Power Factor Compensation Using Teaching Learning Based Optimization and Monitoring System by Cloud Data Logger

Caño, Antonio; Sánchez-Sutil, F.; Hernández, Jesús De la Casa

doi:10.3390/s19092172

Cited by 38 publications

(35 citation statements)

References 29 publications

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Section: Related Workmentioning

confidence: 99%

“…A modified ABC algorithm for constrained optimization problems was presented by Karaboga et al [3] for a set of constrained test problems. Other evolutionary algorithms, such as TLBO, were studied for the optimization of the power factor (PF) in [4].The ABC algorithm has been used for the determination of optimal location and sizing of DG units using the multi objective performance index for enhancing the voltage stability of the radial distribution system in [5].Other algorithms together with ABC have been used, such as the hybrid algorithm ACO-ABC-HS, which combines the framework of ant colony optimization (ACO), artificial bee colony (ABC) and harmonic systems (HS) for solving the problem of economic dispatch for a multi-generator system in [6]. In this sense, Gaidhane et al [7] developed the grey wolf optimizer and ABC algorithm to inherit their advantages and overcome their drawbacks.Also, the ABC algorithm is used to find the optimum PID controller parameters.…”

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confidence: 99%

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Performance Optimization LoRa Network by Artificial Bee Colony Algorithm to Determination of the Load Profiles in Dwellings

Caño

Sánchez-Sutil

2020

Energies

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This paper presents a system to improve the performance of the Long Range (LoRa) network using an algorithm derived from the artificial bee colony (ABC), which obtains a minimum packet lost rate (PLR) in the LoRa network and allows to more accurately determine load profiles of dwellings, with smaller a time measurement and less data transmission. The developed algorithm calculates the configuration parameters of the LoRa network, monitoring in real time the data traffic, and is implemented in gateway LoRa network monitor (GLNM). Intelligent measurement equipment has been developed to determine the dwelling load profiles. This energy measurement device for dwelling (EMDD) measures the variables and consumption of electricity in each home with measurement times that can be configured. This research also develops the GLNM gateway, which monitors and receives data from the EMDDs installed and uploads them to the cloud using Firebase. This developed system allows to perform demand forecasting studies, analysis of home consumption, optimization of electricity tariffs, etc., applied to smart grids.

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Section: Related Workmentioning

confidence: 99%

mentioning

confidence: 99%

Performance Optimization LoRa Network by Artificial Bee Colony Algorithm to Determination of the Load Profiles in Dwellings

Caño

Sánchez-Sutil

2020

Energies

Self Cite

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“…Figure 2(b) illustrates this example. The required capacitor in can then be calculated using (8) [18,19].…”

Section: Power Factor Correction Calculationmentioning

confidence: 99%

Design of power factor meter using internet of things for power factor improvement, remote monitoring and data logging

Gunawan

Anuar

Kartiwi

et al. 2020

IJEECS

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Nowadays, many residential and commercial buildings that used electricity needs to take care the power factor to avoid penalty from the utility companies. A power factor that is close to one provides a good indicator for the overall power quality. Therefore, power factor improvement plays a significant role to reduce electricity consumption and more efficient system operation. In this paper, the design of power factor meter using Internet of Things will be discussed. Voltage and current sensors outputs were interfaced to Arduino, in which the real power and apparent power were calculated to determine the power factor. Results showed the effectiveness of our proposed device in measuring power factor. Moreover, the measured data points were logged in an SD card and can be accessed by computer with Matlab graphical user interface (GUI). In addition, IoT framework analysis for smart meter which can provide power factor improvement, remote monitoring, and data logging was further discussed in this paper.

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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%

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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Power Factor Compensation Using Teaching Learning Based Optimization and Monitoring System by Cloud Data Logger

Cited by 38 publications

References 29 publications

Performance Optimization LoRa Network by Artificial Bee Colony Algorithm to Determination of the Load Profiles in Dwellings

Performance Optimization LoRa Network by Artificial Bee Colony Algorithm to Determination of the Load Profiles in Dwellings

Design of power factor meter using internet of things for power factor improvement, remote monitoring and data logging

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

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