AI-based Building Management and Information System with Multi-agent Topology for an Energy-efficient Building: Towards Occupants Comfort

Abstract

Most of the electrical energy consumption occurs in residential buildings in maintaining the desired comfort level for occupants. Since comfort level and energy consumption are conflicting in nature, there is a need for energy-efficient building management and information system. In this article, Artificial Intelligence (AI) based building management and information system with multi-agent topology for the energy-efficient building is proposed. The multi-agent topology building management and information system are based on minimizing the energy consumption and maximizing the level of comfort by reducing the error between the actual parameters of the environment and the desired environmental parameters. Firstly, the constrained nonlinear optimization algorithm is applied in the first optimization, and secondly the optimization using artificial intelligence incorporating deep learning concept training and validation to obtain a set of optimized solutions. These solutions comprise values of temperature, illumination level, and concentration of CO₂ for maximum comfort level in terms of thermal, visual and air quality and minimum energy consumption at the same time. The developed system is energy efficient and maintains a high comfort level for occupants.

KEYWORDS:

• Artificial intelligence
• Energy-efficient buildings
• Energy management
• Multi-agent system
• Optimization
• Occupant’s comfort

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Department of Science and Technology (DST), Ministry of Science and Technology [Grant Number: TMD/CERI/BEE/2016/081].

Notes on contributors

Anurag Verma

Anurag Verma received the bachelor’s degree in electrical & electronics with honours from the IMS Engineering College, Ghaziabad affiliated to UPTU, Lucknow, India, in 2015, and the ME degree in electrical engineering (Power Electronics & Drives) from Thapar University, Patiala-Punjab, India in 2017. He is currently pursuing the PhD degree with the Council of Scientific and Industrial Research- Central Building Research Institute (CSIR-CBRI), Roorkee, and Thapar Institute of Engineering & Technology, Patiala-Punjab, India. His research interests include energy management systems, smart homes, prediction techniques, and optimization. E-mail: [email protected]

Surya Prakash

Surya Prakash received his Bachelor of Engineering degree from the Institution of Engineers (India) in 2003. He obtained his MTech in electrical engineering (Power Systems) from KNIT, Sultanpur, India, in 2009, and PhD in electrical engineering (Power Systems) from SHIATS-DU (formerly AAI-DU, Allahabad, India) in 2014. Presently, he is working as an associate professor in the Department of Electrical & Instrumentation Engineering, Thapar University, Patiala. His field of interest includes power system operation & control, artificial intelligent control, and distributed generation. Email: [email protected]

Anuj Kumar

Anuj Kumar received the MPhil degree in instrumentation from the Indian Institute of Technology Roorkee, India, in 2000, the MTech degree in instrumentation from the National Institute of Technology Kurukshetra, India, in 2004, and the PhD degree in embedded systems from the Indian Institute of Technology Delhi, India, in 2011. He was a post-doctoral fellow with the University of Seoul, Seoul, South Korea, the University of Pretoria, RSA, and the National University of Singapore, Singapore, from 2011 to 2015. He joined the Department of Energy Efficiency, CSIR-Central Building Research Institute at Roorkee, in 2016, as a Ramanujan Fellow and an assistant professor (CSIR Faculty). He has authored/co-authored over 75 research publications in different international journals, conferences, and book chapters. He has also filed 1 national copyrights, 1 international, and 5 national patents. He is currently an associate editor of IEEE Access. His research interests include sensing applications, wireless sensor-actuator networks, and IOT.