A novel transactive integration system for solar renewable energy into smart homes and landscape design: A digital twin simulation case study

The use of solar renewable energy in landscape design is becoming increasingly popular as the world strives to reduce its reliance on fossil fuels. With the cost of solar energy falling, more and more people are turning to solar as a way to power their homes and businesses. In this article, we will...

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Published in:Solar Energy
Main Author: Nie X.; Mohamad Daud W.S.A.W.; Pu J.
Format: Article
Language:English
Published: Elsevier Ltd 2023
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165572336&doi=10.1016%2fj.solener.2023.111871&partnerID=40&md5=94daa2dc2b161bcb72e470808db5d2b1
id 2-s2.0-85165572336
spelling 2-s2.0-85165572336
Nie X.; Mohamad Daud W.S.A.W.; Pu J.
A novel transactive integration system for solar renewable energy into smart homes and landscape design: A digital twin simulation case study
2023
Solar Energy
262

10.1016/j.solener.2023.111871
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165572336&doi=10.1016%2fj.solener.2023.111871&partnerID=40&md5=94daa2dc2b161bcb72e470808db5d2b1
The use of solar renewable energy in landscape design is becoming increasingly popular as the world strives to reduce its reliance on fossil fuels. With the cost of solar energy falling, more and more people are turning to solar as a way to power their homes and businesses. In this article, we will explore the integration of solar renewable energy into landscape design through a case study. Using local photovoltaics along with suitable power storage systems, a household power management system is proposed to optimize the scheduling of demand-responsive appliances. The beta likelihood distribution function for sun irradiance is used to model the unpredictable behavior of photovoltaic energy production in residential power management systems. The PV system was integrated into the building's existing landscape design by incorporating the system's components into the existing landscape elements. This included the installation of a large solar array on the roof of the building, as well as the integration of solar panels into the existing garden beds and pathways. The solar array was also connected to the building's existing electrical system, allowing the building to draw power from the solar array when needed. Among the major contributions of the study would be to optimize the planning of demand-responsive devices within a domestic power management system by using the improved leader particle swarm optimization method (ILPSO). The purpose would be to reduce peak-to-average ratios (PARs) and energy usage costs in the smart home. A number of scenarios are designed and simulated in a digital twin structure for a household user with various initial loads, uninterruptible deferrable, and interruptible deferrable devices using a real-time power cost program to demonstrate the performance of the suggested optimization method. Based on comparisons with various metaheuristics previously documented, the new ILPSO algorithm efficiently optimizes energy usage costs and PARs. © 2023 International Solar Energy Society
Elsevier Ltd
0038092X
English
Article

author Nie X.; Mohamad Daud W.S.A.W.; Pu J.
spellingShingle Nie X.; Mohamad Daud W.S.A.W.; Pu J.
A novel transactive integration system for solar renewable energy into smart homes and landscape design: A digital twin simulation case study
author_facet Nie X.; Mohamad Daud W.S.A.W.; Pu J.
author_sort Nie X.; Mohamad Daud W.S.A.W.; Pu J.
title A novel transactive integration system for solar renewable energy into smart homes and landscape design: A digital twin simulation case study
title_short A novel transactive integration system for solar renewable energy into smart homes and landscape design: A digital twin simulation case study
title_full A novel transactive integration system for solar renewable energy into smart homes and landscape design: A digital twin simulation case study
title_fullStr A novel transactive integration system for solar renewable energy into smart homes and landscape design: A digital twin simulation case study
title_full_unstemmed A novel transactive integration system for solar renewable energy into smart homes and landscape design: A digital twin simulation case study
title_sort A novel transactive integration system for solar renewable energy into smart homes and landscape design: A digital twin simulation case study
publishDate 2023
container_title Solar Energy
container_volume 262
container_issue
doi_str_mv 10.1016/j.solener.2023.111871
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165572336&doi=10.1016%2fj.solener.2023.111871&partnerID=40&md5=94daa2dc2b161bcb72e470808db5d2b1
description The use of solar renewable energy in landscape design is becoming increasingly popular as the world strives to reduce its reliance on fossil fuels. With the cost of solar energy falling, more and more people are turning to solar as a way to power their homes and businesses. In this article, we will explore the integration of solar renewable energy into landscape design through a case study. Using local photovoltaics along with suitable power storage systems, a household power management system is proposed to optimize the scheduling of demand-responsive appliances. The beta likelihood distribution function for sun irradiance is used to model the unpredictable behavior of photovoltaic energy production in residential power management systems. The PV system was integrated into the building's existing landscape design by incorporating the system's components into the existing landscape elements. This included the installation of a large solar array on the roof of the building, as well as the integration of solar panels into the existing garden beds and pathways. The solar array was also connected to the building's existing electrical system, allowing the building to draw power from the solar array when needed. Among the major contributions of the study would be to optimize the planning of demand-responsive devices within a domestic power management system by using the improved leader particle swarm optimization method (ILPSO). The purpose would be to reduce peak-to-average ratios (PARs) and energy usage costs in the smart home. A number of scenarios are designed and simulated in a digital twin structure for a household user with various initial loads, uninterruptible deferrable, and interruptible deferrable devices using a real-time power cost program to demonstrate the performance of the suggested optimization method. Based on comparisons with various metaheuristics previously documented, the new ILPSO algorithm efficiently optimizes energy usage costs and PARs. © 2023 International Solar Energy Society
publisher Elsevier Ltd
issn 0038092X
language English
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