This question is about analyzing the potential of concentrating solar power (CSP) to meet different load curves, each load curve at one time zone.

I would like to know the best way to analyze the match of a cumulative supply from different CSP plants along different states in the US (the plants are spread along 3 time zones: UTC-8, UTC-7, UTC-6) with the cumulative load curve from the load curves of different states at UTC-8, UTC-7, UTC-6, UTC-5. Any idea on this regard?


To do demand/supply matching, I don't use cumulative load-duration curves, because they lack the time dimension.

Data frequency

Given the sensitivity to Concentrating Solar Power (CSP) of time-of-day, what I'd look for is hourly or more frequent (eg half-hourly) data both for Direct Normal Insolation (DNI), and for electricity consumption.

Some utilities do publish such (half-) hourly electricity consumption; as do some transmission operators.

As for the insolation data, often reanalysis data is 3-hourly or 6-hourly, which might be too infrequent for your purpose. Reanalysis data does have better geographic coverage though. If need be, you might have to use more frequent met-station DNI data, and use that to interpolate the reanalysis data for your putative CSP sites, to get the right combination of precision for both time and place.

Combining data across timezones

When combining data across different timezones, the first thing (after basic cleaning) to do is to convert the timestamps in all the data (DNI data, demand data, everything with a timestamp) so that it's all for the same timezone (typically UTC, aka UTC+00). This requires adjustments for daylight saving time too. Once all the data are in UTC with no daylight saving time, then start doing your accumulation. (If everything's in the same timezone, then it's simplest to keep it in that ... except dealing with daylight saving time can create problems. As soon as I'm doing things across timezones, I switch to UTC as that keeps it all simple, and is most straightforward for any present or future collaborators, wherever they are in the world. )

further issues with synoptic- (continental-) scale analysis

One usual method with such synoptic-scale analyses is to first model without any transmission capacity constraints; and then to introduce such constraints later if it looks like they might become relative. Long-distance transmission is pretty cheap and easy compared to building generation or storage, so ignoring capacity constraints is a pretty reasonable assumption for a first-order estimate.

  • Thanks for the answer. I do have hourly DNI data and hourly demand data. What I meant by a cumulative load curve, is that the supply of all CSP plants has to match at the same time the load curves of different regions at different time zones. Say the combined supply of plants in California and Texas has to match -at the same time- the demand of California and Texas. Therefore if sun shines in California at 12:00 may benefit the demand peak in Texas at 14:00.
    – tom
    Jun 8 '15 at 9:14
  • The question is that I don't know if the supply of the plants in California and Texas has to be at the same time zone (say shifting the supply of Texas two hours less to be the same as the supply in California), and if it is also need to shift the demand in Texas two hours less to match the demand in California. Long story short, if to do this analysis, all hourly supply of DNI and hourly demand curves have to be at one time zone, say UTC-8 of California.
    – tom
    Jun 8 '15 at 9:14
  • @tom ah right, I thought you were referring to what are also called load-duration curves. I've added a couple of paragraphs at the end to talk about the time zones and other spatial issues.
    – 410 gone
    Jun 8 '15 at 10:42
  • Thanks EnergyNumbers. Regarding 'the first thing (after basic cleaning) to do is to convert the timestamps in all the data so that it's all for the same timezone (typically UTC)', should I do as I mentioned to convert all DNI data to the same time zone (say to California UTC-8, therefore subtracting 2 hours if the DNI are in Texas) and also all demand data to California UTC-8 (say subtracting 3 hours if the load curve is from Washington)? When you say 'Once all the data are in UTC' I guess you mean: Once all the data are in the same UTC. Right?
    – tom
    Jun 8 '15 at 11:22
  • Then as you correctly pointed out, all this system would be handled via long distance HVDC lines.
    – tom
    Jun 8 '15 at 11:23

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.