Toward the power InterGrid

Krylov, Vladimir A.; Ponomarev, Dmitry; Loskutov, Alexey

doi:10.1109/energycon.2010.5771704

Cited by 9 publications

(5 citation statements)

References 4 publications

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“…In analogy with communications networks, in a PPG a number of power sources and power consumers exchange power (Direct Current, DC) in the form of "packets", which flow from sources to consumers thanks to power lines and electronic switches. The energy routing process is controlled by a special entity called the energy router [5]. Following this architecture, a local area packetized power network consisting of a group of energy subscribers and a core energy router is 2473-2400 c 2019 IEEE.…”

Section: Online Power Management Strategies For Energymentioning

confidence: 99%

Online Power Management Strategies for Energy Harvesting Mobile Networks

Gambı́n

Scalabrin

Rossi

2019

IEEE Trans. on Green Commun. Netw.

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The design of self-sustainable base station (BS) deployments is addressed in this paper. We target deployments featuring small BSs with energy harvesting (EH) and storage capabilities. These BSs can use ambient energy to serve the local traffic or store it for later use. A dedicated power packet grid is utilized to transfer energy across them, compensating for imbalance in the harvested energy or in the traffic load. Some BSs are offgrid, i.e., they can only use the locally harvested energy and that transferred from other BSs, whereas others are ongrid, i.e., they can additionally purchase energy from the power grid. Within this setup, an optimization problem is formulated where: harvested energy and traffic processes are estimated (at runtime) at the BSs through Gaussian processes, and a model predictive control framework is devised for the computation of energy allocation and transfer across BSs. The combination of prediction and optimization tools leads to an efficient and online solution that automatically adapts to EH and load dynamics. Numerical results, obtained using real EH and traffic profiles, show substantial improvements with respect to the case where the optimization is carried out without predicting future system dynamics. The main improvements are in the outage probability (zero in most cases), and in the amount of energy purchased from the power grid, that is more than halved for the same served load. Index Terms-Online learning, foresighted optimization, energy harvesting, energy routing, energy self-sustainability, power packet grids, mobile networks. 1 Computed as the ratio between the number of BSs that are unable to serve the users within range due to energy scarcity, and the total number of BSs.

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Section: Online Power Management Strategies For Energymentioning

confidence: 99%

Online Power Management Strategies for Energy Harvesting Mobile Networks

Gambı́n

Scalabrin

Rossi

2019

IEEE Trans. on Green Commun. Netw.

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“…Energy cooperation will be the key feature in future MNs. According to [4], energy transfer can be accomplished using the Power Packet Grid (PPG), where power between sources and consumers is exchanged in the form of packets which flow from sources to consumers through power lines and electronic switches via the energy router [5] (which is responsible for the packets routing process). With the advent of Network Function Virtualization (NFV), the energy router can be softwarized (virtualized) and then placed in the MEC server, in a form of an application, in order to enable location-aware energy routing.…”

Section: Introductionmentioning

confidence: 99%

MEC-enabled Energy Cooperation for Sustainable 5G Networks Exploiting the Location Service API

Dlamini

2019

Preprint

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The substantial growth in wireless data traffic, and the emergence of delay-sensitive application/services requiring ultra-low latency, has resulted into a new Mobile Network (MN) design paradigm called Multi-access Edge Computing (MEC). In this, the Base Stations (BSs) are empowered with computing capabilities, and they are densely deployed in order to increase network coverage and provide high throughput to mobile users. These developments require energy self-sustainability in order to minimize the carbon emission into the atmosphere and the dependence on the power grid. As a solution to this, we advocate for the integration of Energy Harvesting (EH) systems, e.g., solar panels or wind turbines (together with energy storage devices), into future BSs and edge computing systems (i.e., MEC servers). However, due to traffic load and harvested energy variations within a coverage area, the stored energy levels will also vary. To compensate for green energy imbalance within the network, energy cooperation (transfer) can be enabled by an energy trading application hosted in the MEC platform, and the energy packets traverse over the Power Packet Grid (DC power lines and switches) from the source BS(s) to the energy-deficient BS(s). In this paper, we jointly perform energy allocation and energy routing using an online algorithm based on Lyapunov drift-and-penalty optimization theorem (named Lyapunov) for enabling energy cooperation, leveraging the MEC Location Service (LS) Application Programmable Interface (API). Our numerical results reveal that the Lyapunov algorithm is able to deliver sufficient amount of energy under normal solar irradiance without the effects of the control parameter.

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“…In the conventional power delivery system, power from different sources such as RESs is converted to a unified form in compliance with the utility grid standard. In the reported PP delivery system, it is not compulsory to convert the RESs voltage to a unified voltage level which is one of the main advantages of the PP transmission system [19][20][21]. The absence of an intermediate voltage conversion stage increases the efficiency of the overall power system.…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of a packeted DC power system using a modified power packet structure

Reza

2018

IET Power Electronics

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Recently, energy internet is introduced aiming to improve power system reliability, security and efficiency through advanced information and power electronic technologies. Power packet (PP) distribution system which integrates information transfer into electric power transfer is a potential candidate for energy internet implementation. It can reduce stand-by power, eliminate voltage conversion stage in the traditional power distribution system, and actively control the load demand intelligently from the source side. This paper improves three areas of the existing PP distribution system, namely (i) a systematic approach to selecting the energy buffer based on the payload, identification bits, the load resistance and bit rate; (ii) a new algorithm to transfer PPs using a modified PP structure to the targeted loads with reduced footer bit, hence it can reduce more than 50% of the switching loss and information overhead; (iii) a simplified algorithm for a mixer to generate PPs according to multiple load requests. Experimental results of the improved packeted DC power system are reported.

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Toward the power InterGrid

Cited by 9 publications

References 4 publications

Online Power Management Strategies for Energy Harvesting Mobile Networks

Online Power Management Strategies for Energy Harvesting Mobile Networks

MEC-enabled Energy Cooperation for Sustainable 5G Networks Exploiting the Location Service API

Design and implementation of a packeted DC power system using a modified power packet structure

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