A Comparative Analysis of Data-Driven Based Optimization Models for Energy-Efficient Buildings

Abstract

Energy-efficient and sustainable buildings have become a specialized research theme for energy planning and the green building industry. Rapidly increased energy consumption in the residential area has attracted researchers' attention to minimize energy consumption without affecting occupant comfort. Accordingly, an effective energy management system is required for energy-efficient buildings to utilize energy resources efficiently and maintain desired comfort. In this paper, data-driven based optimization models are compared to maximize the comfort index and minimize energy consumption simultaneously. Heating-cooling systems are used to maintain indoor thermal comfort, which consumes energy according to the environmental temperature and indoor temperature difference. Therefore, the environmental temperature parameter is optimized using optimization techniques Genetic Algorithm (GA), Bat, Neural Network Algorithm (NNA), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). The main objective of the optimization is to reduce the gap/error between the temperature specified by the user and the environmental temperature. Afterward, the discrepancy between optimized temperature and actual temperature is fed to the designed ML (Machine Learning) based controller. The controller's output is further provided to coordinator agents, which give the power to the actuators accordingly. The linearity of the proposed model improves the performance of the ML algorithm. The obtained dataset from fuzzy temperature controller has been used to design an ML controller. The experimental results show that the designed system significantly improves energy efficiency and occupant comfort for energy-efficient buildings. The BAT model has shown effectiveness in achieving a high comfort index with minimum power consumption compared to other considered models.

KEYWORDS:

• Energy consumption
• Energy efficient buildings
• Global optimization
• Indoor environmental quality
• Thermal comfort

Additional information

Funding

This work was supported by 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 his 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 a PhD degree with the Council of Scientific and Industrial Research (CSIR), Central Building Research Institute (CBRI), Roorkee, and Thapar Institute of Engineering & Technology, Patiala-Punjab, India. His research interests include the internet of things, energy management systems, smart homes, smart buildings, prediction techniques, and optimization.

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 System) from KNIT, Sultanpur, India, in 2009, and PhD in electrical engineering (Power System) 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 copy rights, 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 internet of things.