Forecasting Electrical Energy Consumptions

Electrical energy management of an organization is related to the appropriate planning of required payments and allocation of resources accordingly. It is important for good management to account for past costs and to forecast future costs. An intelligent solution for the mathematical formalization of this process is presented in the study. The research object is the Wildlife Rehabilitation and Breeding Centre “Green Balkans” in Bulgaria, in which the correct allocation of resources is significant due to the minimal financial support. Mathematical models have been developed for forecasting electricity consumption based on data for the past three-year period. The applied methodology is based on linear regression analysis. Two mathematical models were synthesized, which were compared and analyzed depending on the length of the historical data interval. The models represent an intelligent solution for the Centre’s electrical energy management.

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Publication Details

Journal
WSEAS TRANSACTIONS ON POWER SYSTEMS
Published
2024-11-07
DOI
https://doi.org/10.37394/232016.2024.19.34
Primary Topic
Energy Load and Power Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

Forecasting Electrical Energy Consumptions

Krasimira Stoilova, Todor Stoilov, Rusko Petrov, G. Angelova et al.
WSEAS TRANSACTIONS ON POWER SYSTEMS
Energy Load and Power Forecasting
article

Forecasting Electrical Energy Consumptions

Krasimira Stoilova, Todor Stoilov, Rusko Petrov, G. Angelova, Ivailo Klisurov
article en

Abstract

Electrical energy management of an organization is related to the appropriate planning of required payments and allocation of resources accordingly. It is important for good management to account for past costs and to forecast future costs. An intelligent solution for the mathematical formalization of this process is presented in the study. The research object is the Wildlife Rehabilitation and Breeding Centre “Green Balkans” in Bulgaria, in which the correct allocation of resources is significant due to the minimal financial support. Mathematical models have been developed for forecasting electricity consumption based on data for the past three-year period. The applied methodology is based on linear regression analysis. Two mathematical models were synthesized, which were compared and analyzed depending on the length of the historical data interval. The models represent an intelligent solution for the Centre’s electrical energy management.

WSEAS TRANSACTIONS ON POWER SYSTEMSVol. 19
Bulgarian Academy of Sciences (BG), Institute of Information and Communication Technologies (BG)
Affordable and clean energy
Openalex Percentile: Top 82%
Energy Load and Power Forecasting
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