Smart Meter Traffic in a Real LV Distribution Network

Evolving power systems with increasing renewables penetration, along with the development of the smart grid, calls for improved communication networks to support these distributed generation sources. Automatic and optimal placement of communication resources within the advanced metering infrastructure is critical to provide a high-performing, reliable, and resilient power system. Three network design formulations based on mixed-integer linear and non-linear programming approaches are proposed to minimise network congestion by optimising residual buffer capacity through the placement of data concentrators and network routeing. Results on a case study show that the proposed models improve network connectivity and robustness, and increase average residual buffer capacity. Maximising average residual capacity alone, however, results in both oversaturated and underutilised nodes, while maximising either minimum residual capacity or total reciprocal residual capacity can yield much-improved network load allocation. Consideration of connection redundancy improves network reliability further by ensuring quality-of-service in the event of an outage. Analysis of multi-period network expansion shows that the models do not deviate significantly from optimal when used progressively (within 5% deviation), and are effective for utility planners to use for smart grid expansion.

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“…While cellular technologies have been studied for SM transmissions, they are generally preferred for links between DCs and ERs [16].…”

Section: Neighbourhood Area Networkmentioning

confidence: 99%

Optimal placement of data concentrators for expansion of the smart grid communications network

et al. 2019

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“…The European Commission [3] envisions that tomorrow's power grids will be made up of interconnected and diverse systems, with a growing number of distributed energy generation and consumption equipment and appliances that generate a large volume of data [4]. Considering only smart meters, if the average packet size is about 200 bytes [5], with a reading interval of 15 min as suggested in the European Union (EU) regulations and the 200 million smart meters that are deployed in 2020 [6], the total amount of memory in Europe is 5 606 TB of information. Reduce the sampling size to every second for near-real-time network measurement, and this is around 5 exabytes of data to be collected within a year only from smart meters.…”

Section: Introductionmentioning

confidence: 99%

“…For example, AI technology has penetrated the technical applications rapidly in the industrial systems. Technically, in the power and electrical engineering domain, AI techniques, such as expert systems, neural networks, and fuzzy logic have been utilized to solve various technical challenges [16], including but not limited to (1) energy forecasting [17,18], (2) energy market price prediction [19], (3) smart grid fault detection [20], (4) demand-side management [21], (5) building energy management [22], (6) smart home demand response management [23], and (7) smart grid data security with AI and blockchain [24]. In terms of driving the energy transition process, the greatest potential in the use of AI is forecasting renewable energy potential, big data management and optimization of hybrid renewable energy systems, e.g., [25,26].…”

Section: Introductionmentioning

confidence: 99%

Electricity Market Empowered by Artificial Intelligence: A Platform Approach

Ahokangas

Louis

et al. 2019

Energies

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Artificial intelligence (AI) techniques and algorithms are increasingly being utilized in energy and renewable research to tackle various engineering problems. However, a majority of the AI studies in the energy domain have been focusing on solving specific technical issues. There is limited discussion on how AI can be utilized to enhance the energy system operations, particularly the electricity market, with a holistic view. The purpose of the study is to introduce the platform architectural logic that encompasses both technical and economic perspectives to the development of AI-enabled energy platforms for the future electricity market with massive and distributed renewables. A constructive and inductive approach for theory building is employed for the concept proposition of the AI energy platform by using the aggregated data from a European Union (EU) Horizon 2020 project and a Finnish national innovation project. Our results are presented as a systemic framework and high-level representation of the AI-enabled energy platform design with four integrative layers that could enable not only value provisioning but also value utilization for a distributed energy system and electricity market as the new knowledge and contribution to the extant research. Finally, the study discusses the potential use cases of the AI-enabled energy platform.

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“…PLC also ensures higher security against cyber-attacks, as potential hackers cannot easily access the communication system [15]. Moreover, the reliability of this technology is already demonstrated by its wide implementation in low-voltage (LV) networks to support various intelligent applications (automatic meter reading, demand-side management, and so on) [16][17][18][19][20][21][22][23]. As regards reliability issues, different modulation techniques were experimented from the first implementations.…”

Section: Introductionmentioning

confidence: 99%

A New Coupling Solution for G3-PLC Employment in MV Smart Grids

et al. 2019

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This paper proposes a new coupling solution for transmitting narrowband multicarrier power line communication (PLC) signals over medium voltage (MV) power lines. The proposed system is based on an innovative PLC coupling principle, patented by the authors, which exploits the capacitive divider embedded in voltage detecting systems (VDS) already installed inside the MV switchboard. Thus, no dedicated couplers have to be installed and no switchboard modifications or energy interruptions are needed. This allows a significant cost reduction of MV PLC implementation. A first prototype of the proposed coupling system was presented in previous papers: it had a 15 kHz bandwidth useful to couple single carrier PSK modulated PLC signals with a center frequency from 50–200 kHz. In this paper, a new prototype is developed with a larger bandwidth, up to 164 kHz, thus allowing to couple multicarrier G3-PLC signals using orthogonal frequency division multiplexing (OFDM) digital modulation. This modulation ensures a more robust communication even in harsh power line channels. In the paper, the new coupling system design is described in detail. A new procedure is presented for tuning the coupling system parameters at first installation in a generic MV switchboard. Finally, laboratory and in-field experimental test results are reported and discussed. The coupling performances are evaluated measuring the throughput and success rate in the case of both 18 and 36 subcarriers, in one of the different tone masks standardized for the FCC-above CENELEC band (that is, from 154.6875–487.5 kHz). The experimental results show an efficient behavior of the proposed coupler allowing a two-way communication of G3-PLC OFDM signals on MV networks.

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Smart Meter Traffic in a Real LV Distribution Network

Cited by 18 publications

References 24 publications

Optimal placement of data concentrators for expansion of the smart grid communications network

Optimal placement of data concentrators for expansion of the smart grid communications network

Electricity Market Empowered by Artificial Intelligence: A Platform Approach

A New Coupling Solution for G3-PLC Employment in MV Smart Grids

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