Fuzzy-Logic-Based Cascaded Decentralized Control and Power Quantification of Residential Buildings for Effective Energy Load Management

In large buildings, effective load shedding and shifting and providing the maximum power through solar renewable sources remain challenges because of users’ unpredictable load consumption. Conventionally, load shifting, load shedding, and load covering are majorly dependent on user inputs. The lack of user interest in participating in demand responses for effective load shifting and covering remains a problem. Effective load covering through renewables and user-friendly load shedding and shifting with maximized user participation are challenging and demand high-resolution user load consumption information, which are not possible without sophisticated communication and digital twins. In this research work, a novel fuzzy-logic-based cascaded decentralized load-controlling mechanism has been developed that manages the residential building load through load-shifting, load-covering, and load-shedding schemes without any communication protocols and digitization between residential units. The decentralized controller aims to effectively utilize the centralized resources of power generation with the effective automated participation of users. The quantification of the load shifting, covering, and shedding performed during peak hours was well covered under the load-covering scheme, and the results showed that flexibility capacities of 1617 kW were achieved for load covering, 294 kW for load shedding, and 166.34 kW through shifting. A total load of 60 kW, which was reduced during shedding and shifting, was well covered during load covering through renewables.

Authors

Institutions

Publication Details

Journal
Buildings
Published
2024-09-13
DOI
https://doi.org/10.3390/buildings14092896
Citations
4
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
1.06

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fuzzy-Logic-Based Cascaded Decentralized Control and Power Quantification of Residential Buildings for Effective Energy Load Management

Jun-Tae Kim, Fawad Azeem, Zulfiqar Ali Memon, Naeem Shahzad et al.
4 citations
Buildings
Building Energy and Comfort Optimization
1.06
article

Fuzzy-Logic-Based Cascaded Decentralized Control and Power Quantification of Residential Buildings for Effective Energy Load Management

Jun-Tae Kim, Fawad Azeem, Zulfiqar Ali Memon, Naeem Shahzad, Muzzamal Hussain, Muhammad Hanzala
article en
4 citations

Abstract

In large buildings, effective load shedding and shifting and providing the maximum power through solar renewable sources remain challenges because of users’ unpredictable load consumption. Conventionally, load shifting, load shedding, and load covering are majorly dependent on user inputs. The lack of user interest in participating in demand responses for effective load shifting and covering remains a problem. Effective load covering through renewables and user-friendly load shedding and shifting with maximized user participation are challenging and demand high-resolution user load consumption information, which are not possible without sophisticated communication and digital twins. In this research work, a novel fuzzy-logic-based cascaded decentralized load-controlling mechanism has been developed that manages the residential building load through load-shifting, load-covering, and load-shedding schemes without any communication protocols and digitization between residential units. The decentralized controller aims to effectively utilize the centralized resources of power generation with the effective automated participation of users. The quantification of the load shifting, covering, and shedding performed during peak hours was well covered under the load-covering scheme, and the results showed that flexibility capacities of 1617 kW were achieved for load covering, 294 kW for load shedding, and 166.34 kW through shifting. A total load of 60 kW, which was reduced during shedding and shifting, was well covered during load covering through renewables.

BuildingsVol. 14(9)
COMSATS University Islamabad (PK), Kangwon National University (KR), Ajman University (AE), Kongju National University (KR)
Kongju National University, Ministry of Trade, Industry and Energy, Ajman University, Korea Institute of Energy Technology Evaluation and Planning
Openalex Percentile: Top 24%
Building Energy and Comfort Optimization
1.06
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.