Smart sensor network for power quality monitoring in electrical installations

Morales-Velazquez, Luis; Romero-Troncoso, René de Jesús; Herrera-Ruíz, Gilberto; Moriñigo-Sotelo, Daniel; Osornio-Ríos, Roque Alfredo

doi:10.1016/j.measurement.2017.02.032

Cited by 80 publications

(36 citation statements)

References 20 publications

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“…This section assesses the state of the art regarding prototypes of power smart meters for households. Depending on the support platform, these prototypes can be classified as follows: (i) Arduino open-source platform [3,7,14,[43][44][45][46][47][48][49][50][51][52][53][54][55][56][57], (ii) field-programmable gate array (FPGA) technology [4,41], (iii) Lopy [5], and (iv) others [6,8,51,52].…”

Section: Research On Power Smart Meter Prototypes For Householdsmentioning

confidence: 99%

“…Smart meter roll-out in households with PV distributed generation, hereafter known as PV household-prosumers, provides easy access to on-time detailed meter measurements, which enable advanced energy services. The range of services provided include the application of demand response measures [1][2][3][4][5][6], smart home/building automation [7,8], and the provision of balancing services such as frequency control services (frequency containment reserve [9][10][11][12] and frequency restoration reserve [13]). The design of these services is based on the training and validation of models.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Development and Calibration of an Open Source, Low-Cost Power Smart Meter Prototype for PV Household-Prosumers

et al. 2019

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Smart meter roll-out in photovoltaic (PV) household-prosumers provides easy access to granular meter measurements, which enables advanced energy services. The design of these services is based on the training and validation of models. However, this requires temporal high-resolution data for generation/load profiles collected in real-world household facilities. For this purpose, this research developed and successfully calibrated a new prototype for an accurate low-cost On-time Single-Phase Power Smart Meter (OSPPSM), which corresponded to these profiles. This OSPPSM is based on the Arduino open-source electronic platform. Not only can it locally store information, but can also wirelessly send these data to cloud storage in real-time. This paper describes the hardware and software design and its implementation. The experimental results are presented and discussed. The OSPPSM demonstrated that it was capable of in situ real-time processing. Moreover, the OSPPSM was able to meet all of the calibration standard tests in terms of accuracy class 1 (measurement error ≤1%) included in the International Electrotechnical Commission (IEC) standards for smart meters. In addition, the evaluation of the uncertainty of electrical variables is provided within the context of the law of propagation of uncertainty. The approximate cost of the prototype was 60 € from eBay stores.

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Section: Research On Power Smart Meter Prototypes For Householdsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development and Calibration of an Open Source, Low-Cost Power Smart Meter Prototype for PV Household-Prosumers

et al. 2019

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“…A smart sensor network was proposed by Morales-Velazquez et al 21 that permits reviewing an electrical installation. It conveys standard estimations and permits inspecting PQD events in detail and interactions between lines, identifying electrical equipment, and correlating events between monitoring points.…”

Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

A new protection scheme for PQ events prediction and classification in distribution system: A SSO-ANN strategy

Karthikumar

Kumar

Muneeswaran

2019

Measurement and Control

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Increased utilization of nonlinear loads and fault event on the power system have resulted in a decline in the quality of power provided to the customers. It is fundamental to recognize and distinguish the power quality disturbances in the distribution system. To recognize and distinguish the power quality disturbances, the development of high protection schemes is required. This paper presents an optimal protection scheme for power quality event prediction and classification in the distribution system. The proposed protection scheme combines the performance of both the salp swarm optimization and artificial neural network. Here, artificial neural network is utilized in two phases with the objective function of prediction and classification of the power quality events. The first phase is utilized for recognizing the healthy or unhealthy condition of the system under various situations. Artificial neural network is utilized to perceive the system signal’s healthy or unhealthy condition under different circumstances. In the second phase, artificial neural network performs the classification of the unhealthy signals to recognize the right power quality event for assurance. In this phase, the artificial neural network learning method is enhanced by utilizing salp swarm optimization based on the minimum error objective function. The proposed method performs an assessment procedure to secure the system and classify the optimal power quality event which occurs in the distribution system. At that point, the proposed work is executed in the MATLAB/Simulink platform and the performance of the proposed system is compared with different existing techniques like Multiple Signal Classification-Artificial Neural Network (MUSIC-ANN), and Genetic Algorithm - Artificial Neural Network (GA-ANN). The comparison results demonstrate the superiority of the SSO-ANN technique and confirm its potential to power quality event prediction and classification.

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“…They all use existing smart meters provided by the electrical company to gather extra information aside from for billing purposes, meaning that the information is aggregated by individual consumers, making it difficult to act over individual loads and implement measures to anticipate faults in an early stage. To that end, the ground-breaking smart meter developed in paper [27] provides standard PQ information as Total Harmonic Distortion (THD); in addition to event detections such as sags, swells, or interruptions, a complementary NILM approach is implemented in the prototype to identify appliances or industrial equipment. However, data are stored in an external micro-SD memory, so access to the data are offline, meaning no control can be done with it, and it exists only for monitoring purposes.…”

Section: Power Quality Literature Surveymentioning

confidence: 99%

Novel Internet of Things Platform for In-Building Power Quality Submetering

et al. 2018

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Abstract:As the number of facilities adopting a Building Management System under the Industry 4.0 paradigm increases, it is critical to ensure the good health of their operations. Business continuity and uninterrupted operations are key requirements for any building, for which Power Quality and Supply Reliability sophisticated monitoring can play an extremely important role. Submetering, as opposed to bulk-metering, implies measuring power consumption for individual units or appliances in a building complex. An Internet of Things mesh network, which brings ubiquitous power quality submetering inside the entire facility, would be extremely beneficial for the management of the building thus ensuring seamless business operations. This work describes a novel low-cost Internet of Things sensor for measuring and analyzing power quality at the input of any individual Alternating Current (AC) appliance, providing an early detection and analysis system which controls those critical variables inside the facility and leads to anticipate faults with early-stage alerts based on on-time data streams treatment. Moreover, the recorded power quality parameters that are processed in the Cloud system can help to reduce energy consumption, as power quality disturbances can be automatically analyzed and even compared to standard values. The proposed Internet of Things sensor will help users to detect most power quality steady-state and events disturbances, while monitoring the energy consumption. This Internet of Things Power Quality sensor is built around a flexible microcontroller, which manages an energy metering Integrated Circuit (IC) through Serial Peripheral Interface (SPI), increasing its original capabilities by including new sophisticated software functionality. Additionally, it wirelessly communicates with a cloud-based Internet of Things Platform to allow the storage and supervision of the different power quality events for the entire facility. An example of the access to the data is also included.

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Smart sensor network for power quality monitoring in electrical installations

Cited by 80 publications

References 20 publications

Development and Calibration of an Open Source, Low-Cost Power Smart Meter Prototype for PV Household-Prosumers

Development and Calibration of an Open Source, Low-Cost Power Smart Meter Prototype for PV Household-Prosumers

A new protection scheme for PQ events prediction and classification in distribution system: A SSO-ANN strategy

Novel Internet of Things Platform for In-Building Power Quality Submetering

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