Analysis of Variability in Electric Power Consumption: A Methodology for Setting Time-Differentiated Tariffs
The increasing concern for environmental conservation has spurred government initiatives towards energy efficiency. One of the key research areas in this regard is demand response, particularly focusing on differential pricing initiatives such as Time-of-Use (ToU). Differential tariffs are typically...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/17/4/842 |
| _version_ | 1797298355247775744 |
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| author | Javier E. Duarte Javier Rosero-Garcia Oscar Duarte |
| author_facet | Javier E. Duarte Javier Rosero-Garcia Oscar Duarte |
| author_sort | Javier E. Duarte |
| collection | DOAJ |
| description | The increasing concern for environmental conservation has spurred government initiatives towards energy efficiency. One of the key research areas in this regard is demand response, particularly focusing on differential pricing initiatives such as Time-of-Use (ToU). Differential tariffs are typically designed based on mathematical or statistical models analyzing historical electricity price and consumption data. This study proposes a methodology for identifying time intervals suitable for implementing ToU energy tariffs, achieved by analyzing electric power demand variability to estimate demand flexibility potential. The methodology transforms consumption data into variation via the coefficient of variation and, then, employs k-means data analysis techniques and the a priori algorithm. Tested with real data from smart meters in the Colombian electrical system, the methodology successfully identified time intervals with potential for establishing ToU tariffs. Additionally, no direct relationship was found between external variables such as socioeconomic level, user type, climate, and consumption variability. Finally, it was observed that user behavior concerning consumption variability could be categorized into two types of days: weekdays and non-working days. |
| first_indexed | 2024-03-07T22:34:38Z |
| format | Article |
| id | doaj.art-8a24f7640d4449cb9b349594501c5377 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-07T22:34:38Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-8a24f7640d4449cb9b349594501c53772024-02-23T15:15:13ZengMDPI AGEnergies1996-10732024-02-0117484210.3390/en17040842Analysis of Variability in Electric Power Consumption: A Methodology for Setting Time-Differentiated TariffsJavier E. Duarte0Javier Rosero-Garcia1Oscar Duarte2EM&D Research Group, Department of Electrical and Electronic Engineering, Faculty of Engineering, Universidad Nacional de Colombia, Bogotá 111321, ColombiaEM&D Research Group, Department of Electrical and Electronic Engineering, Faculty of Engineering, Universidad Nacional de Colombia, Bogotá 111321, ColombiaDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Universidad Nacional de Colombia, Bogotá 111321, ColombiaThe increasing concern for environmental conservation has spurred government initiatives towards energy efficiency. One of the key research areas in this regard is demand response, particularly focusing on differential pricing initiatives such as Time-of-Use (ToU). Differential tariffs are typically designed based on mathematical or statistical models analyzing historical electricity price and consumption data. This study proposes a methodology for identifying time intervals suitable for implementing ToU energy tariffs, achieved by analyzing electric power demand variability to estimate demand flexibility potential. The methodology transforms consumption data into variation via the coefficient of variation and, then, employs k-means data analysis techniques and the a priori algorithm. Tested with real data from smart meters in the Colombian electrical system, the methodology successfully identified time intervals with potential for establishing ToU tariffs. Additionally, no direct relationship was found between external variables such as socioeconomic level, user type, climate, and consumption variability. Finally, it was observed that user behavior concerning consumption variability could be categorized into two types of days: weekdays and non-working days.https://www.mdpi.com/1996-1073/17/4/842demand flexibilitydemand variabilityelectric powerdemand response (DR)data analysisdifferential tariff scheme |
| spellingShingle | Javier E. Duarte Javier Rosero-Garcia Oscar Duarte Analysis of Variability in Electric Power Consumption: A Methodology for Setting Time-Differentiated Tariffs Energies demand flexibility demand variability electric power demand response (DR) data analysis differential tariff scheme |
| title | Analysis of Variability in Electric Power Consumption: A Methodology for Setting Time-Differentiated Tariffs |
| title_full | Analysis of Variability in Electric Power Consumption: A Methodology for Setting Time-Differentiated Tariffs |
| title_fullStr | Analysis of Variability in Electric Power Consumption: A Methodology for Setting Time-Differentiated Tariffs |
| title_full_unstemmed | Analysis of Variability in Electric Power Consumption: A Methodology for Setting Time-Differentiated Tariffs |
| title_short | Analysis of Variability in Electric Power Consumption: A Methodology for Setting Time-Differentiated Tariffs |
| title_sort | analysis of variability in electric power consumption a methodology for setting time differentiated tariffs |
| topic | demand flexibility demand variability electric power demand response (DR) data analysis differential tariff scheme |
| url | https://www.mdpi.com/1996-1073/17/4/842 |
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