework

Kumar, Naveen; Singh, Gopal K.

doi:10.14445/22315381/ijett-v69i9p233

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…Quality. Te quality module ensures the quality power for equipment and user devices [26]. Vr indicates the energy received from the integrated sources, and VR represents the energy received by devices/appliances.…”

Section: Powermentioning

confidence: 99%

An Optimized Framework of the Integrated Renewable Energy and Power Quality Model for the Smart Grid

Kumar

Singh

Kebede

2023

International Transactions on Electrical Energy Systems

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The smart grid’s structure is distinctive because it incorporates numerous cutting-edge communication and sensor technologies. It is challenging to manage smart grids using conventional power grids’ unified optimum delivery strategy effectively. This work offers a smart grid power production and maintenance collaborative optimization framework with renewable energy based on power generation and maintenance analysis. The operating costs of conventional units, the price of generating solar or wind power, and the cost of maintaining units are the problems of objective functions; the constraints taken into account are primarily system constraints. The genetic algorithm (GA) is used in this research to examine the optimization solution strategy. Depending on the properties of the system, various loads, power sources, and constraints are considered. The difficulty of adjusting load scheduling is transformed into a control problem by developing an efficient objective function. When uncertain system components are considered, the real-time control system can dynamically alter load scheduling to meet the needs of the actual system. In this study, the real-time algorithm put forward in this research is based on a strategy that satisfies the load optimization requirement and achieves dynamic compensation for unpredictable changes in renewable energy power generation. Moreover, the simulation compares the proposed algorithm capabilities with the existing algorithms/study, demonstrating the effectiveness of the suggested approach.

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Section: Powermentioning

confidence: 99%

An Optimized Framework of the Integrated Renewable Energy and Power Quality Model for the Smart Grid

Kumar

Singh

Kebede

2023

International Transactions on Electrical Energy Systems

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“…It can find near optimum solutions regardless of primary parameters, its affinity is fast and requires few control parameters. In addition, its coding is simple and it can handle integer and discrete optimization [18].…”

Section: Differential Evolution (De) Algorithmmentioning

confidence: 99%

Impact of Distributed Generation on a Distribution Network Voltage Sags in Baghdad City

Mohammed¹,

Shahl²

2021

ETJ

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Voltage sags are considered as one of the most detrimental power quality (PQ) disturbance due to their costly influence on sensitive loads. This paper investigates the voltage sag mitigation in distribution network following the occurrence of a fault. Two software are used in this work; the 1st is MATLAB R2017a for implementation of the Differential Evaluation (DE) algorithm to find the optimal location and size DG and while the 2nd software is CYME 7.1 for the distribution system modelling and analysis. The effectiveness of the proposed method is tested by implementing it on IEEE 33-bus system, and then it is applied to Al-Masbh distribution network in Baghdad city as a case study. The paper aims to enhance voltage profile, power loss reduction, and relieve distribution lines overloading, by optimal placement of distributed generation (DG). The results indicate the efficiency of the proposed method comparing with Real Coded Genetic Algorithm (RCGA).

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Piezo-beam Structure in a Pipe with Turbulent Flow as Energy Harvester: Mathematical Modeling and Simulation

Yadav¹,

Kumar²,

Kaushik

et al. 2022

J. Inst. Eng. India Ser. D

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A Novel Algorithm to Improve the Power Quality for the Smart Grid and Integration with the Optimization Framework

Cited by 5 publications

References 13 publications

An Optimized Framework of the Integrated Renewable Energy and Power Quality Model for the Smart Grid

An Optimized Framework of the Integrated Renewable Energy and Power Quality Model for the Smart Grid

Impact of Distributed Generation on a Distribution Network Voltage Sags in Baghdad City

Piezo-beam Structure in a Pipe with Turbulent Flow as Energy Harvester: Mathematical Modeling and Simulation

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