A novel demand control policy for improving quality of power usage in smart grid

Fouda, Mostafa M.; Fadlullah, Zubair Md.; Kato, Nei; Takeuchi, Akihiro; Nozaki, Yousuke

doi:10.1109/glocom.2012.6503938

Cited by 25 publications

(7 citation statements)

References 12 publications

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“…The deregulation of electricity markets [24][25][26][27][28], along with the advances in information and communication technologies [12,[29][30][31], has motivated more active DSM programs. As a result, Independent System Operators (ISOs) and Reliability Transmission Organizations (RTOs) have been implementing DSM for its potential to lower market prices, reduce price volatility, improve customer options, and increase the elasticity from wholesale to retail market [32].…”

Section: Motivationmentioning

confidence: 99%

Demand side management in a day-ahead wholesale market: A comparison of industrial & social welfare approaches

Jiang

Farid

2015

Applied Energy

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Section: Motivationmentioning

confidence: 99%

Demand side management in a day-ahead wholesale market: A comparison of industrial & social welfare approaches

Jiang

Farid

2015

Applied Energy

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“…SG devices and smart appliances are increasingly designed to be "Demand Response-enabled". To realize efficiency and load-management goals, utility companies are adopting two-way networking connectivity to enable consumers to monitor and possibly reduce their energy usage [18,19]. A centralized entity will poll or inform the meter to gather appropriate consumption information.…”

Section: Smart Grid Requirementsmentioning

confidence: 99%

A Review of Wireless and Satellite-based M2M Services in Support of Smart Grids

Sohraby¹,

Minoli

Occhiogrosso

2017

Proceedings of the the 1st EAI International Conference on Smart Grid Assisted Internet of Things

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The Smart Grid (SG) is an evolution of the electricity network that integrates the activities of power consumers, power generators, distribution grid, and devices connected to the grid (e.g., substations, transformers.) Machine-to-Machine (M2M) technology is designed for automated data exchange between devices, and thus has applicability to SGs. With M2M technology, organizations track and manage assets; inventories; transportation fleets; oil and gas pipelines; mines; widespread infrastructure; natural phenomena such as weather conditions, farm production, forestry condition, and water flows; and, as noted, SGs. Wireless communication is a staple of M2M. These wireless technologies range from unlicensed local (so called 'fog') connectivity, to licensed 3G/4G/5G cellular, to Low Earth Orbit (LEO) satellites. All of these technologies are relevant to the SG. Utilities have started to gradually support M2M and Supervisory Control And Data Acquisition (SCADA) systems over satellite links. This article focuses on wireless and satellite-based M2M services, as applicable to the Smart Grid, including the use of Internet of Things (IoT), particularly for the transmission and distribution space (T&D) sector; some comparisons to wireline solutions are also discussed.

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“…With this type of usage, assumptions along with usage states can very easily be implemented to understand energy usage of a device for accountability purposes without implementing a full NILM mechanism. Even in instances where the usage range is very small (simulations [2][3][4][9][10][11][12], the majority of the usage remains near the extreme upper or lower usage amounts. Therefore, the usage state has a more accurate labeling on the amount of energy used whenever usage is in its range.…”

Section: Energy Usagementioning

confidence: 99%

Home area network accountability with varying consumption devices in smart grid

McCary

Xiao

2015

Security Comm. Networks

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Among the principals for securing smart grid infrastructure, accountability is one with lesser addressed concepts in smart grid literature. Even further, studies in the home area network are lacking in enforcement of accountable mechanisms as assigning responsibilities for devices’ actions are generally made the responsibility of the utility. This paper addresses accountability of devices in the home area network by providing a witness‐based method for more accurate monitoring and estimation of the energy usage for devices whose power consumption varies while these devices are powered on. Algorithm analysis and simulation results show that the method is effective, and the method is well within the acceptable rate of error based on today's standards of estimation without need of previous knowledge of device profiles. Copyright © 2015 John Wiley & Sons, Ltd.

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A novel demand control policy for improving quality of power usage in smart grid

Cited by 25 publications

References 12 publications

Demand side management in a day-ahead wholesale market: A comparison of industrial & social welfare approaches

Demand side management in a day-ahead wholesale market: A comparison of industrial & social welfare approaches

A Review of Wireless and Satellite-based M2M Services in Support of Smart Grids

Home area network accountability with varying consumption devices in smart grid

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