Commercial Real Estate Energy Management: Using Real-Time Data as A Tool for Energy Management

As a commercial building owner, you’re probably constantly thinking of reducing operating costs and increasing property (asset) value. The monthly utility bill is just another operating expense (Op-Ex). We all know that thirty to forty percent of the total operating budget of most commercial buildings is spent on energy costs. And the bitter truth is we all are overpaying!

With the next generation of building energy management systems, there’s a much more precise, shorter and low-cost solution to reduce operating costs (Op-Ex) by trimming energy use and by managing energy load while simultaneously improving systems reliability. Managing and maintaining big data in real time is the key to improving building energy performance. It rapidly helps to profile loads, understand building thermal load, detect unnecessary energy use, and test schedules and setpoint changes to optimize building energy operations, all in real-time.

Big Data Analytics is the key to Building Energy Management which offers extraordinary insight into building conditions and asset/equipment behavior. Some of the advanced and powerful applications of big data for building energy management include:

Accurately Predicting Energy Demand and Consumption

Energy demand is the total amount of energy required in a building at a specific time interval. Due to the impact of occupants’ activities, the direct correlation between electricity demand and ambient temperature will show different trends periodically, showing seasonal and hourly variations, respectively. This makes it difficult for conventional data analysis methods to predict buildings’ demand accurately.

By providing historical data, real-time energy usage data, local weather station information and real-time building occupancy, Advanced Low-Cost Software Solution can be utilized by building owners to predict demand and consumption more accurately with Less RMSE (root-mean-square-error) and High R² (the coefficient of determination or simply the thermal load). And this Fully Automatic and Real-Time software solution for Measured vs Predicted energy usage uncovers the wide range of anomalies in building energy operations, thanks to big data!

Peak demand mitigation can generate immediate savings. Real-Time Peak Demand monitoring is an essential tool for proactively managing costs, Which helps manage demand charges. How most tariff rates trigger demand charges, real-time rolling calculations are done to calculate the peak demand in kilowatts per hour today, yesterday, the current week/month, and the previous week/month. All in all, accurate energy tracking in real-time results in Peak Demand Energy Management, Optimizing Equipment Startup/Run Time and Prevention from Unoccupied/Unnecessary runs.

Energy Consumption Analysis with Fault Detection and Diagnosis (FDD)

Total building energy consumption monitoring is one thing, but significant load profiling and sub-metering are also vital for analyzing building energy performance and finding faults preventatively. Existing Building Controllers are already generating enough data to support the Virtual Meter concept, which can bring us down to the right level of data granularity to drive “No-Cost or Low-cost” energy efficiency measures. This is key to identifying specific areas or equipment (floors, lighting zones, halls, common areas) that may consume excessive energy and raise demand charges. Big data can effortlessly bring real-time KPIs like Setback Ratio, Saturday/Sunday Equalization, Heat/Cool Setback, Heat/Cool Load Reduction, Absolute Value Deviation and Integral Deviation to your fingertip.

Arming yourself with the big data and understanding and uncovering the information and how it affects you is the first step to a more cost-effective and efficient operation. Tracking your energy consumption allows you to optimize it and help you understand whether your asset is overvalued or undervalued and by how much. You reduce your operating expenses and increase your net operating income with intelligent decisions.

For example, air handling units can get stuck in a mode where they’re simultaneously using heating and cooling or an Excessive economizer resulting in a heat valve to operate. Real-time monitoring and analysis can spot excessive cycling, allowing building engineers to take corrective action to reduce energy waste immediately. By identifying what’s occurring day-by-day, piece-by-piece equipment, you will likely get an immediate payback by uncovering hidden operational anomalies.

Identifying the Changes Needed to Improve Efficiency and Sustainability

Repair vs Replace decision is often a challenging task when dealing with old equipment. Big data bring transparency into equipment operations, particularly in energy usage, and transparency is the key to evaluating equipment performance in real time. An analytics solution can enhance how we see mechanical or operational issues that may interfere with overall performance. Technology advancement can eliminate the distance between the boiler room and the board room by engaging business managers in justifiable savings without deep technical knowledge. This all would result in a durable equipment lifecycle, long-term savings, contractor fraud prevention and faster approvals for efficiency improvements.

Big-data platforms seamlessly identify and trigger faults if the system is running at desired SOP (Sequence of Operation) or not; it can even suggest a more efficient SOP or suggest low-cost sensor replacement or sensor addition in order to drive the ultimate efficiency. Let’s say we have 25 Air Handling Units on a particular site. Engineers established SOP to operate free-cooling under certain conditions; now, how can we validate all AHUs are working to maintain setpoint using free cooling when possible and not triggering cooling valve throughout the whole summer season? And how do we know that system is reacting, in the same way, every year? Most of us will say system commissioning is the answer to that, correct? But NO, big data can perform real-time commissioning by all itself and eliminate tedious manual labour work.

By and large conventional BAS (Building Automation Systems) is a powerful tool that automates the main controls of a building. Armed with a BAS, property operations teams can program a building to start up, adjust automatically, setback and shut down, all from one central platform, and that’s the main course of action today when we talk about efficient building. Still, we must think that a static piece of code sitting in a control panel alone can’t do much to improve. There are a lot of limitations to BAS when it comes to the dynamic nature of the building and its operation. BAS can’t evaluate real-time energy performance unless costly energy meters are integrated with BMS; optimization implementation becomes very time-consuming and costly, and even the success of that particular optimization strategy is hard to evaluate.

To overcome all the limitations of static BAS controls and get the most out of a BAS, we must have some advanced external dynamic cloud-based technological approach, which potentially utilizes Artificial Intelligence, Machine Learning, and Bid-Data based advanced custom data analytics. Advanced technology can maximize the effectiveness of a BAS. Energy management via this kind of technology can provide detailed transparency into utility resource consumption, which helps uncover a potential problem before it happens.

With real-time monitored data and a next-generation BAS system, problems/issues that have been overlooked, often for years or decades, can be exposed, and mitigation strategies can take place via no-cost or low-cost measures. Savings can be both immediate and permanent.

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