Simulations: Levels of Consciousness

In a recent post I showed these results of simulations for our heat pump system:

I focused on the technical details – this post will be more philosophical.

What is a ‘simulation’ – opposed to simplified calculations of monthly or yearly average temperatures or energies? The latter are provided by tools used by governmental agencies or standardization bodies – allowing for a comparison of different systems.

In a true simulation the time intervals so small that you catch all ‘relevant’ changes of a system. If a heating system is turned on for one hour, then turned off again, he time slot needs to be smaller than one hour. I argued before that calculating meaningful monthly numbers requires to incorporate data that had been obtained before by measurements – or by true simulations.

For our system, the heat flow between ground and the water/ice tank is important. In our simplified sizing tool – which is not a simulation – I use average numbers. I validated them by comparing with measurements: The contribution of ground can be determined indirectly; by tallying all the other energies involved. In the detailed simulation I calculate the temperature in ground as a function of time and of distance from the tank, by solving the Heat Equation numerically. Energy flow is then proportional to the temperature gradient at the walls of the tank. You need to make assumptions about the thermal properties of ground, and a simplified geometry of the tank is considered.

Engineering / applied physics in my opinion is about applying a good-enough-approach in order to solve one specific problem. It’s about knowing your numbers and their limits. It is tempting to get carried away by nerdy physics details, and focus on simulating what you know exactly – forgetting that there are huge error bars because of unknowns.

This is the hierarchy I keep in mind:

On the lowest level is the simulation physics, that is: about modelling how ‘nature’ and system’s components react – to changes in the previous time slot. Temperatures change because energies flows, and energy flows because of temperature differences. The heat pump’s output power depends on heating water temperature and brine temperature. Energy of the building is ‘lost’ to the environment via heat conduction; heat exchangers immersed in tanks deposit energy there or retrieve it. I found that getting the serial connection of heat exchangers right in the model was crucial, and it required a self-consistent calculation for three temperatures at the same point of time, rather than trying to ‘follow round the brine’. I used the information on average brine temperatures obtained by these method to run a simplified version of the simulation using daily averages only – for estimating the maximum volume of ice for two decades.

So this means you need to model your exact hydraulic setup, or at least you need to know which features of your setup are critical and worthy to model in detail. But the same also holds for the second level, the simulation of control logic. I try to mirror production control logic as far as possible: This code determines how pumps and valves will react, depending on the system’s prior status before. Both in real life and in the simulation threshold values and ‘hystereses’ are critical: You start to heat if some temperature falls below X, but you only stop heating if it has risen above X plus some Delta. Typical brine-water heat pumps always provide approximately the same output power, so you control operations time and buffer heating energy. If Delta for heating the hot water buffer tank is too large, the heat pump’s performance will suffer. The Coefficient of Performance of the heat pump decreases with increasing heating water temperature. Changing an innocuous parameter will change results a lot, and the ‘control model’ should be given the same vigilance as the ‘physics model’.

Control units can be tweaked at different levels: ‘Experts’ can change the logic, but end users can change non-critical parameters, such as set point temperatures.We don’t restrict expert access in systems we provide the control unit for. But it make sense to require extra input for the expert level though – to prevent accidental changes.

And here we enter level 3 – users’ behavior. We humans are bad at trying to outsmart the controller.

[Life-form in my home] always sets the controller to ‘Sun’. [little sun icon indicating manually set parameters]. Can’t you program something so that nothing actually changes when you pick ‘Sun’?

With heat pumps utilizing ground or water sources – ‘built’ storage repositories with limited capacity – unexpected and irregular system changes are critical: You have to size your source in advance. You cannot simply order one more lorry load of wood pellets or oil if you ‘run out of fuel’. If the source of ambient energy is depleted, the heat pump finally will refuse to work below a certain source temperature. The heat pump’s rated power has match the heating demands and the size of the source exactly. It also must not be oversized in order to avoid turning on and off the compressor too often.

Thus you need good estimates for peak heat load and yearly energy needs, and models should include extreme weather (‘physics’) but also erratic users’ behaviour. The more modern the building, the more important spikes in hot tap water usage get in relation to space heating. A vendor of wood pellet stoves told me that delivering peak energy for hot water – used in private bathrooms that match spas – is a greater challenge today than delivering space heating energy. Energy certificates of modern buildings take into account huge estimated solar and internal energy gains – calculated according to standards. But the true heating power needed on a certain day will depend on the strategy or automation home owners use when managing their shades.

Typical gas boilers are oversized (in terms of kW rated power) by a factor of 2 or more in Germany, but with heat pumps you need to be more careful. However, this also means that heat pump systems cannot and should not be planned for rare peak demands, such as: 10 overnight guests want to shower in the morning one after the other, on an extremely cold day, or for heating up the building quickly after temperature had been decreased during a leave of absence.

The nerdy answer is that a smart home would know when your vacation ends and start heating up well in advance. Not sure what to do about the showering guests as in this case ‘missing’ power cannot be compensated by more time. Perhaps a gamified approach will work: An app will do something funny / provide incentives and notifications so that people wait for the water to heat up again. But what about planning for renting a part of the house out someday? Maybe a very good AI will predict what your grandchildren are likely to do, based on automated genetics monitoring.

The challenge of simulating human behaviour is ultimately governed by constraints on resources – such as the size of the heat source: Future heating demands and energy usage is unknown but the heat source has to be sized today. If the system is ‘open’ and connected to a ‘grid’ in a convenient way problems seem to go away: You order whatever you need, including energy, any time. The opposite is planning for true self-sufficiency: I once developed a simulation for an off-grid system using photovoltaic generators and wind power – for a mountain shelter. They had to meet tough regulations and hygienic standards like any other restaurant, e.g.: to use ‘industry-grade’ dishwashers needing 10kW of power. In order to provide that by solar power (plus battery) you needed to make an estimate on the number of guests likely to visit … and thus on how many people would go hiking on a specific day … and thus maybe on the weather forecast. I tried to factor in the ‘visiting probability’ based on the current weather.

I think many of these problem can be ‘resolved’ by recognizing that they are first world problems. It takes tremendous efforts – in terms of energy use or systems’ complexity – to obtain 100% availability and to cover all exceptional use cases. You would need the design heat load only for a few days every decade. On most winter days a properly sized heat pump is operating for only 12 hours. The simple, low tech solution would be to accept the very very rare intermittent 18,5°C room temperature mitigated by proper clothing. Accepting a 20-minute delay of your shower solves the hot water issue. An economical analysis can reveal the (most likely very small) trade-off of providing exceptional peak energy by a ‘backup’ electrical heating element – or by using that wood stove that you installed ‘as a backup’ but mostly for ornamental reasons because it is dreadful to fetch the wood logs when it is really cold.

But our ‘modern’ expectations and convenience needs are also reflected in regulations. Contractors are afraid of being sued by malicious clients who (quote) sit next their heat pump and count its operating cycles – to compare the numbers with the ones to be ‘guaranteed. In a weather-challenged region at more than 2.000 meters altitude people need to steam clean dishes and use stainless steel instead of wood – where wooden plates have been used for centuries. I believe that regulators are as prone as anybody else to fall into the nerdy trap described above: You monitor, measure, calculate, and regulate the things in detail that you can measure and because you can measure them – not because these things were top priorities or had the most profound impact.

Still harvesting energy from air - during a record-breaking cold January 2017

No, You Cannot ‘Power Your Home’ by One Hour of Cycling Daily

In the past days different versions of an article had popped up in my social media streams again and again – claiming that you could power your home for 24 hours by cycling for one hour.

Regular readers know that I craft my statements carefully in articles about energy, nearly as in the old times when submitting a scientific paper to a journal, with lots of phrases like Tentatively, we assume…

But in this case, I cannot say it more politely or less distinctly:

No, you cannot power your home by one hour of cycling unless the only electrical appliance in your home is the equivalent of one energy-efficient small computer. I am excluding heating and cooling anyway.

Yes, I know the original article targeted people without access to the power grid. But this information seems to have been lost in uncritical reshares with catchy headlines. Having seen lots of people – whose ‘Western’ homes will never be powered by a treadmill – discussing and cheering this idea, I want to contribute some numbers [*].

This is all the not-exactly-rocket-science math you need, so authors not adding conclusive numbers to their claims have no excuses:

Energy in kWh = Power in Watts times hours divided by 1000

Then you need to be capable to read off your yearly kWh from your utility bill, divide by 365, and/or spot the power in Watts indicated on appliances or to be googled easily.

A professional athlete can cycle at several 100 Watts for some minutes (only) and he just beats a toaster (which needs a power of 500-1000W):

So an average person cannot cycle at more than 100-200W for one hour, delivering 0,2kWh during that hour at best.

With that energy you can power a 20W notebook or light bulb for 10 hours, and nothing more.

Anything with rotating parts like water well pumps, washing machines, or appliances for cutting or mixing need much more power than that, usually a few 100W. Cycling for one hour can drive one device like that for less than half an hour.

An electric stove or a water heater needs about 2kW peak power, at half of the maximum such appliances would consume 1kWh in one hour. An energy-efficient small fridge needs 0,5kWh per day, a large one up to 4kWh.

A TV set could need 150W[**], so you might just be able to power it while watching. I don’t say that this is a bad idea – but it is just very different from ‘powering your home’.

I’ll not link those click-bait articles but an excellent website instead (for the US): Here you can estimate your daily consumption, by picking all your appliances from a list, and learn about the power each one needs. At least it should give you some feeling for the numbers, to be compared with the utility bill, and to identify the most important suckers for energy.

I have scrutinized our base load consumption in this article: In summer (without space heating) our house needs about 10kWh of electrical energy per day, including 1-2 kWh for heating of hot water by the heat pump. The base load – what the house needs when we are away – is about 4kWh per day.

There are numerous articles with energy statistics for different countries, I pick one at random, stating – in line with many others – that a German household needs about 10kWh per day and one in the US about 30kWh. But even for Nigeria the average value per home is about 1,5kWh, several times the output of one hour of cycling.


[*] I’ve added this paragraph on Feb. 8 for clarification as the point came up in some discussions on my post.

[**] Depends on size, see for example this list for TVs common in Germany. I was rather thinking of a bigger one, in line with the typical values given also by the US Department of Energy (300W for a plasma TV!).

Peter von Rittinger’s Steam Pump (AKA: The First Heat Pump)

Peter von Rittinger’s biography reads like a success story created by a Victorian novelist, and his invention was a text-book example of innovation triggered by scarcity ( Bio DE / EN).

Born 1811, he was poor and became an orphan early. Yet he was able to study mathematics and physics as his secondary education had been financed by the Piarist Order. He also studied law and mining. Immediately after having graduated he was appointed as inspector in an iron ore processing plant (stamping mill), and later called a pioneer in that field and accountable for several inventions.

1850 Rittinger became ‘Sectionsrat’ (head of a division) in the Ministry of Agriculture and Mining in Vienna. He was knighted in 1863, so quoting all his titles as a public servant in the higher echelons of the Austro-Hungarian empire he was:
k. k. Sectionsrath Oberbergrath Ritter von Rittinger.

Peter von RittingerYet it seems even as an administrator he was still a hands-on tinkerer. He developed a process for harvesting salt from brine at Saline Ebensee in Upper Austria – saving 80% of input energy compared to processes used at this time. In the mid of the 19th century saltworks in Austria had been dependent on fuel: on wood available locally. Railway tracks have not been built yet, and fossil fuels had not yet been available. The ecological footprint had to be much closer to the physical area than today.

In History of Heatpumps, Martin Zogg writes:

One of the main applications [of mechanical vapor compression] is the salt production from salt brine. In order to get 1 kg of salt there have to be evaporated about 3 kg of water, which illustrates the enormous energy demand of such processes. Whole forests had been cleared for this purpose.
Peter von Rittinger … was the first to try the realisation of this idea on a pilot scale. …. He designed and installed the first known pilot heat pump for heating only with a capacity of 14  kW, … The start-up of Rittinger’s “steam pump” was in 1857.

This is the title page of Rittinger’s publication of 1855:

Rittinger, Abdampfverfahren, 1855. Title page.Translating about to:

Theoretical-practical treatise
on a novel evaporation process
applicable to all varieties of liquids
using one and the same amount of heat
which – for this purpose –
is set into perpetual circular motion by water power.
Taking into account the salt boiling process specifically.

I have created this simplified figure from the description in his paper:

Rittinger, Steam Pump, called the first heat pump.

Simplified sketch showing the principles of Peter von Rittinger’s steam pump as described in his original paper. The vessel had to be opened to remove the salt which had precipitated in the upper part of the vessel (called a brine ‘pan’ in German) and water accumulated in the lower part (‘double bottom’).

Salt brine is feed into the upper part of a vessel can be closed an has two parts: The colder, upper part contains brine mixed with water vapor at low temperature and low pressure; the lower part is separated from this cavity by a metal slab with high thermal conductivity. The colder vapor is compressed; and the compressor is driven by a water wheel. To start the process, all cavities are filled with vapor heated to 100°C at the beginning.

At a higher pressure, the evaporation / condensation temperature is higher. Thus hot, dense vapor condenses on the top of the lower cavity, releasing heat which is available in the upper cavity to heat the colder ‘input vapor’. This makes salt precipitate in the upper chamber where it was collected regularly.

In a heat pump for room heating a refrigerant running in a closed cycle is compressed by a mechanical compressor powered by electrical energy. At low temperatures and low pressures the refrigerant evaporates easily, even when in contact with a cold heat source (such as our water / ice tank at 0°C in winter). After compression, vapor condenses at temperatures higher than room temperature and thus the refrigerant is able to release the heat ‘harvested’ before. Rittinger’s steam pump is called The First Heat Pump by historians: However, in this device the water vapor mixed with salt brine is both the ‘refrigerant’ and the liquid to be heated.

In his paper, Rittinger explained that you could as well start from a brine at a temperature as low as 10°C, not needing any auxiliary heating. The system would operate at lower temperatures and pressures. But due to the lower pressures the same material would occupy a larger volume and thus the system had to be much bigger. I suppose, taking into account investment costs, this would have been less economical than using a bit of fuel to get the process going.

What I found intriguing about Rittinger’s work – and perhaps about the way research publications were written back then – was the combination of hands-on engineering, theoretical modeling, and honest and ‘narrative’ reporting of difficulties. Zogg’s history of heat pump quotes quite a number of Leonardo-da-Vinci-style inventors with diverse interests and an obviously ‘holistic’ approach.

Martin Zogg notes that using today’s technology, such ‘steam pumps’ easily obtain a coefficient of performance of 15 – more than 3 times the COP of a heat pump used for room heating. Mechanical vapor compression is state-of-the art technology in salt processing. The reason for the high COP is the lower temperature difference between hot and cool brine vapor. You just need to provide for a sufficient temperature gradient to allow for heat transport from the hot to the cooler cavity, and to overcome the change in evaporation temperature (according to Raoult’s Law).

I could not find the figures in the original paper that Rittinger referred to. The following image is a link to a clickable, larger version of the figures Rittinger had added to a later paper dated 1857, on the actual results of his experiments:

Figures attached to Rittinger's paper of 1857, steam pump experiments(Provided by the digitized archive of Polytechnisches Journal, by University of Berlin, under Creative Commons by-nc-nd 3.0)

What looks like a top view of spaceship Enterprise is the vessel seen from the top. On the left, the corresponding side view shows that it was rather tall. What had been described as a simple separating wall-style flat heat exchanger was actually built as a system of several cylindrical cavities (to increase the heat exchanger’s surface). In the figure the cavities containing high-pressure vapor are denoted with b/c/d. The steam pump / compressor is denoted with E, Dampf-Pumpe, and shown to the right of the vessel in the side view.

Though the numbers were in line with his theoretical calculations, Rittinger’s pilot system did not work well: This was an unreliable batch process, as the vessel was opened regularly to remove the precipitated salt. Rittinger made some suggestions in his original paper, on how to harvest salt continuously. From experience he knew that salt crystals should easily glide downwards from a tilted plane. But among other issues, Rittinger noted in his research report from 1857 that salt crystals behaved quite differently in his vessel, and he attributed it to the higher temperatures in the closed vessel: Instead of being able to harvest the loose crystal at the tip of the conical vessel, all vertical planes have been covered with a crust of salt that resisted also the strongest chisel.

His epigones finally solved such issues – quoting Zogg again:

Probably stimulated by the experiments of Rittinger at Ebensee, the first truly functioning vapour recompression salt plant was developed in Switzerland by Antoine-Paul Piccard the University of Lausanne and the engineer J.H. Weibel of the company Weibel-Briquet of  Geneva in 1876. In 1877, this first heat pump in Switzerland was installed at the salt works at Bex. It was on a larger scale than Rittinger’s apparatus and produced around 175 kg/h of salt in continuous operation.