Medium/low voltage Smart Grid observability and PQ assessment with Unbundled Smart Meters

Sănduleac, Mihai; Alacreu, Lola; Pons, Lucas; Solar, Alma; Alemany, Rafael; Stanescu, Carmen

doi:10.1109/energycon.2016.7513988

Cited by 2 publications

(3 citation statements)

References 3 publications

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“…Mihaela M et al in their papers [11] and [12] proposed power quality (PQ) monitoring and control using voltage parameter assessment feature implemented in USM. Mihai Sanduleac et al in their researches [13], [14], [15] addressed the LV network observability and control issues and proposes the solution of USM architecture. Mihai Sanduleac et al [16] also presented an approach in his research article for integrating Electrical Vehicles in the Smart Grid with the application of unbundled Smart Metering.…”

Section: Robust State Feedback Controller For Photovoltaic Inverter Smentioning

confidence: 99%

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Robust State Feedback Controller for Photovoltaic Inverter System using Unbundled Smart Meter

Sharma¹,

Chakraborty²

2019

IJITEE

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The paper proposes the integration of photovoltaics into distribution power system through inverter control and optimally managing the power flow based on smart energy meter data. The concept of Unbundled Smart Meter (USM) is used which to optimally integrate the inverter control logic with in the Smart meter which requires the construction of SMX (Smart Meter Extension) library. The proposed approach is adapted to make the design more robust and dynamic. State feedback controller has been designed to control the power flow to and from between the inverter and grid through USM and hence provide additional services to support grid operations. The proposed system gives the flexibility of adding numerous functionalities in the installed smart meter without the fuss of firmware change and hence integration of renewables to grid becomes more efficient as the meter’s instantaneous data are used in the dynamic control of the system. The validation of the proposed scheme is achieved by time domain simulations on MATLAB/Simulink R2018a platform along with Arduino programming on Proteus 8.1 software. These results are further assessed through Hardware experiment observations.

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Section: Robust State Feedback Controller For Photovoltaic Inverter Smentioning

confidence: 99%

“…The delay Td is equal to half the time period of the carrier signal. And the Inverter Gain G is defined as: (14) Where Vdc is DC link voltage and VC is the peak of the triangular carrier used in PWM. The inverter can be mathematically represented as:…”

Section: State Space Representation Of Grid Connected Invertermentioning

confidence: 99%

Robust State Feedback Controller for Photovoltaic Inverter System using Unbundled Smart Meter

Sharma¹,

Chakraborty²

2019

IJITEE

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“…An important step has been made by the authors of [10], where the unbundled functionality had integrated a metrology meter labelled as "smart metrology meter" (SMM) in a multi-actor environment by using a "smart meter extension" (SMX). Authors involved in the project published papers showing different functional applications enabled by such a simple but versatile architecture [11,12]. In study [13] the unbundled smart meter (USM) concept was further extended and another important equipment was integrated, a low cost PMU, connected together with the SMM to an enhanced extension named "smart meter gateway" (SMG).…”

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confidence: 99%

Next Generation Real-Time Smart Meters for ICT Based Assessment of Grid Data Inconsistencies

et al. 2017

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Abstract:The latest technological developments are challenging for finding new solutions to mitigate the massive integration of renewable-based electricity generation in the electrical networks and to support new and dynamic energy and ancillary services markets. Smart meters have become ubiquitous equipment in the low voltage grid, enabled by the decision made in many countries to support massive deployments. The smart meter is the only equipment mandatory to be mounted when supplying a grid connected user, as it primarily has the function to measure delivered and/or produced energy on its common coupling point with the network, as technical and legal support for billing. Active distribution networks need new functionalities, to cope with the bidirectional energy flow behaviour of the grid, and many smart grid requirements need to be implemented in the near future. However there is no real coupling between smart metering systems and smart grids, as there is not yet a synergy using the opportunity of the high deployment level in smart metering. The paper presents a new approach for managing the smart metering and smart grid orchestration by presenting a new general design based on an unbundled smart meter (USM) concept, labelled as next generation open real-time smart meters (NORM), for integrating the smart meter, phasor measurement unit (PMU) and cyber-security through an enhanced smart metering gateway (SMG). NORM is intended to be deployed everywhere at the prosumer's interface to the grid, as it is usually now done with the standard meter. Furthermore, rich data acquired from NORM is used to demonstrate the potential of assessing grid data inconsistencies at a higher level, as function to be deployed in distribution security monitoring centers, to address the higher level cyber-security threats, such as false data injections and to allow secure grid operations and complex market activities at the same time. The measures are considering only non-sensitive data from a privacy perspective, and is therefore able to be applied everywhere in the grid, down to the end-customer level, where a citizen's personal data protection is an important aspect.

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Medium/low voltage Smart Grid observability and PQ assessment with Unbundled Smart Meters

Cited by 2 publications

References 3 publications

Robust State Feedback Controller for Photovoltaic Inverter System using Unbundled Smart Meter

Robust State Feedback Controller for Photovoltaic Inverter System using Unbundled Smart Meter

Next Generation Real-Time Smart Meters for ICT Based Assessment of Grid Data Inconsistencies

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