Optimized Demand Side Management for Refrigeration: Modeling and Case Study Insights from Kenya
According to the International Institute of Refrigeration (IIR), 20% of worldwide electricity consumption is for refrigeration, with domestic refrigeration appliances comprising a fifth of this demand. As the uptake of renewable energy sources for on-grid and isolated electricity supply increases, t...
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MDPI AG
2025-06-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/13/3258 |
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| author | Josephine Nakato Kakande Godiana Hagile Philipo Stefan Krauter |
| author_facet | Josephine Nakato Kakande Godiana Hagile Philipo Stefan Krauter |
| author_sort | Josephine Nakato Kakande |
| collection | DOAJ |
| description | According to the International Institute of Refrigeration (IIR), 20% of worldwide electricity consumption is for refrigeration, with domestic refrigeration appliances comprising a fifth of this demand. As the uptake of renewable energy sources for on-grid and isolated electricity supply increases, the need for mechanisms to match demand and supply better and increase power system flexibility has led to enhanced attention on demand-side management (DSM) practices to boost technology, infrastructure, and market efficiencies. Refrigeration requirements will continue to rise with development and climate change. In this work, particle swarm optimization (PSO) is used to evaluate energy saving and load factor improvement possibilities for refrigeration devices at a site in Kenya, using a combination of DSM load shifting and strategic conservation, and based on appliance temperature evolution measurements. Refrigeration energy savings of up to 18% are obtained, and the load factor is reduced. Modeling is done for a hybrid system with grid, solar PV, and battery, showing a marginal increase in solar energy supply to the load relative to the no DSM case, while the grid portion of the load supply reduces by almost 25% for DSM relative to No DSM. |
| format | Article |
| id | doaj-art-efb2391663c34569b08caa5da8162fa5 |
| institution | DOAJ |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-efb2391663c34569b08caa5da8162fa52025-08-20T03:16:42ZengMDPI AGEnergies1996-10732025-06-011813325810.3390/en18133258Optimized Demand Side Management for Refrigeration: Modeling and Case Study Insights from KenyaJosephine Nakato Kakande0Godiana Hagile Philipo1Stefan Krauter2Chair of Electrical Energy Technology—Sustainable Energy Concepts (EET-NEK), Faculty of Computer Science, Electrical Engineering and Mathematics, Paderborn University, Pohlweg 55, 33098 Paderborn, GermanyChair of Electrical Energy Technology—Sustainable Energy Concepts (EET-NEK), Faculty of Computer Science, Electrical Engineering and Mathematics, Paderborn University, Pohlweg 55, 33098 Paderborn, GermanyChair of Electrical Energy Technology—Sustainable Energy Concepts (EET-NEK), Faculty of Computer Science, Electrical Engineering and Mathematics, Paderborn University, Pohlweg 55, 33098 Paderborn, GermanyAccording to the International Institute of Refrigeration (IIR), 20% of worldwide electricity consumption is for refrigeration, with domestic refrigeration appliances comprising a fifth of this demand. As the uptake of renewable energy sources for on-grid and isolated electricity supply increases, the need for mechanisms to match demand and supply better and increase power system flexibility has led to enhanced attention on demand-side management (DSM) practices to boost technology, infrastructure, and market efficiencies. Refrigeration requirements will continue to rise with development and climate change. In this work, particle swarm optimization (PSO) is used to evaluate energy saving and load factor improvement possibilities for refrigeration devices at a site in Kenya, using a combination of DSM load shifting and strategic conservation, and based on appliance temperature evolution measurements. Refrigeration energy savings of up to 18% are obtained, and the load factor is reduced. Modeling is done for a hybrid system with grid, solar PV, and battery, showing a marginal increase in solar energy supply to the load relative to the no DSM case, while the grid portion of the load supply reduces by almost 25% for DSM relative to No DSM.https://www.mdpi.com/1996-1073/18/13/3258refrigerationdemand-side managementPSOsolarbatterygrid |
| spellingShingle | Josephine Nakato Kakande Godiana Hagile Philipo Stefan Krauter Optimized Demand Side Management for Refrigeration: Modeling and Case Study Insights from Kenya Energies refrigeration demand-side management PSO solar battery grid |
| title | Optimized Demand Side Management for Refrigeration: Modeling and Case Study Insights from Kenya |
| title_full | Optimized Demand Side Management for Refrigeration: Modeling and Case Study Insights from Kenya |
| title_fullStr | Optimized Demand Side Management for Refrigeration: Modeling and Case Study Insights from Kenya |
| title_full_unstemmed | Optimized Demand Side Management for Refrigeration: Modeling and Case Study Insights from Kenya |
| title_short | Optimized Demand Side Management for Refrigeration: Modeling and Case Study Insights from Kenya |
| title_sort | optimized demand side management for refrigeration modeling and case study insights from kenya |
| topic | refrigeration demand-side management PSO solar battery grid |
| url | https://www.mdpi.com/1996-1073/18/13/3258 |
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