Delay-optimal mode selection in device-to-device communications for smart grid

Asuhaimi, Fauzun Abdullah; Nadas, João Pedro Battistella; Imran, Muhammad Ali

doi:10.1109/smartgridcomm.2017.8340710

Cited by 6 publications

(5 citation statements)

References 15 publications

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“…For a discharge time 𝑡 𝑑𝑖𝑠 , the battery discharge energy 𝐸 𝑑𝑖𝑠 , shown in (7) which is a function of open-circuit voltage (E.M.F.) 𝑉 𝑜 , with internal resistance 𝑅 𝑖𝑛𝑡 and constant discharge current 𝐼 𝑐𝑜𝑛 .…”

Section: Battery Modellingmentioning

confidence: 99%

“…The research was carried out to validate the novel energy storage system (ESS) topology using a multisource inverter. Work focusing on the intention of limiting battery peak current and weight, extending battery life, and increasing the driving range for plug-in EV, with the active-controlled parallel operation of a battery and an ultra-capacitor (UC) as energy devices [5]- [7].…”

Section: Introductionmentioning

confidence: 99%

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Implementation of a P&E management system for a dual-source EV powered by different batteries

Thakre,

C. Tapre,

Somnath Kadlag

et al. 2023

Bulletin EEI

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There is an era started in the field of power energy (PE) management in the electric vehicles (EVs) application cloud, which impacts the smart grid in significant ways and necessitates the collaboration of multiple branches of engineering. Most of the problems with EVs stem from their limited range, which can be improved by incorporating additional forms of energy storage. This paper makes an effort to bring a fresh viewpoint to the description of the power and energy management problem facing EV, taking into account all the needs of such a vehicle. Using a novel power and energy management system, the proposed methodology enables a systematic approach to this multidisciplinary problem. Implementing a power and energy management system for a dual-source EV using lead-acid batteries and ultra-capacitors (UCs) exemplifies the novel framework's capabilities. The electronic power development architecture is outlined in detail, along with the implementing modular blocks that make up the entire system architecture.

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Section: Battery Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Implementation of a P&E management system for a dual-source EV powered by different batteries

Thakre,

C. Tapre,

Somnath Kadlag

et al. 2023

Bulletin EEI

View full text Add to dashboard Cite

show abstract

“…Under same assumption of linear search, complexity of HRQ relies mainly on the maximum search performed in eq. (4) and (5). Therefore, complexity of HRQ can be identified using number of actions at a desired state, i.e.…”

Section: B Complexity Analysismentioning

confidence: 99%

“…Nevertheless, the data transfer delay (latency) in existing mobile communication technology is not guaranteed to be satisfactory for latency-critical smart grid services (e.g. synchrophasor applications), and addressing this problem is an ongoing area of research [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

High-Reliability Multi-Agent Q-Learning-Based Scheduling for D2D Microgrid Communications

et al. 2019

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This paper proposes a multi-agent Q-learning-based resource allocation algorithm that allows long-term evolution (LTE)-enabled device-to-device (D2D) communication agents to generate the orthogonal transmission schedules outside the network coverage. This algorithm reduces packet drop rates (PDR) in distributed D2D communication networks to meet the quality-of-service requirements of the microgrid communications. The data traffic characteristics of three archetypal smart grid applications, namely demand response, solar, and generation forecasting, and synchrophasor communications, were simulated under seven different traffic congestion scenarios, where the total aggregate throughput of users ranged from 50% to 140% channel utilization. The PDR and latency performance of the proposed algorithm were compared with the existing random self-allocation mechanism introduced under the Third-Generation Partnership Project's LTE Release 12 standard for such scenarios. Our algorithm outperformed the LTE algorithm for all tested scenarios, demonstrating 20%-40% absolute reductions in PDR and 10-20-ms reductions in latency for all microgrid applications. The use of our algorithm in a simulated D2D-enabled demand response application resulted in a hundredfold reduction in power oscillations about the desired power flows.

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“…Therefore, the relay selection is dependent on the report length and the channel state of each IEM at the beginning of transmission phase. Algorithm 2 [38] is also performed based on brute-force searching method [18] to obtain a set of potential RIs, G which is a set of IEMs that have higher SNR than the average SNR, γ * t and smaller queue length than the average packet length B t . Additionally, based on Algorithm 2, IEMs in F are assigned as reuse IEMs, in which the sub-channels of the IEMs in the set can be reused for D2D-Assisted relaying mode.…”

Section: The Eedo Algorithmmentioning

confidence: 99%

Delay-Aware Energy-Efficient Joint Power Control and Mode Selection in Device-to-Device Communications for FREEDM Systems in Smart Grids

Asuhaimi

Nadas

et al. 2019

IEEE Access

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Cellular technology with long-term evolution (LTE)-based standards is a promising technology for smart grid communication networks. However, the integration of cellular technology and smart grid communications is a significant challenge due to the transmission of simultaneous and delay-sensitive smart grid data. The Device-to-device (D2D) communications are proposed as critical solutions to enhance the performance of the LTE. In this paper, we study energy efficiency and delay problems in D2D underlaying cellular communications for the future renewable electric energy delivery and management (FREEDM) system in smart grid with different message sizes and varying channel conditions. We adopt a D2D-assisted relaying framework to assist links that meet poor channel conditions in order to increase the data rate of intelligent energy management devices with large size report. We propose a joint power control and mode selection scheme to deal with the problem and develop a brute-force-based algorithm to find the solutions. We conduct simulations to show the effectiveness of the proposed scheme in balancing the tradeoff between energy efficiency and end-to-end delay and show significant energy efficiency improvements when exploiting the proposed scheme compared to direct and relaying schemes in a variety of different conditions.

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Delay-optimal mode selection in device-to-device communications for smart grid

Cited by 6 publications

References 15 publications

Implementation of a P&E management system for a dual-source EV powered by different batteries

Implementation of a P&E management system for a dual-source EV powered by different batteries

High-Reliability Multi-Agent Q-Learning-Based Scheduling for D2D Microgrid Communications

Delay-Aware Energy-Efficient Joint Power Control and Mode Selection in Device-to-Device Communications for FREEDM Systems in Smart Grids

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