#SWC2015 - Launching the Regional PV Simulation System in Daegu, Korea at the Solar World Congress

Our conference paper is entitled: Real-time Simulations of 15,000+ Distributed PV Arrays at Sub-Grid Level using the Regional PV Simulation System (RPSS)

[download it here]

It's an absolute pleasure to be writing to you from Daegu, Korea, where a few hundred solar energy scientists are gathered for the International Solar Energy Society's 2015 Solar World Congress.  I've been inspired by the work that I've seen here, and I'm quite proud to be a part of this community.  

At this conference, it is my great pleasure to officially launch my latest research outcome, which progresses my PhD thesis out of the laboratory, and into the real-world.  It's been a fun challenge to make this leap from science to technology, and I'm honestly quite enthused by the outcome.

From Science to Tech, How We Did It

RPSS stands for Regional PV Simulation System, which was developed by Nicholas Engerer during his PhD thesis, and is now undergoing further development to achieve operational deployment in Australia.

Over the past several months, I have been working with ANU Engineering student James Hansard to get the Regional PV Simulation System up and running, live, in the Canberra, Australia region.  This has been made possible through several mechanisms, the foremost of which was excellent ingenuity and determination from James (you can download his thesis here). 


There are 100+ sites reporting their power output into the RPSS as of November 2015

There are 100+ sites reporting their power output into the RPSS as of November 2015

Using an allocation on the National Computational Infrastructure, the RPSS is now running in near real-time via a series of three virtual machines.  The first machine is gathering PV power output data in near real-time (about 10-15 minute delay) from 100+ sites via PVOutput.org, a webpage where users publicly report their PV system's power output.  The second machine runs the RPSS algorithms and produce the output files/graphics.  The latter of these three VMs, is a web server, which hosts the latest simulations at http://rpss.info.  At this webpage, you can see the RPSS output for the day, mapped to ActewAGL's distribution network.  

RPSS version 2: 15,000+ PV Systems Simulated by Transformer Node

In the latest version of the RPSS, I am now simulating 15,000+ PV systems, grouped by transformer.  This is a significant advancement from the 12,000+ PV systems mapped by suburb in my PhD thesis, which progresses the RPSS towards industry relevant outcomes.  If we can quantify the contributions of PV to the grid at a high resolution, and forecast any significant changes ahead of time, then the intermittency of distributed PV can be mitigated.  Getting the RPSS running in near real-time is the first step in this process.

Quantifying PV Power Output by Distribution Node (Transformer)

When we break down our simulations by transformer, we start to observe very interesting behaviours from the collectives of distributed PV installed behind them that have not previously been observed in Australia.  Let me show you what I mean!  First, let's watch a simulation (RPSS output) from 5 March 2014:

Now, if you don't think that video is pretty cool, then you must be much less nerdy than I am.  I think its fantastic how, using only input PV data from a 100+ sites, we can observe cloud-shadow like features in the simulation! (That's the power of KPV!)

Now, let's look in detail, at the simulated power output grouped by transformer node (below)..

The three different coloured lines above, each correspond to the simulated power output at a given transformer (node).  These are shown on the right side of the simulation video above.  What is very interesting, is the observed differences in ramp event timing that occur between the three nodes during the strong negative collective ramp event that occurs around 11AM.  From this, we can see that the timing of these events are very important to predict precisely, in both space and time, as the strong ramping can occur at different times for each of them.  In the strong positive ramp that follows, there is a similar mismatch in the timing of the ramp peaks.  For a scientist, this is fascinating.  For a distribution company, its a clear example of the challenge of PV intermittency.  

And all of it motivates further development and deployment of this tool

If you found this post interesting, you can dig into the science a bit deeper by downloading our paper below, or by viewing the slides from the presentation.  There is also a tag cloud below, to help you navigate through other content in my webpage.

[You can download our ISES SWC 2015 paper here]

[Or you can download a PDF of the talk]

Or view it in the slideshow below:

SWC2015 Action:

Tag Cloud (Find More Stuff)