Energy-Saving News

Smart Meter Bills Will Only Make Sense To Smart People

Posted on 20. May, 2009 by Ross in Energy Prices

Complaints to energy companies about electricity bills will not be solved by smart meters - due to the extra levels of complexity in calculating the charges, they’re only likely to get worse.

Smart meters are very much in the spotlight at the moment, with governments and energy companies keen to install them in every household worldwide. Governments stand to decrease national carbon emissions, energy suppliers aim to make meter readers a thing of the past and even out the lumpy demand for electricity which creates the need for surplus stand-by power stations. Consumers are being told that smart meters will lower their bills, and the key element of smart meters which proponents of the technology cite will deliver these savings is dynamic demand-based pricing.

What is Dynamic Pricing?

Instead of charging a flat rate for energy consumption, dynamic pricing enable smart meters to take into account when the energy is being used as well as how much. The price then varies depending on the demand for energy at the time, with peak levels of demand increasing the price of energy. The pricing structure is used by the energy companies as an incentive for consumers to use less energy when the price (and the demand) is high, deferring their usage to times when it is cheaper.

Simple Time-Of-Use (TOU) schemes achieve this by creating a simple demand-based price band structure  - classifying periods of the day as off-peak, mid-peak and on-peak for example. The times of day which these bands occur on are fixed, so that consumers know the cost of using energy at any given time and can choose to alter their behaviour accordingly.

Real-Time Pricing (RTP) offers another step forward in smart meter dynamic pricing, with prices altering on a systematic scheduled basis (e.g. hourly). The smart meter receives the price from the energy company and displays it to the consumer, who can moderate their behaviour accordingly.

One of the longer-term goals of smart meters is for household appliances to contact the smart meter via wireless communication to find out the current price of energy, and only turn on when the energy price is suitably low. Washing machines, dishwashers, thermostats are two of the prime targets of this functionality, but fridges and freezers would also benefit by turning off for a couple of minutes during strong price/demand spikes. Such intelligent optimisation holds the potential for more savings on household bills if a more responsive RTP scheme was in play - prices updating every 30 seconds, for example - and would also produce the best results for energy companies looking to smooth over lumpy demand profiles.

Whilst a highly-dynamic RTP scheme has the greatest potential to save households money, the additional complexity in the bill calculations also creates a new problem - will consumers understand their new energy bills?

Fixed Rate Bills are Easy To Understand

Currently, when the household energy bill gets pushed through the letterbox, it is a fairly simple task for the consumer to check whether the bill is correct - they can just look at the reading on their electricity meter! If someone doesn’t trust the accuracy of an estimated energy bill, they can pick up a calculator and work out the actual bill themselves:

Energy Bill = (New meter reading - Old meter reading) x Energy price

The maths involved is taught to 5-year old kids, making the current billing system transparent and easy to understand - and contest. Consumers can easily tell if their bills are wrong and challenge them effectively.

The Mathematics of Smart Meter Dynamic Pricing

Whilst smart meters will remove the scourge of estimated bills, the energy companies are replacing one source of mistrust with another. Errors with estimated bills are easy to spot and contest, whereas the structure of dynamic bills will be far beyond the capabilities of most households to calculate themselves. In order to provide RTP schemes to households, smart meters will need to replace the simple subtraction and multiplication above with summations across sprawling data sets of price periods (the time across which a single price stayed constant):

Energy Bill = Σ (Energy used during price period (kW) x Energy price during price period(/kWh) x Price period duration (h))

Know what the ‘Σ’ sign means? Most people won’t.

The ’Σ’ means in this case to sum all the individual sums for every discrete price period across the whole timespan of the billing period. If the price of energy was updated every 30 seconds, which would give the system the responsiveness the energy companies need to iron out demand spikes, the summation would involve 262,800 price periods for every quarterly bill. That’s over a million data points per year!

In Software We Trust

That’s obviously too much data to handle with a calculator, so the consumer would have instead to rely on whatever software or online application the energy companies will provide for bill tracking via computers. Herein lies the new issue of trust: consumers will be forced to trust whatever data their energy company provides them with. The complexity of the bill calculations will make self-verification nigh-on impossible for most consumers.

It will also make interpreting the data far more tricky. Currently, consumers face a simple choice: if their bills are too high they can choose to try to use less electricity. Dynamic RTP schemes make the issue more complicated: consumers can decide to either cut consumption or shift the timing of it (with the latter option severely impacting governments’ desires to reduce carbon emissions). Some of the decision-making also becomes more complicated, such as “what price threshold is it too expensive to run certain intelligent appliances at?” Consumers will rely more and more on their computers telling them when they should do what in order to save money, since most people will be unable to interpret the resulting usage-cost graphs themselves.

The software involved will need to be able to read all the data and make sensible suggestions from it - “use less energy at 5:30pm” just won’t work. “Boil your kettle at 5:40pm or 5:25pm instead of 5:30pm” on the other hand is the sort of analytical detail the software will need to go into in order to make a tangible difference to the consumer’s usage patterns. Google’s PowerMeter in it’s current incarnation certainly isn’t up to the job.

You Don’t Need Smart Meters To Save Energy

Consumers are already highly energy-conscious. Years of escalating fuel costs have made people extremely aware of the costs of transportation. Consistently rising energy prices both for gas and electricity have pushed massive numbers of households into ‘energy poverty’ and have forced people to cut energy bills to save money. There are plenty of ways to save money right now on energy bills: insulation, low-energy lighting, more efficient heating and micro-renewable electricity generation both at home and at work.

To see the true saving benefits from dynamic pricing and smart meters, households will have to invest in new appliances, as well as footing the bill for the smart meter within their utility bills. It’ll mean using the computer for longer in order to check bills and to update appliances with new operation-price thresholds via energy-management software (which may well need expensive purchases and upgrades). It’ll need consumers to trust energy companies to protect their usage data, to calculate the bills properly and to charge them a fair price at all times based on demand. The latter point will always remain an issue, though, as British utility analyst D.J. Bolton noted back in 1938:

There is general agreement that appropriate tariffs are essential to any rapid development of electricity supply, and there is complete disagreement as to what constitutes an appropriate tariff.

Related posts:

1. Who Benefits From Smart Meters?
2. Microsoft Hohm + Smart Meter = Energy Savings?
3. Ford Gets Smart: Electric Cars Will Talk To Meters, Charge At Cheapest Rates
4. Smart Meters in California; Stupid Meters In Scotland
5. Brighter Future For Interoperable Smart Meters And Energy Efficient Appliances

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Tags: consumer, dynamic pricing, household, save energy, smart meter