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I built an open-source, AI-powered solar panel that's 95% optimal
- anglinb 4y agoThis looks incredible, could see this approach revolutionizing so many industries.
- SubiculumCode 4y agothis is not my field, but you couldn't just have it orient to point of brightest intensity?
- mirker 4y agoYeah but that requires knowing control theory rather than “learning” it. Control theory is better if you know what you’re doing. ML is technical debt for sure.
- GlenTheMachine 4y agoI'm more and more convinced of this. Control theory appears to be like lightsabers, "a refined weapon for a more civilized age". It's really unfortunately that the controls literature is so opaque.
- hervature 4y ago>> Control theory is better if you know what you’re doing. The "if you know what you’re doing" here does not refer to the ability to understand control theory. It means that if you know the underlying dynamics, there is mathematically nothing better than controlling those dynamics. Flying a plane, oscillating a circuit, etc. are all things we can do very well without ML because we have exact models of the physical phenomena. Playing chess has no dynamics, control theory is useless. Anything where the dynamics are not "nice" differential equations, ML is probably easier at learning the dynamics than coming up with an ansatz.
- GlenTheMachine 4y agoThere are areas of control theory where you can learn the dynamics ("adaptive control"). The advantage over RL is that in control theory, you generally assume the dynamics are described by differential equations (sometimes difference equations), not by Markov decision processes. MDPs are more general, but basically any physical mechanism you're going to control doesn't need that generality. There is a surprising amount of structure imposed by the assumption that the dynamics are differential equations, even if you don't know what the differential equations look like. As a consequence, adaptive control laws generally converge a lot faster (like, orders of magnitude faster) than MDP-based RL approaches on the same system being controlled. The other advantage is that you can prove stability and in some cases have an idea of your performance margin with control theory. THis is important if you eg want your system to receive any sort of accreditation or if you want to fit it into the systems engineering of a more complex system. There's a reason autopilots don't use RL, and it isn't that RL can't be made to work. It's that you can't rigorously prove how robust the RL policy is to changes in the airplane dynamics.
- rl_for_energy 4y agoYou certainly could, but that doesn't entirely account for shading / system degradation / site-specific diffuse light opportunities (consider a huge amount of light reflecting off the side of a mountain at some time of day). Those are both really difficult and time-intensive to model for, so there's a desire to have an AI that can simply learn those things specific to the system it's optimizing without humans having to do it. I see the larger impact of RL as scaling humanity's problem solving capability. If we have to use N human hours per installation to get to 97% optimality per installation but RL can use N/10000000 per installation to get to 95%, we could free up all those N human hours for things that RL still struggles with. Just my 2 cents though, it's a very fair question
- rl_for_energy 4y agoThank you! RL will eat the world. I'm applying it to batteries optimization next
- goodpoint 4y agoSolar followers have been around for decades and do not need ML or complex models.
- countvonbalzac 4y agoI remember there was this science barge that had a solar panel that passively tracked the sun by being mounted on a metal tube that had some gas in it that expanded and somehow tilted the panel more towards the sun. I wonder how much more accurate your system is and whether the tradeoff is worth the added expense of a motor + the additional maintenance cost of moving parts. I wonder why solar farms don't use active tracking, is that added maintenance + equipment cost just not worth it?
- rl_for_energy 4y agoSo large solar farms are usually single-axis tracking, which provides a huge energy production benefit over static panels. Consider this panel's application more for a standalone installment, where it could make sense to use a dual-axis tracking panel over a single-axis or static panel. Re: solar farms and cost, I actually learned that around ~70% of the cost of solar installation is soft costs, not the actual panels/solar cells etc. Applying RL to much larger installations would be about finding non-obvious ways to leverage the single-axis tracking when the sun is not directly overheard. A fun problem for the future :)
- algo_trader 4y ago> around ~70% of the cost of solar installation is soft costs This is incorrect, especially for solar farms Panels are indeed only about 1/3 of the cost. Additional components, labour, inverter, mounting - another 1/3. The last third is indeed soft(ish) cost, but this includes profit (duh..), certification, survey, tax, fees, etc. This can be reduced, but it is not going to magically disappear ... Another fun fact : newer mega farms in low-altitude deserts are considering no-axis no-mounting zero-tilt - just laying the panels on the ground ... It all comes down to cost vs yield A nice project by the way. Did you ever compare the results to pre-calculated angles based on time/location/season?
- sbierwagen 4y ago>low altitude Low latitude?
- nicois 4y agoDoesn't this model fail to account for seasonal variations in the locus of the sun? The optimal angle will vary across the year, whatever the latitude. Maybe I'm missing something, but i would use a simpler algorithm which doesn't need ML. On day 0, plug in the latitude and allow the system to traverse the range of angles, finding the optimal one at the time - ie: yielding maximum power. Let it run 3-5 times during the day, then fit those points to the theoretical path of the sun across the sky. Now your system is calibrated, without needing any other input. As the seasons change, the system will always know which angle to face for optimal power.
- salty_biscuits 4y agoI'd like to see a comparison with a dumb as a box of hammers controller like PI or extremum seeking on the local gradient. I can't imagine that it is learning much more than a simple strategy like this, but maybe that's my lack of imagination...
- GlenTheMachine 4y agoCorrect. Basically all the gimbal is doing is minimizing the cosine loss. This is, literally, the simplest loss function possible. Even if you don't know where the sun is, damped gradient descent will solve this problem every time, with no learning required (albeit with some jitter because you're having to estimate the gradient by moving the panel around). If you treat it as an iterative learning control (ILC) problem, though, you can learn the correct trajectory for the panel in just a couple of iterations and take the jitter out.
- iosono88 4y ago
- snovv_crash 4y agoYou can do this without jitter by having the panel with a bend in it and comparing power from the 2 sides. The difference drives a motor controller directly.
- sgtnoodle 4y agoI raced solar cars in college. One car we built had a solar concentrator system made up of 1D parabolic mirrors. This was a several hundred thousand dollar system due to the use of specialized concentrator cells, and required multiple team members to temporarily move to LA for months to delicately manufacture the cells in a Spectrolab clean room. The concentrator mirrors had to be aimed within about 2 degrees to aim the light onto the active area of the cells. I tried using a pair of photodiodes as the sensor, and it worked well in early prototypes. We flew out to Australia before the system was fully integrated into the car, though. In the real setup it just wasn't precise enough. On top of that, the aerodynamically shaped acrylic window surfaces created weird refractions and reflections that made the accuracy poor as well. I had a couple weeks to figure something out, with a bunch of PIC18F4680 MCUs on hand, and access to parts from Dick Smith's. I ended up buying a small PAL security camera to experiment with. I went to a nearby photo center and got some overexposed film negative to use as an IR-passing filter. With enough layers of film, the camera image was completely black other than a white dot when pointed at the sun. Looking at the analog video signal on a scope, I was able to rig up a couple fine-tuneable voltage dividers and then use the MCU's dual comparator peripheral to generate interrupts on sync pulses and on white pixels. I could then count scan lines, and detect scan lines with the sun in them, giving me a Y coordinate precise to a fraction of a degree. I also got an X coordinate by timing between syncs and white pixels, but I didn't need it for control. I then mounted the camera on the concentrator mechanism, and wrote a basic PID controller. It worked pretty well, and we were able to happily concentrate sunlight while driving at highway speeds. It turned out the linear servo mechanism had a design flaw, where it would lose too much mechanical advantage at the extremes, and in the presence of road vibrations it would jam. We discovered this fairly early on in the race. Luckily I had wireless control of the motor over our telemetry system, allowing me to keep the motor from burning out. We drove a couple hours with the system jammed, taking the power hit over losing race time. Someone realized we would be driving over a "cattle grid" soon, and we had the idea to try running the motor at full torque to see if the shock would be enough to unjam the mirrors. It worked, and we suddenly started getting several hundred watts of additional power! After that day, we tied a string to the mechanism and routed it up to the driver cockpit. Whenever the mirrors got stuck after that, we simply radioed the driver and they gave the string a yank.
- YossarianFrPrez 4y agoThis is very cool, and a neat application / exploration of RL. Am I correct in understanding that the results are only from the results of simulation? If so, it'd be cool to see this work (both a time-lapse video and a chart) in the real world, over a day or over a week!
- mcdirty 4y agoI'll just leave this here... https://www.youtube.com/watch?v=wL9PcGu_xrA&t=174s https://www.youtube.com/watch?v=wL9PcGu_xrA&t=174s
- YossarianFrPrez 4y agoGreat, simple solution, especially if the axes of motion are un-restricted.
- Mandatum 4y agoSimple Solution is often the best. Although I wonder what this adds to overall build costs?
- ncmncm 4y agoNowadays panels are cheap enough that if you want more power than you get with them fixed in place, you just add more panels.
- psyguy 4y agoAre panels cheaper than the servo motor & Arduino used in this tool? Not to mention that at mass produced scales chip costs are usually 1/5 the price of an Arduino. What if every panel used these tools, we could increase the amount of power we gather from solar.
- bushbaba 4y agoYes. A 400w watt panel is 250$. When you account for labor and cost of all. The parts for a moving panel that can withstand high wind speeds…Placing more fixed panels is cheaper.
- deleted 4y ago[deleted]
- yjftsjthsd-h 4y ago> A 400w watt panel is 250$. Wait, panels are that cheap? Could you point me to a good place to buy them?
- arcastroe 4y agoGiven any GPS coordinates, couldn't one simply calculate the location of the sun in the sky to point directly toward it?
- sli 4y agoMy general approach is if we're not doing X and it sure seems like we could simply do X, we probably cannot simply do X.
- ncmncm 4y agoEverybody else assumes that too, so nobody tries X.
- JaimeThompson 4y agoNot only can you do X you can do it using rather simple math, the links are in my post above this one.
- deleted 4y ago[deleted]
- JaimeThompson 4y agoYes, here is one example of such a site https://gml.noaa.gov/grad/solcalc/ https://gml.noaa.gov/grad/solcalc/ Here is how they do it. https://gml.noaa.gov/grad/solcalc/calcdetails.html https://gml.noaa.gov/grad/solcalc/calcdetails.html
- yarky 4y ago> due to variations in atmospheric composition, temperature, pressure and conditions, observed values may vary from calculations. Isn't this exactly the problem that can be better solved using real power data instead of values expected from theory ?
- JaimeThompson 4y agoOnly if the additional cost and complexity of such a setup is worth said cost. It can also be used to move the panels into approximately the correct location then allow the other techniques to fine tune it. If the more complex systems have a fault it may be possible to fall back to the more simple method which, while probably not as good, would be more efficient then just a static panel.
- teleforce 4y agoSorry for the off-topic. I think if just 10% of the efforts were put on improving mini/micro/pico hydro electric generator rather than on solar systems, most of the rural areas will probably better off now with reliable power supply than relying solely on the intermittent solar power[1], [2]. [1]Micro hydro: https://en.m.wikipedia.org/wiki/Micro_hydro https://en.m.wikipedia.org/wiki/Micro_hydro [2]Micro hydro power with turgo generator: https://youtu.be/njNYuEKW-ek https://youtu.be/njNYuEKW-ek
- cinntaile 4y agoIn the developed world we're moving away from small hydro (bigger than this though) because of the effects it has on the environment. But in the developing world it would be good to see some advances!
- foota 4y agoSolar isn't being developed for rural communities though, so this is a bit of a non sequitur.
- ncmncm 4y agoRural installations are most common, by far. Maybe you mean they are being paid for by urban users?
- numbsafari 4y agoEverything is contextual. Hydro isn’t so good in rural southern NM where there is no running water at all for months on end.
- rtkwe 4y agoThe issue I always see on those is the pipe from the upstream reservoir to the generator gets knocked around and dislodged a lot when there's high water. It's less reliable and more maintenance intensive compared to solar it seems. Though it is more mechanical maintenance which is more friendly to more rural areas.
- tomxor 4y agoThis really feels like far better fitting problem for control theory... but I guess it's not cool enough like ML.
- andbberger 4y agothis is not a funny joke or a particularly interesting toy problem for RL. what's the point
- ok_dad 4y agoIf you know the lat/lon of the panel (they don’t move right?) and the current clock time, just point it at the current Sun position if it’s daytime? Wouldn’t that be as optimal as possible?
- titzer 4y agoI mean, you could literally build a wind up mechanism that you point at the Sun. Here's a simple DIY project that designed one: https://www.youtube.com/watch?v=4ySnb4cPDnw https://www.youtube.com/watch?v=4ySnb4cPDnw
- colordrops 4y agoThe article states that it works for suboptimal situations with shade and reflections and whatnot.
- qayxc 4y agoWhich is cool and all, but it's not like you don't know the exact environment before you install solar panels...
- colordrops 4y agoYes, but that's a different topic. And isn't this just an exploratory project rather than an engineering effort or scientific research? But even then, I got panels on my roof last year. A nearby tree that was trimmed when we installed them and now the shade partially covers panels in the morning. If we had gimbles perhaps they'd be more efficient. Maybe not, and maybe we should trim the tree, but the point is that perhaps there is a use case that hasn't been thought of yet. Say, dropping cells on mars in a relatively unknown environment.
- deleted 4y ago[deleted]
- d--b 4y ago> While primary factors driving optimal panel positioning are readily modeled (i.e., the sun’s position at each time of day), site-specific and panel-specific factors are less so. Elements like dynamic shading from nearby trees or structures, localized panel defects, drift in axis positions as systems degrade, etc. can have significant impacts on energy production. Will changing the orientation of the panel really have some effect on these (besides the drift in axis position) ?
- colordrops 4y agoPerhaps an angle and rotation that is less directly pointed at the sun may also have less shade?
- kkfx 4y agoAs a small p.v. user (domestic, wired by myself): tracking Sun gives around 10-20% annual electricity production (witch is meaningless for self-consumption scenario) and a bit earlier and late electricity during the day (you produce earlier in the morning and later in the evening, witch is interesting for self-consumption) but beside the mere cost you need more space: fixed installs need just to count fixed shadows, not static of course, but easy to handle. Rotating means you need more space for one-axis rotation and far more space for two, clustering panels in small groups. In my personal case I have 12+9 classic chains modules, I need more than 2x physical space to transform them with a dual-axis tracking setup. That means it's cheaper just add some fixed panels eastward and westward to catch extra power earlier and later. Also in those terms: lithium storage is very expensive BUT for self-consumption is still the cheaper option to have electricity for more time, just arriving to a meaningful production 1/1.5h earlier and later in the day does not help much given it's added cost. In costs terms: these days it's even cheaper (in TCO terms) having hot water heated by p.v. than the more efficient thermal because that cost more, have more moving parts and regular maintenance that just making an a bit bigger p.v. The real issue in all cases is that to have enough power to really pay back the investment "quickly" we need much non-shadowed southward space witch can be found somewhere but far from everywhere. A similar issue is for EVs: I like the idea of charging them "for free" from solar, BUT since I normally use a vehicle during the day or I use it only sometimes or I have two or more in a round-robin scheme. Also lithium storage lifetime is an issue, on scale the production capacity and recycling are issues. Until we solve them just produce some more Wh it's meaningless...
- snickmy 4y agoI used to be like OP. (have a similar background and have similar interests in tech for the planet) Then I realised couple of things, an humbling experience: 1) given any position on earth, you can compute exactly what's the optimal inclination at any given point in time for a PV to maximize the energy production. Sure, there are reflection and secondary irradiation conditions (eg.: there is a lake close to it), but again, assuming the environment is static, it's way faster to just compute it statically rather than dynamically. Also, in most scenarios Beam irradiance from diffusion (the beam hitting the object) is order of magnitude higher than from reflective one (the same beam bouncing on a 3rd object first). 2) In mechanics movable part are the things to avoid. They have lower MTBF (mean time before failure) and as such they introduce complexity and increase cost 3) Economics is a key component of engineering. There is a cost to everything, the computational power, the energy needed by the servo, etc, etc. Given 1 and 2, a dynamic solution simply has a lower ROI than a static one. I really appreciate the OP exploration here: there is a good overview of basic control theory and a good foundation of ML (although don't be deceived, this is a very simple modelling task that OP is overkilling with a way more complex model). That said, for everyone reading, this is not something you want to do in a real world situation.
- walrus01 4y agoOn a large scale motorized sun tracking photovoltaics is very costly. The systems that can take the wind loading of six 1.65 x 1.00 meter size 60-cell panels on a pole cost more than the panels. Needs like a 6" OD sch80 pipe set into a concrete foundation. Commodity fixed angle ground mount photovoltaics arrays are low cost. If you do the dollar and kWh produced in year calculation for spending $40,000 on fixed mount ground pv, and $40k on a combination of pv panels on trackers, and compare the kWh proxied by both... The fixed ground mount comes out far ahead. A tracking mount can make sense only if you have a VERY small amount of space to work with and want the absolute most kWh per month per square meter of area occupied on the ground. And don't care about money much.
- xxs 4y agoGotta admire the effortless mix up of metric and imperial units.
- Havoc 4y agoWhy? Surely the exactly position of the sun can be calculated?
- ZeroGravitas 4y agoOptimisation has moved beyond the individual panel onto things like vertical bifacial panels in West/east orientation aiming to complement the fixed south facing output of other panels (and so get paid/avoid higher costs) or roof tile integrated to skip an install step and reduce transmission peaks.
- DonHopkins 4y agoDyson Sphere Program - Solar Ring vs. Polar Solar https://www.youtube.com/watch?v=qguTFa9tj3c https://www.youtube.com/watch?v=qguTFa9tj3c Dyson Sphere Program · Covering Half a Planet with Solar Panels https://www.youtube.com/watch?v=MKxkWgknkco https://www.youtube.com/watch?v=MKxkWgknkco Dyson Sphere Program - Solar Panels https://www.youtube.com/watch?v=yO78pXYnjFA https://www.youtube.com/watch?v=yO78pXYnjFA Full day night cycle of solar panels | Dyson Sphere Program https://www.youtube.com/watch?v=gmJr4HiVCwE https://www.youtube.com/watch?v=gmJr4HiVCwE
- K0balt 4y agoI manage a solar micro grid that powers 9 Holmes, a small farm, and several other structures and utilities. We use intelligent power management over the fiber network to tell certain loads when to turn on or off or to change their operating parameters based on power conditions. I’ve been daydreaming about building a ml based forecaster that just gives the next few hours weather outlook based on pressure, temperature, humidity, and a wide Nigel image of the sky. I know it is doable because I can do it myself, and probably without any intuition about the pressure. It would automatically calibrate the model wights by feedback from the actual events vs the forecast. This would be really useful for me at least, in managing battery usage and otherwise managing the various systems that store energy like air compressors and large mass refrigeration.
- cosmic_shame 4y agoThis sounds interesting, whereabouts?
- rl_for_energy 4y agoNot the exact same but some similar work on wind: https://www.deepmind.com/blog/machine-learning-can-boost-the-value-of-wind-energy https://www.deepmind.com/blog/machine-learning-can-boost-the...