So, welcome back again to the next part of today's lecture.
I just noticed that the recording of the voice in the first part was
done using the internal microphone of my laptop, which is not that bad
because the microphone is directly in front of me.
I noticed that the level, the loudness was a little bit too high, and
so I checked it again.
The panel was not visible when I executed it.
Now I saw it, and now I changed it to the real microphone, so I hope
the power quality, or not the noise, but the voice quality will be
better in this part.
I wanted to address briefly the topic of the exam.
Some of you asked that, so let me switch back here to presentation
mode and just make some annotation with respect to the exam here.
For the exam at the end of this term, you should register by the
latest July 7.
July 7 is the deadline for being able to register for the exam for
this course, and then I can see how many actually have registered, and
if it's more than 10 or something, I will decide to have a written
exam, otherwise it will be an oral exam.
If I look at the number of participants in the course, and what I
normally see, I assume that it will be more than 10, but maybe that
some of the students, like some just said, that they would prefer to
have an oral exam, and since at the end of the winter term, usually
there are smaller numbers of students who register for the exam, they
would go for that option.
So I don't know what will happen.
If it's a larger number, you get an oral exam, which will be
essentially, certainly covering all the topics that we have in the
course, and there's a little bit of a difficulty, certainly for you,
that you did not have a chance during the course to actually show what
you know about the course, about the contents, because I don't offer
tutorials, so you don't get feedback on the degree to what extent you
actually know or have learned what I have told you, but I think the
exam will be set up in a way that if you have listened to the course
and understood it reasonably, you will have no problem getting a good
mark in the exam.
So we still have to set up that exam, but I think it will be not that
much of a problem to provide you with a reasonable exam such that you
can show the degree of knowledge that you have acquired here.
Register by July 7, and after that I can tell you whether it is an
oral exam or a written exam.
You have a question?
You don't know how to register?
You go to the website of...
So let me just...
Yeah, for that you should send... I don't know how we do that.
Send a message to Andre Wiesner, or does it say here anything?
If I go to the website of...
So here we have current information.
So there is International Time-Limited Students something.
I don't know what that is about.
That's just the normal information we have.
I don't know what this is about here.
This actually is in English.
I don't know.
Maybe you register with...
And then we put the information on the website of this course.
There are the announcements.
And then you get the information how you should register.
We find out how to do that.
You either send a message to Andre Wiesner, the person in our
institute who is actually taking care of the exams, or you might have
to register with the Faculty of Mechanical Engineering, the
examination office there, for Schwenk.
Maybe she does it.
I don't know who is actually doing it.
We find out.
You get that information.
Okay.
So, just to repeat, you...
On the day?
Hm?
On the day?
The day?
The date for the exam.
Is...
Date of the exam is either the 22nd or 23rd of July.
Only if it's a written exam.
If it's an oral exam, it will be in that week or the week after.
There I'm much more flexible.
But written exams are on those two days.
In principle, it could also be the 21st, but on the 21st, we only have
very few exams.
We have the very large exams, and usually not smaller ones.
So, smaller ones usually are on the second and third day of that exam
period.
And in my institute, we just have the policy that Monday to Wednesday
of the week after the lectures end are the exam dates.
And so that's the AIFB exams.
And then...
It's a very clearly predictable way of having the exams.
You always know those three days, and that's it.
Yeah?
You cannot register after July 7th.
You have to do it... the deadline is July 7th.
Deregister, if you don't want.
So, there's a very flexible arrangement.
The regulation is not really in favor of those who run the exams, but
in favor of the students.
If they don't show up, they don't show up.
If they are polite, they deregister.
Would be appreciated.
Hmm?
If in an oral exam, you don't show up without telling that you will
not come, then you get zero points, or you get a five.
You fail.
But if you select for an oral exam, you say, oh, I cannot come, then
you cannot come.
Yeah?
This is very flexible, very positive for the students.
Or you could argue whether it's really positive or negative.
Because sometimes it's better to have strict dates, and you have to
follow those things.
So, that's different in other countries.
There, you register for the exam when you register for the course, and
you have to show up.
If you don't show up, then you get a fail.
Very strict.
We are very tolerant and flexible.
Okay.
So, we were looking at ways of optimizing our energy management.
And I would like to show you briefly how we do that in that generic
architecture, this organic smart home interface, or that energy
management system.
So, it is...
Well, the problem is that we have different devices, which would like
to run.
So, the person, the resident in the home, says the laundry should be
done by 6 p.m.
in the afternoon.
So, that's the sub-problem washing machine.
Somehow this...
So, this objective to have the laundry done by 6 p.m.
is formulated as some sub-problem.
And that sub-problem will depend on when actually was the event where
this intention was specified.
When did you actually put the laundry into the washing machine and
say, now I provide time till 6 p.m.?
That's my degree of freedom for the washing machine.
The same could happen for the dishwasher.
You get a sub-problem for the dishwasher.
You put in the dishes, say, okay, should be done by 5 p.m., should be
finished.
And the combined heat and power plant might need to run for about two
hours during the day to provide certain...
either to provide heat or provide power.
And so you look for the appropriate time of the day where this should
run.
Now, this has to be coordinated in a reasonable way.
You have to find the best possible schedule for those devices.
There may be more devices in the house which have to be included in
that.
There may be more devices in the house which will just run anyway.
And you'd have to take care of their requirements and then find a
reasonable schedule.
And the schedule will depend not only on prices, but maybe also on
power constraints.
So you have to run some kind of global optimizer.
And the result of that, where you optimize with respect to certain
goals that you have, so cost-effective or renewable energies or
whatever you like, and you have certain external signals like power
constraints, you get some result solutions for these different
components and appropriate times for running your devices.
So you have here different starting times for those devices.
The question is how we can actually find out that these are the most
appropriate starting times for the devices.
So how do I describe a washing machine, a dishwasher, a combined heat
and power plant, such that I can optimize their schedule and get
solutions which actually optimize what I would like to get.
So how do we do that?
You have your washing machine which is loaded with some kind of
laundry.
This means you put in some laundry there, you push some button in the
washing machine, and this is noticed as some activity by your
observer, the local observer.
Now this is transformed into some kind of sub-problem.
That's what I mentioned on the previous slide.
You create a sub-problem describing this person has just put laundry
into the washing machine, closed the door, and now it should start at
some time.
And it's provided some kind of deadline for having that washing done.
And then this is sent to the global observer.
So we have this sub-problem.
The same is happening for other devices.
So we get several of those sub-problems which are currently either
waiting for getting scheduled or just being generated.
Then this is sent to the controller.
A description of what's just happening there.
And then this is optimized by some kind of optimization process which
I will show you in a moment.
Then this is optimized and the sub-problems or those partial solutions
for the different devices are sent back to those originating devices
and they will then be started at the appropriate times.
So this is what's happening in that architecture.
So it is, compared to what we had seen before, it is this multi-level
hierarchical system.
They can do something locally.
They can send information upwards and get some information back.
This here is some kind of registry is necessary for actually
registering all the individual devices such that the global observer
actually can deal with them appropriately.
So the optimizer was there.
That's the important point.
How do you actually do that?
And that's an evolutionary algorithm.
You know what an evolutionary algorithm is.
I have shown you that in one of the previous lectures.
Just to repeat, we generate some initial population.
We evaluate all the elements in that population.
We have the different potential schedule.
Evaluating something in this context would mean we look at the power
profile that is generated by a schedule for starting all those
devices.
And then we see how they perform.
We select certain elements from that population.
We recombine them, perform crossover and mutation.
Here, mutation.
Evaluate again.
And if we are satisfied with the quality of the best solution, we just
choose that and we are done.
So that's the optimizer.
And the question is how we actually code all the individuals.
We need some kind of genotype, genetic representation of our devices.
And the question is how do we do that?
How do I code the washing machine sub-problem that wants to be started
or carried out sometime in between, let's say, 2 and 6 p.m.?
We have to specify that in some way.
So that's the question, how we actually construct an abstract sub
-problem.
And for that, we have designed a system where you specify a certain
bit vector of a certain length.
So this is representing, for example, a starting time on a device.
Or essentially, if it is a bit vector of length k, it means we have 2
to the k different situations that we can specify.
2 to the k different values for those k bits.
And that means we can distinguish 2 to the k different ways of solving
that sub-problem.
For every situation that is coded there, we have to be able to
interpret what it means with respect to the power profile.
So if we have a certain value there, this will result in some power
profile for the specific device.
So a washing machine might have something which looks like that.
And that's just in some time frame, which certainly might be moved
backwards or forwards depending on the starting time that you choose.
So this is the load profile of that device depending on that value of
the bit vector.
Now this is just some internal representation.
And then, at the end, you need an actual starting time for your device
for some specific time of the day.
So you need some kind of back transformation of this bit vector into
the solution that has to be sent to the device.
This here is just an internal evaluation function which might be an
abstract view on what's actually happening in reality.
And this back transformation also has to be provided.
Now this here, if you have specified all this, you have specified a
way of, or some kind of driver, or some kind of optimization driver,
or some descriptor that is the problem part which describes the
problem to be solved for the global optimizer.
So you come up with a new device.
If it wants to be optimized, it just sends its problem part to the
optimizer.
So, again, subproblem might be typical profile of a washing machine or
dishwasher.
This is such a typical profile.
Now we look for the most appropriate time for doing that.
The latest possible time would be that one.
So the deadline is DJ in this case.
PJ is the runtime of that device.
So DJ minus PJ is the latest possible starting time.
And this here, all those times in between are the potential starting
times which we have to distinguish.
The question is, how do we discretize that?
Is that actually a real interval?
Infinitely many values, doesn't make sense.
Maybe we just say, okay, every five minutes or every ten minutes is a
reasonable discretization for that.
We just have to select a certain way how to specify the different
possibilities.
So this is the degree of freedom of that device.
Depending on this, like this was the deadline at that point in time,
it should be done.
So this, like knowing the profile of the device, we know the degrees
of freedom.
And so we have to divide that, to discretize that into an appropriate
number of time slots.
And so if we have 2 to the K time slots, we need K bits.
And so that is our bit vector of length K.
And then we have the evaluation function which would map any bit
vector of length K into a profile.
This is somehow the profile, a certain sequence of power values over a
certain specified amount of time.
So you just have to provide this sequence of power values.
That's the profile, which has to be some way put into a large
evaluation.
But this is showing what this system actually is providing as a power
profile.
And in the end, you have to be able to back transform that into a real
starting time.
And it means, for example, here this 010011 might mean a certain
value, and this has to be re-transformed into a real time, which is,
you have to take this Rj, which is the release time of your device.
These different values in that interval, that degree of freedom, time
interval is numbered from 0 to 2 to the K minus 1.
And you have to re-transform that into the actual starting time.
Very simple way of doing that.
Very straightforward.
And then, this is the sub-problem for the component.
And you certainly have to provide some reasonable way of describing
that and describing that.
An example is if the release time is 2 p.m.
and the final time here, let's say, is you provide 6 bits as degrees
of freedom.
You have 2 to 6, for example, minutes.
It's the way how you interpret that.
If you say it's minutes or 5 minute intervals, that's the number of
time slots you can actually provide here.
If we say this is minutes, it would mean 63 minutes that you have as
potential starting times.
And if, for example, here this value 010011 would have the value 19,
it would mean that you would start at 19 minutes past 2.
For example.
One possibility.
So this is the way we would actually generate the
problem part.
So this is subproblem for the component J.
And then we have, in this way, subproblem descriptions for the
different components.
The washing machine, the dishwasher, the combined heat and power
plant.
You can imagine that for the dishwasher and the washing machine, it's
almost the same way of specifying that.
The power profile will be different, but the type or the way you
specify that is very similar.
For a combined heat and power plant, it's not that obvious how you do
that, because you can run it any time inside a certain optimization
interval.
As you see, 43 bits.
You have larger variability for the combined heat and power plant that
you have to specify.
I don't go into the details of that genotype.
This results in the genotype for the global optimization.
It's just the combination of the bits of those three devices.
And then you perform a genetic algorithm.
Perform a genetic algorithm means this is one individual.
And now you have to put that into the population.
So this is the current or the initial population, all those bit
vectors.
You evaluate.
We will just see how we evaluate that.
You select corresponding to the results of the evaluation.
The higher probability, those that perform better.
Maybe you use tournament selection or whatever you might think is
appropriate.
You perform recombination and mutation.
You get a new population.
So how do we actually at some time, you actually have in the
evaluation.
This is shown now.
In the evaluation, you take one of these individuals.
And now you have to evaluate that.
It's just a bit vector.
The optimizing algorithm does not by itself know how to evaluate that.
This is provided by the description sent from the individual
components.
So it's a very modular and in some way self-organizing approach for
optimization.
You have these different components and they have their profiles.
So for each of those components, you have a certain profile, which is
generated corresponding to the current value of those bits here.
And then you have to combine that into an evaluation of the complete
system.
So you have to join those three profiles into just one profile.
So the resulting profile is just some superposition of those three
individual profiles.
You get the profile for the complete system.
This certainly is done in a standard way of combining different load
profiles into one.
And then you can evaluate what this profile means with respect to the
objectives you have for optimizing.
Then, yes.
The CHP is generating power.
It's not consuming power.
It's generating power.
And so you have a certain fitness function which will evaluate this
profile and then you have an evaluation of this individual.
And the evaluation will be done like the fitness function depends on
the objectives that have been specified before.
And then you just run that as often as you like or until you finally
are satisfied with the results and then you have the best individual
of the last generation which is taken as the solution to use.
So it's a metaheuristic, as you know, evolutionary algorithm.
You extract your bits from the genotype, use your subproblem
descriptions, in particular the backtransformation, you decode the
solutions and then you get in your local UOC unit, you get the real
starting times.
And so in this way you have actually found optimum solutions for that
or at least something which looks sufficiently positive.
You're never guaranteed to get the optimum because you just use an
evolutionary algorithm which is only providing something which is more
or less good and usually it's an improving process.
It's set up such it is never deteriorating but it's always improving
and so the result usually is quite acceptable or should be acceptable.
Okay, this is actually implemented in our smart home on campus and
used by if we had living phases there, students looked at it or those
who lived there tested that and it's running quite well.
As you saw on these slides where we showed something on self
-consumption and self-supply, the effects are significant.
Okay, now this has been transferred into a different setting in our
Research Center for Information Technology, FZI House of Living Labs.
We have actually built something, we have built some kind of microgrid
into that house so we have here a living lab, so-called living lab.
What's a living lab?
In a living lab, it's not that it lives and needs to be fed and so on,
but it's just a lab where you can see what research or what kind of
research is done.
We show the results of our research, we show ongoing processes and
cooperate there with companies on more or less innovation projects.
So it's on research and development there in the Research Center for
Information Technology whereas in the university it's more on
fundamental research.
So here we are extending the work we have done on the energy
management system and we have extended the software there.
So it's just a very large area where we have different labs, in
particular we have a smart home lab with nice appliances in the house,
in the kitchen and some more things.
We have ambient assisted living in there for tools for elderly people.
We have a lab on smart energy systems where we can show what we are
doing there and we have other areas which are of interest.
So what kind of energy relevant systems have we integrated into that
house?
Essentially you could say it's some kind of microgrid.
Now the term microgrid is a very unspecified name.
Microgrid can be something which is part of the distribution grid.
Here we say it's just something where we have some kind of power
generating capabilities.
Solar panels and combined heat and power plant.
We have some storage facilities.
So here, battery storage.
We can store power.
We have cold water tanks.
We have hot water tanks.
So we can generate hot water using the combined heat and power plant
or using the condensing boiler.
In winter we need that as an extension to the combined heat and power
plant which doesn't have the necessary capacity on its own.
We would like to have cold in summer.
Cold water to cool down certain rooms.
In summer we can use the heat from the combined heat and power plant
to generate cold water in the absorption chiller.
And so in this way we can then generate cold.
And so we also have certainly power inverters for the solar panels.
And so we have all the ingredients you need in a microgrid.
We have generation.
We have consumption.
We have flexible storage.
And we not only have that with respect to the power grid or power
system, but also the thermal system is included in there.
And so we can experiment there with the thermal and electric energy
management system which we are extending there compared to what we
have in the energy smart home lab.
And there are all kinds of other living labs integrated into that
house.
So this is again showing the different devices we have.
We also have here for example intelligent metering systems.
We have smart plugs.
I mentioned all the other.
So dishwasher.
I mentioned all the components I guess.
And this is controlled by the smart energy living lab.
We have this energy management system on top here.
And this energy management system has to communicate with those
devices.
Also with the utilities, transmission system operators, distribution
system operators getting relevant information with respect to the
state of the grid.
So that's the grid status that we would like to get.
We also need price signals and things like that.
And we have to communicate with the consumers and producers inside the
house and maybe around it.
Okay, so that's what we have to do there.
And then we have to set up such a system.
Just to show you what kind of infrastructure has to be installed if
you would like to do all the metering and recording of energy
generation and power generation and power consumption that is needed
in order to get all the potential subsidies.
You would like to get extra payment for PV in-feed.
If you have a combined heat and power plant, power generation, you get
extra payment for that.
But it's a different amount that you get for that, much less than for
photovoltaic power or solar power.
And then you have to pay something for power that you get from the
system.
And sometimes there was also some subsidy for self-consumption, which
is now turned into the opposite.
And certainly what we would like to have is a possibility to claim
towards the system that what we have generated from our photovoltaic
panels can be fed into the grid at any time later on, because we have
stored that in a battery, which only gets its power from the
photovoltaic panels.
So every energy that is taken out of that battery is always solar
power.
And so whenever we use that, it is usage of renewable energy, because
it's solar energy.
Although it can be used at a time that is much later than the time
that we actually generated the power.
Okay, so what kind of components do you see here?
You see the energy, this is the Wärtsilä energy manager, which is the
inverter and some kind of management system, managing the battery.
There are possibilities to either put the power into the battery or
send it directly into the system.
Now you can send it directly into the system, and then you go that way
here, for example, into the grid, that would be one path.
For the consumers here, you could get power directly from the battery
or from the photovoltaic system.
And the combined heat and power plant could provide some power and
would have to be metered independently of that.
So you have to measure several different things.
You would like to measure how much actually has been generated from
the photovoltaic panels.
Now this is the power that is coming out of that line and through that
line.
So metering system C and A, if you add that up, that's what has been
generated by the photovoltaic cells.
Then you have a certain surplus which might be fed into the system.
That's meter D.
And what else do we have?
The metering system F, we get subsidies for the combined heat and
power plant.
It should be CHP, not KVK.
So you see many different metering systems.
Here you have load metering, how much actually is used there.
How much actually do you get from the grid.
So this is a two-way metering device which is needed there.
And the interesting point was when we had built or installed the
system there, our PV panels, battery and this system, we went to the
local municipal power system and told them we would like to get some
advice how we should actually set up the metering systems in order to
document to you how much we have actually generated from photovoltaic
panels taken out of the battery and generated from combined heat and
power They said there's one similar installation at Karlsruhe, but we
don't know how to configure that.
If no way, this is too complex.
So we designed a system which still is quite complex, but it's only
that complex if you actually have to provide information on how much
we generated from the combined heat and power plant, how much we
generated from the photovoltaic cells, how much we used locally, and
so on.
If you would like to get all the subsidies.
If you don't want to get all the subsidies, you don't need all these
metering devices.
But here, we actually set up a system where we had these six different
metering systems, and the Stadtwerke Karlsruhe said, okay,
interesting, that's acceptable.
And so that's a system which actually runs, but you see that it's not
that easily done, actually.
Yes.
Well, these are just metering systems that certainly they have to
certify.
Certified meters, intelligent metering systems, and then they accept
what has been recorded by those metering systems.
Yes, definitely.
Yes.
Yes, they have to do that.
So, looks like a complex system, and it is a complex system.
But it's only that complex because we want to document all the
different parts of that architecture.
And then we have infrastructure for the thermal part.
So we are having our combined heat and power plant, which is certainly
providing power.
That was on the previous slide.
It's also providing hot water, and that hot water can be additional
hot water from the peak load burner.
The hot water is put into that storage.
So we have the warm water storage.
We have the cold water that is always fed back into the system.
And then this is also used by the, or can be used by the absorption
chiller to generate cold from that temperature difference.
And then we have here the cold water storage.
And from there, we feed the air conditioning devices in our meeting
room called Hollywood in the House of Living Labs.
So that's the thermal infrastructure which has to be controlled
adequately also.
And so, to control that means, for example, that for our meeting room,
if we have a timetable, and if it says, okay, at that time slot, there
is a meeting there, then the system knows that at that time, this will
be needed.
And so they will provide sufficient amount of cold water such that the
system is able to cool down the room at that time slot.
So this is an intelligent control of the thermal system to make sure
that you always have sufficient cold water available.
If possible, you do that beforehand, or while it is needed, you just
run the system.
So we need intelligent management systems certainly on top of that.
So what do you need or what do we have here?
Again, we have the decentralized energy supply, 15 kilowatt peak
system for the photovoltaic panels.
It's actually three times five.
We have distributed that over the three phases of the power system.
We have stationary electrical storage, three times 10 kilowatt hours
batteries for the three different phases.
Again, we have a combined heat and power plant, 5.5 kilowatt electric,
12 kilowatt thermal.
So that's the same actually as we have in the Energy Smart Home Lab on
campus.
The absorption chiller, the condensing boiler, much more powerful, but
in winter, if it's really cold, we need more heat.
And then we also have batteries from our electric vehicles, which are
also attached to that system.
And we have the thermal energy storage.
And what we would like to do is to have intelligent consumption by
optimizing the schedule for the electrical and thermal devices,
respecting user constraints.
So we have certain user constraints in the office and laboratory
building, different from what you have in the private smart home.
And so we also need certainly sensors and actuators for the energy
management system.
And do that with...
We also look at smart automation, so you can monitor, you can control
things in industrial processes.
And we also would like to provide something called smart mobility,
make sure that electric vehicles get their batteries recharged in a
reasonable way.
And then use the power from that battery in a reasonable way, so they
get services for...
under the name which we call green navigation, we give them services
to have an energy-aware navigation system.
Lots of things that can be done here, which we work on in the Research
Center for Information Technology.
So this integrated energy management system across that House of
Living Labs addresses several different aspects of the energy
management for devices inside the house, but also outside of the house
in the electric vehicles.
Okay, here's again the situation where I said we have all kinds of
components which might speak different languages.
So here we have power line control, we have ZigBee, KNX, HabiTech, by
General Electric, or just these REST service interfaces of web
services.
And they can be combined using the eBus, which we also do in that
house.
And different from the smart home that we have on campus, there we
have only Miele at home devices.
Just one interface.
Here in the House of Living Labs, we on purpose have many different
devices, many different communication protocols, and then provide some
integrating interface on top of that.
And so we get this energy management system on top of it, where we
have to communicate with the different other components, utilities,
energy market, grid, get grid status information, and get information
from the users.
Those are the different devices.
Also smart plugs.
Smart plugs are important because if you have a house or an apartment
which does not provide that nice functionality that it tells you from
all the different locations of your apartment what the power
consumption is, you just put in this smart plug and then you get the
information.
They communicate using ZigBee and then, for example, getting that from
PlugWise, you can get data sets and you can turn your apartment or
your house into a smart home where you get information on where in the
house energy is consumed.
And you can switch those plugs, you can switch them on and off and in
that way control the devices that are connected to that.
And so you might have devices which have no intelligence built in
whatsoever, but because of the smart plugs you can control the way
they are actually used.
For example, for a washing machine you could just switch it off until
you say now it should run.
And then you switch it on and it starts running.
You have a question?
Right.
Well, this depends.
So the question was that there are devices which you cannot just turn
on or off.
A washing machine is a difficult topic.
So there are the old washing machines which actually you just start
them and then you switch power off and it stops.
And you put power on again and it continues to run.
You don't have to reprogram at all.
Then there are modern, more intelligent, smarter washing machines
which are intelligently programmed.
And if you switch off the power and switch it on again, you have to
restart it manually.
It doesn't work.
So those, I would say, half-smart devices which cannot be controlled
externally until now you should start running, but which are started
manually and then if you switch off the power and have to be restarted
again, that's bad.
So these are half-smart devices.
They have nice, intelligent control, but cannot be controlled
remotely.
And then there are the really smart systems where you can send
commands for pausing or stopping in between or restarting and things
like that.
So Miele at home is that really smart interface.
And I actually have a Miele washing machine at home.
I can switch off the power, I can switch it on again, and it will
continue running.
So there it works.
The fridge is no problem at all, because for the fridge, you can
easily switch on or off the power, and it's a manual setting, it's a
mechanical setting of the thermostat in there.
And so you could control it.
Certainly, you should know something about the temperature inside the
fridge.
You could even put in a thermal sensor in there and then get the
temperature reading.
Or you could, say, have some standard estimate on how often it has to
run.
I observe how often it would run normally, and then I just make small
deviations to that.
You could use it that way.
You have a question?
As I said, Miele at home is one interface, actually designed by
Siemens and Bosch.
And Miele is just using that technology, and Siemens and Bosch don't
use it.
And it's just those devices from Miele which have that interface, for
those to pay at least 50% more than for the others.
At least.
Sometimes even double the price.
Although the difference in technology is just a few euros.
And so we are actually cooperating with one of the largest
manufacturers for control devices for appliances, and we are designing
new controllers together with them in order to actually in the future
provide every appliance with a reasonable controller.
And the price difference is just marginal.
Yes.
Exactly.
Okay.
That's exactly what we have built in the House of Living Labs.
And so we have different devices there.
And then some of them are just looked at by measuring their power
consumption using a smart plug.
For example, a coffee machine.
It's only looked at, observed, and we see the profile that we have.
It doesn't make sense to start it at some time because you want the
coffee now and not two hours later or within the next half hour.
That doesn't make sense.
But for some devices, we can control them using the smart plugs.
And then we use that, or we do that.
And what we try to do is to get some standard interface.
So the e-bus is providing, like for systems that have some
intelligence using different protocols, they can communicate using the
e -bus.
And we have this hardware abstraction layer and we actually are using,
for some of those communication protocols, we use the e-bus.
For others, we just use our way of abstracting from the relevant
information that we can get, either from KNX or HaviTech or some other
services and transform that into a standard format that is usable by
our energy management system.
And we are not the only ones who are doing that.
There is a consortium called the e-bus consortium or the e-bus
association where they work on norming that interface.
And if you have a norm, international or national norm, the goal
certainly is to put that into an international norm and then everybody
would be compliant with that.
So people work on that, but it's not the only initiative.
And I would say the best thing is to be able to notice a certain piece
of information that is sent to you and being able to discover what
kind of information is in there and extract the relevant information.
In some part, this is the idea of the e-bus.
So it's not there in the moment.
We actually are having e-bus components in there in the House of
Living Labs and use them, but in reality, widely available, the e-bus
is not normally at this time.
But quite a few relevant manufacturers of devices, of components for
the household are actually participating in that e-bus initiative.
So there is some hope that it will develop in a situation where they
can all communicate.
Okay.
You're waiting for putting this to an end, I have the impression.
You have to leave.
Yeah.
Okay.
Good.
Or not.
Fine.
So let's continue.
What do we want to do?
We want to have a nice energy management system which can actually
cope with all these different devices.
And so we want to use that in a reasonable environment.
Now, what is a reasonable environment?
Usually you would not invest in a specific device just for energy
management in your house.
But if it is coming with certain assistance functions, comfort
functions, entertainment functions, some general information, safety,
security features, and also energy, you might consider buying that.
And then you have the energy control on top of it.
So that's what we would like to have.
So this organic smart home should combine all these different
functionalities.
That's what we are working on in the House of Living Labs in the
Research Center for Informatics.
We have certainly the eBus gateway to other systems, and that way we
try to address the problems of energy management in a house or also in
a building.
So there are different levels at which you actually have to get in
energy management.
So when we talk about addressing the topics of energy management,
there are quite a few different aspects.
I have mentioned quite a few of them before.
So we have looked at...
I mentioned that we need to deal with decentralized load management
because we have decentralized generation of power.
So we have to monitor and control energy demand and supply.
I have shown you these screenshots of this software which would
visualize the situation in some grid segment showing different voltage
levels, either lower reduced voltage in blue or increased voltage in
red.
And then you have to find out how you can actually combine the control
of different components in order to stabilize the system and make sure
that those voltage drops do not occur or those voltage increases and
bottlenecks there don't actually happen.
So we need some kind of automatic and self-organized adaptation of the
building's energy demand.
I showed you how that is done in the house with this optimizing
system.
And what I have written here is just the standard things.
Electricity rate in intraday trading there, like that is the energy or
showing the energy demand of the system.
If you look at the current price of power in intraday trade, then you
see the current situation on the energy market, the current situation,
whether there's a surplus of power or a deficit of power.
You may have the objective to maximize local consumption.
You have to control decentralized suppliers of power.
If you can control them, like combined heat and power plant, you
certainly could also control biogas facilities.
You don't have them in your private home, but maybe in a larger
building.
If you have a biogas facility, you can control them in the flexible
way, because there you can store gas or burn gas, but normally they
get a fixed price regardless of the situation in the grid.
They can just produce power, which is not really reasonable.
So that should be controlled in a more reasonable way, similar to
other components which can be controlled in their energy or in their
power generation.
We have to coordinate these things.
We have to integrate energy storages, as you know.
And then we would like to do that on the level of a smart home.
That's private environment.
You have your household appliances.
Some may have smart grid capabilities, some don't, and you try to make
them more intelligent.
Then you have situations in buildings.
A building can be just an apartment building, having several
apartments, which you would like to, in some way, control on a higher
level.
Maybe you have an office building or a lab building or a factory.
For that you need building automation systems or building energy
management systems.
And the important point is that if you look at the interface that you
need in a smart home, this energy management panel, that we had this,
you remember here, these devices, which, for example, showed how you
actually have here the energy flows in a system in your house.
Such a picture, showing the energy flow in a house, might be of
interest.
The energy flow in a smart building, like for example in the House of
Living Labs, looks much more complex than just the energy flows in a
simple house.
If you have a factory and you would like to look at energy management
panels, what do you actually provide as information?
If you have a large building, maybe having several offices, and then
you have a lab, you have other areas having different functionality,
different load profiles, and also different regulations, different
policies as to who actually is allowed to look at the energy
consumption.
If you provide energy management, for example, to an office building
and somebody would like to see how much energy is consumed in that
office, you have to check that with the Personalrat, or Betriebsrat,
so with the representatives of the workers, the workers' union, to
make sure that privacy issues are actually respected there.
Not everybody should be allowed to look at the energy consumption in
all these different offices.
If you are the person sitting there, you should get the information on
what you are consuming personally.
Maybe you should also get, or be able to get information on what's
happening there, if you're responsible for that area.
But somebody who's not responsible for that might only get information
from that area.
So the question, what you actually visualize in such an energy
management panel, is a difficult question.
What are the objectives that you have?
What kind of information is needed for those who see that in order to
be able to provide the adequate decisions on their energy consumption,
or energy generation?
So this is a design issue.
What is the realistic way of generating or designing such an energy
management panel for a smart home, or a building, or a factory?
Because there are all kinds of different aspects that have to be
addressed if you design those systems.
We are currently running projects where we design, sample
installations here for buildings on campus for that, on top of what we
do in the House of Living Labs.
So smart office, smart factory.
I mentioned that already you would like to have efficient production
processes.
Now you would like to do that in a factory.
So imagine, or what I actually experienced was that we talked to a car
manufacturer and talked about energy management and exploiting load
flexibility in order to get more appropriate response of the energy
consumption to the needs of the grid.
And he said, what?
You want to provide or have more flexibility from those production
processes?
You know our return on investment that we have, or our profit that we
make is from selling cars and not related to energy.
And he laughed at us.
Meanwhile, we have a nice project with them.
But the question is, how can we actually find out what the potential
for energy flexibility is inside production processes?
Sometimes you have some flexibility in there or some potential for
flexibility for load shifting, which is actually not interfering with
the production process, but maybe just having to do with providing
heat for the production process.
But there is some hidden flexibility in there, which is not affecting
the productivity of the production line.
And normally these production lines are designed without any
consideration for the energy demand.
And so we have to change that attitude and also look at the energy
demand and the energy aspects in order to get a better way of
controlling production processes.
And then there are also other things certainly that companies would
like to show to the public that they have green products, meaning that
they are using renewable energies for producing certain products,
certain commodities or certain goods that they would like to sell.
So all kinds of different objectives that you have to use there.
And then another problem is if you try to optimize your production
processes by reducing energy consumption as much as possible, you
might take out all the potential flexibility that you have.
If you completely optimize the energy consumption, there is no
flexibility anymore in the system.
And so this is not always appropriate to completely optimize or make
the production processes completely efficient because you might have a
business case if you can provide demand response services which allow
you to get extra revenue from offering those demand response services.
It may get you more revenue than what you save by having a more
efficient process.
So this is different types of design and management issues.
Reduction of peak loads is relevant with respect to smart factories if
you have a tariff which says, okay, if you have a certain peak load
here, I charge you, I give you a tariff that is only based on the peak
load.
So the peak power consumption is determining what you have to pay or
at least is determining a significant amount of your energy bill.
So if you can reduce that, say I only reduce that maximum power to a
lower value, then you get a better deal for the energy company.
Normally, I object to people who say we have to follow the goal of
reducing peak loads because in our energy future or in the situation
that we describe all the time, we know that at noon we have this kind
of power or during the day we have this kind of power generation from
photovoltaic panels, for example.
And if we have strong wind, this might even be more power during noon
time.
That means here we would like to have peak power demand at a specific
time of day or what we would like to have is that our load profile is
adapting to a predetermined desired profile.
And so a special case of that, let me write that here, adapt to
desired load profile.
This can be a special or reduction of peak loads can be a special
case, but normally you would like to minimize the deviations from a
desired load profile.
And then you have the best possible description of the objectives of
energy management.
So what we would like to have here is decentralized load management
and provide all kinds of services for the system, provide reactive
power management, provide operating reserves, so being able to on very
short notice modify the current load that we have.
So there are quite a few challenges that have to be addressed there
and we can only do this here if we know quite a bit more about the
flexibilities hidden in production processes, factories, buildings,
and individual smart homes.
And these load shifting scenarios are of interest.
There are some economical issues with respect to that.
We have time variable electricity tariffs.
We know that we might have different prices during the day and we
would like to adjust our energy profile with respect to those prices.
We might have load-based electricity tariffs, so depending on how much
you use the specific time, you have different prices.
So if you go beyond a certain power limit, you have to pay extra.
Then you try to optimize with respect to that.
Maybe that your objective is to improve self-supply.
You would like to get best possible self-supply for your power and
reduce the need for getting power from the grid.
That's what industry currently is doing, trying to invest more.
For example, KIT is investing in a 1 MW photovoltaic panel system.
1 MW is the power that is always needed.
It's guaranteed that this power generated from those photovoltaic
cells will always be used inside KIT.
So it's best possible use of the power.
It's a business case because that power is much cheaper than the power
we would get from the grid.
And then we have the demand from the system.
We had looked at the balancing power approaches.
We had looked at this elite group mechanism where we have some way of
primary and secondary power management.
So this is something which has to be addressed also.
And another objective can be just to improve or to optimize with
respect to using power only from renewables.
So this is just the topics again that we have to address here in that
scenario in the house, in the building, and by appropriate instances
of energy management.
We have to design appropriate in-house communication systems.
So how do we actually communicate the information inside a house?
We talked about that.
What are the communication standards?
How can we provide smart grid functionality or in some way smart home
functionality or smart building functionality with a minimum amount of
extra facilities, extra devices that we have to install?
So smart plugs are an interesting way of providing information on what
is actually consumed inside offices or rooms in a house without having
to invest very much in home automation infrastructure.
We have to certainly test also prototypes in all kinds of
environments.
If you test these communication standards and you have many different
communication protocols running at the same time, they might
interfere.
They might not be available all the time.
So if you look at ZigBee communication, sometimes you have missing
values.
How can you deal with that?
So you have to look at reliability.
When I showed you this generic architecture for the observer
controller, like the organic system architecture, we had this pre
-processing of the data.
So if you know there are certain missing data, what do you do with
that?
How can you provide something which will run, provide functionality
without running into problems due to missing values, for example?
You would like to be able to communicate between the appliances.
Definitely something has to be done there.
It has to be taken care of by the devices that we have.
And we combine that with home and building automation systems.
So in buildings, you have much more widespread use of automation
systems.
In individual houses, usually you don't have that much home
automation.
Okay, that's just a wrap-up of the different aspects that are
important if we design energy management systems in a home, in an
apartment, in a building, in a factory.
And here is again this energy management panel that is an extension of
what we had designed for the Energy Smart Home Lab.
So what you see here is some kind of extension.
You have some storage, battery storage.
You have the photovoltaic panels here, 14 kilowatt.
Today it was around that value, so 15 kilowatt peak is the maximum
value.
Actually, we have seen in some situations more than 15 kilowatt,
although it is 50 kilowatt peak.
It came up to 16, I think.
So under certain conditions, sometimes it may be more than that.
So what you see here is the electricity part and the thermal part.
So here is the heater, the hot water tank, the cold water tank, the
absorption chiller, and then you can click on that device.
You can click on all these different devices.
I think it's not linked to the system.
I think I don't have to show you the running device.
I promised you that we will go and visit the House of Living Labs at
least for one time slot here for the course, and then you can see that
running in reality.
And here you see the different, like I said, 3 times 5 kilowatt peak.
These are the values of the different inverters that are running
there.
So you can always click on the different icons here and get more
information of what's happening there.
So if you click on the PV system, you get this menu here or this
information showing what has been produced on the previous days and
what is the current situation there.
So this is just showing that this is slightly different from what we
had in the Energy Smart Home Lab.
Here adapted to the requirements of the House of Living Labs.
And meanwhile, we have made that into a configurable tool where you
can just configure the panel such that you can adapt it to different
requirements.
This is showing what we have there for the electric vehicle.
Again, the minimum range that you would like to specify when you leave
the car there.
You would like to see, okay, at least 40 kilometers should be the
minimum range.
Then you specify the next starting time, next departure time, and you
also specify what the range is.
Here it's a very short distance.
Maybe you put in a larger distance or a larger destination.
And then if you put in a certain range, you do not necessarily need a
fully charged battery, but only as much power in there as you need for
that trip to get there and to get back.
And then you get information on the current state of charge and so on.
And we actually have in there some other components which can also be
addressed with that panel, which you could say it's some kind of
unnecessary, but here we can actually ask the service robot, the
Holley robot, to bring you a cup of coffee or whatever you would like
to get there.
This is still some virtual component.
It's actually there, but it's not obeying our commands.
Yeah.
Okay.
Segways could also be controlled for that panel.
It's just showing what's possible in that environment.
And then we again have our washing machines, disk washers and so on,
which are integrated into that house.
And as I said, here having different communication facilities.
All this should be integrated into some kind of hierarchical
management.
We have it inside the house.
Just ten more minutes and we are done.
It's a long time listening for three hours, but it's also a long time
lecturing for three hours.
So I'm as glad to be finished after this as you are that it's over.
Okay.
So what we need is data on the current status of the system inside a
house.
So you may have different houses.
Then you would like to have a system on top of that.
You have the devices inside a house.
You have a demand-side manager.
You might have some kind of data repository somewhere where you store
all the data about what's happening inside a house.
This is a difficult issue because usually, would you really like all
your data being stored somewhere in the central repository?
I just had an interesting list of project proposals on smart data.
Actually, what could you do with all this nice information from
intelligent meter readings?
And the aspect of security and safety and privacy control was not
really handled in a very satisfying way.
What is this here?
Oh, come on.
I don't want this now.
So, okay, this is sending information somewhere.
Maybe you would like to exchange information with your direct
neighbors.
That might be possible.
The major point is you have to at least have control about what's
happening to your data.
Then you have some kind of network control system, which needs
information to control your network, to configure the network.
It needs some information on what's happening inside, or what's
happening on the system.
And the network control system, as I showed you these screenshots with
the network segment that had predicted voltage losses or voltage
reduction or voltage increase, these would be bottlenecks which might
reside in the generation of priority signals, which then are used to
influence the activities of demand-side managers.
And so these priority signals could have low priority or high
priority.
And if you have...
So this is different.
This is... okay, just the other way around.
Priority zero is the highest priority.
Priority larger zero is low priority.
And if you have priority zero, it means you have to respond
immediately.
This is sent directly to demand-side managers.
And if you have priority larger than zero, then demand-side managers
could compete for a certain demand response service on the market.
And what I have just indicated here on these few lines is something
which we actually have built in a system in the project Miragio.
So this was part of Miragio.
The project where we are collecting information from the households,
from 1,000 households and small and medium enterprises.
So this then is sent to the network control system and sent back to
demand response and demand-side managers, which depending on the kind
of priority signal that they get, they will, with priority zero, act
immediately.
If it's priority larger zero, they will go to a market and then using
merit order assignment, the demand-side managers will get an
opportunity to provide the service that they offered on the market.
So for that, you need something which is shown here again.
So here we have the network control system and we have a certain data
flow from the smart metering data.
So you have here some flow of data.
So the network control system would like to get some data.
It's provided from the data repository, has all that data available
and the demand-side managers get information, what kind of activity is
required from them.
Sometimes they can go to the regional market and then compete for
offering actually services.
And so the regional market tells what is available.
The demand-side managers provide their bids and then some assignments
are made and they can actually provide a certain service.
And then this is sent to displays at the local user or sent as a
command to a smart home control box where a certain device is
controlled.
This is a complex picture which has certain numbers which indicate the
order in which this is actually occurring.
So the demand of the network control system was sent into the data
repository and then from all that data, the signals from the network
control systems are actually put onto that market or sent directly to
the demand-side manager and then executed in some local houses.
And what's happening there again can be measured by those smart
metering systems and sent back to the data repository and this results
in another round of information exchange between the different
components.
We have actually built such a system having all these, like it's
better on this picture here, implementing all those different devices
where this year actually, I should draw it here, like this was ENVW,
this was ABB, this was SAP, this was IBM, and KIT was somewhere in
between and you can imagine that it's not easy to design a system
where you have to go through that many different systems forward and
backwards and go to the market and go back there and between all these
different institutional borders you have some safety regulations, you
wait for some time, you have time out regulations and so the whole
process, this whole cycle took something like 30 to 45 minutes and
it's much too long.
And so this has to be optimized in some way.
I just wanted to indicate that if you would like to set up such an
intelligent system having such an information cycle from smart
metering systems to a data repository to the network control system,
back to the marketplace, to demand-side managers and back to the
individual houses, this is quite some complex infrastructure and you
cannot have immediate response for that.
So this emphasizes again what I mentioned before, if you need
immediate response, you need something like the self-organized
balancing power approach for the elite groups, but if you have some
more, some not real-time requirements, you can use a system like this.
This is actually like the architecture we have designed here is the
template, meanwhile, for something which is called the Ampel-Modell.
So you could say the traffic light model of energy management, where
you have a red phase, a yellow phase, and a green phase.
And in the green phase, everything would run over the market.
In the yellow phase, the priority would be quite low, going almost
down to zero, so very short response time here.
And in the red phase, you would have something with priority zero,
where the network control system tells immediately what has to be done
by the demand-side manager in some location.
So different possibilities to respond using markets or using direct
control.
I think that's it for today.
Next time, I will show you a little bit more about some commercial
smart home solutions, and then we come to the next topic.
I will tell you something about security aspects of smart metering
systems.
That will be the next chapter.
The question is, at what time we meet again?
I think we have said that we meet again next week, is that correct?
Next week at 2 p.m., I think.
The week after, because next week you will be on excursion.
The four of you.
So we meet on the 7th, right?
Next lecture.
7 plus 7 makes 14.
This is...
Yes.
Right.
Would it be?
I don't know if it would be the last one.
It depends on how far we get.
So we have still one more week that we could go.
The week after that would also be a potential date.
And maybe we could say that on the 14th, it should be available there
also.
I think the Senate is meeting the week after that.
We could have a visit of the House of Living Labs at the last meeting
of this course.
We can do
that in the House of Living Labs.
We have to check whether it is available on the 14th would be a good
date to do that, because then I have decided whether it will be a
written or an oral exam.
Yes?
Good.
So, that is the lecture for today.
Thank you for your attention.
Have a nice evening.