lt0202

On page 6 of your paper you assume a 90% efficient ESS with no time-varying leakage, then proceed with a model of a system that requires energy storage times of days, weeks, even months or years. This is not a valid assumption for the math you're doing. Lithium ion ESSs (and other types) have time energy shifting capabilities, but they all suffer from energy loss across this time. Lithium ion batteries not stored at a ~40-60% SOC suffer chemical degradation, affecting their potential max SOC. The depth of discharge, the cycling behavior, even temperature affects how well an ESS behaves. I don't see any of this taken into account in your work. You could potentially keep the stored energy at the levels you discuss by keeping individual cells at 40-60% and having a BMS both for the individual batteries AND for the group, but there is no mention of that in your paper, and your work doesn't really model that type of system.

Simply put, you model a system with unrealistic assumptions that cannot be matched by a real world system. The math seems reasonable, but this cannot be applied to a real world system until you take into account losses and the battery effects.

Could you please comment? I'm not trying to knock this down, I'm trying to understand what I may have missed.

However, after I do take this into consideration, it just going to give me different results.

This is like saying "My model of a ball bouncing in a bounded box shows that the ball will bounce forever! Once I take friction and gravity into account, it is just going to give me different results." You have to be realistic with your assumptions, otherwise you can draw unrealistic and nonsensical conclusions from the data.

You should put your data sources "power_supply_san_diego" and "power_demand_commercial_building" on GitHub so that people can actually run your program. Based on line 80, "power_supply = circshift(power_supply,4380);", it looks like you're simulation's time step is only an hour. After line 117, you'd want something like "energy_stored(i) = energy_stored(i-1)*EnergyLossOverAnHourAtThisSOC(energy_stored(i));", and you'll want to throw in a function that gives you the energy loss. That said, this still doesn't take into account the cycling and DOD effects on the battery, which absolutely CANNOT be dismissed, because it has a non-trivial effect on the battery's max SOC over time. You also work in total stored energy, not SOC (multiplied by the rated battery max capacity), which makes this whole thing... weird.

I'm not saying this is bad work. This is a great start. I think if you include battery aging effects (which you could learn about here as a start) and the PV ratings, this could be some great and novel work. Keep up it up. Don't let any of my words or anyone else's discourage you.

The power data is on GitHub. It's the file called example_power_data.mat.

Oops! I simply missed that, sorry.

... if I include air resistance (time-varying leakage), it is going to give me different results.

Good analogy. My point is simply that you draw a conclusion (the optimal curve) from your "ideal" model, but that that shape (the curve) may not even exist when time-varying leakage is taken into account. For example, the curve could change over time, which would be quite interesting to see. As such, your results may be a different paradigm entirely, and not just "different". I think I'm just trying to say that "different results" is not a strong enough term, that's all :).

To be clear, I'm not intending to be hostile at all. I'm intrigued by your work, and wouldn't be critical of it if it wasn't worth the time. I can't go into details because of an NDA, but for the last few months I've been programming in MATLAB on work related to energy storage systems. I'll probably play with your code tonight or this weekend and see what happens when some simplified PV and battery aging effects are implemented just for fun :).

I think you're right. It would look something like that, and because the ends don't really change much at the extremes, there will still be an inflection point worth studying.

Nobody is going to buy a stand-alone renewable + ESS system if they don't intend to use it until end of life. I think that your curve will change significantly over time (especially over the years), and that that "optimal" inflection point therefore changes with it. With some further math, one could optimize the system financially as it evolves through time to find the best system mix.

Basically, you've neatly demonstrated a method of handling two dimensions. It just gets much more interesting and produces useful results when you introduce the third dimension (time) and the associated effects (e.g. battery aging). That could be some novel work.

Again, not arguing with you. I really want to see the results of the introduction of time and how that changes the curve :).

Any time someone does some work, we just jump all over it as if there is no value because it isn't perfect.

Are you talking about me? Did I give the impression that I thought it had no value? Really, I'm genuinely asking. I only meant for there to be an amicable back and forth. I like the work, I think it has value, I think it points in an interesting direction, and I'd love to see the work furthered. I guess I just don't understand the intent of your comment :/.