Load Shifting as a Demand Side Management Technique

The continuous growth of the global population, achieves a domino effect that includes among others, technological evolution, climate change, overexploitation of resources, loss of biodiversity but also increased production, storage and consumption of energy. This paper focuses on developing new algorithms to streamline energy consumption (reduction of the energy consumed during peak hours and during the rest of the day, as well as cost reduction) in one of the largest sources of greenhouse gas emissions, the building sector. A brief display of general methods that are available to both consumers and distribution network operators, with the highlight on the demand side management model and its techniques was made. Mathematical functions were developed having as base information on the areas of interest as well as on the day-ahead load shifting technique. Based on the results of the simulations of the formulated functions and the comparative analysis performed with the results obtained by other techniques, the superior performance of these functions can be noted.

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Publication Details

Published
2024-10-17
DOI
https://doi.org/10.1109/epei63510.2024.10758065
Citations
1
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.35
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Load Shifting as a Demand Side Management Technique

Mihai Gavrilaș, Mihaela Nastase
1 citations
Scheduling and Optimization Algorithms
0.35
article

Load Shifting as a Demand Side Management Technique

Mihai Gavrilaș, Mihaela Nastase
article en
1 citations

Abstract

The continuous growth of the global population, achieves a domino effect that includes among others, technological evolution, climate change, overexploitation of resources, loss of biodiversity but also increased production, storage and consumption of energy. This paper focuses on developing new algorithms to streamline energy consumption (reduction of the energy consumed during peak hours and during the rest of the day, as well as cost reduction) in one of the largest sources of greenhouse gas emissions, the building sector. A brief display of general methods that are available to both consumers and distribution network operators, with the highlight on the demand side management model and its techniques was made. Mathematical functions were developed having as base information on the areas of interest as well as on the day-ahead load shifting technique. Based on the results of the simulations of the formulated functions and the comparative analysis performed with the results obtained by other techniques, the superior performance of these functions can be noted.

Gheorghe Asachi Technical University of Iași (RO)
Openalex Percentile: Top 33%
Scheduling and Optimization Algorithms
0.35
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