Business Process Services White Paper Leveraging the Internet of Things and Analytics for Smart Energy Management About the Author Akhil Bhardwaj Akhil Bhardwaj is a Senior Manager in the Analytics and Insights division of Tata Consultancy Services' (TCS) Business Process Services (BPS) unit. He has over 11 years of experience in providing innovative solutions for a range of analytical problems across domains such as banking, supply chain, retail, and marketing. He is currently working on driving technological transformation in product based analytics. Bhardwaj graduated from the Indian Institute of Technology, Bombay and Xavier Labor Relations Institute, Jamshedpur. Abstract The rising cost of energy is causing organizations to evaluate smart ways of saving energy. Energy suppliers are increasingly penalizing organizations that use inefficient assets or devices with a low power factor. Simultaneously, governments are raising the bar for compliance with energy standards and reduction in carbon footprints. Smart energy management systems (EMS), combined with the Internet of Things (IoT), provide the ideal solution for these pressing challenges by supporting radical changes in the way energy consumption is monitored and managed. This paper examines how the combined power of the IoT and energy management systems can revolutionize energy management. It illustrates how these systems leverage information collected through different devices to automatically control operational parameters and minimize energy consumption across buildings or campuses. The paper also highlights the role of analytics in optimizing energy management by helping organizations make holistic sense of the large volumes of data gathered by various devices. Contents The Need for Energy Management 5 Planning for Efficient Energy Management 5 Exploring the Possibilities: Internet of Things and Analytics 6 Making Sense of Data 7 Controlling operational parameters of chillers 7 Optimizing lighting 8 Realizing Holistic Benefits through Analytics Future Outlook: Revolutionizing Energy Management with IoT 9 10 The Need for Energy Management Effective energy management is an increasingly critical focus area for utilities and energy service providers, as well as end-customers. Energy consumption needs to be minimized without compromising on comfort and other ergonomic considerations such as appropriate humidity, fresh air, carbon dioxide levels, and so on. An efficient energy management system helps optimize energy consumption for heating, ventilation, air conditioning, refrigeration, lighting, fire systems, and security systems, ensuring that energy is used only when needed. An advanced energy management system can ensure monitoring of building conditions, equipment status, utility sub-metering, climatic data, and demand limiting that includes load scheduling and duty cycling. Such a system can also focus on maintenance (remote operation and control of equipment, generation of maintenance schedules, and diagnosis of breakdowns), and record generation (modification or replacement analysis, energy conservation documentation). Planning for Efficient Energy Management Many enterprises are now developing different hardware, software, and analytical solutions for energy management. Effective planning serves as the foundation for this exercise. Planning for a building energy management system starts with the layout of the building. Based upon the floor space area, the cooling or heating capacity needs to be determined; this should be greater than the expected maximum requirement for a given area and set of environmental conditions. This might require installation of multiple chillers with separate piping plans. Another important factor to be considered is that certain chillers might have lower procurement costs but higher operational costs due to lower efficiency. Typically, higher efficiency chillers are associated with a higher procurement cost but a lower operational cost. If the business decides to install higher efficiency chillers, they will need to consider the breakeven tenure involved. For lighting, the aim is to leverage as much natural light as possible. This can be hampered by factors such as reflection glare of neighboring buildings. High floor space can also prevent the utilization of natural light. In such a case, the type of lighting installation becomes important. It is imperative to ensure optimization of procurement cost, energy efficiency (operating cost), and the life of each energy consuming asset. The power factor also plays a key role. It indicates the relationship between real power (power consumed by electrical equipment) and apparent power (power that is drawn by equipment but not completely used, so that it includes wasted energy). If the power factor of an asset is low, it implies a loss of energy. Therefore, energy management also calls for effective planning and monitoring of the power factor. 5 Exploring the Possibilities: Internet of Things and Analytics In the age of the Internet of Things (IoT), each device can be connected to the internet or intranet, or to other devices on the network. This enables the collection of a variety of information from the devices, including data on operations, configuration, energy consumption, and the power factor. The IoT enables devices to make smart decisions based upon analytical rules that serve the purpose of the devices best. The devices can send, receive, store, and leverage information, sending the information individually to another device or broadcasting it to all devices. Figure 1 illustrates such a set-up. Chiller data Lighting data Air handling Hub room/ units data workstation data One specific section of the building Different sections in the building Energy management system application on a central computer LAN Connectivity Temperature sensors Illumination sensors Humidity sensors Fire sensors Figure 1: IoT based energy management system in buildings Data scientists can use analytics and study historical data usage patterns in the building. They can create scorecards and algorithms that allow individual devices to make better decisions about operational parameters in different scenarios. The scorecards and algorithms might also govern the flow of data from the devices to different destinations. Depending on the building, data scientists might create individual scorecards and algorithms for individual devices, or joint algorithms for a set of devices that are supposed to operate together in a certain order. Data from each device can be stored in a central repository for future reference. While the communication between devices may be synchronous or asynchronous based upon the requirement, a central intelligence unit such as the energy management system serves as a facilitator. The EMS can also help control the devices when direct communication between devices fails to serve the required purpose. In such cases, the system optimizes the operational parameters and broadcasts them to the respective devices over the LAN. On receiving the new instructions from the EMS, the devices change their operational parameters accordingly. 6 In addition to assets and devices, different sensors are also connected to the internet through the LAN. Sensors for illumination, humidity, occupancy, and temperature transmit information in real time, enabling different assets to leverage the information. The EMS also receives and stores this information, and leverages it to make smart decisions. Making Sense of Data A host of analytical solutions is emerging in the area of energy management backed by the increased ability of the IoT to connect devices, collect data from devices, and distribute data. These solutions leverage historical patterns of occupancy, people movement, temperature, provision of natural lighting, energy consumption, and other information collected by smart meters, sensors, actuators, and controllers. Below are two scenarios where analytics enables smart insights for intelligent decision-making. Controlling operational parameters of chillers Commercial chillers operate by circulating chilled water into the rooms' water pipes. In each room, a number of blowers blow air over the chilled water pipes, in turn cooling the air and leading to air conditioning of the room. (The same mechanism is followed by central heaters; the only difference being that the water is heated instead of chilled.) This is a two-stage process of energy expenditure. First, energy is consumed in cooling the water that is then circulated through pipes that run in the rooms. In the second stage, energy is consumed by the blowers that blow air over the water chilled pipes. The ability to maintain a static temperature in a location depends upon a host of factors. These include the occupancy, weather conditions, chiller parameters, the temperature of chilled water, the blowers in the room, and other factors such as heat-producing items in the room. The IoT brings together information from all these controllable and uncontrollable factors for all sections in the building. The EMS then makes real-time decisions about the number of blowers to be switched on to maintain the required temperature in each room and achieve ergonomic comfort. However, the EMS needs smart algorithms to leverage the data and make intelligent real-time decisions. A set of scorecards also needs to be developed. One set of scorecards needs to consider the environmental conditions of the building and inform the EMS about the amount of energy required to chill the water to the required temperature. The EMS then computes the operational parameters at which the chiller should operate and sends this information to the chiller, enabling it to operate efficiently. The second set of scorecards needs to consider environmental conditions, occupancy patterns, information about the room, the number of blowers available, and past energy consumption patterns. Using this information, the scorecards can predict the amount of energy required to maintain a specific temperature in the room. Separate scorecards will be required for each room and each chiller. Figure 2 illustrates this process. 7 Based on the information from multiple rooms, the EMS leverages the scorecards to determine the optimal temperature of the chilled water Chiller EMS switches air blowers/fans on/off to control the room temperature Room 1 Chilled Water Energy Management System EMS leverages analytical scorecards to determine the scenario of minimal energy consumption Information on occupancy and temperature sent to EMS Figure 2: How the IoT and EMS help control the key parameters of chillers Optimizing lighting The EMS monitors the Air Handling Unit parameters to maintain optimal air circulation for dynamic occupancy. This helps ensure that occupants can comfortably breathe and work in their respective rooms. With such a system in place, lighting can also be automatically turned on when the first person enters the room and automatically turned off in case the last person to exit the room forgets to do so. When granular occupancy information is available, the EMS effectively governs the required lighting for individuals who are entering or exiting. Similarly, the EMS can interact with workstations to determine if they can be turned off or not. The workstations send information to EMS over the LAN that no active thread is running and the EMS then validates that the user has, in fact, exited the building. It then sends instructions to the workstation to turn itself off. 8 Realizing Holistic Benefits through Analytics Here are a few ways to leverage the IoT and analytics simultaneously to realize benefits across the energy management spectrum: Asset efficiency analysis: Asset efficiency can be calculated for a variety of assets in real time. This also helps determine the cost implications of non-optimal device performance. The efficiency of assets can drop due to age or maintenance issues. Benchmarking techniques compute the optimal efficiency levels at which the devices should run under the given set of environmental conditions. This can be used to identify scenarios involving excessive energy consumption within a building. Root cause analysis: This can be performed in cases where a higher than expected level of energy was consumed. Given the IoT enabled data, the hypothesis generated through root cause analysis can be statistically validated. Predictive analytics on asset maintenance: The cost implications of maintaining all energy consuming devices can be determined using predictive analytics. Similarly, warranty lifetime analysis can also be performed to arrive at the optimal warranty period and costs. If certain devices are observed to fail early in their lifecycle, the warranty tenure is expected to be long enough to cover all such early lifetime failures. Also, while the device might not be likely to fail as a whole, certain components might be more prone to failure than others. Furthermore, warranty analysis acquires importance if the error-prone components in the device are expensive. Correction and exception analysis: Analytical techniques help identify areas where power factor correction might be required early on to enable cost savings. Analysis of exceptions, alarms, and manual overrides to EMS is important to highlight the discrepancies that are likely to be registered in operations from time to time. Such analysis helps determine the optimal state, the factors responsible for deviation, and the preventive and corrective actions required to run the automated operations optimally. Carbon emission analytics: Scenarios that help minimize the total carbon emissions from the commercial buildings can be simulated using carbon emission analytics. Energy management standards mandated by relevant laws can be taken into account for such simulation. This can help tailor energy management solutions according to the location of the building. 9 Future Outlook: Revolutionizing Energy Management with IoT IoT is expected to play a pivotal role in efficient energy management in the future. As people walk into a commercial building, devices and assets will gather important information about their movements. The occupancy of each location at every point of time will also be captured, transmitted, and stored. The control parameter of the assets and devices will be auto adjusted to levels that create ergonomically convenient working conditions and simultaneously optimize the consumption of energy. In offices, unique tagging of desk space to individual employee consumption will further contribute towards efficient management of energy requirements. Artificial lighting in the rooms will be oriented in ways that ensure the total illumination in the room is ergonomically convenient for all the occupants. This will also allow for the best use of the natural light. As the sunlight in the room increases, artificial illumination is automatically reduced so that the total illumination remains constant at the desired ergonomic level. This optimized energy consumption of lighting will be maintained by the energy management system in real time. The results are savings in lighting costs and enhanced life of the lighting equipment. Fire sensors can become active in the event of fire and flash the nearest exit. The same fire exits can detect the number of people in the process of exiting through different routes. The EMS can use this information to develop and highlight routes to streamline traffic through exit routes, ensuring that more people reach safety. With the rising cost of commercial energy, smart energy management systems will be used by organizations for competitive advantage. As the volume of data collected by smart meters increases over time, these systems will increasingly leverage the latent information hidden in the data to make smart choices. Big Data and Hadoop are expected to be extensively used in the process as data scientists begin to mine this data to develop smarter algorithms and decision making tools. Furthermore, robust analytical algorithms will be applied across varied scenarios, to identify and prioritize energy optimization opportunities. 10 About TCS Business Process Services Unit Enterprises seek to drive business growth and agility through innovation in an increasingly regulated, competitive, and global market. TCS helps clients achieve these goals by managing and executing their business operations effectively and efficiently. TCS' Business Process Services (BPS) include core industry-specific processes, analytics and insights, and enterprise services such as finance and accounting, HR, and supply chain management. TCS creates value through its FORETM simplification and transformation methodology, backed by its deep domain expertise, extensive technology experience, and TRAPEZETM suite of solution accelerators and governance enablers. TCS complements its experience and expertise with innovative delivery models such as using robotic automation and providing Business Processes as a Service (BPaaS). TCS’ BPS unit has been positioned in the leaders’ quadrant for various service lines by many leading analyst firms. With over four decades of global experience and a delivery footprint spanning six continents, TCS is one of the largest BPS providers today. Contact For more information about TCS’ Business Process Services Unit, visit: www.tcs.com/bps (http://www.tcs.com/bps) Email: bps.connect@tcs.com Subscribe to TCS White Papers TCS.com RSS: http://www.tcs.com/rss_feeds/Pages/feed.aspx?f=w Feedburner: http://feeds2.feedburner.com/tcswhitepapers About Tata Consultancy Services (TCS) Tata Consultancy Services is an IT services, consulting and business solutions organization that delivers real results to global business, ensuring a level of certainty no other firm can match. TCS offers a consulting-led, integrated portfolio of IT and IT-enabled infrastructure, engineering and assurance services. This is delivered through its unique Global Network Delivery ModelTM, recognized as the benchmark of excellence in software development. A part of the Tata Group, India’s largest industrial conglomerate, TCS has a global footprint and is listed on the National Stock Exchange and Bombay Stock Exchange in India. 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