Relationship between electricity demand and temperature: methodology for load forecasting using weather numerical simulation

Authors

DOI:

https://doi.org/10.5902/2179460X55304

Keywords:

Temperature, Load, WRF

Abstract

This work aims to study the relationship between the demand for electricity and the temperature for the concession area of a given electricity distributor, in order to develop a representative load forecast method for this area. For this purpose, a weather numerical simulation is made using the regional meteorological model Weather Research and Forecasting (WRF) for the study area and, from that, the average temperature in the distributor's concession area is calculated, considering the number of consumers in each city that makes up that same area, called Average Temperature Weighted by the Number of Consumers (TMPNC). With this, a temperature index is obtained that effectively describes the influence of temperature on the load, since a greater weight is given to temperatures in cities where there are more consumers. Thus, it is observed that the relationship between the load and the TMPNC differs depending on the month, day of the week and time of day, due to different causes related to human activity, socioeconomic factors, weather conditions, etc. However, a load forecast method is developed based on a regression algorithm that uses the load and TMPNC data as input, returning regression functions that describe the load behavior as a function of the TMPNC. The forecasting method developed resulted in load estimates with an mean absolute percentage error of 1.8%.

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Author Biographies

Kauan Vargas Casarin, Universidade Federal de Santa Maria, Santa Maria, RS

Doutorando em Meteorologia, pelo Programa de Pós-Graduação em Meteorologia da Universidade Federal de Santa Maria (UFSM). Formação: Graduação em Meteorologia pela UFSM (2015) e Mestrado em Meteorologia pela UFSM (2018). Possui experiência em Meteorologia Sinótica, Meteorologia de Mesoescala, Modelagem Atmosférica e Previsão do Tempo, desenvolvendo pesquisas relacionadas à Sistemas Convectivos de Mesoescala e sobre aspectos meteorológicos relacionados a demanda de energia elétrica e previsão de carga.

Vagner Anabor, Universidade Federal de Santa Maria, Santa Maria, RS

Graduado em Meteorologia pela Universidade Federal de Pelotas (2001), Mestrado em Sensoriamento Remoto pela Universidade Federal do Rio Grande do Sul (2004) e Doutorado em Física pela Universidade Federal de Santa Maria (2008). Atualmente é professor nos cursos de Graduação e Pós-Graduação em Meteorologia da Universidade Federal de Santa Maria. Desenvolve pesquisas em Meteorologia Sinótica, Tempestades Severas, Modelagem Atmosférica Regional, Sensoriamento Remoto, Meteorologia de Mesoescala, Sistemas Convectivos de Mesoescala e o desenvolvimento de produtos para análise e previsão de Tempo.

Franciano Scremin Puhales, Universidade Federal de Santa Maria, Santa Maria, RS

Possui graduação em Física - Licenciatura Plena pela Universidade Federal de Santa Maria (2006), graduação em Física - Bacharelado pela Universidade Federal de Santa Maria (2010), graduação em Meteorologia - Bacharelado pela Universidade Federal de Santa Maria (2008), mestrado em Física pela Universidade Federal de Santa Maria (2008) e doutorado em Física pela Universidade Federal de Santa Maria (2011). Atualmente é docente do Departamento de Física da Universidade Federal de Santa Maria. Tem experiência na área de Física e Meteorologia, com ênfase em modelagem numérica: simulação dos grandes turbilhões (LES), modelagem em escala regional com WRF (Weather Research and Forecasting) e abordagem teórico-experimental em escoamentos turbulentos.

Everson Dal Piva, Universidade Federal de Santa Maria, Santa Maria, RS

Possui graduação em Meteorologia pela Universidade Federal de Pelotas (1999), mestrado (2001) e doutorado (2005) em Meteorologia pelo Instituto Nacional de Pesquisas Espaciais. Foi pesquisador-bolsista na Universidade Federal de Santa Maria e bolsista PCI no Centro Regional Sul (CRS/INPE) em Santa Maria. Atualmente e professor de nivel superior na Universidade Federal de Santa Maria. Tem experiência na área de Geociências, com ênfase em Meteorologia Sinótica e Dinâmica, atuando principalmente nos seguintes temas: ciclones extratropicais e tropicais, sistemas convectivos de mesoescala e formação de nevoeiros, com uso frequente de modelos regionais, em especial o BRAMS.

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Published

2020-09-25

How to Cite

Casarin, K. V., Anabor, V., Puhales, F. S., & Piva, E. D. (2020). Relationship between electricity demand and temperature: methodology for load forecasting using weather numerical simulation. Ciência E Natura, 42, e4. https://doi.org/10.5902/2179460X55304

Issue

Vol. 42 (2020): Special : II ENCONTRO DE METEOROLOGIA DO ESTADO DE SC

Section

Wind, Photovoltaic, Geothermal, Hydraulic, Other Energies

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