What is it about?
This paper presents a novel method to optimize energy utilization in smart buildings. Firstly, multiple transfer-retention ratio (TRR) parameters are added to the evaluation of distributed renewable energy. Secondly, the normal-boundary intersection (NBI) algorithm is improved by the adaptive weight sum, the adjust uniform axes method, and Mahalanobis distance to form the improved normal-boundary intersection (INBI) algorithm. The multi-objective optimization problem in smart buildings is solved by the parameter TRR and INBI algorithm to improve the regulation efficiency.
Featured Image
Photo by Alice Donovan Rouse on Unsplash
Why is it important?
In response to the needs of decision-makers with evaluation indicators, the average deviation is reduced by 60% compared with the previous case. Numerical examples show that the proposed method is superior to the existing technologies in terms of three optimization objectives. The objectives include 8.2% reduction in equipment costs, 7.6% reduction in power supply costs, and 1.6% improvement in occupants’ comfort.
Perspectives
With the widespread use of distributed energy sources, the advantages of smart buildings over traditional buildings are becoming increasingly obvious. Subsequently, its energy optimal scheduling and multi-objective optimization have become more and more complex and need to be solved urgently. This paper presents a novel method to optimize energy utilization in smart buildings.
Professor/PhD Supervisor/SMIEEE Yang Li
Northeast Electric Power University
Read the Original
This page is a summary of: Improved normal-boundary intersection algorithm: A method for energy optimization strategy in smart buildings, Building and Environment, January 2022, Elsevier,
DOI: 10.1016/j.buildenv.2022.108846.
You can read the full text:
Resources
Contributors
The following have contributed to this page
