Our IA platform saves a remarkable 40% on energy costs for commercial real estate
Revolutionize the energy efficiency and benchmarking of your business
Proven Ready-to-Go Use Cases
Pre-Trained Machine Learning Models and Prebuilt Data Engineering for Accelerating AI Implementation
The operation and energy profiles of commercial buildings have become more sophisticated. Its energy profile is vulnerable to instantaneous change, responding to signals from internal controls or grid operators. As energy efficiency becomes increasingly important, new technology aims to save energy costs and carbon emissions. To make sense of the energy profiles, you need to have a good idea about what goes on in the building. Our model helps to gain an understanding of the essential factors related to energy.
BUILDING ASSET SCORE
This simple energy efficiency rating compares buildings and identifies investment opportunities for energy efficiency upgrades. While the tenants and energy usage patterns within a building frequently change, physical structure and major equipment mostly remain constant. These underlying energy “assets” such as the building envelope (roof, walls, and windows), lighting, hot water, and HVAC systems significantly impact how energy is used in a building regardless of its operation or occupant’s behavior.
Improving energy efficiency is the cheapest and often the most immediate way to reduce the use of fossil fuels. Building designers are looking to optimize building efficiency and then incorporate renewable energy technologies, leading to the creation of zero energy buildings. Our model helps to identify changes that can be made to eliminate energy waste in existing buildings through several different data factors such as site energy use intensity, upgrade opportunities and energy costs & savings.
How much energy your buildings use should matter to you. If you can measure it, you can control it. If you can control it, you can manage it. One of the most helpful tools in energy analysis is benchmarking the relative performance of peer buildings in a property portfolio. Decision-makers can make wise, energy consumption decisions by using energy benchmarking data. Our program automates that data for you to clearly highlight energy issues and opportunities.
POWER QUALITY FACTORS
PQ is a highly newsworthy issue. Increasing use of semiconductor-based electronic equipment and non-linear loads (such as computers and their peripherals, data servers, adjustable speed drives, arc furnaces, etc.) and rapid integration of non-conventional energy sources into grid network throws new challenges for the PQ environment. It’s important to measure the effective use of electricity as a company’s power factor will have a significant impact on its electric utility bill costs.
A line loss is a decrease in power from the source to the destination, which can be limited by several factors. Obtaining a line loss value may be difficult, depending on the circuit’s physical makeup and environment. However the basic calculation is simple for our machine learning model, which displays a full line loss analysis of consumer, revenue loss prediction and average percentage trends. Once understood, computing and a line loss for any variable or environment is straightforward.
Smart Grid Analytics We Connect Meter Data with Billing for Financial Forecasting
From device to enterprise, our Intelligent Augmentation platform uses machine learning capabilities to transform extensive amounts of data into connected energy analytics. Easily view grid analytics, energy insights and financial forecasting all in one place to help evaluate the costs and performance of within your business.
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Discover the Power of IA First-Hand
At Comerit, we want you to be just as confident in your IA implementation as we are—which is why we let our product do the talking. Interact with a demo of our platform and let one of our Intelligent Augmentation energy experts demonstrate the path to adopt quickly measurable business values.