The Internet of Things (IoT) is transforming many industries and energy is no exception. With the growing use of advanced technologies such as energy management systems, smart meters and networked controls, there’s more available information about building energy use than ever before. Such big data requires analytics software to help users identify inefficiencies, set priorities and take actions to save energy. Cloud-based software as a service (SaaS) programs add mobile access and remote control.
Big data is expanding the scope of energy audits, benchmarking, measurement and verification. Buildings are becoming intelligent, modeling their own environmental systems, accessing historical data from other buildings and predicting maintenance. Building owners can react faster and extract even more value from these data sets. Cost savings will multiply and conservation targets will be met sooner, contributing to customer and shareholder value. One example of big data use is digital twins. The cyber representation of the physical building is powered by high-performing databases, advanced reasoning engines, KPIs (such as efficiency) and context (occupant behavior and geography).
Retailer Kohl’s is already taking advantage of this trend. A central energy management system controls most indoor and outdoor lighting, as well as heating and cooling, at all of its stores. Leveraging such data helped Kohl’s achieve 24% energy savings across more than 110 million square feet of building space.
Despite these inroads, three major barriers remain to widespread usage of big data:
1. Standardization. Data must be consistent and reliable, which requires standardizing both inputs and outputs. A national standard may be necessary so data is easy to access and understand. One step in this direction is the Standard Energy Efficiency Data (SEED) Platform developed by the U.S. Department of Energy. SEED is designed to provide users with a standardized but flexible platform to manage building energy performance data from a variety of sources.
2. Privacy. Who owns and controls the energy data? How do you make so much data secure? These questions must be answered to successfully leverage data for energy savings.
3. Value. Building owners must be convinced the data has value through demonstrated examples of its ability to change behavior and provide energy savings.
Big data is also tightly connected to IoT systems. That’s both an advantage and a potential disadvantage. During a power outage, the flow of information could be disrupted at critical times, resulting in data losses and affecting operational continuity. Power protection is critical.
Once these challenges are overcome, big data is expected to revolutionize energy management. Energy conservation will become the new normal.