Most if not all industries will be impacted by the growth of Big Data, but the utilities industry is in for a particularly dramatic transformation. Advanced metering infrastructure (AMI), commonly known as smart meters, that “phone home” energy usage data every 15 minutes are increasingly replacing aging, traditional meters that require manual readings. The result is a deluge of machine-generated data that offers both opportunities and challenges for utilities companies.
To grasp the scope of the impact of smart meters on the utilities industry, consider that traditional meters that track electricity consumption routinely generate just 12 readings per year, or just one per month, and they must be read manually. Many smart meters, by contrast, are capable of two-way communication and produce and transmit 12 readings in just three hours, or once every 15 minutes. The result is the annual number of meter readings at any given residential or commercial structure increases from 12 to 35,040, on average, with the use of AMI. Multiply that increase across millions of customers, and you will start to understand the just how dramatic the impact will be.
Current estimates peg the penetration rate of AMI in the United States at around 16%, with 50% penetration expected by 2016 and near 100% penetration by 2020*. (See Figure 1.)
Just like the data volumes, the opportunities for utilities companies offered by AMI are enormous. With years of historical customer data at its disposal and near-real-time smart meter data flowing in every few minutes, a utility company is in possession of the raw material (read: the data) needed to dramatically improve efficiencies, reduce downtime, and improve customer service.
Specifically, intelligent use of smart meter data will allow utilities companies to:
- Better monitor and forecast energy consumption patterns;
- Identify inefficient energy use at both the macro and household levels;
- Accurately predict potential power outages and equipment failures before they occur;
- Improve customer segmentation and tailor service offerings based on customer behavior.
Utilities companies that take such approaches will both reduce the amount energy and money wasted due to inefficiencies, and potentially identify new ways to package and productize energy deliverables to increase revenue. Instead of reacting to changing market conditions and consumption behavior, utilities companies can be proactive in their approach to energy efficiency and management.
Consumers also stand to benefit. Today, most consumers are unaware of the degree of savings that can be achieved by changing their energy usage habits. Just making energy usage data available to consumers increases the likelihood that some will identify areas either to cut back or shift usage to less expensive times of the day. Taken a step further, consumers may be incentivized to improve their efficient use of energy by having a comparison of their personal energy usage data with aggregate usage data from the surrounding community.
But harnessing smart meter data in such ways presents significant challenges to utility companies as well. The first and most obvious is they must undertake efforts to replace existing meters with smart meter technology. Luckily governments in the US and Europe have adopted policies, such as accelerated equipment depreciation, to incentivize the adoption of AMI. But beyond installing smart meters at customer sites, utilities companies must also:
- Upgrade existing IT infrastructure in order to ingest, process, integrate, and store the torrential streams of data smart meters generate;
- Invest in analytics software, platforms and personnel necessary to transform such raw data into meaningful insights;
- Adjust (and in some cases abandon) decades-old ways of operating and implement mechanisms necessary to take actions when new insights are identified.
Action Item: In order to harness the benefits of smart meter technology to drive efficiencies and increase revenue, utilities companies should first identify the business use cases where such use of AMI data in conjunction with analytics will provide the most value. Then, evaluate related business processes to gauge the level of adjustment necessary to implement data-driven decision-making enabled by smart meter data and analytics. Finally, work with both internal IT organizations and outside parties to evaluate the ability of current data management and IT infrastructure to support such Big Data analytics projects.
Footnotes: * Data sourced from Berg Insight http://www.berginsight.com/
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