A record 191 countries signed the historic Paris Climate Accord in December 2015, serving as a reminder to combat the threat of climate change. This first-of-its-kind, legally-binding deal mandates governments and businesses to change their approach to energy management. The good news is the timing could not be better. With the advent of the Internet of Things (IoT), entities can leverage smart energy management to not only reduce carbon footprint, and favorably impact climate change, but also optimize energy costs.
However, there are some aspects that need to be considered in order to fully realize the potential of IoT.
For businesses, the primary challenge is the lack of visibility into real-time data on energy consumption across equipment as well as geographical locations. Other issues include irregular cost allocation based on non-actuals, and heavy dependence on legacy and proprietary systems that are not equipped to derive data for analysis. Disparate and non-networked systems that do not allow two-way communication between the newer smart energy meters and utility providers further impede information flow and analysis.
For governments, it is vital to ensure enhanced quality of life through reduced energy consumption, as cities outgrow the resources.
Can IoT coupled with analytics change energy management?
In 2015, Gartner predicted the number of connected devices will reach 20.8 billion by 2020, with 2016 alone accounting for 5.5 million new IoT connections, daily. With the emergence of IoT, data collection becomes easier, as devices are designed to record the minutest amount of data generated, and communicate with each other. Based on the data generated by smart devices, algorithms that self-analyze and adjust themselves to pre-set parameters, can be deployed to monitor and control energy usage. At the same time, predictive analytics is helping companies forecast power usage at any given point in time, providing the flexibility to source energy as required from utility providers, at lower rates.
IoT coupled with analytics can maximize benefits for enterprises by providing an integrated view of energy usage across various functions and locations. It enables enterprises to visualize their energy consumption through sensor-based data acquisition, and generate actionable insights through cloud-based data analytics engines and dashboards. Two common scenarios where analytics enables smart insights for intelligent decision-making include controlling operational parameters of chillers, and optimizing lighting systems. For instance, Qualcomm uses sensors and intelligent infrastructure to detect building occupancy levels to help control lighting and HVAC in real time in order to slash energy costs.
Using predictive algorithms and artificial intelligence, companies can also predict their future energy consumption patterns and asset performance. Based on these insights, an active energy management system can be programmed to optimize energy consumption by turning off certain equipment during peak periods or running efficient equipment more frequently. This level of enterprise visibility and automation makes it easy for energy managers to predict their energy requirement, and plan maintenance of their assets, resulting in significantly improved operational efficiency.
A self-managed energy management model also reduces enterprises carbon footprint. Businesses can expect to lower their energy bills by at least 10 to 20%.
Why smart energy management makes good sense
Navigant research estimates that in the US, by the year 2020, there will be some 70,000 customers with pilot scale utility IoT engagements, representing approximately $50 million market. Companies are willing to spend on technologies that will allow them to control their energy expenses. A survey of 202 respondents, with over two-thirds representing facilities management and building operations, revealed that around 37.5% of their energy budget for 2016 is dedicated for smart energy solutions. The Wendys Company is leveraging smart energy solutions across 300 company-owned restaurants, while Macys uses data analytics for fault detection and diagnostics across 700 stores.
Programs such as the Smart Energy Analytics Campaign, a part of Better Buildings initiative by the US Department of Energy, are encouraging enterprises to uncover energy-saving opportunities by implementing energy management solutions. Eighteen members representing 1,800 buildings and 49 million square feet are part of the program as of September 2016. With such solutions, power usage is baselined, and anomalies are managed based on an intelligent, prescriptive, and preconfigured system
Digitizing energy management is the Way Forward
Implementing IoT-based solutions to optimize energy consumption is leading to intelligent demand-side operations. This enables collaboration between enterprises and utility service providers. In the emerging energy value ecosystem, utilities are providing services through demand-response systems, adopting just-in-time (JIT) methodology for supplying power. While the JIT concept for utilities is not new, IoT helps reduce the cost for the provider through real-time monitoring and analytics. Utilities are also tapping into alternative sources of renewable energy and using algorithms to predict the availability and reliability of these sources, further driving JIT energy.
Digitization of energy management provides incredible opportunities for enterprises to improve their operations, while responsibly achieving their eco-sustainability targets. The convergence between digital technologies and energy management is poised to pave the way for a new ecosystem of services in both smart and smart cities.