NYS REV Investment Cost Effectiveness

Earlier this month I did a series of posts on the Citizens Budget Commission Getting Greener Report and this post addresses one of their recommendations.  In particular, they recommended that New York State “Establish a prioritization system to pursue renewables that provide the greatest GHG reductions at lowest cost.”  The Clean Energy Dashboard has data to start just such a system.

In my post on the New York Clean Energy Dashboard I noted that it provides data describing Reforming the Energy Vision program activity by electric and gas utilities and the New York State Energy Research and Development Authority (NYSERDA)”.  The dashboard has data that can be used to determine the cost efficiency of CO2 reductions.   In my previous post I presented the total cost effectiveness of all the programs and in this post, I break down the cost effectiveness by program for a first attempt at setting priorities.


In order to determine which programs provide the greatest GHG reductions at the lowest cost we can filter Clean Energy Dashboard data twice and calculate a cost per ton reduced for each program.  To get emission reductions, the Clean Energy Dashboard needs filters for C02e Emission Reductions, Gross Annual (Metric Tons) and acquired savings.  I accessed the data tables and downloaded the data in the View Progress by Program tab that includes CO2e Emission Reductions, Gross Annual (Metric Tons).

To get the money spent to get those emission reductions, the Clean Energy Dashboard needs filters for Budget (dollars) and acquired savings.  We are asking for the money spent when “both the measure is installed and currently operational, and the funds associated with the measure or project have been expended.”  I access the data tables and downloaded the data in the View Progress by Program tab that lists the Budget (Dollars) data.

The next step was to combine the two data sets so that I could match the programs listed in each data set.  There was not a complete one-to-one correspondence between the programs so I manually edited the file to match all the programs possible.


Once I had a data file with one-to-one correspondence, I found that there were three categories.  One program was included with emission reductions but no budget dollars and 52 programs had budget dollars but no emission reductions.  There were 107 programs with data for CO2e Emission Reductions and Budget dollars so that I could calculate cost effectiveness.

There was one Central Hudson program that had CO2e Emission Reductions but no budget funds.  In their Community Lighting program Central Hudson partners with local not-for-profit organizations to distribute free LED lightbulbs to eligible residential  customers and has reduced 334.21 tons of CO2e.

The 52 programs with spent money but no emission reductions were primarily NYSERDA projects.  These programs had an acquired budget total of $113,401,265. There were five Con Ed programs, two National Grid (NiMo) programs and the remaining 45 programs were all from NYSERDA.  I think I will return to these programs later because the emphasis in this post is on the programs where we can estimate cost effectiveness.  For now the New York State Clean Energy Dashboard Programs with Budget Money but No CO2e Emission Reductions table lists the programs.

For the 107 programs with both emission reductions and budget data, I divided the funds spent by the CO2 reductions to determine the CO2 invesment efficiency ($/ton) for each program.  The Carbon Dioxide Equivalent Cost Effectiveness Reductions table lists the cost effectiveness data for each program along with the administrator, program name and description, CO2e reduction and acquired funds spent ranked by the cost per ton.  I summarized the results in the Summary of Carbon Dioxide Equivalent Cost Effectiveness Reductions table.  Note that there were a total of 3,056797 CO2e emission reduction tons and an acquired budget total of $937,958572 which works out to an overall cost per ton rate of $306.84 per ton CO2e reduced.

The Social Cost of Carbon (SCC) is supposed to represent the future cost impact to society of a ton of CO2 emitted today.  I believe New York is going to base its carbon pricing on the $50 global social cost of carbon at a 3% discount rate.  In other words, if we spend more today than $50 per ton then we exceed the future cost impact to society. The summary table lists data by different multiples of the $50 SCC cost and shows that only two programs are below that criterion.  Seven programs are under $100, 19 more are under $250, and 79 programs exceed five times the SCC threshold.


There are a wide range of project types in the 107 programs included in the analysis.  There are concerns about the quality of the CO2 reduction estimates especially with regards to a verifiable methodology and how the costs for the programs are calculated.

I worry more about the CO2 reduction estimates.  For example, compare NYSE&G Energy Marketing Gas Program (#6 in the Carbon Dioxide Equivalent Cost Effectiveness Reductions table) with Central Hudson Behavorial Modification (#7).   The NYSE&G program is an online Energy Marketplace that offers instant rebates to residential customers who purchase qualifying  Wi-Fi thermostats.  I imagine that the program managers for this project found some analysis that provided a range of CO2 reduction estimates for wi-fi thermostat installations and then combined that estimate with the number of thermostats sold to come up with the reduction.  However, this estimate has to assume that the installation of the thermostat led to an energy-saving change at the homes in question and how much of a change.  Unfortunately this assessment is a relatively strong one as compared to the Central Hudson behaviorial modification program.  In that project Central Hudson set up a customized web portal for customers to access and track energy usage, and to access energy saving tips and savings.  The only way I to see how to quantify how that access changed behavior that in turn reduced CO2 emissions is to guess.

As noted previously, there are only two programs with claimed CO2 reduction effectiveness less than the SCC target value of $50.  The better of the two, NYSERDA Clean Energy Communities program, claims 220,182 tons in reductions at a cost of $4,947,773.  The program provided  assistance, technical support, and tools and resources to local governments for implementing clean energy High-Impact Actions in local communities.  The NYSERDA website describes the Clean Energy Communities program:

“Building a more sustainable New York starts with building more sustainable communities. Local governments affect energy choices in their communities, from government operations to homes, businesses, and community institutions.  Local governments in New York State can use the Clean Energy Communities program to implement clean energy actions, save energy costs, create jobs, and improve the environment. In addition to providing tools, resources, and technical assistance, the program recognizes and rewards leadership for the completion of clean energy projects.”

I classify this program as more unverifiable than most others.   Digging down into the project descriptions for this program you find for example providing incentives to a local government to install an electric vehicle charging station.  There is no way to estimate how much use that charging station has been used and how much CO2 was avoided.  As a result, I am not comfortable that this program did in fact produce the CO2 emission reductions claimed.

On the other hand, the second program that was better than the SCC target, NYSERDA Industrial Transition program (#2), provided technical and financial support to assist industrial and data center facilities with process improvement projects to help link energy and their core mission.  Those facilities very likely quantified the before and after implementation energy usage and could therefore provide a emission reduction that can be traced to verifiable information.  Therefore, I am more comfortable that this program did produce the CO2 emission reductions claimed.

There also are issues with the cost estimates.  On the face of it this should be simpler because the project managers must know how much money is being spent.  However, it gets more complicated when you consider the lifetime effectiveness of the investment.  For example, if you pay for LED lighting to replace  incandescent bulbs the investment is effective over the lifetime of the LED lights.  For my calculation I made the simple assumption that it is appropriate to use the total cost to get the reduction irregardless of the expected lifetime of the investment.


There is political, personal, and organizational pressure for larger as compared to smaller CO2 reductions for these programs.  As shown above, many of the programs have largely unverifiable emission reduction calculation methodologies.  I conclude it is likely that the emission reduction estimates for these programs are higher than we can actually expect to see.  The costs over time could be different too.

Nonetheless, these are numbers that can be used to meet the Citizens Budget Commission recommendation that New York State “Establish a prioritization system to pursue renewables that provide the greatest GHG reductions at lowest cost.”  This post provides a first cut list to set those priorities.

My bigger concern is the very poor performance of these programs relative to the SCC target levels.  As Resources for the Future explains:

One of the primary ways the SCC is used in policy design and evaluation is through benefit-cost analysis. A benefit-cost analysis compares the total economic benefits of a proposed policy to its total economic costs. Take, for example, a regulation that limits air pollution: its total benefits—including those from improvements to public health and the environment due to better air quality—would be compared against the implementation costs, such as the purchasing and installation of equipment to control air pollution. Benefit-cost analysis has been a required part of federal regulatory analysis since it was implemented by the Reagan administration in 1981.

The SCC is used in benefit-cost analysis to quantify the dollar-value of a policy’s effect on climate change due to changes in greenhouse gas emissions. For policies that increase emissions, the expected increase in emissions (in tons) is multiplied by the SCC, and the result is included as part of the total estimated costs of the policy. For policies that decrease emissions, the change in emissions is multiplied by the SCC, and the result is added to the expected benefits of the policy.

The bottom-line concern is whether New York State should be pursuing any of the 105 programs whose decrease in emissions exceeds the SCC cost benefit threshold of $50.  The performance of these programs is not encouraging.  There are 79 programs that exceed five times the $50 SCC threshold that total $801,173,268 but only claim reductions of 1,494,548 tons for a cost effectiveness of $536 per ton reduced.  Combine those programs with the 52 programs that claim no CO2 reductions, REV programs in the Clean Energy Dashboard have spent over $914 million with very little emissions reductions to show for it.

NYISO Wind Generation Record Publicity

The New York Independent System Operator (NYISO) issued a press release on December 17, 2019 announcing a new wind generation record for the state.  I disagree with the tenor of the press release and this post explains why I think it is inappropriate.  It was a lost opportunity to educate the public about the magnitude of the effort needed to meet the State’s ambitious clean energy goals.

Press Release

The press release stated:

Strong winds across New York State over the weekend pushed electricity generated by wind power to a new record.

The new record output of 1,675 megawatts (MW) was set during the 11:00 p.m. hour on Saturday, December 14, eclipsing the previous record of 1,651 MW which was set during the 8:00 p.m. hour on April 26, 2019.

When overall wind production peaked at 1,675 MW on Saturday night, it provided 11% of all energy generation in New York. The record output represents 84% of the 1,985 MW of installed wind capacity in New York State.

One megawatt is approximately the amount of electricity required to supply 800 to 1,000 homes. Interested parties can track the NYISO’s real-time fuel mix on our website, www.nyiso.com.

In my opinion the press release is thinly veiled propaganda support for the Climate Leadership and Community Protection Act (CLCPA) which includes a requirement to eliminate the use of fossil-fueled electric generation by 2040.  Announcing this record without qualifying the wind resources of New York gives the impression that the State is on track to meet that target.

Right off the bat note that the “record output represents 84% of the 1,985 MW of installed wind capacity in New York State.  Think about that.  The State has invested in wind energy and the best they have done is 84% of the total installed.  Unfortunately, when you look at the big picture serious problems show up.


I used two sources of data from NYISO to evaluate the existing New York wind energy resource.  For an overview I used the annual report that presents load and capacity data including historical and forecast seasonal peak demand, energy usage, and existing and proposed generation and transmission facilities.  The Load and Capacity Date Report or Gold Book is a featured report in the NYISO document library.  This post and a summary I posted in April 2019 use data in Table III-2 Existing Generating Facilities from those reports to describe the annual wind energy resources available.  Note that in 2018 all wind energy came from on-shore facilities.

The NYISO Real-Time Dashboard includes a window for the real-time fuel mix that includes the amount of wind generation being generated in the state.  The window also includes a link to historical data.  I downloaded data for all of 2018, sorted out the wind production numbers, and then calculated hourly averages to compare with the annual numbers from the Gold Book.  I use Statgraphics Centurion software from StatPoint Technologies, Inc. to do my statistical analyses and in this case I loaded the hourly data and calculated frequency distribution statistics.


The NY 2018 Wind Facilities in the NYISO 2019 Gold Book table lists all the New York wind energy facilities.  The NYISO table provides the name plate ratings and 2018 net energy produced.  I used that information to calculate the annual capacity factor for each facility.  Note that there is a wide variation of capacity factors, that the highest is only 35.7%, and the state-wide capacity factor is only 24.5%.  In other words, New York wind facilities only provide a quarter of their name plate capacity.  So in the best hour wind energy has reached 84% of the nameplate capacity and over the year wind energy only produces only 24.5% of the possible power that could be produced.  But wait, there’s more.

Another wind-resource issue is the distribution of the hourly output.  The 2018 Hourly Wind Generation (MW) Frequency Distribution document lists frequency distribution data for all of 2018.  The histogram of wind output categories shows a skewed distribution such that low output is more frequent than high output.  The frequency tabulation for wind table shows that there were 10 hours when none of the 24 wind facilities in the state produced any power and that 32% of the time less than 200 MW per hour was produced.  The percentiles indicate that half the time hourly wind output is less than 346 MW and that for 876 hours (the tenth percentile) wind energy provides less than 49 MW of energy.

If New York has to rely on renewable energy in the future it is important to know the frequency distribution of wind at night when solar output is unavailable.  I used the New York City sunrise and sunset times and calculated when it was dark.  The 2018 Hourly Wind Generation (MW) Frequency Distribution at Night document lists the same statistics as before but only for night time hours.  While there was only one hour with no wind output and the frequency of hours with output less than 200 MW was down to 28% there still is a significant number of hours when there is no appreciable renewable energy being generated. The percentiles indicate that half the time at night hourly wind output is less than 367 MW and that for 876 hours (the tenth percentile) wind energy provides less than 65 MW of energy.  That means that energy storage is going to be absolutely necessary.


I think that the independent system operator has an obligation to the consumers of the state to tell it like it is.  This politically expedient press release did not mention any of the issues associated with wind energy relative to the CLCPA target.  Based on my results I am sure they could have easily found a day when the wind resources were weak.

I have no doubt that NYISO knows about these issues.  They know that the annual capacity factors are low.  I have never seen them publish the distribution of hourly wind output but I have to assume that they have looked at the resource in a similar manner.  I did not think it would be as bad as it is, and these results have important implications with respect to energy storage.  In an earlier post I estimated how much energy storage would be needed for one example period and the costs are startling.

Advocates for renewable power maintain that it is possible to address the problem of calm winds at one location by simply adding facilities in other locations where the wind is blowing.  If that were the case using New York resources the hourly distribution would not show that 5% of the time the total wind energy production for the entire state was less than 24 MW.  Furthermore, I suspect that even expanding the location of wind facilities to off-shore New York and adjoining jurisdictions is not going to significantly reduce the number of hours when wind resources are going to have to be supported by energy storage.  The fact that night time wind generation also shows significant hours with low levels exacerbates the need for energy storage because we cannot use solar to shave the amount needed.

I am very disappointed that NYISO ignored the opportunity to educate the public about the limitations of New York’s wind energy resource.  These results reinforce my position that New York State has to do a comprehensive analysis of the availability of renewable resources to determine a strategy for meeting demand with an all-renewable system.  Until that is complete, we are only guessing whether this can be done, much less how much this is all going to cost.  The NYISO should be pressing for this analysis and this was an opportunity to explain why it is necessary.

New York Resource Adequacy Proceeding Comments

The New York State Public Service Commission (PSC) issued an order commencing a proceeding to examine how to reconcile resource adequacy programs and the State’s renewable energy and environmental emission reduction goals. This post describes the comments I submitted in this proceeding.

Materials and information are available in the Department of Public Services (DPS) resource adequacy matters docket Case 19-E-0530.  .  According to the Order Instituting Proceeding and Soliciting Comments, the inquiry is “necessitated by the Commission’s statutory obligations to ensure the provision of safe and adequate service at just and reasonable rates. Costs to consumers are a primary and ultimate consideration, recognizing that the necessary investments in resources must have sound economics.”

The PSC order solicited comments on the following questions.  Does the New York Independent System Operator (NYISO) have sufficient resource adequacy evaluation mechanisms in place to deal with the State’s ambitious renewable energy and environmental emission reduction goals?  Do the policies and market structure mechanisms insure just and reasonable consumer rates? There were several specific questions about existing products and their value with respect to costs.  Finally, there was a general question about the State’s role with respect to resource adequacy and request for recommendations for what to do next.

I submitted comments because I am not sure that the Climate Leadership and Community Protection Act (CLCPA) can be implemented so that it does not jeopardize safe and adequate energy service at just and reasonable rates. I based the comments on evaluations I did for previous posts on Solar Issues in Upstate New York , CLCPA Solar and Wind Capacity Requirements and CLCPA Energy Storage Requirements.

My filed documents (dated 9/16/2019 as a filing on behalf of an individual) illustrate my concerns with two examples.  I prepared a white paper that provides an initial estimate of the likely energy storage component requirement based on real world data.  It shows that at night when winds are light the energy produced from these sources will have to be supplanted with stored energy if New York shuts down all its fossil generation.  Given the extraordinary cost of battery energy storage I estimate that the batteries alone will cost over $12 billion to replace existing fossil generation and Indian Point after it retires.  The second example describes a potential problem with winter peak loads once the CLCPA is implemented.  Because of the stringency of the law, home heating is going to have to be electrified.  The preferred retrofit option is an air source heat pump.  However, they don’t produce heat when the temperature gets below zero so homeowners will need a backup system and the cheapest alternative is radiant heat which is much more inefficient.  As a result there will be a spike in electrical load that cannot be avoided.

Both examples used data from the NYS Mesonet.  I believe the best way to determine resource adequacy is to base the analysis on historical meteorological information as shown in the examples.  In order to determine the amount of energy storage you have to calculate how much wind and solar power is available and when.  In order to determine the effect of air source heat pumps meteorological data from the winter 2017-2018 peak load period was used.  I recommended that historical meteorological data be used to characterize potential solar and wind energy production to determine the feasibility of the CLCPA emission reduction target that eliminates emissions from electricity production by 2040.

In addition, I believe that the State needs to do a cumulative environmental impact assessment of this regulation.  The problem is that while an individual industrial wind facility or solar facility may not have a significant environmental impact the cumulative impact of all the facilities necessary to provide enough power to meet the reliability needs of the state could have significant environmental impacts.  For example, if one raptor gets killed by every ten wind turbines that might be acceptable but if we need a thousand wind turbines is one hundred raptors per year acceptable?

My final recommendation is for an independent review of the findings of the feasibility studies.  The CLCPA is the result of political pandering and the likelihood that a feasibility study would be subject to political influence is high.  The only way I can think of to prevent that is to establish an independent group to review the findings.  Membership should deliberately be chosen to represent both “sides” of vested interests in the outcomes.  They may not be able to come agree but their evaluation report can list where they have agreed to disagree and that will be useful for the public.

I think it is obvious that the resource adequacy proceeding must determine if the CLCPA can be implemented such that it does not jeopardize safe and adequate energy service at just and reasonable rates.  If renewable resources and energy storage are inadequate during the winter peak, then safe and adequate energy service could easily be jeopardized.  No jurisdiction has ever successfully reduced greenhouse gas emissions by developing renewable energy resources and managed to keep prices down and I see no reason that New York will be able to reverse that result.  Most importantly, the increase in energy prices will affect those who can least afford the increased costs.

If you are a resident of New York I ask that you submit comments to the DPS resource adequacy matters docket Case 19-E-0530 supporting the request for comprehensive, independent feasibility and cumulative environmental impact assessments.

Rocky Mountain Institute – Natural Gas Plants are Doomed

According to Bloomberg author David Baker Gas Plants Will Get Crushed by Wind, Solar by 2035.  The basis for this claim is a Rocky Mountain Institute (RMI) study.  This post looks at this claim in the context of New York State energy requirements.

Baker’s description of the study “The economics of clean energy portfolios”, states:

“Natural gas-fired power plants, which have crushed the economics of coal, are on the path to being undercut themselves by renewable power and big batteries, a study found.  By 2035, it will be more expensive to run 90% of gas plants being proposed in the U.S. than it will be to build new wind and solar farms equipped with storage systems, according to the report Monday from the Rocky Mountain Institute. It will happen so quickly that gas plants now on the drawing boards will become uneconomical before their owners finish paying for them, the study said.”

The RMI study claims that a “clean energy portfolio” can “provide the same services as power plants, often at net cost savings”.  These portfolios combine the following different resources: energy efficiency, demand flexibility, distributed and utility-scale battery energy storage, and variable renewable energy.  In previous work I have come to the conclusion that for New York State the critical planning scenario will be winter time heating caused high energy demand night-time loads when winds are calm. Keep in mind that during winter it is not only a short-term load concern but the shorter days and generally weaker winds mean that seasonal solar and wind resources are so low that seasonal storage will likely be necessary.  Let’s look at each of these resources in more detail in that context.

According to RMI the energy efficiency resource includes “Physical measures, software controls, or other strategies to reduce the amount of energy required to perform a given service (e.g., insulation and smart thermostats to reduce heating and cooling energy use)”.  Because there are tangible savings many structures already have insulation and smart thermostats.  In fact, I doubt that my home is all that unusual in that since we purchased the home in 1981, we added insulation to the attic a couple of times, insulated the walls, put in double paned insulated windows and doors, and have a smart thermostat.  Anything else we do will cost quite a bit and not get that big an energy reduction.  As a result, I believe that there is a limit to how much energy can be reduced with the proposed energy efficiency resource.  More importantly, the New York Climate Leadership and Community Protection Act has a greenhouse gas emission reduction target that will require electrification of wintertime heating.  RMI cannot claim a reduction in wintertime electric energy when there is a requirement for more winter electric energy use.

The study describes demand flexibility as: “Load controls to enable electricity consumption to shift through time without reducing overall energy use or service quality (e.g., thermal storage in water heater tanks, managed charging of electric vehicles)”.  In general, the theory that load controlling smart meters can make a significant difference is mostly “theory”.  As before in the case of wintertime heating, how much load shifting will be possible?  It is appropriate to point out that the four case studies that “proved” their claims were on the west coast, Florida, mid-Atlantic and in Texas.  None of these regions have winter peaks now and I doubt that even if winter heating is electrified it is unlikely to shift the peak to winter.

The RMI study defines variable renewable energy as: “Behind-the-meter and front-of-the-meter distributed and utility-scale solar photovoltaics (PV) and wind turbines that provide weather-dependent, non-dispatchable energy”.  The resources necessary in this study use a “clean energy portfolio optimizer” that “draws on the other components to define the constraints and objective function of a linear program that finds the lowest-cost portfolio of resources that can provide at least as much monthly energy, capacity during the 50 peak hours, and single-hour ramp capability during the highest period of system-level net-load ramp as the announced natural gas-fired power plant, while staying within resource potential limitations.”  Therein lies a potential fatal flaw for New York.  RMI minimizes the magnitude of peak load impacts with its energy efficiency and demand flexibility resources but averages out renewable energy deficits by using monthly energy and a limited number of peak hours.  The only way to determine if their portfolio will work is by evaluating shorter time periods, at longest an hourly period but even shorter would be better, over years of real-world data.  Based on my analysis of real-world examples I believe it is possible that the worst-case planning scenario will not be the peak load but the minimum renewable energy output.

Finally, the study includes battery energy storage: “Dedicated battery storage assets, either in front of the meter or behind the meter, providing energy balancing and flexibility via controlled charging and discharging.”  RMI published a study in 2015 that describes 13 different services that battery energy storage can provide.  There is a large gap between saying that batteries can provide the services and how they would do that.  Again, an hour-by-hour feasibility needs to be done to determine if this is possible.  In addition, RMI claims more value by stacking these services from “the same device or fleet of services”.  In other words, they claim that one battery system might be used, for example, for frequency regulation, voltage support, and energy storage.  A much more sophisticated study than this overview study is needed to determine whether that is feasible.  Frequency regulation and voltage support might require batteries to be at mid-charge levels to balance peaks and valleys whereas you want your energy storage to be at the maximum charge for use when renewables are not available.

In general, this study chooses how it wants to treat its resources.  There are hopeful assumptions for distributed resources and battery energy storage that have no track record.  There is no consideration of life-cycle resources needed for all the batteries, solar panels and wind turbines. Finally, while the treatment of the technological components necessary to provide the resources are overly optimistic in my opinion, their treatment of costs is much worse.  Both current costs and expected cost expectations in the future are more aspirational than rational.

No doubt this study will be cited as proof that natural gas is not necessary for the future because renewables can do everything they do cheaper.  It would take an electrical engineer with transmission and generation expertise to fully evaluate this study.  However, there are enough broad assertions and convenient assumptions that I do not take this study as definitive evidence that a clean energy portfolio will be able to replace natural gas fired power plants anytime soon in New York.

New York City Energy Storage Peaking Turbine Replacement

The biggest air quality issue in New York State is compliance with the National Ambient Air Quality Standard for Ozone. In order to meet that limit the New York State of Department of Environmental Conservation (DEC) proposed regulations earlier this year to lower allowable nitrogen oxide (NOx) emissions from simple cycle and regenerative combustion turbines during the ozone season. The problem is that these turbines are needed to keep the lights on during periods when needed most so replacement is not very simple as I explained in an earlier post.

This post describes the State’s evaluation of the politically correct alternative, energy storage, to provide the power generated by these turbines. This post addresses the report findings for turbines that could be directly replaced by energy storage. I want to emphasize that the following represents my opinion and not the opinion of any of my previous employers or any other company with which I have been associated. I have been following the operational implications of these turbines and their effect on ozone for over 20 years.


The evaluation of using energy storage to replace these peaking units is part of the New York State Energy Storage Roadmap announced by Governor Cuomo in June 2018. As part of that effort the Department of Public Service (DPS) established an Energy Storage Deployment Program. On July 1, 2019, Energy Storage Deployment Program Report – Unit by Unit Peaker Study was submitted to the docket for Case 18‐E‐0130 – In the Matter of Energy Storage Deployment Program. DPS staff, working with New York State Energy Research and Development Authority (NYSERDA), Long Island Power Authority (LIPA), New York Independent System Operator (NYISO), NY Department of Environmental Conservation (DEC), Con Edison, and consulting firm Energy and Environmental Economics, Inc. (E3) prepared the report. The DPS December 12, 2018 Order Establishing Energy Storage Goal and Deployment Policy directed them to develop a unit‐by‐unit operational and emission profile study and methodology to determine which downstate peaking power plant generating units are potential candidates for repowering or replacement. My previous post describes these peaking turbines and more detail on the rationale for replacement so I will not repeat that material here.

The December 2018 DPS Energy Storage Goal and Deployment Policy specified what was to be included in the analysis. It was to “include a series of reliability and operational assessment studies looking at the equivalent level of ‘clean resources’ that could provide the same level of reliability as the existing peaker units. Hybridization and repowering with energy storage, as well as replacement with stand-alone energy storage, should be explicitly examined, according to the Roadmap.”

According to the description in Energy Storage Deployment Program Report – Unit by Unit Peaker Study:

The analysis relies on historical 2013 hourly operational and emissions data for the approximately 4,500 MW of affected peaking units across the state (almost entirely concentrated in New York City, Long Island, and the Lower Hudson Valley) to examine the technical feasibility of energy storage or energy storage paired with solar providing equivalent historical generation of the peaking units. Peaker operational and emissions data from 2013 was chosen because this reflects the peak NYISO demand year, and the correspondingly high levels of peaker operation which occurred in July 2013. This served as a proxy for representing peak‐level system operations, although theoretical peak system operations may impose incremental needs beyond those of 2013. The study did not consider system changes after 2013 that may impact how conventional peaking units and energy storage resources operate in the future, such as retirements of existing units, changes in the overall levels and patterns of demand, new transmission solutions, and/or the addition of more intermittent, renewable energy.


I am not a fan of the approach used in this analysis because I think it gives some mis-leading unit specific information. In the first place they considered all turbines as candidates not understanding that the primary purpose of some turbines is not to provide power during high load demand periods. They wasted effort considering the Jamestown Public Utilities turbine in Western New York that runs on the order of half the time. Peaking turbines are defined as units with an “average annual capacity factor of 10.0 percent or less over the past three years”. In addition there are turbines at steam boiler facilities that are necessary for “black start” situations when there is a blackout and the power necessary to start up the boiler is unavailable from the grid. Because that is a very rare instance the units are also run to provide power for peak power periods. In my opinion it would not be cost effective to dedicate energy storage for this application. You could not use it for peak loads because you never know when the grid power won’t be available. In conclusion the report considered units that should not have been included.

According to Table A-1 in the report, there are 3,780 MW of peaking turbines in New York. The report concludes that “Overall, at least 275 MW of peaking units, or around six percent of the total rated capacity of the fleet, are found to be potential candidates for replacement with 6‐hour energy storage sized to the maximum 2013 output of each peaking unit.” That means that a 6-hr energy storage system would be able to replace 7% of the existing peaking turbine capacity. The report goes on to say that “This number increases to over 500 MW when using 8‐hour duration storage”, but that only increases the replacement of existing capacity to 13%.

I don’t disagree with their conclusion that “Energy storage or a combination of energy storage and solar can contribute towards meeting NOx limits for a large number of units”. However there is a long way between “can contribute” and “will actually be an option used”. This is a preliminary scoping study. It notes that the “minimum size storage required to meet the NOx requirements can vary between units of the same facility” but does not recognize that the variation between sister units at a facility does not mean that one unit is more of a candidate than another.  The reality is that affected sources will adopt a facility‐wide strategy to meet the NOx limits and those strategies were not examined in this report.

There are other issues as noted in the Conclusion and Recommendations for Further Study. They note that “A more detailed analysis will be needed to understand the reliability impacts of specific unit replacements, especially as loads and resources change with greater electrification of transport and buildings and higher penetrations of renewables.” Many of these peaking units are in load pockets and changes in the load will drive whether energy storage is viable.


The report states that “A more detailed and thorough benefit‐cost analysis would need to be performed to understand the true economic viability of the replacement and/or hybridization options presented in this analysis.” Therein lies the biggest issue of energy storage – the cost. For those of us outside of Albany who care about costs a recently released report from the National Renewable Energy Lab (NREL): “2018 U.S. Utility-Scale Photovoltaics-Plus-Energy Storage System Cost Benchmark” provides information that can be used to estimate the costs of the energy storage option.

The NREL study lists costs for durations up to four-hours but the DPS report also includes six-hour and eight-hour durations. Table 3 in the NREL document, Detailed Cost Breakdown for a 60-MW U.S. Li-ion Standalone Storage System with Durations of 0.5–4 Hours, provides the information necessary to extend their projections to those different durations. I fit a linear regression model to describe the relationship between the specific costs and energy storage duration from the NREL table. I use Statgraphics Centurion software from StatPoint Technologies, Inc. to do my statistical analyses because it enables the user to choose the best relationship from 27 different linear regression equations. In this evaluation, in every instance, the reciprocal-X model (Y = a + b/X) statistic was the best choice and every regression had an R-squared coefficient great than 99.9% which indicates a strong relationship and suggests that these estimates are good enough for this analysis.

The NREL analysis includes all the costs for a greenfield energy storage project so I calculated values of retrofit potential costs that exclude the land acquisition costs. I estimate the installed cost for energy to be $343/kWh for an eight-hour battery system, $355/kWh for a six-hour battery system, and $380/kWh for a four-hour battery system.

The table NYC Energy Storage Peaker Replacement Summary lists data from the DPS study and calculated values. Table E1 in the DPS report lists the total nameplate capacity (MW) of peaking units that can potentially be fully replaced with storage to meet the 2025 NOx limits at 100% sizing to each unit’s 2013 peak generation. Note that I did not include the upstate turbine included in the DPS report in this analysis because it is not a peaking turbine. There are 36 MW of peaking unit capacity in New York City and Long Island that can be replaced with four hours of storage, 229 MW that can be replaced with six hours of storage, and 463 MW with eight hours of storage for a total of 728 MW. This is 18% of the 2013 peak load in New York City and on Long Island. Table A estimates the replacement cost estimate using the NREL report numbers and shows that replacing 18% of the load with Li-ion battery storage would cost $1.8 billion.

The cost per ton removed further demonstrates the staggering cost implications. I could not figure out which particular units were candidates for replacement because my analysis of Table B-1 did not result in the same number of units in each category. As a result I could not calculate the unit-specific cost per ton removed. Instead I just used the total emissions from all the sources the report’s Table 3: Peaking Units 2013 Operational Data. Table B shows the costs if all the emissions from all the peaking units came only from the 728 MW that can be replaced by energy storage. The cost to remove a ton of NOx is over $900,000 per ton and cost to remove a ton of CO2 is over $1,000 per ton. In order to put those numbers in perspective consider that the social cost of carbon (the alleged societal cost per ton of CO2 emitted) is currently around $50 by the Obama administration method and less than $5 by the Trump administration.


The report concludes “Overall, the findings suggest that there is an opportunity to consider replacing or hybridizing a substantial portion of the peaking units subject to DEC’s proposed NOx rule with a fleet of storage resources paired with solar. Such an outcome would potentially deliver significant environmental benefits, advance the state’s carbon reduction and clean energy goals, as well as benefit historically disadvantaged populations and communities such as environmental justice areas in line with the goals of the Climate Leadership and Community Protection Act.” However these results show that the cost of energy storage replacement is at least an order of magnitude greater than the cost of carbon’s impacts so this opportunity is not a cost-effective way to advance the state’s carbon reduction and clean energy goals.

NYS Annual Wind Energy Production


New York’s transition to the clean energy utopia envisioned by Governor Cuomo’s Reforming the Energy Vision and New York Green New Deal depends in no small part upon wind energy. This post summarizes the status of wind energy in New York at the end of 2018.

The New York State Independent System Operator (NYISO) publishes an annual report that presents load and capacity data including historical and forecast seasonal peak demand, energy usage, and existing and proposed generation and transmission facilities. The Load and Capacity Date Report or Gold Book is a featured report in the NYISO document library. This post uses data in Table III-2 Existing Generating Facilities from those reports.


In order to summarize the current state of wind energy generation in New York I will provide a table with all the existing wind facilities based on the NYISO data. Gold Book Table III-2, Existing Generating Facilities lists all existing generating resources operating in the New York Control Area. It provides information on generator ownership, location, in-service date, fuels used, and generator type. It includes values for nameplate rating, NYISO summer Capacity Resource Interconnection Service (CRIS) MW values for generators, summer and winter capability, and net energy generated during the preceding calendar year.

The New York State Wind Facility Status table lists the generating facilities categorized as wind units. It lists the nameplate capacity rating in MW and the capacity factor for each facility. The capacity factor is a calculated value that describes how much energy was actually produced (MWh) relative to the total generation that could have been produced if the unit ran at the nameplate rating 8,760 hours per year. The table lists the calculated statewide net energy produced by all the wind facilities and the annual potential capacity and the statewide wind energy capacity factor. The spreadsheet with all these data is available upon request.


At the end of 2018 there were 24 wind facilities in the NYISO report including two new facilities that began operating during the year. There are 1,982 MW of wind power available within New York. However, the capacity factor for all the facilities was only 24.5% and they only produced 3,985 GWh of energy when the wind was blowing.

I have read that wind turbine performance degrades over time so I checked that out. The Maple Ridge 1 wind farm has been in operation for 12 years. The 2018 capacity factor was lower than the peak year five years ago but no lower than any of the proceeding years. This indicates that there has been no degradation of the performance of the turbines over 12 years.


Air Source Heat Pumps In New York

New York’s proposed Community and Climate Protection Act has a goal for “the state of New York to reduce greenhouse gas emissions from all anthropogenic sources 100% over 1990 levels by the year 2050, with an incremental target of at least a 50 percent reduction in climate pollution by the year 2030”. In order to reach that ambitious CO2 reduction goal all sources of CO2 emissions have to be reduced. One energy sector with relatively large emissions is residential home heating and the clean energy alternative for home heating is electric heat pumps. In this post I explain why I think that air source heat pump deployment in New York coupled with the simultaneous goal to eliminate greenhouse gas emissions is fatally flawed based on a case study for conversions near Caledonia, NY.


How Stuff Works explains that “heat pumps use a small amount of energy to move heat from one location to another”. Air conditioners cool our homes by removing heat from the air inside and moving outside. An air-source heat pump acts like an air conditioner in the summer and in the winter works in reverse moving heat from the outside air into the home to warm it. Obviously this kind of heat pump eliminates the need to have two separate systems and advocates tout its energy savings too. According to the Department of Energy (DOE):

An air-source heat pump can provide efficient heating and cooling for your home. When properly installed, an air-source heat pump can deliver one-and-a-half to three times more heat energy to a home than the electrical energy it consumes. This is possible because a heat pump moves heat rather than converting it from a fuel like combustion heating systems do.

Air-source heat pumps have been used for many years in nearly all parts of the United States, but until recently they have not been used in areas that experienced extended periods of subfreezing temperatures. However, in recent years, air-source heat pump technology has advanced so that it now offers a legitimate space heating alternative in colder regions.

For example, when entire units are replaced in the Northeast and Mid-Atlantic regions, the Northeast Energy Efficiency Partnerships (NEEP) found that the annual savings when using an air-source heat pump are around 3,000 kWh (or $459) when compared to electric resistance heaters, and 6,200 kWh (or $948) when compared to oil systems. When displacing oil (i.e., the oil system remains, but operates less frequently), the average annual savings are near 3,000 kWh (or about $300).

Reading this statement gives the impression that this technology is a “no regrets” solution for replacing oil heating CO2 emissions because it saves money for home heating. However, there is a critical caveat for New York State. Air-source heat pumps only work when they move heat and when it is really cold (below zero degrees Fahrenheit) there is no heat in the air to move.

The American Council for an Energy-Efficient Economy published a paper that illustrates this issue with air source heat pumps: Field Assessment of Cold Climate Air Source Heat Pumps (ccASHP) (https://aceee.org/files/proceedings/2016/data/papers/1_700.pdf). The report describes a Center for Energy and Environment field study in Minnesota where cold climate air source heat pumps were directly compared to propane and heating oil furnaces. The report notes that “During periods of very cold temperatures when ccASHPs do not have adequate capacity to meet heating load, a furnace or electric resistant heat can be used as backup.” Figure 2 (ASHP Supplemental Energy Use) from that document graphically shows the problem. In this field study homes were instrumented to measure the heat pump and furnace backup usage. Backup furnace usage was relatively low and the heat pump provided most of the heat until about 20 deg. F. For anything lower, heat pump use went down and the furnace backup went up. Below zero the air source heat pumps did not provide heat and furnace backup provided all the heat.

I believe that there are two problems with the plan to deploy air source heat pumps. I suspect but will not try to evaluate that because a fossil fired furnace or electric resistant heat must be used as backup in a typical New York State winter the cost savings from a more efficient heat pump are offset by the need to maintain a second heating system. The other problem is what might happen to peak electrical loads if electric resistant heat is the preferred backup system. The analyses that I have reviewed point out that converting a natural gas system to an electric heat pump system increases operating costs because natural gas is so low. Propane or fuel oil conversions save money so would be the first to convert because of the higher costs of propane and fuel oil. However, I am not sure that homeowners who convert would want to maintain an oil or propane furnace simply because of the storage system requirement. Consequently, I believe radiant electric heat will be the preferred option for air source heat pump conversions. If residential home heating is electrified significantly electric load will increase and I wonder what could happen to load when the efficient heat pump is replaced with radiant electric heat when the temperatures get really cold.


I hypothesize that the combination of widespread air source heat pump deployment and increased reliance on wind and solar renewable energy will create unacceptable reliability issues during peak winter load periods. I evaluated energy usage for one week before and one week after the 2017-2018 peak winter day (January 5, 2018). I had previously analyzed data near Caledonia, NY and will use that for this analysis.

 I used two sources of data. Electric load data for New York State are available from the New York State Independent System Operator and meteorological data are available from the NYS Mesonet meteorological system. The NYS mesonet is a network of 126 weather observing sites across New York State. The official website of the Mesonet includes a tab for live data that brings up station information for the 125 operating individual sites that shows that available data include wind direction and speed, temperature at two levels, relative humidity, precipitation, pressure, solar radiation, snow depth, and camera images. I obtained hourly and 5-minute archived meteorological data for two sites near Caledonia, NY where a 180 MW solar farm has been proposed.

The Winter 2017-2018 load peak occurred during an intense cold snap. From December 29 to January 8 the temperature did not get above freezing and there were four days with below freezing temperatures as shown in the table of Daily temperature and load statistics. Note that the highest load did not occur on the coldest day. This was because the coldest day was a Saturday when business loads are lower. Also note that the New Year’s holiday occurred during this period which also reduced the load. The graph of load, temperature and wind speed for winter peak 2017-2018 shows how hourly load varies with temperature over the 15 day peak period.

In order to estimate how much renewable energy would be available during these conditions I converted to solar insolation and wind speed into power generated in MW using example utility-scale facilities. For solar power I used the 180 MW Horseshoe Solar Farm estimated output because it is near the NYS mesonet stations. In my analysis of Solar Issues in Upstate New York using that facility I assumed that 180 MW of power would be generated when the solar insolation equaled 600 watts per square meter and power output the rest of the time would be proportional so observed solar insolation. I believe that is a conservative assumption but would welcome comment.

There aren’t any wind farms nearby. So I estimated power output for a 100 MW wind farm. I found a reference that stated “Wind turbines start operating at wind speeds of 4 to 5 metres per second and reach maximum power output at around 15 metres/second”. I assumed that below 9 mi/hr wind output was zero and that power output was proportional to the wind speed difference between 9 mi/hr and 33 mi/hr consistent with that reference. The NYS mesonet measures wind at 10m and I assumed that the wind farm hub height was 90m. I modified observe wind speed using the wind profile power law with a coefficient of 1/7 to account for the relationship between wind speed and height.

I used Field Assessment of Cold Climate Air Source Heat Pumps Figure 2 (ASHP Supplemental Energy Use) to estimate the amount of power needed when an individual home convert to an air source heat pump and uses radiant electric heat when the heat pump becomes ineffective (assumed to be 15 deg F). I crudely digitized the lines in Figure 2 and calculated the best fit lines for ASHP Consumption and Furnace Backup Consumption. I converted the energy use to electrical energy by converting Btu to watts by dividing the Btu energy use by 3.41. The Energy Use for Residential Home Heating Electrification Table Table illustrates my concern that residential home heating conversion to air source heat pumps has the unintended consequence that when it gets below 15 deg F and consumers really need to heat their homes that the rate of energy use increases over six times per five degree drop in temperature.

Case Study

The purpose of this analysis is to determine if there are problems if the 100% renewable solar and wind target is coupled with widespread implementation of residential home heating with air source heat pumps. The Housing Units by Space Heating Fuel Table lists the number of occupied housing units for two counties near Caledonia. The Field Assessment of Cold Climate Air Source Heat Pumps report states that liquefied propane (LP gas) and fuel oil or kerosene space heating are the most likely sectors to convert to heat pumps because of fuel cost savings. There are 18,244 housing units that burn those two fuels. I calculated the electricity required for 10%, 15% and 25% conversions for 18,244 housing units.

The figure entitled Residential Home Heating ASHP Conversion and Renewable Power Case Study shows the relationship between home heat electrical load and meteorological conditions affecting renewable wind and solar power. Colder days in Upstate New York often occur on clear, windless nights. When the sun rises the temperature increases quickly. Although cloudless skies maximize solar power the sun is low in the sky and the days are short so the power output is low. Of course the cold weather increases the need for home heating energy.

The Cumulative Renewable Charging and Discharging Margins graph attempts to estimate energy storage requirements. Clearly the only way that solar and wind can be expected to cover winter peak loads is by incorporating energy storage. During this windless case study energy storage needs to discharge to cover the residential home heating power requirement as shown in blue. During the day solar power recharges the energy storage as shown in red. In this case study the maximum storage needed was 372 MW-hr on hour 82. It turns out that renewable excess power charged to the system before this case study was sufficient to cover that requirement.


This case study illustrates my concern that wide-spread implementation of air source heat pumps coupled with increased use of renewables will be difficult. In this analysis the meteorological conditions on New Year’s Eve 2018 show that the proposed Horseshoe solar facility with a nameplate capacity of 180 MW and a wind farm with a nameplate capacity of 100 MW would have been just able to cover the conversion of 2,737 homes to air source heat pumps. However, energy storage capable of at least 372 MW-hr has to be available somewhere. There already are 47,000 homes using electricity and another 15,000 homes that are supposed to be cost-effective candidates for conversion just in two local counties. Most importantly, this is just one component of residential electricity load which is one component of total load.

The Horseshoe Solar Farm – Public Involvement Program claims that the facility will provide enough electricity to meet the average annual consumption of 33,000 or 50,000 households, based on average annual household electric consumption of 10.8 MWh for the U.S. and 7.2 MWh for New York State, respectively. I bet that these household electric consumption averages do not reflect an electrically heated home in cold regions. If I guess that the average consumption for this 15 day period is a decent number for the heating season and assume a 90 day heating season that more than doubles the electric consumption for a New York State household. In other words there is no way Horseshoe Solar Farm is going to provide enough electricity for 50,000 homes using air source heat pumps.

Even though this is a crude “back of the envelope” analysis, the sobering results suggest that the Legislature should do a complete winter peak analysis correctly before codifying reductions that eliminate fossil fueled power plants and require the conversion of residential home heating to meet some arbitrary CO2 reduction goal. According to Patterns and Trends – New York State Energy Profiles: 2002-2016 there are over a million homes currently using fuel oil or kerosene, 500,000 homes using electricity and another 200,000 using propane in New York State.

Based on my analysis I think that even moderate air source heat pump deployment for the residential home heating sector in New York coupled with the simultaneous goal to eliminate greenhouse gas emissions using extensive deployment of wind and solar power is fatally flawed.  I cannot imagine how much wind power, solar power and energy storage would have to be deployed to cover the winter peak, much less the winter peak adding significant electrification of residential home heating, for the entire state because those renewable resources are very weak during winter peak load periods. It is incumbent upon the advocates for the Climate and Community Protection Act to determine what renewable resources will be required and how much they will cost before their legislation is considered by the Legislature.