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System Advisor Model (SAM)

LEAC and Energy Rates on Guam

frohro
Topic Author

21 Jan 2020 00:04 #7884 by frohro

LEAC and Energy Rates on Guam was created by frohro

Greetings,

I'm trying to use SAM to help on a feasibility study for putting solar in, here on Guam, for a christian shortwave radio station, where the LEAC (fuel cost adjustment) is a major part of the energy charges. LEAC is readjusted every six months. What I need is a way to either predict this with some accuracy, or a way to put my estimations done using another way into SAM.

We are under the Schedule P rates structure shown here. I'm trying to get data from the Guam Power Authority on their predictions of how LEAC will go in years to come. I know for example that the island has 200MW of solar that is to be installed in the next couple of years, and this will reduce the LEAC because it will supply a large portion of the island's needs.

Can you give me any tips on incorporating LEAC?

Thanks,

Rob

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pgilman

21 Jan 2020 16:41 #7887 by pgilman

Replied by pgilman on topic LEAC and Energy Rates on Guam

Hi Rob,

There is not a way in SAM to explicitly model an energy charge rate in $/kWh that is adjusted every six months.

You could use the "Electricity bill escalation rate" to approximate the effect of this varying charge. The escalation rate is an annual rate that applies to the total annual electricity bill, so it would only be a rough approximation of the effect of this type of increase.

Another possibility would be to estimate the total cost of the LEAC outside of SAM, and then apply it as a fixed monthly charge by averaging the cost of the LEAC over the life of the project.

These approaches might give you results for an approximate worst and best case scenario that you could use to inform your analysis.

Best regards,
Paul.

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frohro
Topic Author

22 Jan 2020 03:06 #7889 by frohro

Replied by frohro on topic LEAC and Energy Rates on Guam

Thanks Paul!
Your answer is helpful. What do you think about using the python API to add something like that in, so Guam's energy changes could be more accurately modeled?
Thanks,
Rob

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frohro
Topic Author

22 Jan 2020 04:24 #7890 by frohro

Replied by frohro on topic LEAC and Energy Rates on Guam

Hi Paul,
I guess I should be a little more precise on what I am considering doing with PYSAM. I would not include the LEAC in the cost of electricity, and run the SAM simulation without it. That would give me the expenses and the times they occur, (excluding LEAC). It would also give me the kWh generated/used. I would then include my best estimate of the LEAC rate as a time series, and use the LEAC rate to calculate LEAK charges as a time series. With these I could recalculate the present value, break even time, and any other financial benchmarks of interest.
It would be really nice if I could put those monthly expenses back into the SAM financial model, and be able to use it to do the benchmark calculations. I also like the ability to export to a spread sheet, because the financial guys I'm working with like excel, and don't know python. Is there a way to use SAM for the system, use python (or maybe LK) to create a time series of expenses for LEAC, and then put those back in so SAM's financial calculator can give the final results?
Is any part of this a good plan?
Thanks,
Rob

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pgilman

24 Jan 2020 22:57 - 24 Jan 2020 22:57 #7895 by pgilman

Replied by pgilman on topic LEAC and Energy Rates on Guam

Hi Rob,

You could use this kind of approach to calculate the "energy value" (annual_energy_value) input for the cashloan module: That value is the total annual electricity bill savings. That would look something like this:

1. Run pvsamv1 to get the time series (hourly or subhourly) generation profile in kW.

2. Run utilityrate5 to calculate the electricity bill with and without system ignoring the LEAC.

3. In your own Python code, adjust the monthly bill with system to account for LEAC to calculate a new value of annual_energy_value.

4. Run cashloan to get NPV, and other financial metrics based on SAM's cash flow model.

Best regards,
Paul.

Last edit: 24 Jan 2020 22:57 by pgilman.

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