Short Term Load Forecasting in Smart Grids: Case Study of the City of Évora

Svetlana Roudolfovna Chemetova; Paulo Santos; Mário Ventim-Neves

doi:10.20897/jisem.201718

Short Term Load Forecasting in Smart Grids: Case Study of the City of Évora

Svetlana Roudolfovna Chemetova ¹ ^* , Paulo Santos ¹, Mário Ventim-Neves ²

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¹ Instituto Politécnico de Setúbal, PORTUGAL
² Universidade Nova de Lisboa, PORTUGAL
^* Corresponding Author

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Research Article

Journal of Information Systems Engineering and Management, 2017 - Volume 2 Issue 3, Article No: 18
https://doi.org/10.20897/jisem.201718

Published Online: 02 Aug 2017

Views: 2976 | Downloads: 2021

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How to cite this article

APA 6th edition

In-text citation: (Chemetova et al., 2017)
Reference: Chemetova, S. R., Santos, P., & Ventim-Neves, M. (2017). Short Term Load Forecasting in Smart Grids: Case Study of the City of Évora. Journal of Information Systems Engineering and Management, 2(3), 18. https://doi.org/10.20897/jisem.201718

Vancouver

In-text citation: (1), (2), (3), etc.
Reference: Chemetova SR, Santos P, Ventim-Neves M. Short Term Load Forecasting in Smart Grids: Case Study of the City of Évora. J INFORM SYSTEMS ENG. 2017;2(3):18. https://doi.org/10.20897/jisem.201718

AMA 10th edition

In-text citation: (1), (2), (3), etc.
Reference: Chemetova SR, Santos P, Ventim-Neves M. Short Term Load Forecasting in Smart Grids: Case Study of the City of Évora. J INFORM SYSTEMS ENG. 2017;2(3), 18. https://doi.org/10.20897/jisem.201718

Chicago

In-text citation: (Chemetova et al., 2017)
Reference: Chemetova, Svetlana Roudolfovna, Paulo Santos, and Mário Ventim-Neves. "Short Term Load Forecasting in Smart Grids: Case Study of the City of Évora". Journal of Information Systems Engineering and Management 2017 2 no. 3 (2017): 18. https://doi.org/10.20897/jisem.201718

Harvard

In-text citation: (Chemetova et al., 2017)
Reference: Chemetova, S. R., Santos, P., and Ventim-Neves, M. (2017). Short Term Load Forecasting in Smart Grids: Case Study of the City of Évora. Journal of Information Systems Engineering and Management, 2(3), 18. https://doi.org/10.20897/jisem.201718

MLA

In-text citation: (Chemetova et al., 2017)
Reference: Chemetova, Svetlana Roudolfovna et al. "Short Term Load Forecasting in Smart Grids: Case Study of the City of Évora". Journal of Information Systems Engineering and Management, vol. 2, no. 3, 2017, 18. https://doi.org/10.20897/jisem.201718

ABSTRACT

Currently, load forecasting is a fundamental task for planning, operation and exploration of the electric power systems. The importance of forecasting has become more evident with the restructuring of the national energy sector, thus, promoting projects linked to smart grids, namely in Portugal - InovGrid. This study proposes the computational forecast model of the load diagram based on the Levenberg-Marquardt algorithm of Artificial Neural Networks. The used data are the time series of active power, recorded by EDP Distribution Telemetry System, and the climatic time series of the Portuguese Institute of the Sea and Atmosphere, collected on the city of Évora. The forecast horizon is short term: from one hour to a week. The results showed that main statistical error parameter (mean absolute percentage error) was not exceed 5%.

KEYWORDS

load forecasting smart-grids substations artificial neural networks time series

REFERENCES

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.