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Introduction

Intelligent Building Monitoring and Control System for Energy Efficient Operation



  • Principal Investigator (PI): Dr. Kashif Javed
  • Co-Principal Investigator (CPI): Dr. Zahir Fikri
  • Co-Principal Investigator (CPI-II): Prof. Dr. Waqar Mahmood
  • Principal Investigator’s Organization (PIO): Al-Khawarizmi Institute of Computer Science, UET Lahore
  • Other Organizations Involved in the Project: Smart Systems (Smc-Pvt) Limited, Lahore
  • Funding Organizations: National ICT R&D Fund

Executive Summary:

Pakistan is facing acute shortages of electric power with disastrous consequences in terms of deterioration of quality of life and breakdown of industrial production. The removal of these shortages is an uphill task due to many factors such as the continued increase in energy prices, increase in demand as a result of new appliances and devices as well as the huge investments which are required to bridge the gap between supply and demand. One immediate remedy is to cut down the power and energy demand of the existing stock of buildings, through energy retrofits. The research partners under the present project have carried out energy retrofit studies in large buildings in Lahore and Dubai. It was found that the cooling loads are about 75%-80% of the total load. Retrofits of cooling load can lead to dramatic reductions of this kind of demand, in many cases up to 80%. The motor load if properly controlled can be reduced by 35% to 50%. The lighting loads can be reduced by about 90%. Other loads such as computers and appliances can be cut down by about 80%. The technologies are commercially available but the energy retrofit implementation process requires high level of engineering and techno-economic assessment and design. The whole development cycle can be divided into three stages: Stage 1-optimizing the energy needs through intelligent energy performance assessment and energy retrofit evaluations, Stage 2-optimizing the design of the Heating, Ventilation and Air-Conditioning (HVAC) Systems and Stage 3-optimizing the operation and maintenance of HVAC Systems through intelligent Building Energy Management Systems. KICS and partners Smart Systems/Linked Data Solutions have already defined and submitted to ICT R&D Fund, a research proposal entitled “Linked Data Based Building Energy Management System”. This proposal is under review by ICT R&D. The present project is focusing on stage 3. Whereas, our proposal for LDB BEMS focused on development and assessment of energy retrofits, the current project deals with stage 3, to achieve energy system optimization. The energy retrofit design can lead to a maximum of 90% energy savings. The optimized operations result in 15% to 35% reduction in consumption. We feel that the stage 1 and 3 projects require lesser inputs to achieve good results. Whereas the stage 1 and 3 projects will impact operation and maintenance in existing buildings, the stage 2 projects are needed in design of new buildings. Such projects require a multi-disciplinary approach by different design partners. We feel that research projects for stage 1 and 3 can give immediate results. This explains why we have taken up the present project as a stage 3 project. We expect that stage 2 research projects are taken up as a more detailed understanding of the subject develops. Both our research proposals complement each other but meet clearly defined Energy Retrofit needs. In due course we shall be able to build on our research efforts in stage 1 and 3 projects, to define needs for research in stage 2 energy retrofit projects. These considerations led us to define the present project as a project that can be taken up simultaneously as each retrofit approach can be taken up independent of the other. Although considerable energy monitoring and control systems are available commercially, none offers the predictive control approach linked to the building information and weather model that we are proposing in this project. We have defined this project to predict the energy requirements on short term basis and offer intelligent control to achieve the targeted reduction in energy consumption and demand. The existing Building Management Systems (BMS) offer hard wired control specified by the vendors. The versatile and intelligent Building Monitoring and Control System for Energy Efficient Operation, which we are proposing under the present project, is not included in traditional BMSs. The reason is the complexity and the variability of the HVAC systems in large buildings. There is a large vacuum of knowledge and understanding here. We believe that the output of our project will lead to integration of monitoring, energy simulation and control in existing BMSs. Also the intelligence to be provided by the proposed Decision Support System (DSS) for monitoring and control can be integrated into the different systems. How does the Intelligent DSS differ from conventional systems? One aspect that is missing in conventional systems is the lack of intelligent systems. Secondly, there is no energy forecasting. Thirdly, integration of different technologies to achieve an open access and reasoning system is lacking. The ultimate intelligent monitoring and control system would learn from the monitored data, evaluate different control strategies and adopt the best control strategy to optimize the energy system operation. This is the main concept in the present project. We expect to link the energy monitoring and control function to Smart Grid concepts. Prior to design of the project, we carried out a detailed literature review. This review covered 151 references dealing with energy monitoring and control, wireless sensor networks, Arduino based energy monitoring and sensors and actuators. Different forecasting methodologies and mathematical models, artificial intelligence concepts, energy optimization algorithms, issues in wireless sensor networks in intelligent buildings, application of the popular Arduino platform for energy monitoring and control and the application of sensors and actuators under European Energy projects were studied. The literature review revealed that it would be appropriate to focus on regression and building information models for energy forecasting, MATLAB based simulation and evaluation of control strategies, Arduino based local power and energy monitoring and control, wireless sensor networks for climatic monitoring and control. The DSS can be set up using Artificial Intelligence concepts. Existing open source software, tools and portals can be used for energy monitoring. There is ample room for research in forecasting models, energy optimization algorithms, wireless sensor networks and climatic monitoring motes, power monitoring sensors and actuators, design of intelligent control systems and Decision Support Systems. State of the Art review showed that at least three European Union (EU) energy projects are using technologies such as wireless sensor networks and climatic monitoring motes, which can be used in the present project. The projects using mathematical models, optimization algorithms, artificial intelligence concepts and control systems will be good references for our work. Major research challenges internationally are development of suitable Information Communication Technologies (ICT) for intelligent monitoring and control, seamless integration of different communication protocols, optimization of energy use of wireless sensor motes, integration of Smart Grid Concepts etc. Our research challenges as described above will be development of suitable building information and forecasting models, development of optimal intelligent control system and a Decision Support System using Artificial Intelligent Tools, integration of different open source tools into a DSS, linking the system with BMS software of existing vendors and guide the user to achieve the targets. Key approach here is software reuse. We are targeting the HVAC systems and the existing buildings which are major users of energy. A general purpose monitoring and control system would provide the users the opportunity to optimize their operations. The project envisages a number of modules for sensors and actuators interfacing, weather, building information and user scenarios knowledgebase, human machine interface for forecasting, forecasting modeling tools, Decision Support Tools, Intelligent control tools and a web based monitoring and display portal. The project outputs will be a fully integrated set of open source software tools, which may be integrated with existing BMSs, research publications and theses, seminars and conferences, demonstration projects, training of users, educators and researchers. The project visualizes four phases and 12 deliverables over a period of 3 years. Phase 1: Research and resource acquisition has tasks: Task 1: Identification of controllable energy consuming devices and Task 2: Review of Sensors, Actuators, Controller Boards, Shields and Internet Gateway. Phase 2: Analysis and customization of selected open source tools: Task 3: Selection and implementation of Building Controller Platform and Task 4: Design and Implementation of Building Energy Monitoring & Control Knowledgebase Interface energy forecasting using mathematical models. Phase 3: System implementation: Task 5: Design and Implementation of Weather Data, Energy Models and Control, Task 6: Design and Development of Human Machine and Forecasting Interface (HMI), Task 7: Development of Building Forecasting Interface and Web Based Monitoring Dashboard and Task 8: Development of Building Energy & Demand Forecasting Modeling Tools Models Interface. Phase 4: The advanced Control Algorithms Research, and implementation: Task 9: Design and development of Intelligent Building Energy Monitoring & Control Decision Support System (DSS), Task 10: Integration of Intelligent Building Energy Analysis, Presentation and Monitoring Tools, Task 11: Design and Implementation of Building Intelligent Energy Control System and Actuators Interface, Control System and Actuators Interface and Task 12: End of project report. There is a deliverer able on quarterly basis for each task, in all 12 from D1 to D12. The project key staff includes Principal Investigator, two Co-Principal Investigators, Team Lead, one Senior and one Junior Software developer, two Electrical/Electronic Engineer, one Field Engineer, one Ph.D, one Masters and two undergraduate researchers, Computer Engineer, Accountant and one Energy simulation Engineer. In all, the project will have a team of 16 professionals. The users will greatly benefit from this project. With little investment, the energy and power demand can be reduced by about 15% to 20%. Using 40% share in the total demand of 18,000 MW, it means a reduction of about 2,700 to 4,500 MW, which translates to release of capacity of about 2,700 to 4,500 Million dollars. Large buildings in Pakistan have energy bills running in millions of rupees. The individual benefits to the building owners will be substantial. We believe that our concept has great commercial value and its adoption will be quick and profitable. We see great commercialization prospects. Currently, this domain is exclusively handled by a select number of vendors. Our product will open doors for many opportunities for the local industry, education, research, engineering, installation and maintenance communities. Our entire focus is on open source software development. Our end product will be offered free of cost with support, training and software customization and integration services as paid services. The education and research community will be a big winner. Also development of wireless sensor and control technologies will create many opportunities for development of new products by the local industry. Cooperation with building owners will lead to projects for Pakistani firms, research establishments and educational institutions. We hope to develop a comprehensive solution for energy monitoring and control and ultimately negotiate with BMS vendors and integrate our code according to their requirements. We shall provide customization and support services. We feel that our project meets the most urgent need of the time.