Energy Pulse – the Efficient Solution for Monitoring Electricity Consumption from Decentralized Data Sets

Berciu, Alexandru G.; Jurj, Dacian I.; Czumbil, Levente; Micu, Dan D.; Dulf, Éva-Henrietta

doi:10.1109/mps52805.2021.9492626

Cited by 3 publications

(3 citation statements)

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“…Although progress has been made in this area, the method is an archaic solution that no longer meets today's requirements Considering the advantages and disadvantages of each technology, this paper will use the Wi-Fi protocol together with cloud data storage to monitor electricity consumption. A combined detection method using MAD, Moving MAD, and IQR methods will be used to detect and remove outliers [20]. The proposed method involves following a series of successive steps.…”

Section: Electricity Consumption Monitoring Methodsmentioning

confidence: 99%

“…These data were provided with the help of the BEMS TUCN computer application that saved the consumption recorded during the years from 2017-2022 every 15 min. In order to test the performance of the outlier detection and correction algorithms presented in [20], the consumption initially recorded by the BEMS TUCN application and the consumption obtained by using the Median Absolute Deviation, Moving Median Absolute Deviation, and Interquartile Range detection methods, together with the Piecewise Cubic Hermite Interpolating Polynomial method for the outlier data replacement, were plotted.…”

Section: The Efficiency Of the Clustering Methodsmentioning

confidence: 99%

“…It can be seen that, due to the communication errors of the remote electricity consumption data or due to reading errors, some outlier values influenced the clustering algorithm a lot. For this reason, it was imperative to use the detection and correction method [20].…”

Section: The Efficiency Of the Clustering Methodsmentioning

confidence: 99%

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Improving the Efficiency of Electricity Consumption by Applying Real-Time Fuzzy and Fractional Control

2022

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Using energy more efficiently is one of the easiest ways to save money, reduce greenhouse gas emissions, and meet growing energy demands. Electricity consumption control is an emergent topic worldwide. The passive house idea is not new, but it is still actual and is discussed by researchers. This paper brings to the reader’s attention the combined use of fuzzy and fractional control methods to increase the performance of electricity consumption control, taking into account the current challenges in the energy field, together with a method for the automatic definition of fuzzy rules. In comparison with the no-control case, a 20% reduction in consumption is achieved with the present proposal. In the case of another control method, a 15% reduction was possible using Shakeri’s team’s method. The simulation of the proposed passive house control proves that it could ensure efficient electricity consumption that can be translated into electricity cost savings between 10 and 50 percent.

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Section: Electricity Consumption Monitoring Methodsmentioning

confidence: 99%

Section: The Efficiency Of the Clustering Methodsmentioning

confidence: 99%