Smart Grid at the Doorstep
In the past, the rapid development of power distribution networks was mirrored by the same development in energy measuring. There were big names involved in electric meter development such as Thomas Edison, Lord Kelvin, and even Sir Hiram Maxim, the machine gun inventor.
Conservative Evolution in Power Distribution
It is possible to draw another parallel with power distribution networks: almost all subsequent developments have been very conservative. This slow evolution process has been interrupted by political intervention with the nearly fanatical efforts to decrease the global carbon footprint.
However, impact analysis of this effort has not been undertaken, and the authors of the policies have disregarded the fact that energy is expensive and challenging to store, and that the distribution system needs to be in a state of equilibrium between production and consumption. Moreover, under the pretext of low efficiency, purely ohmic loads are forced out of the system.
Challenges in Modern Energy Systems
The result is that there is dynamic, mostly unpredictable production of energy out of classic distribution schematics on one hand; and on the other, modern appliances with high rates of reverse network influenced by higher harmonics.
The natural dampers of these higher harmonics, such as incandescent bulbs, are now no longer being produced. It serves no purpose to bemoan this state of affairs. Instead, we have to look for a solution that will be available to control and stabilise the state of the power distribution network.
What are the Limitations of Current Systems?
The systems deployed, based on the European directive ‘20-20-20’, have one basic disadvantage: they concentrate above all on decreasing energy consumption. They may help to decrease costs, but the question remains to what extent and for whom?
These expensively built systems (with the final deployment deadline of 2020) are helpless in dealing with critical-state solutions. There are two main reasons for this.
Firstly, they are not intended to support these states and secondly they are controlled and managed from the one central point that results in their high latency. The big accidents have, regardless of the place of formation, one common attribute: chaining of (often) banal failures.
Here we have scope for developing a device with the working title ‘electric meter’. Besides the obvious ability to measure energy, these devices have one strategic characteristic: they are located at every load point. It follows that they should support measures to, respectively, prevent emergency states in distribution systems and minimise the negative impacts of these states.
The Dilemma: How to deal with Big Data?
Pilot projects, based on the EU directive ‘20-20-20’, have revealed the phenomenon of ‘big data’. If we think over this problem, we find surprisingly that it makes no sense to waste time on the big data issue. From a logical point of view, the utility needs one energy reading – either monthly or yearly – and about six times daily to switch tariffs. You could thus ask: why has this problem actually appeared?
The answer is relatively simple: we have two-way communication, so we naturally download extra data and information – for example, voltage values – every 15 minutes. The distribution system is three-phased, the power is both active and reactive, and moreover we include orientation direction. We end up with five values per phase, which means that we send 15 values every 15 minutes.
Example: Data Count in Czech Republic
Let’s take a small country like the Czech Republic. Assuming two people per electric meter on average, we end up with a total of five million meters. The system described above would thus generate 75 million pieces of data every 15 minutes!
Daily, the number reaches over 7.2 billion values of data that practically nobody needs. If you add inappropriately chosen protocols to this terrifying number, a colossal problem emerges from the triviality.
This is an illustration of just one potential data challenge – downloading too much data for your needs. Yet how do you proceed with a suitable solution for a large and extensive system? All information is directed to a central point where subsequently decisions are taken.
Unfortunately, this central control is very expensive and needs very high communication capabilities for throughput. Moreover, if the channels are slow and a little permeable (PLC, GPRS) a large number of end-devices may stay unserved.
Better Solution: The Distributed Control
A better way to solve this problem is to transfer, to central control, only the important and critical data. The management should be distributed to the place of its execution. The centre is then responsible for strategy creation.
This solution significantly reduces the big data problem, as only the necessary information goes to the control centre. The system is thus dynamic (even if the communication channels are slow) because it is available to solve emergency situations at source and effectively uses a mass of small tools, such as the above-mentioned modern electric meters.
Obviously, this system also has its problems, but fortunately its characteristics are different and crucially have no influence on system control.
Conclusion
If you see an attractive picture of a smart grid system fully based on central control and are told that the slowness of communication channels will be solved, as if by a magic wand (preferably by 5th or 6th generation networks), you should not believe it!
I am absolutely convinced that if the smart grid concept is to be fulfilled, it is necessary to use distributed control. The cost constraints, time difficulties and technical challenges give us no alternative.