Category: Clean Energy Concerns

A recent paper, Getting to 100%: Six strategies for the challenging last 10%, provides a concise summary of six technologies that could be used for the Climate Leadership and Community Protection Act (Climate Act) legal mandate for New York State greenhouse gas emissions to meet the ambitious net-zero goal by 2050.  I continue to be amazed that the parties responsible for Climate Act implementation continue to ignore the risks associated with these aspirational technologies so this article summarizes this useful paper.

Everyone wants to do right by the environment to the extent that they can afford to and not be unduly burdened by the effects of environmental policies.  I submitted comments on the Climate Act implementation plan and have written extensively on New York’s net-zero transition because I believe the ambitions for a zero-emissions economy embodied in the Climate Act outstrip available renewable technology such that this supposed cure will be worse than the disease.  The opinions expressed in this post do not reflect the position of any of my previous employers or any other company I have been associated with, these comments are mine alone.

Background

The implementation plan for New York’s Climate Act “Net Zero” target (85% reduction and 15% offset of emissions) by 2050 is underway.  The Climate Action Council has been working to develop plans to implement the Act.  Over the summer of 2021 the New York State Energy Research & Development Authority (NYSERDA) and its consultant Energy + Environmental Economics (E3) prepared an Integration Analysis to “estimate the economy-wide benefits, costs, and GHG emissions reductions associated with pathways that achieve the Climate Act GHG emission limits and carbon neutrality goal”.  Integration Analysis implementation strategies were incorporated into the Draft Scoping Plan when it was released at the end of 2021.  Since the end of the public comment period in early July 2022 the Climate Action Council has been addressing the comments received as part of the development of the Final Scoping Plan that is supposed to provide a guide for the net-zero transition.

I have previously written that the Climate Action Council has not confronted reliability issues raised by New York agencies responsible for keeping the lights on.  The first post (New York Climate Act: Is Anyone Listening to the Experts?) described the NYISO 2021-2030 Comprehensive Reliability Plan (CRP) report (appendices) released late last year.  The difficulties raised in the report are so large that I raised the question whether any leader in New York was listening to this expert opinion.  The second post (New York Climate Act: What the Experts are Saying Now) highlighted results shown in a draft presentation for the 2021-2040 System & Resource Outlook that all but admitted meeting the net-zero goals of the Climate Act are impossible on the mandated schedule.  Recently I wrote about the “For discussion purposes only” draft of the 2021-2040 System & Resource Outlook report described in the previous article. 

Challenges of a Zero-Emissions Electric Grid

It is generally recognized that as increasing amounts of intermittent wind and solar energy are added to the electric grid, unique issues arise as grid operators balance generation and load.  I maintain that the ultimate problem with a net-zero energy system is that increased electrification will markedly raise loads during weather conditions that cause peak loads but also can have low wind and solar resource availability.  A recent paper, Getting to 100%: Six strategies for the challenging last 10% (“Getting to 100% report”), describes approaches for providing power during peak conditions.  It describes the general peaking problem, how wind and solar will exacerbate the problem, and what the authors think is necessary to solve the future problem.

The authors from the National Renewable Energy Laboratory provided the following summary:

Meeting the last increment of demand always poses challenges, irrespective of whether the resources used to meet it are carbon free.  The challenges primarily stem from the infrequent utilization of assets deployed to meet high demand periods, which require very high revenue during those periods to recover capital costs.  Achieving 100% carbon-free electricity obviates the use of traditional fossil-fuel-based generation technologies, by themselves, to serve the last increment of demand—which we refer to as the ‘‘last 10%.’’ Here, we survey strategies for overcoming this last 10% challenge, including extending traditional carbon-free energy sources (e.g., wind and solar, other renewable energy, and nuclear), replacing fossil fuels with carbon-free fuels for combustion (e.g., hydrogen- and biomass-based fuels), developing carbon capture and carbon dioxide removal technologies, and deploying multiday demand-side resources. We qualitatively compare economic factors associated with the low-utilization condition and discuss unique challenges of each option to inform the complex assessments needed to identify a portfolio that could achieve carbon free electricity. Although many electricity systems are a long way from requiring these last 10% technologies, research and careful consideration are needed soon for the options to be available when electricity systems approach 90% carbon-free electricity.

The Getting to 100% paper describes six strategies that are summarized in the following table.  Note that the strategies are compared to an ideal solution.  Ideally, the solution for peak loads would have low capital expenses and low operating expense, low resource constraints, be technologically mature, have low environmental impacts, and work well with other resources.  Needless to say, no technology comes close to meeting those ideal conditions.  The authors note that: “Although existing studies generally highlight the same fundamental causes associated with the last 10% problem, there is a lack of consensus on the preferred strategies for meeting this challenge. This is not surprising, given the diversity of possible solutions and the speculative nature of their costs, given their early stage of development.”

Although I think the Getting to 100% paper is useful, I want to point out a few issues with it.  It is hardly unexpected that authors from the National Renewable Energy Laboratory appear to over-estimate the maturity and economics of wind and solar technologies.  Also note that in New York, the implementation plan calls for offshore wind capacity to be at least one third to over one half of the projected wind capacity but the report claimed that wind economic factors were low, capital costs low, operational expenses low and that wind has high technological maturity.  All true perhaps for land-based wind but certainly not true for off-shore wind. 

My biggest concern is that the analysis does not consider the ‘‘inverter challenge’’ as a major constraint.  Another report, “The challenges of achieving a 100% renewable electricity system in the United States”, explains that in the existing electrical system synchronous generators provide six services shown in the following table that provide system stability.  Wind and solar resources are asynchronous generators that do not provide those services.  Somebody has to provide them so this analysis that concentrates only on the levelized cost of energy that ignores those services under-estimates the cost and technological challenges to provide electricity to consumers.

The Getting to 100% paper explains that the biggest problem is making sure there is sufficient available capacity during all periods, even if that capacity is seldom used.  This problem is not new and exists in the existing system.  The paper notes:

The increase in costs associated with approaching 100% carbon-free electricity is a special case of the more general problem of meeting peak demand, which has always been part of the planning process for electric power systems. Variations in demand profiles and the existence of demand peaks are caused by variation in weather, end-use technology stock, and, ultimately, consumer preferences and behavior.

The Getting to 100% paper explains that there are differences between daily load and daily renewable energy (RE) generation over the year.  The following figure shows the seasonal patterns in the daily imbalance (daily load minus daily RE generation) for hypothetical high RE systems where about 90% of annual load is met by wind, solar, and other RE generation technologies for New York State. As noted previously the fundamental problem is that when the loads are the highest in the summer and winter, RE generation can be low.  In the spring and fall the RE resources are generally high but loads are low.   As the share of RE increases,” these aspects are increasingly accentuated”.  The paper makes the point that:

Eventually, with high enough VRE shares, the addition of new VRE capacity would offer very little benefit in reducing peaks in net load, while causing additional oversupply conditions where unusable VRE needs to be curtailed. The low capital utilization problem of meeting demand is exacerbated in high VRE systems. These issues shape the characteristics of a last 10% solution.

In the following I will address each strategy.

Variable renewable energy, transmission, and diurnal storage

This approach is “technologically conservative, as it relies only on technologies currently being deployed at gigawatt (GW) scale”. The seasonal mismatch problem is addressed by overbuilding wind and solar resources as well as adding more transmission capacity.  Diurnal storage is deployed to fill hourly supply gaps and excess wind and solar is curtailed during high-resource periods.  The authors claim: “Increasing oversupply during high-resource times decreases the amount of storage necessary to supply low-resource times.”  The authors admit that wind and solar “curtailment in such systems can reach 35%–50%”.  There is an associated problem.  As more wind and solar resources are added to minimize storage requirements, those additional resources markedly increase curtailment rates for all those resources.  

In order to address those issues, the authors claim that new developments could “make this approach more competitive” In particular: “Higher-capacity-factor system designs (low-windspeed and/or high-hub-height wind turbines; tracking PV arrays with high inverter-loading ratios preferentially increase output during low-resource periods, increasing VRE dispatchability”.  My impression however, is that those are tweaks and do not eliminate all issues.  The authors mention hybrid systems, “including concentrating solar power with thermal energy storage”, but neglect to mention that the Crescent Dunes Solar Energy Project that used this technology failed.  They also claim that “Increased long-distance transmission deployment (over distances larger than the extent of weather systems decreases curtailment, cost, and storage needs by exploiting the declining spatial correlation of VRE availability with increasing distance”.  Advocates of this approach never discuss just what distances are needed for it to work and just how it would work in practice.

According to Table 1 in the Getting to 100% paper, on the positive side the economic factors are relatively low cost and technological material is high.  The resource constraints are listed as medium but I think that is optimistic given the volume of these resources required.  Frequent claims of the low costs of wind and solar generation ignore the fact that the real cost that matters is the delivered cost.  When the costs to keep the lights on when the wind is not blowing at night are considered the low cost claims are wrong.

Other renewable energy

The study claims that “geothermal, hydropower, and biomass are renewable energy resources that do not rely on variable solar and wind resources and have higher capacity credit”. While the report claims that these resources can play an important role in a net-zero-emissions power system the fact is geothermal and hydro resources depend on certain physical site constraints so there is not a lot of potential availability in New York.  The main problem with biomass is that there are limits on how much could be produced and it is not enough to be a major contributor to the overall energy needs.  In New York there are members of the Climate Action Council that believe that zero-emissions means no combustion so there is an ideological constraint as well.

According to Table 1 in the Getting to 100% paper, on the positive side the technological material is high and some of the economic factors are favorable.  However, all the options have high resource constraints that limit the applicability of these options.

Nuclear and fossil with carbon capture

The study notes that “Nuclear and fossil with carbon capture and storage (CCS) are widely cited as potentially important resources in a decarbonized electricity system”.  There is no question that nuclear is the only emissions-free dispatchable resource that could be deployed in sufficient quantities to provide all needed baseload power.  The report notes that: ”The existing nuclear fleet comprises reactor designs with large nameplate capacities and designed to operate near their maximum output potential”, and that “Advanced nuclear reactor designs are typically smaller in scale and more flexible” .  Consequently, nuclear might be viable for the last 10% problem.  Alas New York, for example, on one hand worries about an existential threat of climate change but shuts down 2,000 MW of zero-emissions nuclear generation which suggests that this option is off the table.

The report notes that “Fossil CCS plants have yet to be deployed at scale, but some studies find significant deployment potential, including from retrofits of existing fossil fuel-fired Plants”.   The report sums up the pragmatic dilemma associated with this option:

Fossil CCS has a capture rate of less than 100%; therefore, some emission offsets are needed for fully net carbon-free electricity unless technology advancements, such as through oxy-combustion, can enable zero or near-zero emissions.  he role of fossil CCS could be impacted by how strictly the ‘‘100%’’ requirement is interpreted with respect to any remaining emissions that are not captured and emissions from upstream fuel extraction, including methane leakage.

There is another issue associated with CCS.  A fossil plant capturing CO2 has a derate of about one third because of the energy needed to run the equipment required to capture and compress the CO2 so that it can be transported and sequestered underground.  Finally, in order to safely store the CO2 particular geologic formations are required which limits where these facilities can be located.

According to Table 1 in the Getting to 100% paper, advanced nuclear has high capital expenses and moderate operating expenses; medium resource constraints, medium technological maturity, and security, supply chain, regulatory and cost uncertainties.  Fossil CCS has high capital expenses, medium operating expenses, medium resource constraints, low technological constraints, and issues with upstream emissions, CO2 transport and sequestration.

Seasonal storage

Seasonal storage refers to the use of electricity to produce a storable fuel that can be used for generation over extended periods of time later:

This group of technologies is not well defined, but it could include batteries with very low-cost electrolytes capable of longer-than-diurnal durations. Because of the requirement for very low-cost energy storage, most seasonal storage pathways focus on hydrogen, ammonia, and other hydrogen-derived fuels stored in geologic formations.

Hydrogen produced using electricity to split water (i.e., electrolytic hydrogen) is a form of storage because the energy it carries can be converted back to electricity.  Electrolytic hydrogen technology has been used at an industrial scale since the early 20th century. Although currently higher cost than hydrogen from natural gas reforming, electrolytic hydrogen production costs can be reduced if low- cost electricity, such as zero-cost otherwise-curtailed renewable energy, is used.

In the New York implementation plan the dispatchable emissions-free resource (DEFR) place holder is hydrogen produced using wind and solar.  In addition to the irrational ideological prohibition against combustion sources there are technological issues for New York.  The report notes that “current high-cost electrolyzers need to operate almost continuously to recover their capital expense” and that “Storage and transport costs would add to the delivered cost of hydrogen”. 

The New York ideologues plan is to use hydrogen in fuel cells, but the report notes:

Fuel cells have diverse applications, but their use for bulk power generation is currently limited. Given the range and scale of applications especially for transportation, substantial capital cost reductions for fuel cells are possible. With low capital costs for combustion turbines and future potential cost reductions for fuel cells, the economic case for hydrogen mainly hinges on lowering the cost of electrolytic hydrogen.

According to Table 1 in the Getting to 100% paper, it really is a stretch to say that there are any positive aspects for using hydrogen with combustion turbines or in fuel cells.  For hydrogen used in combustion turbines the report claims low capital expenses (apparently referring only to the combustion turbine but not including the generation of the hydrogen itself), medium operating expenses and resource constraints, and concerns about hydrogen storage and transport as well as competition for using hydrogen in other sectors.  For hydrogen used in fuel cells there is a potential for low capital expenses, high operating expenses, low resource constraints (apparently referring only to the fuel cell and not assuming that the hydrogen is generated with wind and solar resources), low technological maturity, and the same other considerations as hydrogen used in combustion turbines.

Carbon dioxide removal

The report describes carbon dioxide removal (CDR) strategies which are “dedicated efforts to reduce atmospheric CO2 levels.  In theory this can offset emissions from carbon-emitting power generation so that fossil-fired units can operate to fulfill the last 10% requirement. This is too far fetched to be credible in my opinion.

According to Table 1 in the Getting to 100% paper, there are no positive aspects of this technology except that there are low resource constraints for direct air capture and storage. 

Demand-side resources

Net-zero advocates are enamored with “smart planning” approaches that reduce load which reduces generating resource requirements.  The report notes that “Demand-side resources, also referred to as demand response or demand flexibility, have unique properties compared with the supply-side solutions”.  The report explains:

To a limited extent, they are already relied upon for grid planning and operations today. By reducing electricity consumption during times of system stress, these resources help avoid capital expenditures associated with new peaking capacity.  Through flexible scheduling or interruption of electricity consumption, they can also reduce operating costs or be used for important grid reliability services.

While there are indisputable advantages, I think that advocates lose track of the limitations.  There are demand-side programs in place today but the applications are limited.  Today’s programs limit reduction requests to rare instances of limited duration primarily to shave peak loads primarily by large industrial or commercial users. The problem is that applying demand-side options as a last 10% strategy for decarbonization “requires them to be reliably available over extended multi-day periods”. This means that they cannot be used for residential heating and cooling loads and electric vehicle charging. Moreover, the report notes that “Large-scale commercial or industrial customers can provide multi-day response, but extended interruptions would negatively impact these capital-intensive (non-power) applications”.  As a result, I don’t think this approach will provide adequate reductions when needed the most.

According to Table 1 in the Getting to 100% paper there are low capital expenses but there are uncertain opportunity costs.  The paper claims that resource constraints are uncertain and that the technological maturity is medium.  There are concerns about communications, control equipment and reliability.

Discussion

An Inside Clean Energy article on the paper offers a summary from the climate advocacy side.  Of note is a plug for the 100% renewable option:

A growing segment of energy researchers say that the electricity system can run on 100 percent renewable energy, which would mean renewables and energy storage would provide the last 10 percent. This approach sees no good reason to build new nuclear plants or to use carbon capture systems on fossil fuel plants, citing high costs and a variety of other concerns.

The author admits that the myth of low-cost solar and wind resources does not take into account the resources needed for reliability during periods of peak demand:

At the same time, a sizable group of energy researchers maintain that nuclear and carbon capture are essential parts of getting to carbon-free electricity. This side has doubts about the ability of renewable sources to meet all needs, citing concerns about the availability of land and the intermittent nature of wind and solar. They note that wind and solar are not a low-cost option when taking into account the amounts of storage and power line capacity needed to make those resources reliable for meeting peak demand.

I find the author’s conclusion naïve:

Within all of this is something encouraging: Researchers and energy companies have figured out how to start the transition to 100 percent carbon-free electricity and they have a pretty good idea of what the in-between steps will look like. Now, they are beginning to dig deep on how this journey to a carbon-free grid may end.

Academic researchers are not accountable for reliability and have found a cash cow for funding.  No one is funding them to make a responsible estimate of future resources that does not fit the alarmist narrative.  In a de-regulated world energy companies are also not responsible for reliability and are toeing the line of the net-zero narrative.  New York’s organizations responsible for reliability are not as optimistic (here and here). New York’s Draft Scoping Plan presumes that the State can transition to net-zero without addressing reliability and affordability feasibility but the reality is that even this report suggests that substantive issues have to be addressed.

Conclusion

I think this is a biased report that is too optimistic for future projections.  Nonetheless, it does offer a concise summary of potential approaches to address the last 10% problem that is my ultimate concern.  With respect to New York’s implementation plans, if the concerns of the National Renewable Energy Laboratory staff are ignored in the Final Scoping Plan, then New York will surely have a catastrophic blackout with consequences far beyond any impacts that can be attributed to climate change.

In the process of preparing an article about the New York State Reliability Council (NYSRC) Executive Committee approval of the Extreme Conditions Whitepaper on July 8, 2022, I found a reference to a very nice report Resource Adequacy Modeling for a High Renewable Future.  The report provides important background information necessary to understand the NYSRC whitepaper so my first thought was to include a summary of the report in the NYSRC post.  It made the article too long so this post focuses exclusively on the background paper.

Everyone wants to do right by the environment to the extent that efforts will make a positive impact at an affordable level.  I have written extensively on implementation of New York’s Climate Leadership and Community Protection Act (Climate Act) because I believe the ambitions for a zero-emissions economy embodied in the Climate Act outstrip available renewable technology such that it will do more harm than good.  This post also addresses the mis-conception of many on the Climate Action Council that an electric system with zero-emissions is without risk.  The opinions expressed in this post are based on my extensive meteorological education and background and do not reflect the position of any of my previous employers or any other company I have been associated with, these comments are mine alone.

Resource Adequacy Modeling for a High Renewable Future

The National Regulatory Research Institute (NRRI) is the research arm of the National

Association of Regulatory Utility Commissioners (NARUC).  NRRI provides research, training, and technical support to State Public Utility Commissions. The June 2022 report “Resource Adequacy Modeling for a High Renewable Future “gives an excellent overview of electric resource adequacy planning as performed today and describes what they think will be needed in the future.

Traditional Resource Adequacy Planning

The report describes traditional resource adequacy planning:

Electric utilities have used the resource planning process for decades to develop long-term, least-cost generation supply plans to serve expected customer demand. Resource adequacy planning ensures that a system has enough energy generation throughout the year to serve demand with an acceptably low chance of shortfalls.  Resource adequacy is measured by the metrics described in Figure 1.  Reliability metrics provide an indication of the probability of a shortfall of generation to meet load (LOLP), the frequency of shortfalls (LOLE and LOLH), and the severity of the shortfalls (EUE and MW Short).

The industry has traditionally framed resource adequacy in terms of procuring enough resources (primarily generation) to meet the seasonal peak load forecast, plus some contingency reserves to address generation and transmission failures and/or derates in the system.  This approach and the metric used to define it is called the “reserve margin.”  Planners establish a reserve margin target based on load forecast uncertainty and the probability of generation outages. Required reserve margins vary by system and jurisdiction, but planners frequently target a reserve margin of 15 percent to 18 percent to maintain resource adequacy. Figure 2 shows the standard conceptualization of a load duration curve, rank ordering the level of a power system’s load for each hour of the year from highest to lowest on an average or median basis in a typical weather year. The installed reserve margin is a margin of safety to cover higher than expected load and/or unexpected losses in generation capacity due to outages.

New York resource planning analyses use the “one day in ten years,” criteria (LOLE), meaning that load does not exceed supply more than 24 hours in a 10-year period, or its equivalent metric of 2.4 hours loss of load hours (LOLH) per year. This analysis is performed at the “bal­ancing authority” (BA) level. In the past New York BAs were vertically integrated utilities with defined service terri­tories. After deregulation this responsibility passed to the state’s independent system operator (ISO).  The region covered now includes many utility service territories.  More importantly the New York Independent System Operator (NYISO) has to develop market or compliance-based rules to main­tain sufficient system capacity which adds another layer of complexity.  BA’s typically conduct resource adequacy analysis based on their own load and resources. The NYISO does their resource adequacy planning using resources within its geographic region or have firm transmission deliverability into the New York Control Area (NYCA).  There is another complication in the state.  New York City has limited transmission connectivity so there are specific reliability requirements for the amount of in-city generation that has to be operating and other rules to prevent blackouts.

The report goes on to note:

The standard metrics shown in Figure 1are generally reported as mean values of simulated power system outcomes over a range of potential future states, but planners also need to understand and plan for the worst-case outcomes and associated probability of such outcomes. Figure 3shows the mean and percen­tile values for loss of load hours for a power system over a three-year period.

In Figure 3,on average, the power system is resource adequate, remaining below the target of 2.4 hours per year. However, if the power system planner were more risk averse, she might want to bring a higher percentile line under the 2.4-hour target. She would need to add more firm capacity, adding to customer cost. The 95th percentile is the worst-case outcome, providing addi­tional information on the upper bound risk of outages for a given portfolio. Only power systems with no recourse to import energy in a shortage, such as an island, would consider planning to the 95th percentile due to its high cost.

The report’s traditional planning section concludes with this:

Resource adequacy planning is fundamentally con­cerned with low probability events and planning for average outcomes; although a common practice, this planning is not sufficient and increasingly risky with more uncertain supply, such as renewables. In the past, planners only needed to worry about unusually high loads or high forced outages. Now, they must worry about unusually high loads during periods of unusually low renewable output and limited storage duration. Adding supply uncertainty and, as we discuss later, more extreme weather, compounds risks and thus requires a fundamental rethinking of planning for low probability, high impact tail events.

Problems with Traditional Resource Planning with a High-Renewable System

Despite the fact that the NYISO and the consultants for the Integration Analysis that provides the framework for the Climate Act Draft Scoping Plan have identified a serious resource adequacy problem, there are vocal members of the Climate Action Council who claim there are no reliability concerns for the future 100% zero-emissions New York electric grid.  However, analyses have shown otherwise.  E3 in their presentation to the Power Generation Advisory Panel on September 16, 2020 noted that firm capacity is needed to meet multi-day periods of low wind and solar output.  The NYISO Climate Change Phase II Study also noted that those wind lull period would be problematic in the future.

The NRRI report opens the discussion of the new problems that have to be addressed:

With weather emerging as a fundamental driver of power system conditions, planning for resource ade­quacy with high renewables and storage becomes an exercise in quantifying and managing increasing uncer­tainty on both the supply and demand side of the equation. On the load side, building electrification, electric vehicle adoption, and expected growth in customer-sited solar and storage are likely to have pronounced effects on future electric consumption. Uncertain load growth and changing daily consump­tion patterns increase the challenge of making sure that future resources can serve load around the clock. Simply modeling future load based on past load with added noise does not characterize uncertainty from demand side changes.

The report goes on to explain that supply-side changes create a need for new modeling approaches.  In particular, the traditional system consists mostly of dispatchable resources that operators can control as necessary to keep the generation matched with the load.  In the future the system will be comprised mostly of resources with limited or no dispatchability. Table 1 compares past approaches with current needs.  Note that weather impacts need to be “Incorporated as a structural variable driving system demand, renewable generation, and available thermal capacity”. 

There is another fundamental change.  In the past the resource adequacy modeling could use average annual generation profiles to meet expected loads.  In the future, there will have to be: “multiple renewable generation simulations using historical generation and weather data”. The modeling scenarios will need to meet future expected resource development and maintain the correlation

between renewable availability and load.  In particular, the highest and lowest temperatures and thus the expected high loads are typically associated with large high-pressure systems that have low wind speeds and thus low wind resource availability.

The NRRI report shows an approach that addresses these concerns in Figure 5.  The report notes:

Weather, primarily in the form of temperature, but potentially including insola­tion, humidity, wind speed, etc., drives simulations of renewable generation and customer load. Generation outage simulations can be modeled as random (the traditional approach) or as correlated with extreme heat or cold events. Once the simulations are in place, models can compute multiple future paths on an hour-by-hour basis to determine when load cannot be fully served with the available resources. For every hour of the model time horizon, there are independent simulations of load, renewables, and forced outages to determine if load shedding must occur. If a particular model contains 100 simulations and four show a lack of resources to serve load for a particular hour, the hour in question would have a loss of load probability of 0.04 (4/100).

In my opinion, the weather drivers have to be carefully considered.  In my Comment on Renewable Energy Resource Availability  on the Draft Scoping Plan, I explained why an accurate and detailed evaluation of renewable energy resource availability is crucial to determine the generation and energy storage requirements of the future New York electrical system.  I showed that there is a viable approach using over 70 years of data that could robustly quantify the worst-case renewable energy resources and provide the information necessary for adequate planning. 

The problem however is what will be the worst case?  The NRRI report brings up the issue of energy storage:

Energy storage presents a unique challenge in re­source adequacy models. Unlike traditional resources, storage devices such as batteries, compressed air, or pumped-hydro act as both load and generation de­pending on whether they are charging or discharging. Modern resource adequacy models need to simulate this behavior when determining the capability of en­ergy storage to serve load during periods of resource scarcity. What state of charge should we expect for energy storage at times when the storage is truly needed? Are batteries likely to be fully charged at 6:00 PM on a weekday in August? What about grid charging versus closed systems where batteries must charge from a renewable resource? At the high end of renew­able penetration, how much storage would be required to cover Dunkelflaute, the “dark doldrums,” that occur in the winter when wind ceases to blow for several days. Questions surrounding the effective load-carrying capability of energy storage significantly increase the complexity in modeling resource adequacy.

The worst-case meteorology has to consider the energy storage resource.  The worst-case may not be the lowest amount of wind and solar resources over a few days.  Instead, it could be an extended period of conditions that prevent battery re-charging.  I suspect that the long-term historical records will be used to identify potential problems and then a set of scenarios based on different meteorological regimes will be developed that can be used to address the questions raised in the previous paragraph.

The NRRI report explains how this might work:

Figure 6 provides an illustration of modeling the use of batteries in resource adequacy. The figure shows bat­tery storage in blue, load in orange, and the available thermal generation in grey. When load exceeds thermal generation, the system is forced to rely on battery discharge for capacity. If the event lasts long enough to fully discharge the battery, the green line (generation minus load) will turn negative, indicating a load shed event.

The report goes on to explain how the modeling analysis is done.  It notes that:

Simulations of random variables fit Monte Carlo meth­ods by creating multiple future time series of the ran­dom variables, while maintaining correlation across time within variables (if wind is high in hour 1, it will likely be high in hour 2) and correlations between the variables, such as the strong relationship between temperature and load. If wind tends to be higher in the spring and fall, the simulations will exhibit that trend. Monte Carlo applications differ dramatically between resource adequacy models, with some models using a sequential approach that solves the model in hourly steps whereas others use techniques that solve the models quickly without stepping through each hour. Accurate representation of energy storage in resource adequacy models necessitates sequential solution techniques to account for the time dependencies for storage state of charge inherent in models.

I believe it is necessary to use the worst-case meteorological scenarios as the primary driver of these simulations.  In other words, the Monte Carlo weather parameter adjustments should be small increments on top of the observed values.  The report is talking primarily about correlations in time but spatial correlations are a critical wind resource availability consideration too. 

The NRRI report addresses my concerns.

When using the Monte Carlo approach with weather as a fundamental driver, individual simulations represent independent futures for weather, load, and renewables. Realistic simulations maintain the statistical properties of the underly­ing resource and correlation be­tween resources and load. For example, if historic data show no correlation between load and wind generation, the simulations should maintain this relationship unless a reasonable expectation exists for correlations to change in the future

However, they use simple examples of the load and resource correlations.  There are those that believe that because the wind is always blowing somewhere that transmission upgrades will ensure reliability.  However, if during the worst-case conditions New York has to rely on wind resources in Iowa because the high-pressure system is huge, that may not be practical.  I cannot over-emphasize the need for an analysis that simulates wind and solar resource availability over wide areas.  As the report notes analyses that fail to replicate the proper correlation between wind, solar, and load for the electric grid can underestimate the risk of load shedding.

The report goes on to explain other adjustments to traditional resource planning that will be necessary to address a high renewable future.  That discussion is beyond the scope of my concern.  The report concludes:

The electric grid is transitioning quickly from a system of large, dispatchable generators to a system reliant on high levels of variable renewable energy, energy storage, and bi-directional flow. Against this backdrop, analytical tools used for decision making regarding resource adequacy are more important than ever and those tools need to evolve to meet the modern grid challenges outlined in this paper. Models based in realistic weather-driven simulations more accurately capture the risk of load shedding due to inadequate generation. Simulations derived from historical data ensure models include load and generation patterns as well as correlations among resources and the ability to adjust to future climate conditions. Models that do not account for these factors may lead to decisions that underinvest in resources or invest in the wrong re­sources. Recent events in California and Texas indicate the importance of getting these projections right to keep the grid reliable.

To model resource adequacy in future power systems with high penetration of renewables, we recommend several enhancements in modeling tools and tech­niques. Modeling tools should simulate key structural variables and allow for validation of the simulations by benchmarking against the historical data used to create the simulations. While maintaining statistical properties derived from historical data, simulations should also include future expectations of load growth along with changes in seasonal and daily load shapes. Genera­tion-forced outage simulations should include the possibility of correlated outages from extreme weather. Finally, climate change will drive more weather events in the power system and this risk should be accounted for in the models, at least in the form of sensitivity cases or stress tests.

Conclusion

I found this report to be a very useful description of the particulars of electric grid reliability analysis now and in the future.  It is clear that the transition to a high renewable future introduces issues that could cause problems.

Finally, this report and other similar studies always claim that climate change should be considered in future analyses.  As I will explain in my future article on the NYSRC Extreme Conditions Whitepaper I believe that the most important future weather concern is that changing the resource mix to one relying upon weather-dependent wind and solar generation is the critical vulnerability that has to be addressed.  I think that the trend of extreme weather events due to greenhouse gas concentrations in the atmosphere is much smaller than natural variability.  Therefore, using a long record of data for evaluation will cover most of the potential future variability.  Unfortunately, recent major blackouts due to extreme weather suggest that we haven’t even been able to plan for the past.  So far New York has avoided such a blackout either due to more stringent standards and better policy development or luck.