A decision support system using combined-classifier for high-speed data stream in smart grid

Yang, Hang; Li, Peng; He, Zhian; Guo, Xijuan; Fong, Simon; Chen, Huajun

doi:10.1080/17517575.2015.1086495

Cited by 8 publications

(3 citation statements)

References 8 publications

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“…In [287], the authors proposed the scheduling algorithm for energy consumption management systems. To construct a smart city, researchers have used DTs to solve challenges such as companies, air pollution, urban transportation, and food [288].…”

Section: Enhanced Approaches To the Energy Management Systemmentioning

confidence: 99%

Energy Management Systems Using Smart Grids: An Exhaustive Parametric Comprehensive Analysis of Existing Trends, Significance, Opportunities, and Challenges

Khan

Shahid

Alam

et al. 2022

International Transactions on Electrical Energy Systems

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The integration of widely fluctuating distributed generation (such as photovoltaic panels, wind power, electric vehicles, and energy storage systems) puts the stability of power technologies and distribution structures in jeopardy. However, the fundamental reason is that the electrical supply and demand ratio may not be balanced. An excess or scarcity of electricity in the production or consumption of energy can disrupt the system and cause serious difficulties such as voltage drops/rises and, in extreme cases, power outages. Energy management systems can efficiently increase the balance between supply and demand while reducing peak load during unscheduled periods. The energy management system can handle distributing or exchanging energy among the many energy resources available and economically supplying loads in a stable, safe, and effective manner under all power grid operating situations. This article examines the energy control system’s structure, goals, benefits, and challenges through an in-depth investigation of the various stakeholders and participants involved in this system. This review provides a detailed essential analysis of the operation of several programs used inside the power management system, such as demand response, demand management, and energy quality management. It also includes a summary of the smart grid’s functionalities, features, and related techniques and has discovered research gaps, challenges, and issues. Furthermore, in this article, the authors review the literature on the enabling technologies of smart grid and investigate the energy management system, which is among one of the major emerging technologies and quantifications of the various uncertainty techniques. In this paper, the authors also discussed the comprehensive review of researchers’ efforts and contributions to the smart energy management system in the smart grid. It also compares and evaluates the key optimization approaches utilized to achieve the remarkable aims of energy management structures while also fulfilling a variety of constraints. This comprehensive review will be very beneficial for the new researchers, and it would be a great contribution to the research community.

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Section: Enhanced Approaches To the Energy Management Systemmentioning

confidence: 99%

Energy Management Systems Using Smart Grids: An Exhaustive Parametric Comprehensive Analysis of Existing Trends, Significance, Opportunities, and Challenges

Khan

Shahid

Alam

et al. 2022

International Transactions on Electrical Energy Systems

View full text Add to dashboard Cite

show abstract

“…They are among the most powerful inductive inference algorithms and are successfully used in many different energy systems. 76 Researchers have applied DTs to address the issues related to businesses, air pollution, urban transport, and food to develop a smart city. 77 Another ML method which has been applied to solve problems of energy forecasting is Ensemble methods.…”

Section: Solution Approaches For Emsmentioning

confidence: 99%

Energy management in the smart grid: State-of-the-art and future trends

Meliani

Barkany

Abbassi

et al. 2021

International Journal of Engineering Business Management

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Integration of distributed generations that fluctuate widely (such as Photovoltaic panels, Wind power, Electric Vehicles and Energy Storage Systems), poses a chance to the stability of power technology and distribution structures. However, the primary reason is that the electricity ratio between supply and demand may not be balanced. An extra or scarcity inside the production or intake of electricity can disrupt the system and cause critical problems which include a drop/rise in voltage and, under difficult conditions, power outages. The use of Energy Management Systems can effectively increase the balance between supply and demand and decrease peak load throughout unplanned durations. The energy management system is capable of not only sharing or exchanging energy between the different energy resources available, but also of economically supplying loads in a reliable, safe and effective manner under all conditions necessary for the operation of the power grid. This work outlines the structure, goals, benefits and defies of the energy control system via an in-intensity analysis of the distinctive stakeholders and participants engaged on this system. A detailed essential analysis of the functioning of distinct programs which includes Demand Response, Demand Management and Energy Quality Management implemented inside the electricity management gadget is presented in this review. It also summarizes quantifications of the various strategies of uncertainty. It includes as well a comparative and an important assessment of the primary optimization techniques which are used to obtain the extraordinary goals of energy management structures while at the same time meeting a wide range of requirements.

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“…Particularly in the field of decision support systems (DSS), the interest in efficiently converting data streams into operational intelligence is increasing. In this sense, some previous works have proposed the application of streaming methods to DSS as in [10,11].…”

Section: Introductionmentioning

confidence: 99%

Incremental Decision Rules Algorithm: A Probabilistic and Dynamic Approach to Decisional Data Stream Problems

et al. 2021

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Data science is currently one of the most promising fields used to support the decision-making process. Particularly, data streams can give these supportive systems an updated base of knowledge that allows experts to make decisions with updated models. Incremental Decision Rules Algorithm (IDRA) proposes a new incremental decision-rule method based on the classical ID3 approach to generating and updating a rule set. This algorithm is a novel approach designed to fit a Decision Support System (DSS) whose motivation is to give accurate responses in an affordable time for a decision situation. This work includes several experiments that compare IDRA with the classical static but optimized ID3 (CREA) and the adaptive method VFDR. A battery of scenarios with different error types and rates are proposed to compare these three algorithms. IDRA improves the accuracies of VFDR and CREA in most common cases for the simulated data streams used in this work. In particular, the proposed technique has proven to perform better in those scenarios with no error, low noise, or high-impact concept drifts.

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A decision support system using combined-classifier for high-speed data stream in smart grid

Cited by 8 publications

References 8 publications

Energy Management Systems Using Smart Grids: An Exhaustive Parametric Comprehensive Analysis of Existing Trends, Significance, Opportunities, and Challenges

Energy Management Systems Using Smart Grids: An Exhaustive Parametric Comprehensive Analysis of Existing Trends, Significance, Opportunities, and Challenges

Energy management in the smart grid: State-of-the-art and future trends

Incremental Decision Rules Algorithm: A Probabilistic and Dynamic Approach to Decisional Data Stream Problems

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