By applying analytics to make sense of smart meter data, utilities believe they will be able to reduce their operating costs, optimize deployment and the operational health of their networks and systems.
Data disrupts, big data disrupts absolutely. That holds true across multiple industries, including the utilities space, where software and analytics are providing insights that change everything from consumption of energy down to business model and beyond.
As global population continues to explode and with ongoing urbanization, global energy consumption has increased exponentially over the past few decades. This has led utility companies to clamor for greater efficiencies in both supply and demand optimization, as well as implementing technology which can detect any leaks or inefficiencies in the system, to cut down on how much energy is used and take stress out of the energy system.
Current estimates are that around 900 million smart meters will be installed between 2016 and 2023.
Betting on technology has been a smart move for the utilities industry, perhaps none more so than IoT, where billions of connections mean trillions of dollars in value.
IDC has said that by 2019, 51% of nodes on the internet will belong to machines, not people, and with smart household meters generating 400MB a year and smart buildings netting out at a whopping 250GBs a day each (on average), there’s a lot of utilities data to process. Petabytes of data.
Rather than waste it, and let it evaporate into the ether, many utilities companies are now trying to mine that data, looking for nuggets that will help them to optimize and streamline their businesses and solve problems in new ways.
For electricity usage, a smart meter is meant to people better monitor their energy usage and avoid waste by carefully tracking where energy is being used and by what. Is your TV sucking up too much juice? Is your central heating system on full blast but your windows open? Do you need more energy efficient light bulbs? Smart meters don’t just monitor consumption, they supposedly offer customers a holistic picture of their energy use, the health and status of their appliances and personalized tips on how to improve.
Similarly, smart water meters help better track consumption and can flag normal vs abnormal patterns while monitoring water infrastructure for issues in real time. Current data seems to suggest that simply by installing a water meter, consumption drops by around 35 percent, and energy savings follow because less water has to be pumped to heating tanks.
Utility companies implementing analytics software to make sense of the data believe they will be able to reduce their operating costs, optimize deployment and the operational health of their networks and systems. They also believe it will help them get a head start on product development and innovations that will further improve customer engagement.
To be selected as a software vendor for the industry, however, isn’t easy. Utility companies are apparently only looking to vendors who can demonstrate the maturity, scalability, and extensibility required to make smart metering a success. Prior success in industrial IoT is a plus.
To make the smart meters extra smart, the next gen of software and hardware will also draw on artificial intelligence (AI) and machine learning to shuck its way through massive amounts of big data and get more accurate predictive analytics.
The data comes in all shapes and sizes, from various sensors, devices and systems, as well as external data sources like social media, traffic flow and weather conditions, all ideally collated into one cloud-based system able to run machine learning at scale, in near-real time.
The most useful systems will help utility firms track meter deployment and installation, as well as the overall health of the system they are monitoring, with systems that can identify problems, prioritize them in terms of urgency and schedule predictive maintenance.
While all of this sounds fantastic to utility business owners, it may not be quite as good for customers, beyond their getting a cool looking gadget that can give them prettier looking reports on how efficient or inefficient they’re being. Some analysts maintain that most smart meters provide more value to the company deploying them than to the customers themselves, most of whom bear the brunt of the cost.
The problems for consumers range from having to deal with closed, proprietary networks, potentially shoddy security, infrastructure constraints and the issue of rapid technology obsolescence.
Many of the millions of smart meters already deployed over the past 1-3 years are already redundant when it comes to their hardware, cybersecurity standards, and communications protocols, though customers will have to stick with them until the next cycle of device upgrades happen. Since that’s a costly endeavor, it’s not likely to happen soon.
Additionally, most of the data collected and analyzed goes towards helping business efficiencies rather than money saving efficiencies for customers. Those who are invested in checking their energy usage and attempting to improve it are a subset of customers who typically cared about their energy usage before the advent of the smart meter, while others will simply ignore the findings, no matter how attractively they are set out.
Mandated adoption of smart meters is all well and good, but many times customers are being charged for the device and its installation, with questionable financial benefit.
What utility companies still need to do is figure out whether deploying more hardware to customers is actually going to improve value on both ends of the value chain, providing benefit to the end user as well as the utility firm. In addition, a plan to deal with obsolescence needs to be better thought out, as tech improves by leaps and bounds year over year. Finally, companies need to consider how smart meters can integrate seamlessly with other systems in smart households and cities, providing more value than just a fancy looking electricity bill.