Unified Framework for Energy Monitoring and Demand Based Optimization for Commercial Buildings – IoT based Enterprise Implementation and Beyond
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2017 by IJETT Journal|
|Year of Publication : 2017|
|Authors : Jayakumar Vk, Kasi Viswanathan U, Ch Avinash, R Kiruthiga
|DOI : 10.14445/22315381/IJETT-V44P220|
Jayakumar Vk, Kasi Viswanathan U, Ch Avinash, R Kiruthiga "Unified Framework for Energy Monitoring and Demand Based Optimization for Commercial Buildings – IoT based Enterprise Implementation and Beyond", International Journal of Engineering Trends and Technology (IJETT), V44(2),98-101 February 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
The importance of efficient and optimal use of energy is continually on the rise. With depreciating natural resources and increasing demand for energy, it has become imperative for corporate buildings to monitor and optimize the energy usage. The effective operation of commercial buildings is practically difficult as the conditions change in dynamic manner. In the current communication, different assets that contribute to energy bills are analyzed. The assets include Chillers, Air Handling Unit (AHU), Uninterrupted Power Supply (UPS) and Lighting which are the chief contributors to energy bills. Algorithms for demand based optimization of the assets were developed. Time series analysis was used for forecasting the demand on the assets. Occupancy pattern and head count were considered as demand for the assets. Four slots were considered for demand forecasting which include weekday, weekend, and days before and after holidays, holidays before and after weekend. With hour on hour forecasting for the demand, scheduling recommendations for chillers were provided .Based on peak load consumption, rightsizing of UPS and potential energy savings recommendations to minimize the loss were provided. Similarly, health index model for AHU was developed which identifies the wastage for AHU in the building. Based on occupancy forecasting AHU can be made to switch on/off. The same model was used to identify the wastage for lighting. Based on occupancy forecasting pre-determined switch on/off of appliances was scheduled in a semi-automatic manner. The unified generic framework algorithms were developed using Python 2.7. Deployment and testing were performed for close to 60 buildings and the results for energy savings were found to be satisfactory
 European Commission Directorate General for Energy and Transport. European energy and transport trends to 2030. Brussels, 2003
 Zaheer-Uddin M. Optimal, sub-optimal and adaptive control methods for the design of temperature controllers for intelligent buildings. Building and Environment 1993;28(3):311–22..
 Zaheer-Uddin M. Intelligent control strategies for HVAC processes in buildings. Energy 1994;19(1):67–79..
 Kolokotsa D, Kalaitzakis K, Antonidakis E, Stavrakakis GS. Interconnecting smart card system with PLC controller in a local operating network to form a distributed energy management and control system for buildings. Energy Conversion and Management 2002;43:119–34.
 Yao Y, Lian Z, Hou Z, Zhou X. Optimal operation of a large cooling system based on an empirical model. Applied Thermal Energy 2004;24:2303–21..
 Al-Rabghi OM, Akyurt MM. A survey of energy efficient strategies for effective air conditioning. Energy Conversion and Management 2004;45:1643–54.
 Mathews EH, Arndt DC, Piani CB, Heerden E. Developing cost efficient control strategies to ensure optimal energy use and sufficient indoor comfort. Applied Energy 2000;66:135–59.
 Smart Gateway Reference Architecture for Industrial Internet of Things- Design, Enterprise Implementation, Experience Jayakumar Vk, Kasi Viswanathan U, Kannan Sankar
Energy optimization for buildings, Chillers, AHU, UPS and Occupancy based demand forecasting