Towards smarter grid: Policy and its impact assessment through a case study

Chakraborty, Ratul; Samanta, Anuva; Agrawal, K. M.; Dutta, Arindam

doi:10.1016/j.segan.2021.100436

Cited by 9 publications

(5 citation statements)

References 20 publications

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“…Recently, seeking to achieve the Sustainable Development Goal 7 (SDG 7), which aims to ensure the affordable, reliable, sustainable and modern energy for all systems [6], hence it is necessary to shift from the conventional electric power grids to smart and active grids, enabling self-healing and resilient operation, optimizing the usage of the assets, decrease power consumption and investment cost [7]. Also, this evolution has been made possible by the development of real-time secure information and communication technologies (ICT) such as wide-area measurement systems, smart meters, smart sensors, and intelligent electronic devices [8,9].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Another solution method reported in reference [37] uses polynomial transformation model probabilistic power flow analysis of the WT integrated power system; the research study introduces a new multivariate quadrature formulation for the statistical analysis of power flow. The reference [38] elaborates the probabilistic optimal power flow and highlights the key challenges FIGURE 7 Journal citation map on the investigated subject (Note: Only journals are included in this analysis. Also, the minimum number of documents per journal was set to 7 so that 31 out of 609 publication sources meet the threshold) of random and interval variables in power networks; to deal with the random and interval variables, a new clustering-based analytical method was proposed for the problem solution.…”

Section: Systematic Literature On Advanced Studies For P-opfmentioning

confidence: 99%

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Advanced studies for probabilistic optimal power flow in active distribution networks: A scientometric review

Ullah

Wang

et al. 2022

IET Generation Trans & Dist

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In the active distribution networks (ADNs), the emerging trend of high penetration of sustainable energy sources such as wind turbines, photovoltaics, and the forthcoming integration of energy storage devices and additional dynamic loads like plug-in-electric vehicles (PEVs) influences to change the nature of electric distribution networks. Consequently, it deteriorates power quality and reliability in terms of unacceptable voltage rise-drop, harmonic distortion, voltage unbalance, and excessive power loss. In this context of transition into the active distribution network, the probabilistic optimal power flow (P-OPF) in the ADN is considered an important tool that helps the distribution grid operators for defining the optimal settings of the system's control variables. However, the optimal solution of P-OPF becomes highly complex while considering the multiple variables, timevarying characteristics and operational uncertainties associated with sustainable resources, consumer behaviour and electricity market prices. This review aims at promoting the research and discussion of P-OPF studies in the context of ADNs characteristics and challenges. First, we perform a data-driven and visualized scientometric analysis of 1988 quality documents retrieved from the Scopus during the last ten years using VOSviewer software. Second, an in-depth investigation of the recent and emerging techniques for solving the P-OPF problem is presented. Third, a set of recommendations and highlights of future challenges for P-OPF in ADNs are offered. The review findings showed high interest among the scientific community in sustainable energy source integration, given the recent rise in publications and citations. Also, there is still a lack of innovative optimization techniques that can adequately handle the current issues associated with P-OPF and objectives with fair computational efficiency and accuracy. Finally, this paper offers a guide for P-OPF researchers to navigate the recent studies considering the sustainable sources, spot the new research frontiers, and identify the most impactful countries and publishers.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Systematic Literature On Advanced Studies For P-opfmentioning

confidence: 99%

Advanced studies for probabilistic optimal power flow in active distribution networks: A scientometric review

Ullah

Wang

et al. 2022

IET Generation Trans & Dist

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“…Enhancement of Quality of Life for all stakeholders [18,19] Economic: Creation of new jobs and improvement in the quality of people's lives. Social: Revolution in industrial and energy sectors leading to the modernization of equipment for efficient grid usage.…”

Section: Outlining Of Workmentioning

confidence: 99%

A Comprehensive Review on Sustainable Aspects of Big Data Analytics for the Smart Grid

Kumar¹,

Kasinathan²,

Elavarasan

et al. 2021

Sustainability

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The role of energy is cardinal for achieving the Sustainable Development Goals (SDGs) through the enhancement and modernization of energy generation and management practices. The smart grid enables efficient communication between utilities and the end- users, and enhances the user experience by monitoring and controlling the energy transmission. The smart grid deals with an enormous amount of energy data, and the absence of proper techniques for data collection, processing, monitoring and decision-making ultimately makes the system ineffective. Big data analytics, in association with the smart grid, enable better grid visualization and contribute toward the attainment of sustainability. The current research work deals with the achievement of sustainability in the smart grid and efficient data management using big data analytics, that has social, economic, technical and political impacts. This study provides clear insights into energy data generated in the grid and the possibilities of energy theft affecting the sustainable future. The paper provides insights about the importance of big data analytics, with their effects on the smart grids’ performance towards the achievement of SDGs. The work highlights efficient real-time energy data management involving artificial intelligence and machine learning for a better future, to short out the effects of the conventional smart grid without big data analytics. Finally, the work discusses the challenges and future directions to improve smart grid technologies with big data analytics in action.

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“…It also directly affects the operating efficiency of power grid enterprises [1]. Electric energy is lost in all links of the power grid transmission process [2]. Among them, line loss management has always been one of the key work contents of the power grid company.…”

Section: Introductionmentioning

confidence: 99%

Power quality and energy consumption prediction model of transmission line based on grey multiple linear regression

Wang,

Wang

2024

Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023)

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Power quality and energy consumption management is one of the key tasks of power grid companies. With the increasingly prominent power quality problems, it is necessary to study the additional losses caused by power quality problems on transmission lines. Therefore, the power quality and energy consumption prediction model of transmission lines based on grey multiple linear regression is constructed. The power quality and energy consumption prediction data of transmission lines are processed under the grey multiple linear regression, the characteristic attributes between samples are calculated, and the weight value of the characteristic attributes is obtained. The characteristic attributes of the calculation results are input into the grey multiple linear regression network, the power quality energy consumption prediction results of the transmission line are output, and the construction of the power quality energy consumption prediction model is completed. The experimental results show that the energy consumption prediction curve obtained by the model is consistent with the actual energy consumption curve, and the energy consumption in summer is generally higher than that in winter. Based on this result, we can effectively establish the demand response of the transmission line with a good prediction effect.

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Towards smarter grid: Policy and its impact assessment through a case study

Cited by 9 publications

References 20 publications

Advanced studies for probabilistic optimal power flow in active distribution networks: A scientometric review

Advanced studies for probabilistic optimal power flow in active distribution networks: A scientometric review

A Comprehensive Review on Sustainable Aspects of Big Data Analytics for the Smart Grid

Power quality and energy consumption prediction model of transmission line based on grey multiple linear regression

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