The Knowledge Exchange / Business Analytics / Smart meter data analytics

Smart meter data analytics

Think smart. Think analytics.

Lately I’ve been particularly energized, likely due to it being the beginning of the year when new projects kick off and conversations revolve around taking fresh approaches. So it’s fitting that one of the projects I have been involved in deals with the analysis of smart meter data from the energy sector. The use of smart meters is a developing field in the United Kingdom; utilities are interested in gathering consumers’ energy usage data on a much more granular level than ever before. A so-called smart meter is installed in a household to allow consumers to view their household electricity consumption on a real-time basis, while also transmitting this information back to the energy supplier.

The smart meter not only allows consumers to have a better understanding of their energy consumption, but also allows energy companies to understand the detailed consumption patterns of their consumers and plan more accurately for energy needs. This new strategy will benefit the entire energy supply chain, including energy retailers, distributors and generators. It is also a UK government-backed initiative with a full rollout of smart meters to residential and small business customers planned to be completed by 2019.


Ten thousand times the data

Today in the UK, meters are typically read on a monthly basis, since most electricity meters are situated inside and thus meter reading is reliant on someone being home to provide access. Instead, estimates are often relied on for billing and consumer budgeting. Smart meters can record data on a more granular level, providing, for example, half-hourly consumption information to the energy supplier via wireless data networks.

With approximately 30 million residential houses in the UK, getting half-hourly readings would equate to 1.6 trillion smart readings a year. This ten-thousand-times increase in readings means BIG data! With big data there’s great potential to mine for insights into customers’ behaviors.

Customer segmentation to find your best customers

For energy providers, the most costly consumers to serve are those who demand energy during a daily peak period, which typically occurs in the late afternoon or early evening. If utilities do not generate or contract enough energy to meet peak demand, they are forced to buy short-term contracts through the wholesale energy market. The wholesale cost of energy is highest during peak, so with current single-rate costs, energy companies are likely to be making little or no profit – maybe even a loss – during this peak period. To prevent this operating loss, energy suppliers want to identify those consumers who are lower than average users during this peak period, since they have the potential to be the most profitable customers. They may also want to identify heavy peak users to modify their usage patterns or avoid acquiring them as customers.

In a recent project, we applied segmentation analysis to half-hourly usage data, identifying the various types of usage patterns, for both “peaky” and “nonpeaky” customers. Since suppliers want to smooth out the demand made by peaky customers, they can offer them financial incentives to move their consumption to off-peak hours using time-of-use guidelines with lower rates during off-peak times. This could entice consumers, for example, to set their dishwashers and dryers to run during off-peak hours or set heaters in the winter to come on before arriving home from work.

Stress relief: Dual-purpose data

Another purpose of the smart meter is to reduce the strain on the system during heavy usage periods; as electricity cannot be economically stored, it has to be generated on demand – this means the more peaky the demand, the more unused (or wasted) generation capacity there is for other times of the day. Once the customer energy usage segments have been identified, other data such as socio-demographic information (e.g., household size, location, household income) regarding consumers can then be overlaid onto these segments to identify which consumer groups display similar consumption patterns.

An example segment (Figure 2), displays the standard usage curve (dotted line) and the consumption pattern identified in the segment (solid line). The standard usage curve is used throughout the industry as a representation of average usage across the population. It shows a slight peak in energy usage around 8-9 a.m. and a more extensive peak in the early evening. In the example segment, we identified that usage in the weekday evening period was 40 percent higher than the standard usage across the entire population. This clearly identifies a segment which is “peakier” than the normal peak, and maybe a customer group an energy supplier would want to target in order to try and spread energy usage throughout the day.

Consumers benefit from this segmentation through greater understanding of their own energy consumption, allowing them to better manage cost of their consumption. It also allows them to understand which energy rate may suit their consumption needs more cost-effectively. Suppliers benefit by meeting energy demand without having to build expensive power-generating capacity, improving efficiencies in load management and smoothing out demand by offering consumers more appropriate rates. Everyone benefits by better understanding and managing energy demand, so that we can ensure sustainability of energy supply for future generations. Analytics can also be used in forecasting future demand to better plan for strain on the network and determine when and where new generators need to be built.

There is a magnitude of potential within the field of smart meter analytics, and this is just the beginning of what can be achieved when analytical techniques are applied to mine a rich new stream of information.

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  1. RobertWilliams
    Posted February 16, 2012 at 11:49 pm | Permalink

    Why Does This Article Ignore That The Government Has Recently Removed The Mandatory Policy From Smart Meters and Made It Voluntary.

    This will reduce the installation of smart meters by huge magnitudes.

    Customers are concerned with issues of Privacy, Health, Higher bills and National Security risks via millions of unprotected Wireless access points at each meter.

    • Iain Brown, Analytics Specialist, SAS
      Posted February 17, 2012 at 10:21 am | Permalink

      Hi Robert,

      Thank you for your comment and interest in this blog post.

      The main focus of this post was to highlight the potential benefits that could be realised from both the consumers and suppliers of energy in the UK. You are correct in saying that the UK Government have recently confirmed that they will no longer be rolling out smart meters on a compulsory basis. However, although it is of course right that consumers should be given the choice as to whether a smart device is fitted within their premises, this has the potential to have long term negative connotations to the UK’s ability to manage and lower its energy usage. It is also worth noting that the final design and specification of the smart meter devices has yet to be decided, and the issues that you mention (privacy, health implications and national security risks) will all form important considerations in the final specifications.

      As highlighted in this post consumers could realise benefits from the use of smart meters, giving them a better understanding of their energy consumption as well as managing their costs. I therefore believe that with the right information and proper advice from the UK government in educating consumers there is a strong likelihood that resistance could be avoided.

      Thanks again,


      • RobertWilliams
        Posted February 18, 2012 at 5:59 am | Permalink


        Energy monitors assist customers by giving them real time information on energy usage of every electrical device in their home. The energy monitor can be hooked up at the fuse box (circuit breakers), it does NOT emit RF radiation and energy monitors cost less than 10% of a smart meter.

        Smart meters do emit RF radiation. Smart meters do NOT isolate electric use for different devices for customers and smart meters require professional installation at significant cost plus the high cost for the meter itself.

        During this age of security concerns, Wireless smart meters offer millions of unguarded access points to the smart grid.

        I understand the concepts, but in practice the cost for customers and society overwhelms the promoted advantages of smart meters that are NOT occurring in practice. Utility companies and meter manufacturers love the smart meters and techies like to play with the systems, but for customers and society smart meters are a disaster.

        • Iain Brown, Analytics Specialist, SAS
          Posted February 20, 2012 at 3:03 pm | Permalink

          Hi Robert,

          As you are aware, energy monitors do not transmit the electricity usage back to the energy supplier. This therefore does not allow the energy supplier to understand their consumer’s consumption patterns and better manage the use of energy. Consumers may also not realise any benefit from the use of an energy monitor, as it is less likely to change their usage patterns in the long-term. With the implementation of smart meters, analytics can be employed to understand consumer patterns more precisely and to help suppliers proactively offer them the right tariff.

          With regards to cost, the roll-out of smart meters in the UK is a government backed initiative and there will be no upfront costs to customers upgrading to a smart meter (with the cost of roll-out likely to be recouped by marginally higher gas and electricity bills). With regards to RF radiation there has not been any medical evidence suggesting that the use of smart meters is unsafe.

          This all falls within EU legislation which is aiming for 80% of consumers to have a smart meter installed by 2020 as part of a long term goal of helping EU countries to meet energy-efficiency targets. This would not be possible through the sole use of energy monitors.

          The key takeaway here is that through analysing smart meter data the country as a whole can benefit from increased awareness of energy consumption as well as the ability to better forecast future use, which could in turn save the need for expensive additional power-generating capacity,

          Thanks again,


      • Posted March 1, 2012 at 10:40 am | Permalink

        Hi Iain

        May I ask when the decision to NOT make smart meters compulsory was announced and where?


        • Iain Brown, Analytics Specialist, SAS
          Posted March 2, 2012 at 11:36 am | Permalink

          Hi Steve. The decision by the UK government to no longer make the rollout of smart meters compulsory was made last month:

          But as I mentioned in my comment to Robert I strongly hope that consumers will not only understand the benefits that they can personally achieve from smart meters but also the benefits to the UK as a whole, with regards to meeting our energy-efficiency targets.

  2. Posted February 27, 2012 at 9:13 pm | Permalink

    Iain, great article. I agree completely with your contention that “consumers benefit from a greater understanding of their consumption”. Non-residential consumers often see more immediate benefits because their use & costs are greater. I offer a smart meter analytics service to commercial & industrial users at Much more than simple visualization, identifies potential savings opportunities from this detailed record of historical use.


    • Iain Brown, Analytics Specialist, SAS
      Posted March 2, 2012 at 11:24 am | Permalink

      Thanks Dave, it is interesting to hear that you have had similar experiences in the field. I agree that non-residential consumers have the potential of realising greater benefits quicker and this will most likely be an imporant focus in the UK as well.

  3. Posted February 29, 2012 at 11:55 pm | Permalink

    Great article. There is a misconception about energy monitors. These devices do not provide consumption on every electrical device unless one is referring to the TOTAL consumption of the home. A device by device consumption tracking is not part of the smart meter form factor. This can be done by adding a program that determines load signatures from the power usage (very expensive hardware/software) but is not normally included nor developed in smart meters. Nor is there a continuous use power graph provided to consumers so that can see the power spikes and time of occurrence to correlate to appliance usage. Just my thoughts.

    • Iain Brown, Analytics Specialist, SAS
      Posted March 2, 2012 at 11:52 am | Permalink

      Thanks for your thoughts Bill this certainly clarifies some of the conceptions regarding energy monitors. It will be interesting to see moving forward whether there is a push from consumers for device level consumption levels, or indeed whether energy providers would be interested in harvesting this level of data through additional hardware/software.

  4. Tony Johnstone
    Posted March 1, 2012 at 10:40 am | Permalink

    Both commercial and domestic customers are already familiar with day and night tariffs – if the “smart” meter concept starts by extending the use of these, there should be little problem with persuading customers – and little resistance.
    Additional banding and a domestic equivalent of Triad warnings could be phased in gently – all by agreement with the customer as our politicians prefer (and I tend to agree with).
    So – where is the problem – for domestic consumers a signal from the meter and a basic home automation arrangement could start the ball rolling now. – and do it digestible phases at that.
    Start with the time based signal of old – add the use of comms when necessary. Simple upgrades on an expandable PC card I would have thought.

    • Iain Brown, Analytics Specialist, SAS
      Posted March 2, 2012 at 11:43 am | Permalink

      Thanks Tony, you make a very good point. The key to avoiding consumer resistance is the way in which the smart meters are introduced. I feel the UK government have a guiding role in this and need to educate consumers with regards to the overall purpose and beneficial effect smart meters present.

  5. Posted March 6, 2012 at 2:31 am | Permalink


    Interesting article. We’ve been doing “smart meter driven energy analytics” for the last several years. Extensive data available in US for commercial & industrial customers at 15 min intervals. We use this data to understand the systemic issues in building operations using our patent pending decision support systems. We also simulate the buildings using methods similar to those used to quantify Value at Risk in commodity portfolios. We also provide 7 day running forecasts for kW and Kwh taking into account temperature, dew point, wind speed, cloudiness and building memory.

    We’ve done more than 325 buildings across 10 different industries. Truly amazing when you use almost 6000x as much data to understand patterns and suboptimal performance than just monthly bills.

    Most annual savings in 10-20% range often with little additional expense.

  6. Posted September 11, 2013 at 11:50 pm | Permalink

    Will you please let me know detail about this smart meter Working. Currently i am in last year of Engineering and we are doing Project on Smart Meter Data Analytics. From your article, I got so much useful information,thanks. Please mail me at if you have some more detailed information about this smart meter data analytics.

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