“Can Our Company Use AI to Lower Our Energy Consumption?”
Yes, it can. Companies can lead the way in reducing wasted energy, and AI can help them.
How much energy can your business afford to waste?
None, of course. But how much power does your business waste?
More than you want to waste, of course.
You can’t know how much, but it could be quite a lot depending on your sector. About 30% of the energy used in U.S. commercial buildings is wasted. With end-use efficiency estimated at 65% for retail, 49% for industrial, and only 21% for transportation, your business is probably wasting at least a third of the energy it pays for.
Energy is a perennial source of overlooked costs for companies with manufacturing facilities, complex supply chains, and numerous locations. Because it’s big money, energy-intensive companies try to reduce consumption with techniques like buying more efficient machines or turning the lights off at the end of the day.
But what if companies like yours could use artificial intelligence (AI) to reduce energy consumption? What if you could use automation and advanced analytics to help uncover ways to become more energy-efficient in areas it never occurred to you to look before?
Applying AI and analytics to minimize wasted energy
You can connect to data on your energy usage using automation and analytics, even when it’s siloed in different company areas and other formats. Bringing multiple streams into a single one is how you collect enough data for the truly robust modeling and optimization needed to address the problem of wasted energy.
Then, you can apply AI to uncover insights into where and why waste is happening. Those insights enable you to take steps to reduce energy waste, operate with greater energy efficiency, and monitor the effects of your actions.
We examine four real-world areas where businesses can use AI to find ways to cut their energy consumption and dramatically reduce their energy costs.
Building and factory energy
Use AI to help consolidate your utility bills and analyze how you use energy. You can identify energy-intensive operations and times of peak load, then spread those operations to off-peak hours.
For example, Google reduced energy for cooling its data centers by 40%, thanks to the IoT and artificial intelligence from its DeepMind project. Using temperature data recorded in its data centers, the company applied AI and predictive analytics to control air conditioning.
Smart grid management
If your energy strategy includes renewables like solar and wind, you’ll have to factor in their unpredictable nature. You can apply AI to help with energy forecasting and storage in innovative grid management.
Suppose that, based on real-time meteorological data, your models predict a sharp decrease in your rooftop solar generation for the next three days. Either automatically or with human intervention, you can postpone charging your electric fleet and switch to a different energy source.
In moving both passengers and freight, the transportation sector in the U.S. is becoming less efficient while most other sectors of the economy are becoming more efficient. Innovative companies focus on the main factors behind energy efficiency in transportation and act on them:
- Fuel-efficiency — newer, more-efficient vehicles use less fuel to deliver the same load.
- Mode of transport — Trains are generally more fuel-efficient than planes or trucks. The choice pits an energy budget against a financial budget.
Occupancy rate — Between any two points, a single vehicle can usually transport people and goods more efficiently than multiple vehicles.
AI has a role to play in transportation management by helping to consolidate transportation data from numerous sources and applying analytics that reveals inefficiency. For example, in freight operations, the more data you can harvest and the more variables you can identify, the more inefficiency you can find.
AI can improve transportation management by:
- Checking that human drivers are operating within legal guidelines
- Optimizing routes
- Ensuring loads are complete, both outbound and on the return journey
- Notifying business partners of delays well in advance
- Scheduling maintenance to preserve fuel economy
- Automating arrival notifications to reduce wait time for drop-off
Supply chain efficiency
Every supply chain invites inefficiency simply by the nature of cumulative links. AI has the potential to reduce slack in those links and keep supply chain actors like transporters, suppliers, and purchasers synchronized with automatic prediction and decision making.
AI can anticipate the date by which a supplier will run out of a product by working with production and inventory data. It can automatically notify the buyer of the anticipated restocking date and extend the option of changing the order or waiting. Conversely, AI can predict expected product shortages or price fluctuations, allowing buyers to stock up.
AI can also shed light on inefficient planning, scheduling, and building and managing an intelligent warehouse with reduced total costs. AI-enhanced supply chains:
- Optimize inventory management
- Provide more traceability
- Trim waste
- Lower CO2 emissions
- Improve production efficiency
- Reduce delays in supply or overstocking
Again: How much energy can your business afford to waste?
There are easy steps that organizations can take to improve energy efficiency life, ensuring insulation in buildings, using energy-efficient equipment, and making sure lights turn off when they’re not in use. The more complicated steps can be daunting, and hard to measure their impact. That’s where Alteryx comes in.
With Alteryx Designer, you can easily connect to all data sources to view your energy efficiency. With the Alteryx Intelligence Suite, you can even automate pulling data off PDFs like energy bills, energy reports, and more. This data can be used to robust power dashboards that grant insight into the current state of your energy usage.
Download the Alteryx Intelligence Suite Starter Kit to try it yourself. Alteryx Machine Learning makes data science easy and gives anyone the power to understand associations in data and the factors that lead to high energy bills. To learn more about Alteryx ML, you can request a demo as we’ll show you how Alteryx can solve your most daunting energy analytics problems.
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