Why Smart Meters And Real Time Prices Are Not The Solution

The story that we are often told about modern electricity grids goes like this: In the smart grid, the smart meter is the gateway for all smart appliances in our smart home to know when the electricity is cheap. They will use this information to decide between our comfort level and cost when doing their duty; an economist might say they optimize the utility value.


The beauty of this idea is that the price will align the needs of the customer with the state of the system. If a lot of electricity is available because the sun is shining on the solar cells the price will fall and the smart dishwasher will decide to clean everything now rather than later, meanwhile not only saving you money but utilizing all the green energy from the sun.

Even with the overuse of the “smart” qualifier, this sounds like a very neat world. The problem is, this story is not compatible with the way things are done in the electricity markets now – and they are done this way for a good reason. As we have shown in our research, if current practices for smart appliances would be scaled up prices would rise for everyone.

So how is it possible that the market forces, manifesting themselves in the price of a good, should lead to a collapse of the electricity system, while we rely on them to steer whole economies? The reason is some core misunderstandings about the inner workings of the electricity system and its design.

The price to be charged from the customers with smart meters are called real-time prices. However, what they really are is not what most of us would consider real time at all. Instead, the prices are taken from the so-called day-ahead market, which, as the name implies, closes a day ahead.


While there are electricity markets operating much closer to real-time as we commonly think of it, the prices we see there still have another problem: once we see them, things are already settled. The marketplaces in the electricity system are used as an optimization and planning tool and to cover any short-term deviations from the plan. Once a public price from any of them is known, a plan was already made, or a deviation was settled. In fact, the price is only one part of the result from the day-ahead market, the much more important part is a detailed schedule of who will produce and consume how much electricity at what time.

In other words, your utility company has to make a bet when you will use your dishwasher or any other kind of appliance. It then buys that electricity at the same time as everybody else. Only once the market closes are the prices known. However, how should your utility know what your smart dishwasher will do when the dishwasher will only decide what to do after the prices are known?

With a very small number of smart devices in the system and a production system mainly based on traditional power plants, this is no big deal. The prices at the market are very predictable since they are mainly demand driven. The utility can assume that morning and evening prices during the winter are high, so your smart dishwasher will turn on during midday.

However, if the prices are less predictable because of a high share of renewables the situation becomes more difficult, as the utility must know about the forecast for renewables to estimate the market prices. The problem becomes impossible to solve, however, once the smart devices are numerous enough to influence the price themselves.


To illustrate the situation: if the price in hour A is assumed to be lower than during hour B, because of more solar power, we might assume that all smart devices will prefer hour A. This, however, would drive up the price during hour A. This, in turn, will result in the devices not switching to hour A in the first place, since the price is too high.  So, the utility cannot know how much it should buy for hour A.

The situation might appear easy to solve, only so many smart devices will switch until the price becomes high enough. However, the price does not change during the very hour, since it was made the day before, but more importantly, for many smart devices it does not really matter if they do their duty during hour A or B they just choose whichever is the cheapest one and it is the same for all of them.

The core problem of the idea of smart meters and real-time prices is that the price does not contain enough information to make an operational decision. The information contained is enough to maybe result in long-term human behavior change but it cannot tell a smart dishwasher when is the right time to switch on. When they all just look for the cheapest price between 10 – 18, how should they know that only enough energy for half of them is available at any point in time?

All the needed information is available inside the marketplaces. Every producer and buyer submits his bids and offers to the market, which can then solve for the biggest social welfare. Therefore, if we want to make the most of all the “smart” appliances they cannot hide behind the smart meter and decide what they do based on some price made at least 12 hours ago. Instead, they need to be a part of the market, where their flexibility can be put to use in the best way for everybody.

These findings are described in the article entitled Implementing flexible demand: Real-time price vs. market integration, recently published in the journal Energy. This work was conducted by Florian Kühnlenz, Santtu Karhinen, and Rauli Svento from the University of Oulu, and Pedro H. J. Nardelli from Lappeenranta University of Technology. This work was funded by the Strategic Research Council at the Academy of Finland.



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