An intelligent shell game optimization based energy consumption analytics model for smart metering data
Smart metering is a hot research topic and has gained significant attention since the electromechanical metering is not reliable and requires more energy and time. All the existing methods are focused only on how to deal with data rather than how to do efficiently. Prediction of electricity consumpt...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University)
2023-04-01
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| Series: | Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki |
| Subjects: | |
| Online Access: | https://ntv.ifmo.ru/file/article/21914.pdf |
| _version_ | 1797845379685810176 |
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| author | Ramalingam Saravanan Arulnanthisivam Swaminathan Sankaralingam Balaji |
| author_facet | Ramalingam Saravanan Arulnanthisivam Swaminathan Sankaralingam Balaji |
| author_sort | Ramalingam Saravanan |
| collection | DOAJ |
| description | Smart metering is a hot research topic and has gained significant attention since the electromechanical metering is not reliable and requires more energy and time. All the existing methods are focused only on how to deal with data rather than how to do efficiently. Prediction of electricity consumption is essential to gain intelligence to the smart gird.
Precise electricity prediction allows a service provided in resource planning and also controlling actions for the demand and supply balancing. The users are beneficial from the smart metering solution by effective interpretation of their energy utilization, and labelling them to efficiently handle the utilization cost. With this motivation, the paper presents intelligent energy consumption analytics using smart metering data (ECA-SMD) model to determine the utilization of energy. The presented ECA-SMD model involves three major processes namely data pre-processing, feature extraction, classification, and parameter optimization. The presented ECA-SMD model uses Extreme Learning Machine (ELM) based classification to determine the optimum class labels. Besides, shell game optimization (SGO) algorithm is applied for tuning the parameters involved in the ELM and boosts the classification efficiency. The efficacy of the ECA-SMD model is validated using an extensive set of smart metering data and the results are investigated based on accuracy and mean square error (MSE). The proposed model exhibited supremacy with the maximum accuracy of 65.917 % and minimum MSE of 0.096. |
| first_indexed | 2024-04-09T17:38:05Z |
| format | Article |
| id | doaj.art-09b079373d724315aa780cc83bcf9e15 |
| institution | Directory Open Access Journal |
| issn | 2226-1494 2500-0373 |
| language | English |
| last_indexed | 2024-04-09T17:38:05Z |
| publishDate | 2023-04-01 |
| publisher | Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University) |
| record_format | Article |
| series | Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki |
| spelling | doaj.art-09b079373d724315aa780cc83bcf9e152023-04-17T10:01:34ZengSaint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University)Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki2226-14942500-03732023-04-0123237438110.17586/2226-1494-2023-23-2-374-381An intelligent shell game optimization based energy consumption analytics model for smart metering dataRamalingam Saravanan0https://orcid.org/0000-0003-3503-1133Arulnanthisivam Swaminathan1https://orcid.org/0000-0001-7672-1339Sankaralingam Balaji2https://orcid.org/0000-0002-9013-9801PhD, Associate Professor, Sri Manakula Vinayagar Engineering College, Puducherry, 605107, India, sc 57211236494PhD, Associate Professor, Panimalar Engineering College, Chennai, 600123, India, sc 55624126400PhD, Associate Professor, Sri Manakula Vinayagar Engineering College, Puducherry, 605107, India, sc 55310821000Smart metering is a hot research topic and has gained significant attention since the electromechanical metering is not reliable and requires more energy and time. All the existing methods are focused only on how to deal with data rather than how to do efficiently. Prediction of electricity consumption is essential to gain intelligence to the smart gird. Precise electricity prediction allows a service provided in resource planning and also controlling actions for the demand and supply balancing. The users are beneficial from the smart metering solution by effective interpretation of their energy utilization, and labelling them to efficiently handle the utilization cost. With this motivation, the paper presents intelligent energy consumption analytics using smart metering data (ECA-SMD) model to determine the utilization of energy. The presented ECA-SMD model involves three major processes namely data pre-processing, feature extraction, classification, and parameter optimization. The presented ECA-SMD model uses Extreme Learning Machine (ELM) based classification to determine the optimum class labels. Besides, shell game optimization (SGO) algorithm is applied for tuning the parameters involved in the ELM and boosts the classification efficiency. The efficacy of the ECA-SMD model is validated using an extensive set of smart metering data and the results are investigated based on accuracy and mean square error (MSE). The proposed model exhibited supremacy with the maximum accuracy of 65.917 % and minimum MSE of 0.096.https://ntv.ifmo.ru/file/article/21914.pdfelectricity consumptionpredictive modeldata analyticssmart meteringmachine learning |
| spellingShingle | Ramalingam Saravanan Arulnanthisivam Swaminathan Sankaralingam Balaji An intelligent shell game optimization based energy consumption analytics model for smart metering data Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki electricity consumption predictive model data analytics smart metering machine learning |
| title | An intelligent shell game optimization based energy consumption analytics model for smart metering data |
| title_full | An intelligent shell game optimization based energy consumption analytics model for smart metering data |
| title_fullStr | An intelligent shell game optimization based energy consumption analytics model for smart metering data |
| title_full_unstemmed | An intelligent shell game optimization based energy consumption analytics model for smart metering data |
| title_short | An intelligent shell game optimization based energy consumption analytics model for smart metering data |
| title_sort | intelligent shell game optimization based energy consumption analytics model for smart metering data |
| topic | electricity consumption predictive model data analytics smart metering machine learning |
| url | https://ntv.ifmo.ru/file/article/21914.pdf |
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