Enhanced Operation of Electricity Distribution Grids  Through Smart Metering PLC Network Monitoring, Analysis and Grid Conditioning

Sendin, Alberto; Berganza, Iñigo; Arzuaga, Aitor; Osorio, Xabier; Urrutia, Iker; Angueira, Pablo

doi:10.3390/en6010539

Cited by 37 publications

(21 citation statements)

References 26 publications

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“…Different from conventional distribution systems, it is difficult for the smart grids to use a single control center to regulate the whole system rapidly and efficiently. Control of the new distribution systems should base on local information as much as possible [1,18,19]. Therefore, the theory of distributed control for new distribution systems can be far more complicated than traditional control theory.…”

Section: The Layered Fault Treementioning

confidence: 99%

A Layered Fault Tree Model for Reliability Evaluation of Smart Grids

Song

Chen

2014

Energies

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Abstract:The smart grid concept has emerged as a result of the requirement for renewable energy resources and application of new techniques. It is proposed as a practical future form of power distribution system. Evaluating the reliability of smart grids is of great importance and significance. Focusing on the perspective of the consumers, this paper proposes a layered fault tree model to distinguish and separate two different smart grid power supply modes. Revised importance measures for the components in the fault tree are presented considering load priority, aiming to find the weak parts of the system and to improve the design and using. A corresponding hierarchical Monte Carlo simulation procedure for reliability evaluation is proposed based on the layered fault tree model. The method proposed in this paper is tested on a case of reliability assessment for the Future Renewable Electric Energy Delivery and Management (FREEDM) system. The proposed technique can be applicable to other forms of smart grids.

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Section: The Layered Fault Treementioning

confidence: 99%

A Layered Fault Tree Model for Reliability Evaluation of Smart Grids

Song

Chen

2014

Energies

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“…Recall that in the proposed framework, only data blocks corresponding to (m S , m T ) are reported where (m S , m T ) can be determined for each (n S , n T ) as described in Section III-B. Specifically, we have (m S , m T ) = { (10,194), (13,190), (16,180), (19,166), (22,151)} for n T =256 and n S = {32, 48, 64, 80, 96}, respectively. Again, this figure confirms that the proposed CSMA-CS scheme outperforms the TDMA scheme.…”

Section: B Numerical Results and Discussionmentioning

confidence: 99%

“…Here, we use AR (1) as an appropriate and simple data model; however other more complicated methods can be used as well [36], [37], [41]. We now present the method to determine the parameters (χ 0 , χ re,i , χ im,i , m h , ϕ t ) in (13) and (14). These parameters are coupled as indicated in (13) and (14).…”

Section: A Data Modeling and Simulation Settingmentioning

confidence: 99%

“…We focus on reporting injected powers at different grid reporting points once in every reporting interval (RI) [9], [10]. This is motivated by the fact that information on injected powers can be very useful for various grid applications such as line failure prediction [11]- [13] or congestion management and grid control applications [14], [15]. Furthermore, the utility control center can utilize the collected data to further estimate the complete phasor data at different nodes [16] which can be then used in the control of voltages and reactive powers or in the active load management [9], [10], [17], outage management [18], [19] as well as illegal electricity usages and data intrusion/anomaly detection [20], [21].…”

Section: Introductionmentioning

confidence: 99%

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Joint data compression and MAC protocol design for smartgrids with renewable energy

Tan

2016

Wireless Communications

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Abstract-In this paper, we consider the joint design of data compression and 802.15.4-based medium access control (MAC) protocol for smartgrids with renewable energy. We study the setting where a number of nodes, each of which comprises electricity load and/or renewable sources, report periodically their injected powers to a data concentrator. Our design exploits the correlation of the reported data in both time and space to efficiently design the data compression using the compressed sensing (CS) technique and the MAC protocol so that the reported data can be recovered reliably within minimum reporting time. Specifically, we perform the following design tasks: i) we employ the two-dimensional (2D) CS technique to compress the reported data in the distributed manner; ii) we propose to adapt the 802.15.4 MAC protocol frame structure to enable efficient data transmission and reliable data reconstruction; and iii) we develop an analytical model based on which we can obtain efficient MAC parameter configuration to minimize the reporting delay. Finally, numerical results are presented to demonstrate the effectiveness of our proposed framework compared to existing solutions.Index Terms-CSMA MAC protocols, renewable energy, compressed sensing, smart grids, and power line communications.

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“…In order to accomplish this task, communications have to be enabled throughout all the components of the power grid, thus enabling a two-way data interchange involving producers and consumers of energy. That is one of the cornerstones of the Smart Grid, because the interchange of information will provide the basis for smart power management, and it can be used to achieve the objectives it was conceived for, such as carbon emissions reduction [5] or a better distribution of low power electricity [6]. Plus, as long as a historical record is stored and can be accessed, other applications as power consumption forecast or consumption statistic can be obtained as well.…”

Section: Introductionmentioning

confidence: 99%

Middleware Architectures for the Smart Grid: Survey and Challenges in the Foreseeable Future

et al. 2013

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Abstract:The traditional power grid is just a one-way supplier that gets no feedback data about the energy delivered, what tariffs could be the most suitable ones for customers, the shifting daily needs of electricity in a facility, etc. Therefore, it is only natural that efforts are being invested in improving power grid behavior and turning it into a Smart Grid. However, to this end, several components have to be either upgraded or created from scratch. Among the new components required, middleware appears as a critical one, for it will abstract all the diversity of the used devices for power transmission (smart meters, embedded systems, etc.) and will provide the application layer with a homogeneous interface involving power production and consumption management data that were not able to be provided before. Additionally, middleware is expected to guarantee that updates to the current metering infrastructure (changes in service or hardware availability) or any added legacy measuring appliance will get acknowledged for any future request. Finally, semantic features are of major importance to tackle scalability and interoperability issues. A survey on the most prominent middleware architectures for Smart Grids is presented in this paper, along with an evaluation of their features and their strong points and weaknesses.

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Enhanced Operation of Electricity Distribution Grids Through Smart Metering PLC Network Monitoring, Analysis and Grid Conditioning

Cited by 37 publications

References 26 publications

A Layered Fault Tree Model for Reliability Evaluation of Smart Grids

A Layered Fault Tree Model for Reliability Evaluation of Smart Grids

Joint data compression and MAC protocol design for smartgrids with renewable energy

Middleware Architectures for the Smart Grid: Survey and Challenges in the Foreseeable Future

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