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...

詳細記述

書誌詳細
出版年:Energies
主要な著者: Josephine Nakato Kakande, Godiana Hagile Philipo, Stefan Krauter
フォーマット: 論文
言語:英語
出版事項: MDPI AG 2025-06-01
主題:
オンライン・アクセス:https://www.mdpi.com/1996-1073/18/13/3258
_version_ 1849472860475621376
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
container_title Energies
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 Directory of Open Access Journals
issn 1996-1073
language English
publishDate 2025-06-01
publisher MDPI AG
record_format Article
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
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
work_keys_str_mv AT josephinenakatokakande optimizeddemandsidemanagementforrefrigerationmodelingandcasestudyinsightsfromkenya
AT godianahagilephilipo optimizeddemandsidemanagementforrefrigerationmodelingandcasestudyinsightsfromkenya
AT stefankrauter optimizeddemandsidemanagementforrefrigerationmodelingandcasestudyinsightsfromkenya