concept

smart grid

Also known as: SG

Facts (69)

Sources

A comprehensive overview on demand side energy management ... link.springer.com Springer Mar 13, 2023 52 facts

referenceJavaid N, Javaid S, Abdul W, Ahmed I, Almogren A, Alamri A, and Niaz I published 'A hybrid genetic wind driven heuristic optimization algorithm for demand side management in smart grid' in 2017 in the journal Energies, volume 10, issue 3, page 319.

referenceRehman et al. (2021) published 'An optimal power usage scheduling in smart grid integrated with renewable energy sources for energy management' in IEEE Access, volume 9, pages 84619–84638.

referenceJavaid N, Ahmed F, Ullah I, Abid S, Abdul W, Alamri A, and Almogren AS published 'Towards cost and comfort based hybrid optimization for residential load scheduling in a smart grid' in 2017 in the journal Energies, volume 10, issue 10, page 1546.

referenceFang X, Misra S, Xue G, and Yang D (2011) provided a survey on the smart grid, characterizing it as a new and improved power grid.

referenceJavaid N, Mohsin SM, Iqbal A, Yasmeen A, and Ali I presented 'A hybrid bat-crow search algorithm based home energy management in smart grid' at the 2018 Conference on Complex, Intelligent, and Software Intensive Systems.

referenceShuja SM, Javaid N, Khan S, Akmal H, Hanif M, Fazalullah Q, and Khan ZA published 'Efficient scheduling of smart home appliances for energy management by cost and PAR optimization algorithm in smart grid' in 2019.

referenceIn the context of energy management systems, the abbreviation SG stands for Smart grid.

referenceAwais M, Javaid N, Shaheen N, Iqbal Z, Rehman G, Muhammad K, and Ahmad I published 'An efficient genetic algorithm based demand side management scheme for smart grid' in the proceedings of the 2015 18th International Conference on Network-Based Information Systems.

perspectiveFairness between users, standardization, and Smart Grid (SG) interoperability must be guaranteed when developing a Demand Side Management (DSM) program.

referenceDong Q, Yu L, Song W-Z, Tong L, and Tang S (2012) presented 'Distributed demand and response algorithm for optimizing social-welfare in smart grid' at the 2012 IEEE 26th International Parallel and Distributed Processing Symposium.

claimSmart grid hardware and software components enable utilities to immediately identify and address issues between customers and producing plants, thereby protecting the consistency and quality of the power supply.

referenceKumar A, Rizwan M, and Nangia U (2022) developed a hybrid optimization technique for energy management within a smart grid environment, published in the International Journal of Hydrogen Energy.

referenceKannayeram G, Prakash N, and Muniraj R (2020) developed an intelligent hybrid controller designed for power flow management in systems integrating photovoltaic, battery, fuel cell, and supercapacitor technologies within smart grid applications.

referenceLu X, Zhou K, Zhang X, and Yang S conducted a systematic review of supply and demand side optimal load scheduling within smart grid environments, published in the Journal of Cleaner Production in 2018.

referenceGelazanskas L and Gamage KA (2014) provided a review of demand-side management in the smart grid and proposed future directions for the field.

referenceLiu Y, Yuen C, Yu R, Zhang Y, and Xie S published 'Queuing-based energy consumption management for heterogeneous residential demands in smart grid' in IEEE Transactions on Smart Grid in 2015.

referenceRoy C and Das DK published a study in 2021 titled 'A hybrid genetic algorithm (GA)–particle swarm optimization (PSO) algorithm for demand side management in smart grid considering wind power for cost optimization' in the journal Sādhanā.

referenceBharathi C, Rekha D, and Vijayakumar V published 'Genetic algorithm based demand side management for smart grid' in Wireless Personal Communications, volume 93, issue 2, pages 481–502, in 2017.

referenceGuo Y, Pan M, and Fang Y (2012) developed an optimal power management strategy for residential customers within a smart grid framework.

referenceGK JS (2020) proposed a MANFIS-based smart home energy management system designed to support smart grid operations.

referenceSaad W, Han Z, Poor HV, and Basar T published an overview in 2012 titled 'Game-theoretic methods for the smart grid: an overview of microgrid systems, demand-side management, and smart grid communications' in IEEE Signal Processing Magazine.

referenceRehman AU, Wadud Z, Elavarasan RM, Hafeez G, Khan I, Shafiq Z, and Alhelou HH published a study in 2021 titled 'An optimal power usage scheduling in smart grid integrated with renewable energy sources for energy management' in IEEE Access.

referenceThe research article investigates implementation issues for integrating demand-side management (DSM) into the Smart Grid (SG), including proposed solutions and optimization methodologies not covered in previous reviews.

referenceKannayeram G, Prakash N, and Muniraj R (2020) developed an intelligent hybrid controller for power flow management in systems integrating photovoltaic, battery, fuel cell, and supercapacitor technologies for smart grid applications, as published in the International Journal of Hydrogen Energy.

referenceKumar A, Rizwan M, and Nangia U (2022) developed a hybrid optimization technique to improve energy management within smart grid environments.

referenceLu X, Zhou K, Zhang X, and Yang S conducted a systematic review of supply and demand side optimal load scheduling within smart grid environments in 2018.

claimJavaid et al. (2017b) developed a hybrid genetic wind-driven (HGWD) technique to build a demand-side management (DSM) controller for residential areas in a smart grid.

referenceAwais et al. presented a paper titled 'An efficient genetic algorithm based demand side management scheme for smart grid' at the 2015 18th International Conference on Network-Based Information Systems.

referenceLogenthiran T, Srinivasan D, and Shun TZ published 'Demand side management in smart grid using heuristic optimization' in 2012.

referenceAmbreen K, Khalid R, Maroof R, Khan HN, Asif S, and Iftikhar H presented the paper 'Implementing critical peak pricing in home energy management using biography based optimization and genetic algorithm in smart grid' at the International Conference on Broadband and Wireless Computing, Communication and Applications in 2017.

referenceA smart grid is a system that combines self-monitoring, self-healing, pervasive control, adaptive, and islanding mode mechanisms to facilitate energy transit from production to consumption, as suggested by Fang et al. (2011) and Xu et al. (2016b).

claimDemand-side management (DSM) is a development in smart grid technology that enables communication between energy suppliers and consumers.

referenceRoy and Das (2021) published 'A hybrid genetic algorithm (GA)–particle swarm optimization (PSO) algorithm for demand side management in smart grid considering wind power for cost optimization' in Sādhanā, volume 46, issue 2, pages 1–12.

referenceKhan AR, Mahmood A, Safdar A, Khan ZA, and Khan NA (2016) reviewed the integration of load forecasting, dynamic pricing, and demand-side management (DSM) within smart grid environments.

referenceFang et al. (2011) provided a survey on the smart grid, characterizing it as a new and improved version of the traditional power grid.

claimDemand response (DR), distributed energy resources (DER), and energy efficiency (EE) are three categories of demand-side management (DSM) activities that are increasing in popularity due to smart grid technological advancements.

referenceNawaz A, Hafeez G, Khan I, Jan KU, Li H, Khan SA, and Wadud Z published the paper 'An intelligent integrated approach for efficient demand side management with forecaster and advanced metering infrastructure frameworks in smart grid' in IEEE Access, volume 8, pages 132551–132581, in 2020.

referenceSaad et al. (2012) published 'Game-theoretic methods for the smart grid: an overview of microgrid systems, demand-side management, and smart grid communications' in IEEE Signal Processing Magazine, volume 29, issue 5, pages 86–105.

referenceHussain HM, Javaid N, Iqbal S, Hasan QU, Aurangzeb K, and Alhussein M published 'An efficient demand side management system with a new optimized home energy management controller in smart grid' in 2018 in the journal Energies, volume 11, issue 1, page 190.

referenceFaisal HM, Javaid N, Qasim U, Habib S, Iqbal Z, and Mubarak H (2019) presented a method for efficient scheduling of user appliances using multi-objective optimization in the smart grid.

referenceGuo Y, Pan M, and Fang Y (2012) published 'Optimal power management of residential customers in the smart grid' in IEEE Transactions on Parallel and Distributed Systems, volume 23, issue 9, pages 1593–1606, which addresses methods for optimizing power management for residential customers within smart grid environments.

referenceZhu Z, Tang J, Lambotharan S, Chin WH, and Fan Z published 'An integer linear programming based optimization for home demand-side management in smart grid' at the 2012 IEEE PES Innovative Smart Grid Technologies (ISGT) conference in 2012.

referenceGK JS (2020) published 'MANFIS based SMART home energy management system to support SMART grid' in Peer-to-Peer Networking and Applications, volume 13, issue 6, pages 2177–2188, which details a MANFIS-based smart home energy management system designed to support smart grids.

claimJavaid et al. (2017b) developed a hybrid genetic wind-driven (HGWD) technique to build a demand-side management (DSM) controller for a residential area in a smart grid.

referenceA smart grid is defined as a system that combines self-monitoring, self-healing, pervasive control, adaptive, and islanding mode mechanisms to facilitate energy transit from production to consumption, as suggested by Fang et al. (2011) and Xu et al. (2016b).

referenceErol-Kantarci and Mouftah (2011) explored the use of wireless sensor networks to achieve cost-efficient residential energy management within smart grid systems.

referenceErol-Kantarci M and Mouftah HT (2011) investigated the use of wireless sensor networks for cost-efficient residential energy management within the smart grid.

claimSmart grid hardware and software components enable utilities to immediately identify and address issues between customers and producing plants that threaten power supply consistency and quality.

claimIn the context of energy management systems, SG is the abbreviation for Smart grid.

referenceFaisal et al. (2019) proposed a multi-objective optimization method for scheduling user appliances within a smart grid environment.

referencePhuangpornpitak N and Tia S (2013) analyzed the opportunities and challenges of integrating renewable energy into smart grid systems, published in Energy Procedia.

referenceZhu Z, Tang J, Lambotharan S, Chin WH, and Fan Z presented 'An integer linear programming based optimization for home demand-side management in smart grid' at the 2012 IEEE PES Innovative Smart Grid Technologies (ISGT) conference in 2012.

Global perspectives on energy technology assessment and ... link.springer.com Springer Oct 30, 2025 7 facts

claimHybrid methods such as CNN-GRU are well suited for applications in the wind and solar energy sectors because they handle fluctuating data patterns and improve prediction accuracy in renewable energy and smart grid applications.

claimA smart grid is defined as a network of electrical power plants that utilizes digital technology to increase reliability, sustainability, and efficiency.

claimSmart grids enhance the integration of variable renewable energy sources, such as wind and solar, and variable loads, such as electric vehicles.

claimSmart grids improve power system efficiency and support features including automatic healing and power re-routing.

claimSmart grids rely on Advanced Metering Infrastructure (AMI) and information and communication technologies.

claimGermany is developing smart grid technologies to manage increasing amounts of renewable energy, thereby improving the overall efficiency and reliability of the energy system.

referenceRathor SK, Saxena D. (2020) published 'Energy management system for smart grid: an overview and key issues' in the International Journal of Energy Research, detailing the management systems required for smart grids.

Comprehensive framework for smart residential demand side ... nature.com Nature Mar 22, 2025 5 facts

referenceThe paper 'Recent challenges and methodologies in smart grid demand side management: State-of-the-art literature review' by Nasir, T. et al. was published in Mathematical Problems in Engineering, 2021, pages 1–16.

referenceVikramGoud et al. (2022) published a survey on strategies, challenges, modeling, and optimization techniques for demand-side management of electric vehicles in smart grids in Energy Reports.

referenceMohanty et al. (2019) surveyed algorithms for distributed charging control of electric vehicles within smart grid systems in the IEEE Transactions on Intelligent Transportation Systems.

claimIn the current smart and microgrid scenario, it is necessary to adopt strategies for energy consumption patterns in Residential Demand Side Management (RDSM) that consider multi-consumption level pricing schemes, incentives for load shifting, consumer priorities, and uncertain load demand variations.

claimOn-site photovoltaic (PV) systems are widely preferred for residential use in smart-grid and microgrid environments due to their ease of access and implementation.

Demand side management using optimization strategies for efficient ... journals.plos.org PLOS ONE Mar 21, 2024 2 facts

referenceWen L., Zhou K., Feng W., and Yang S. authored 'Demand Side Management in Smart Grid: A Dynamic-Price-Based Demand Response Model' published in IEEE Transactions on Engineering Management in 2022.

referenceMacedo M. N. Q., Galo J. J. M., de Almeida L. A. L., and Lima A. C. de C. investigated the use of artificial neural networks for demand-side management in a smart grid environment in a 2015 review in Renewable and Sustainable Energy Reviews.

Sustainable Energy Transition for Renewable and Low Carbon Grid ... frontiersin.org Frontiers Mar 23, 2022 1 fact

claimThe transition to a more resilient smart grid is necessary to handle the variable loads associated with the electrification of transport.

A critical review on techno-economic analysis of hybrid renewable ... link.springer.com Springer Dec 6, 2023 1 fact

referenceBabonneau, Haurie, Tarel, and Theni (2012) assessed the future of flow and smart grid technologies in regional power systems in the Swiss Journal of Economics and Statistics.

The technical, geographical, and economic feasibility for solar ... ideas.repec.org RePEc 1 fact

referenceEdward Barbour, David Parra, Zeyad Awwad, and Marta C. González authored the 2018 paper 'Community energy storage: A smart choice for the smart grid?,' published in Applied Energy (Elsevier, vol. 212(C), pages 489-497).