CLCPA Solar and Wind Capacity Requirements

CLCPA Solar and Wind Capacity Requirements

On July 18, 2019 New York Governor Andrew Cuomo signed the Climate Leadership and Community Protection Act (CLCPA), which establishes targets for decreasing greenhouse gas emissions, increasing renewable electricity production, and improving energy efficiency. This is one of a series of posts on the ramifications of the “most aggressive climate law in the United States”.  This post addresses the wind and solar capacity necessary to implement the CLCPA by looking at a “best case” scenario.

CLCPA Target Overview

The Citizens Budget Commission developed an overview of the CLCPA targets in Green in Perspective: 6 Facts to Help New Yorkers Understand the Climate Leadership and Community Protection Act. The goals of the law are truly aspirational:

Reduce greenhouse gas (GHG) emissions:

    • Reduce GHG emissions to 60 percent of 1990 emissions levels in 2030;
    • Generate zero GHG emissions from electricity production by 2040; and
    • Ensure GHG emissions are less than 15 percent of 1990 emissions levels in 2050, with offsets to reduce net emissions to zero.
    • GHG offsets means that for every ton emitted into the air one ton is removed via GHG capture of some sort. For example, a company or individual can pay a landowner to leave trees standing that would otherwise be removed or plant additional trees to offset GHG emissions.

Increase renewable electricity:

    • Increase renewable sources to 70 percent by 2030; and

Develop or support:

    • 9 gigawatts (GW) of offshore wind electric generation by 2035;
    • 6 GW of distributed photovoltaic solar generation by 2025; and
    • 3 GW of energy storage capacity by 2030.
    • Conserve 185 trillion British thermal units (TBTUs) of annual end-use energy use by 2025, of which at least 20 percent should be from energy efficiency improvements in disadvantaged communities.
    • The CLCPA also requires between 35 percent and 40 percent of spending on clean energy or efficiency programs be in disadvantaged communities and mandates an air monitoring program in at least four such communities.

Simple Wind and Solar Capacity Model

I follow Michel at the Trust, yet Verify blog because he evaluates Belgian “green” technology quantitatively and has given many insights into potential issues that might also arise in New York. Moreover, like me he prefers working with real-world data. In a recent post Michel evaluated the potential effect of increased electricity production from intermittent energy sources with a simple solar and wind capacity increase data analysis model. He down-loaded solar generation, wind generation, and total load data for an entire year from the ELIA site. The solar and wind data were summed together for every time period, in his case 15 minutes. Then he projected solar and wind resources by multiplying the observed sum by different values.

Please go to the post and review the methodology and results. The results show that additional intermittent wind and solar capacity increases production peaks but does not increase production nearly as much during production valleys. In addition, the results show that as capacity increases more balancing mechanisms will be required. In my opinion the best part of the analysis was that the graphical results clearly showed these impacts.

As you can see in the comments I complimented Michel for the clarity of the analysis and asked if his model could be applied with New York data. He responded that it would be possible and I sent a link to the New York production data. I had intended to process the data for him to input but Michel graciously did the processing himself. (Fortunately for me because I no longer have access to data processing software, apparently I am the only one who wants to be able to use FORTRAN, so I have to brute force process data in a spreadsheet.) His results for 15x wind plus other renewables relative to total load are reproduced here.

Simple Wind and Solar Capacity Model with New York Data

Michel’s results used the historical data available at the New York Independent System Operator (NYISO) real-time fuel mix data dashboard. I will respond to his comments in the original post in more detail here.

Michel correctly determined that I only want to look at wind and “other renewables”.   I agree that the intermittent source results will not be as clear-cut as the Belgian data where wind and solar are registered on their own, showing the pure effect of the intermittent energy sources. The problem trying to estimate the effect of New York solar capacity increases is that solar is buried in “other renewables” which includes methane, refuse, or wood firing. Those other sources are not intermittent so we get mixed signals.

Michel used solar and wind capacity data but could not find corresponding New York capacity data, so he didn’t correct for potentially increasing capacity over the year. Unfortunately the NYISO data base does not provide a nice spreadsheet format capacity report like the ELIA generating facilities link. However, I don’t think there is enough added capacity to make a difference for this analysis. On the other hand Michel found that Belgian wind capacity increased by 500 MW and solar capacity increased by over 400 MW so he had to correct for that or the results would have been flawed.

Michel notes that the result is quite different from the Belgian data. In the first place New York is bigger. The ELIA link notes that total capacity in Belgium is 15,660 MW. The NYISO data are buried in Table III-3a Capability by Zone and Type in their annual Load and Capacity Data Report. In the summer the total capacity in New York was 39,245 MW in 2019. Secondly, peak loads are different. New York State production is highest in summer and lower in winter, just the opposite as Belgium. He correctly infers that air conditioning drives the peak load to the summer.

He correctly assumed that there is less solar capacity relative to wind in New York because solar capacity is so small that it does not have its own category. In the NYISO capability table there are only 31.5 MW of solar capacity. The ELIA solar-PV generation data link notes that “Elia has updated the register of total installed solar capacity in Belgium. As a result, the installed solar capacity increases with 416.27 MW” well over ten times as much as NY. However, the link also states that the monitored solar PV capacity is 3,369.05 MW. I assume that this refers to distributed solar PV capacity and also suggests the New York would be well served to start monitoring this capacity as well. The NYISO claims that there are 1,862 MW of solar PV nameplate capacity behind the meter.

Michel observes that consumption is higher in New York than Belgium and the share of intermittent energy smaller. As a result, the point where surpluses and shortages cancel out (without taking the losses into account) will be higher (somewhat higher than 25.5x, versus 8.5x for Belgium).

New York Simple Wind and Solar Capacity Model for August 2018

Michel’s model results indicate that August 2018 has many shortages so I looked at August 2018 data myself using a spreadsheet. My primary concern is the effect of the CLCPA on future capacity keeping in mind that the target is to eliminate fossil fuel use so I compared solar and wind only to fossil load, i.e., the output from the generators listed as fossil in Table III-3a: Capability by Zone and Type. Using the same data as Michel but only using renewables to replace fossil load gives a similar result. Note in the table August 2018 Simple Model 26 x New York Wind + Other Renewables vs. fossil load that surpluses are blue and deficits are red. There are more surpluses simply because fossil load is less than total load. Note that even if the wind and other renewable categories are increased 26 times the current rate existing fossil cannot be replaced without a lot of shortages.

I believe that the CLCPA claims that renewable energy can completely replace the current fossil fuel load are extraordinary. As such, its proponents have to provide extraordinary evidence that it can work. I have tried to modify the data to incorporate reasonable assumptions about the future using “best case” assumptions about the availability of solar and wind. These are “best case” estimates because I assumed that solar and wind are available at their rated capacities every hour in my test period. Because those sources are intermittent the amount of time when they are available at full load is not constant. For example, solar availability varies during the day and over the month of August there will be periods when the wind is blowing less than optimal. On the other hand assuming that Indian Point capacity is not available at its rated capability is a reasonable assumption because it usually runs at full load except for maintenance.

I don’t think there will be any significant increase in hydro or the other renewable category sources of methane, refuse, or wood firing and they are not intermittent so I made no changes to those categories. Incredibly New York is shutting down 2,067 MW of nuclear at Indian Point in the next several years because public perception of nuclear is a more important consideration than the existential threat of climate change. I subtracted that amount from every hour. The CLCPA plan currently calls for 9,000 MW of off-shore wind power so I added that amount to every hour. The CLCPA plan also calls for 6,000 MW of solar PV power. In order to account for daylight I added 6,000 MW to every time period from 0700 to 1955. The results in August 2018 Simple Model CLCPA Renewables vs. fossil load show the same thing: adding solar and wind capacity significantly adds to surplus loads but does not reduce the deficits nearly as much even if it were available at the full capacity every hour.

I tried to estimate capacity from an even more aggressive implementation plan (doubling the offshore wind and solar additions to 18,000 MW and 12,000 MW respectively). However, doing that would show positive numbers unless there is a correction for off shore wind intermittency if I simply added another 9,000 MW of wind to every hour. In order to account for wind intermittency I scaled the offshore wind resource down when the on shore resource reached half of the observed maximum. I scaled the resource proportional to the observed decrease in the 99th to the 70th percentile on-shore resource to the 50th. For example, when the on shore wind resource was at the 50th percentile I estimated that the off-shore wind resource was proportional to the 99th divided by the maximum observed onshore wind resource. I made similar corrections for even lower levels and I believe this is conservative. Again, as shown in August 2018 Simple Model Aggressive CLCPA Renewables vs. Fossil Load, the surplus increases by adding solar and wind capacity at full capacity but we still will have to deal with significant deficits.

My takeaway point is that even with unrealistic assumptions about the “best case” availability of solar and wind capacity, there are periods with significant deficits. In order to prove the extraordinary claim that solar and wind can replace existing fossil the State of New York, a similar type of analysis using actual data to estimate realistic energy production must be done. That is the only way to provide the extraordinary proof showing just how much energy storage will be required to prevent deficits. I will take a preliminary look at the energy storage ramifications of this in a future post.

 

Author: rogercaiazza

I am a meteorologist (BS and MS degrees), was certified as a consulting meteorologist and have worked in the air quality industry for over 40 years. I author two blogs. Environmental staff in any industry have to be pragmatic balancing risks and benefits and (https://pragmaticenvironmentalistofnewyork.blog/) reflects that outlook. The second blog addresses the New York State Reforming the Energy Vision initiative (https://reformingtheenergyvisioninconvenienttruths.wordpress.com). Any of my comments on the web or posts on my blogs are my opinion only. In no way do they reflect the position of any of my past employers or any company I was associated with.

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