User-friendly demand side management for smart grid networks

Bae, Hyoungchel; Yoon, Jongha; Lee, Yunseong; Lee, Juho; Kim, Tae-Jin; Yu, Jeongseok; Cho, Sungrae

doi:10.1109/icoin.2014.6799728

Cited by 12 publications

(3 citation statements)

References 13 publications

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“…The proposed system, "fuzzy TOPSIS decision-making", gives an assessment of power consumption of multiple power users and directs for optimum energy distribution. HEMS is proposed in Bae et al (2014), which is based on binary particle swarm optimization and the major concern is to curtail partially interruptible loads within a smart home. The proposed scheduling mechanism takes care of voltage profile as well as user power demands.…”

Section: Role Of Optimization Techniques In Hemssmentioning

confidence: 99%

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Utilization of ICT and AI techniques in harnessing residential energy consumption for an energy-aware smart city: A review

al.¹

2021

Int. j. adv. appl. sci.

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Fusion of Information and Communication Technologies (ICT) in traditional grid infrastructure makes it possible to share certain messages and information within the system that leads to optimized use of energy. Furthermore, using Computational Intelligence (CI) in the said domain opens new horizons to preserve electricity as well as the price of consumed electricity effectively. Hence, Energy Management Systems (EMSs) play a vital role in energy economics, consumption efficiency, resourcefulness, grid stability, reliability, and scalability of power systems. The residential sector has its high impact on global energy consumption. Curtailing and shifting load of the residential sector can result in solving major global problems and challenges. Moreover, the residential sector is more flexible in reshaping power consumption patterns. Using Demand Side Management (DSM), end users can manipulate their power consumption patterns such that electricity bills, as well as Peak to Average Ratio (PAR), are reduced. Therefore, it can be stated that Home Energy Management Systems (HEMSs) is an important part of ground-breaking smart grid technology. This article gives an extensive review of DSM, HEMS methodologies, techniques, and formulation of optimization problems. Concluding the existing work in energy management solutions, challenges and issues, and future research directions are also presented.

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Section: Role Of Optimization Techniques In Hemssmentioning

confidence: 99%

“…The combination of these two pricing mechanisms automatically leads to lower PAR and power consumption. Bae et al (2014) presented a user-friendly DSM naming it UDSM by exploiting ICT advancements. The foundation of UDSM is timely information regarding price variations.…”

Section: Fig 7: Classification Of Optimization Techniquesmentioning

confidence: 99%

Utilization of ICT and AI techniques in harnessing residential energy consumption for an energy-aware smart city: A review

al.¹

2021

Int. j. adv. appl. sci.

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“…It is vital first to clarify that customers have two main interests with clear conflicts between them. First, each user wishes to minimize his payment [18]. Second, depending on the appliance, users also care about their comfort and getting the work done, e.g.…”

Section: Problem Formulationmentioning

confidence: 99%

Artificial intelligent-based optimization of automated home energy management systems

Elkazaz

Hoballah

Azmy

2016

Int. Trans. Electr. Energ. Syst.

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SUMMARYWith the tendency to move toward automated home energy management systems, the cooperative capacity of the smart grid "SG" became more and more significant. Distributed generation "DG", in addition to the novel patterns of electricity production, enabled the two-way energy flow. The concern of this paper is on introducing an automated control technique for optimizing the operational performance of the DG units within the residential applications. This problem is formulated in a constrained-nonlinear optimization structure based on a detailed economic system. Genetic algorithm "GA" technique is used to solve this problem by defining the optimal settings of the DG units. Availability of two-way communication and the use of smart meters will enable online implementation and facilitate data collection within a fully automated system. Based on certain tariffs and realistic load curves, many scenarios of operation are analyzed and assessed. The results show that using optimization technique in cooperative with advanced smart meters can enhance the economic situation of the overall grid significantly.

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Progress on the demand side management in smart grid and optimization approaches

et al. 2020

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The integration of demand side management (DSM) with smart grid (SG) can facilitate residents' transfer into smart homes and sustainable cities by reducing the carbon emission. This manuscript reviews the recent works related to the application of DSM in SG through discussing the techniques and algorithms and their associated challenges for effective implementation. This paper also critically discusses the operation mode of DSM, the profile of energy production, storage and consumption, and finally the benefit obtained by the DSM implementation. Previous literature suggested that DSM practice reduced peak-to-average ratio, energy cost and carbon emission by approximately 10% to 65%, 5% to 50%, and 14%, respectively. The implementation of DSM in SG deals with a number of challenges such as security and privacy, tariff regulation, energy transmission, distribution, and effective utilization of energy resources. A number of international organizations have taken various measures and solutions to guarantee the security and privacy of the DSM in SG discussed. So far, a number of algorithms have been used as optimization approach to solve the DSM optimization problems; however hybrid algorithms have showed better performance than single algorithms due to their faster convergence speed. At the end, the paper presents the research gaps and future research directions.

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User-friendly demand side management for smart grid networks

Cited by 12 publications

References 13 publications

Utilization of ICT and AI techniques in harnessing residential energy consumption for an energy-aware smart city: A review

Utilization of ICT and AI techniques in harnessing residential energy consumption for an energy-aware smart city: A review

Artificial intelligent-based optimization of automated home energy management systems

Progress on the demand side management in smart grid and optimization approaches

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