The 10-MW-hour electric (MWhe) energy storage solution, developed by Storworks, is charged using heat from supercritical steam generated by Gaston’s Unit 5. As designed, high-pressure steam from the power plant flows through tubes, heating the concrete, which stores the thermal energy until it is returned to the power plant by converting feedwater into steam to generate electricity in response to grid demand. The project received funding from the U.S. Department of Energy under award DE-FE0031761.

The technology can be applied to existing or new thermal power plants, including coal, natural gas, nuclear, or concentrating solar power, the companies said, and the core technology can go beyond electric power to applications including decarbonizing industrial heat.

“Advancements in long-duration energy storage are key to unlocking the full potential of variable renewable energy resources on the path to net-zero,” said Neva Espinoza, EPRI vice president of Energy Supply and Low-Carbon Resources. “As the power sector navigates a highly complex transition, CTES could play an important role in efficiently delivering the reliable and affordable electricity society depends on.”

The companies said the original goals of the project were exceeded, as steam production at several pressure levels was demonstrated. More than 80 energy charge and discharge cycles were also successfully performed over 700 hours of total operation.

“We appreciate the vision and support from our partners that made this pilot demonstration possible,” said Scott Frazer, co-founder of Storworks. “Low-cost long-duration energy storage is increasingly critical in the shift to low-cost intermittent renewable energy, and the Gaston project represents an important milestone in advancing the commercialization of our technology. With industry-leading low cost, Storworks’ modular system can be tailored to a range of applications for both power plants and industrial decarbonization solutions.”

Originally published in Renewable Energy World.

Constellation said the 38 percent mark nearly doubled the previous blending record for similar generators. The blending test at Hillabee occurred May 18 on a Siemens Energy SGT6-6000G gas turbine.

Constellation said only “minor modifications” were required for the blending test. The company said it added an inlet for the hydrogen to be blended, a control valve and calibrated instrument to measure fuel flow.

The company said nitrogen oxide (NOx) emissions did not increase during this blending test.

NOTE: We are currently accepting speaker submissions for presentations at POWERGEN International on January 23-25, 2024 in New Orleans. Topics include hydrogen co-firing through our track Unlocking Hydrogen’s Power Potential. Submit an abstract for a chance to join our speaker lineup here.

The Environmental Protection Agency (EPA) recently released new rules aimed at reducing carbon emissions from the electric sector, citing hydrogen co-firing as a primary technology to help decarbonize the U.S. power sector and achieve the nation’s climate goals.

Constellation said it will use the results from this test to inform its plans for transitioning its natural gas facilities to carbon-free technology in the coming years. The company has a large nuclear fleet and produces nearly 90 percent of its energy from carbon-free sources, with a goal of achieving 100 percent carbon-free electricity generation by 2040.

Hillabee Generating Station is a three-unit plant that began operating in 2010. The plant is fitted with Selective Catalytic Reduction technology, which significantly reduces nitrogen oxide emissions.

To this end, WEC is exploring the use of low-carbon fuels. One of its subsidiaries, Upper Michigan Energy Resource Corporation (UMERC), hosted a hydrogen-natural gas blending demonstration at the A.J. Mihm Generating Station. The demo, conducted in the fall of 2022, involved blending hydrogen in one of the three grid-connected 18.8 MW Wärtsilä reciprocating engines at the plant.

The partners, which included the Electric Power Research Institute (EPRI), demonstrated 25% hydrogen by volume fuel blending in the engine that was tested. Other project team members included Blue Engineering, Burns & McDonnell, Certarus, Lectrodryer, and Mostardi Platt. EPRI released the results of the blending demonstration in March, and we had the opportunity to discuss them with Dr. Andrew Maxson, a senior program manager with the nonprofit.

Link to executive summary for the blending project

Why engines?

Calling it a “seminal study,” Maxson said this was the first hydrogen blending test on a commercial-scale, grid-connected and operating reciprocating engine.

Reciprocating engines have superior fuel and operational flexibility compared with gas turbines, he said. They can start quickly and ramp to balance the grid in areas with high renewable penetration. Engines are good at burning virtually any fuel and can accordingly be sited in places where the fuel quality isn’t stellar. Maxson said that was a factor in choosing the plant and location for the blending test.

“In this particular region, there is lower pressure natural gas and varying natural gas quality, which engines can handle better than turbines,” said Maxson. “So that was one of the primary reasons why they went with engines.”

Site safety and preparation

Because hydrogen is so flammable and can leak easily, a detailed plan was followed to ensure safety on site.

Safe operating conditions of the engine were identified ahead of time, as well as corrective actions to be implemented if key performance indicators exceeded established thresholds.

“We took it very seriously and we had an experienced team involved in this,” said Maxson.

All contractors visiting the A.J. Mihm plant were required to complete an online environment, health and safety orientation to confirm all personnel on site were familiar with the plant’s existing safety policies and procedures.

Both written and verbal forms of communication were employed, with signs placed throughout the plant to indicate hazardous areas or where additional personal protection equipment was required.

A restricted access zone was placed around the perimeter of the hydrogen blending system equipment. The location of the blending equipment, brought in from out of state, was determined based on access within the facility, roads, proximity to fuel gas tie-ins and preferred engine in addition to meeting requirements of the National Fire Protection Association 2 – Hydrogen Technologies Code (NFPA 2).

All the equipment and piping that touched the pure hydrogen was American Society of Mechanical Engineers (ASME) code certified. Hydrogen leak detection tape – yellow tape that turns black if hydrogen contacts it – was applied on all flanged connections for piping that contained either pure hydrogen or the hydrogen/natural gas blend. All flanged connections were inspected before each engine startup and after each engine shutdown or trip.

When the engine was operating, no one was allowed into the engine hall. Hydrogen sensing monitors were placed there to detect any possible hydrogen leaks.

Team members working directly with the hydrogen supply, pressure reduction and fuel blending equipment were required to wear personal hydrogen gas monitors as part of their normal operating procedures.

In the end, there was no evidence of any hydrogen leaks during testing, including from the engine itself.

“We were pretty careful, and we learned a lot,” said Maxson. “I think we learned a lot of lessons learned that we’re going to pass on the industry about handling hydrogen as a result.”

Engine loads, emissions and efficiencies

The grid-connected 18.8 MW Wärtsilä reciprocating engine was tested at different engine loads and to operate on various fuel blends, ranging from 10–25% hydrogen by volume.

As different hydrogen levels were tested, Maxson stressed that it was important for the teams to see how the engine would perform without any mechanical modifications. As it turns out, the engine, on a 25% hydrogen blend (the highest % tested), did not require mechanical modifications. Maxson said the only modifications made involved some manual tuning at increased engine loads.

For the 50% engine load runs, engine tuning was not performed as the engine was able to operate reliably on hydrogen blends up to 25% by volume.

For the 75% and 100% engine load runs, the charge-air pressure and ignition timing were adjusted to maintain stable operation of the engine.

For each of the 50%, 75%, and 100% engine load runs, the engine was able to achieve the full load setpoint at all hydrogen blends, with the exception of the 25% hydrogen blend.

At that blend, the engine was only able to make 95% capacity. As Maxson explained, engines have a closed volume and hydrogen is much less energy-dense than natural gas. Therefore, getting enough hydrogen into the [engine] cylinder to produce all the power the engine can provide is a challenge.

“We were thinking when we were at 25% blend ratio, we weren’t going to be able to provide the full capacity of the engine,” said Maxson. “And we were expecting as much as a 15% reduction. And we only saw 5%, which everyone was ecstatic about, that the engine was still able to put that much output out.”

The teams measured emissions, heat rate and efficiency at various engine loads and hydrogen blends, relative to a 100% natural gas baseline.

As expected, carbon dioxide levels decreased as increasing levels of hydrogen were introduced. CO₂ was reduced by approximately 10% at 25% by volume hydrogen co-firing.

“These were all things that we expected but we were happy to see,” said Maxson. “It’s always good when measurements back up your expectations.”

Carbon monoxide (CO) and nitrogen oxides (NOx) were also measured at both the engine outlet and the outlet of the selective catalytic reduction (SCR) system going to the stack. One environmental concern with using hydrogen is because it burns hotter than other fuels like natural gas, it can produce more thermal NOx.

When blending hydrogen without NOx controls, Maxson said the teams did see a NOx increase coming out of the engine in some cases. But after the NOx SCR controls, Maxson said there was little change in these emissions coming out of the stack compared to the baseline.

“It wasn’t dramatic,” said Maxson, speaking of the uncontrolled NOx emissions. “And we did change how the engine operated a little bit by increasing the air fuel ratio so that it burned a little bit leaner. That reduces some of this higher temperature coming out.”

 Uncontrolled Emissions

• At 50% Engine Loads: CO emissions decreased by 21–35% as a result of faster, more complete combustion with increased hydrogen blend ratios. By contrast, NOx increased by 21–74% at higher hydrogen content due to increased cylinder temperatures. No engine tuning was done in these test runs.

• At 75% Engine Loads: The engine was retuned after performing the baseline to lower NOx emissions, resulting in NOx emissions actually being lower at 10% and 15% by volume hydrogen blends and then increasing to 20% above the baseline at 25% by volume hydrogen. The teams noted that further engine tuning could have been done to maintain even lower NOx emissions levels. CO emissions decreased by 10–25% over the tests, with the reductions increasing with hydrogen content.

• At 95% engine load: CO and NOx emissions were substantially lower than the baseline as the engine was manually tuned to reduce NOx and the CO was reduced in part due to the lower carbon content in the fuel.

• At 100% engine load: CO emissions increased by 20% during the 12% by volume hydrogen full-load testing because the air-fuel ratio and ignition timing were changed to keep NOx low. NOx emissions were substantially lower than the baseline by 58%.

Controlled Emissions

Stack emissions of CO and NOx after emission controls were kept well below the regulatory permit limits of the plant in all cases and test runs.

• At 50% engine loads: CO emissions decreased by up to 15%, and NOx decreased by 13–17%.

• At 75% engine loads: CO emissions decreased by 12–18%, and NOx increased by 10–20%.

• At 95% engine load: CO emissions increased by 18%, while NOx decreased by 2.5%.

• At 100% engine load: CO emissions increased by 54% during the 12% hydrogen by volume full-load testing, while NOx was comparable to the baseline.

Efficiencies

At the 25% hydrogen blend, the heat rate and efficiency were almost identical compared to the natural gas baseline. From a thermal performance point of view, Maxson said the engine basically operated the same.

• At 50% Engine Loads: The teams observed an increase in gross plant efficiency of about one percentage point as the hydrogen blend percentage was increased. The primary reason for the improvement in efficiency is from faster, more complete combustion with higher hydrogen blends.
• At 75% Engine Loads: The engine was retuned, which resulted in keeping the efficiency at nominally the same level as the baseline for all hydrogen blends.
• At 95% Engine Load: Only one hydrogen blend test run was conducted at this load setting. Based on the test setup, a maximum hydrogen blend of 25% by volume was achieved with the same efficiency as the baseline.
• At 100% Engine Load: Only one hydrogen blend test run was conducted. Based on the test setup, a maximum hydrogen blend of 12% by volume was achieved, which resulted in a 2.4% drop in efficiency compared to the baseline. However, the test configurations of the hydrogen blending system, fuel supply piping and fuel gas system tie-ins were not optimal, limiting the hydrogen content for blending and adversely affecting the efficiency.

“In some cases, they were a little higher – in some cases, a little lower – but nothing appreciable,” said Maxson. “So that was great news that hydrogen really doesn’t impact the efficiency of an engine.”

Takeaways

Maxson said the test helped provide data to engine manufacturer Wärtsilä, who can use these results to accelerate the development of its hydrogen-capable fleet. The manual tuning to accommodate increasing volumes of hydrogen during testing would ideally be implemented into the company’s future engine design.

Wärtsilä aims to have commercially available 100% fired hydrogen-fired engines by 2025.

Several mechanical changes will be needed for engines to be able to handle 100% hydrogen, Maxson said.

One of them is to change the compression ratio to reduce temperatures, thus avoiding NOx increases and engine knocking. Maxson said another tweak could be implementing pre-chamber combustion to better control the ignition.

Piping will also need to be code-certified for 100% hydrogen to prevent leaks.

“Over the long term, hydrogen also can destroy certain metals because of embrittlement,” said Maxson. “So you have to use the right materials to be able to handle 100% hydrogen coming in and out of the engine.”

NOTE: We are currently accepting speaker submissions for presentations at POWERGEN International on January 23-25, 2024 in New Orleans. Topics include hydrogen co-firing through our track Unlocking Hydrogen’s Power Potential. Submit an abstract for a chance to join our speaker lineup here.

Wärtsilä and WEC Energy Group announced the successful test of a commercially operating Wärtsila engine running on a 25% hydrogen blend.

Testing was completed in October 2022 at WEC’s 55 MW A.J. Mihm power plant in Michigan, using an unmodified Wärtsilä 50SG engine.

The Electric Power Research Institute (EPRI) also participated in the tests and led the assessment of the engine’s performance. Over three days of testing, EPRI found there were improvements in engine efficiency and reduced emissions, while staying compliant with NOx emissions.

A 95% engine load was achieved with the 25% hydrogen blend. Further testing showed that with a 17% hydrogen blend, a 100% engine load was attainable.

The EPRI report states that this class of engines can maintain its higher efficiency compared to simple-cycle gas turbines. Because engines in general have higher efficiency, their relative CO2 output compared to turbines will also be lower, as was shown in this study.

Wärtsilä said this was the largest commercially operated flexible balancing engine ever to run on a hydrogen fuel blend.

“We continue developing and futureproofing our engines to run on sustainable fuels and expect to have an engine and power plant concept for operating with pure hydrogen available by 2026,” said Anja Frada, Chief Operating Officer for Wärtsilä Energy.

The U.S. Department of Energy has awarded $2.8 million to a coalition of partners who will research fuel management options for next-gen nuclear reactors.

EPRI will lead the team, which also includes Oak Ridge National Laboratory (ORNL), Southern Company and Deep Isolation. The funding comes from DOE’s Advanced Reactor Research Projects Agency – Energy (ARPA-E).

Specifically, the two-year project aims to expand the available options of nuclear fuel management by creating a tool to optimize processes for the recovery of uranium from used nuclear fuel. The scope of the project would include an at-scale study for market readiness of some of these techniques.

EPRI will provide project management and expertise in advanced reactor development, ORNL will provide technical expertise in nuclear fuel cycles and system modeling for developing the tool, Southern Company will provide real-world data and their experience in shepherding new technology from the laboratory to full-scale commercial deployment and Deep Isolation will assist with technical expertise in the disposal of used fuel in deep borehole repositories approximately a mile underground.

“This project is at the heart of two of our focus areas at ORNL — advancing the next generation of nuclear technology to meet the nation’s energy needs and climate goals while reducing the demand on waste generation storage and ultimate disposal,” said Andy Worrall, section head of Integrated Fuel Cycle research at ORNL.

Climate change, energy independence, renewable power, the hydrogen economy, etc., are all terms used in recent years (or even decades) to describe the most important challenges of society today. 

While arguments are made over the proper direction to face these challenges, it is important to estimate the potential of candidate technologies for reaching these goals before society commits completely to them. While it is popular to look for a “quick-fix”, solutions almost always require an assortment of varied technologies implemented throughout the entire energy value chain, involving millions of people and costing hundreds of billions (if not trillions) of dollars.  These solutions are also likely to involve technologies that require incremental steps to gain public acceptance and/or prove parts of the process are feasible. 

Combustion or “gas” turbines are highly valuable power generation and heating commodities. In many gas turbines, natural gas (NG) is the fuel of use.  NG is generally a low cost and relatively high energy density fuel with a lower carbon content then coal or liquid fuels. This leads to reduced carbon emissions relative to those fossil fuels. However, while burning NG, carbon dioxide (CO₂) remains a primary constituent of the exhaust emissions.  Therefore, shutting down gas turbines or re-envisioning them for a low-carbon future is a popular research, discussion and development topic. One such proposed re-configuration is blending Hydrogen (H₂) with the NG fuel stream to further reduce CO₂ emissions.

The reduction in CO₂ emissions trends generally with the mass ratio of H₂ in the fuel, such that burning 100% H₂ reduces the CO₂ emissions by 100%. Note the reduction of CO₂ is non-linear with volume % of H₂ in the fuel, with the largest reductions being realized at the higher H₂ volumetric percentages (20% by vol is 3% by mass and 80% by volume is 33% by mass).  

OEMs have been working for many years now to prove out or upgrade their combustion systems for higher H₂ content for which they were originally designed.  Mitsubishi Power has been doing this same work for its M501G advanced class gas turbine. 

Overall, this case study is focused on the H₂/NG blending and burning project conducted at Southern Company/Georgia Power’s Plant McDonough in the Atlanta, GA metro area.  The unit is a Mitsubishi Power M501G gas turbine with a nameplate load of 265MW at baseload and a dry, low NO_x (DLN) combustion system. 

Getting to a H₂ economy which provides H₂ for fueling gas turbines for low- or no-carbon emissions will require many technological advancements. However, this fact should not dissuade the reader.  These advancements appear achievable as several OEMs and 3^rd party vendors are working on viable options.  Included here, are details of the work of Mitsubishi Power, EPRI, and Southern Company who have teamed together to advance the technology further. The value of this project cannot be overstated.  This allows the industry and society to view H₂ as a potentially viable fuel for modern turbines to reduce CO₂ emissions, CO emissions and allow further flexibility of operation of gas turbines with no, or minimal, changes to NOx emissions compared to traditional NG gas turbines. 

Hydrogen impacts on gas turbines

The impacts of H₂, whether in blends or pure form, on gas turbines is varied and often misunderstood.  Recent reports have been issued, or are in progress, to provide more information regarding the influence of H₂ containing fuels on emissions, performance, durability, and service life[1]^,[2],[3].  Albeit details can be found with these and other additional sources, it is important to baseline some considerations when contemplating H₂ inclusion.

Flame Speed

As indicted in Figure 1, the flame speed of H₂ is much faster than NG.  Higher flame speeds require design variation in the DLN combustion systems, which is a primary driver for current gas turbine DLN technology %H₂ blend limitations².   The prominent way to include H₂ in NG fueling up to the allowable % by volume is through control of fuel to air ratios in the combustor.  To push further, total redesigns are needed, which typically aim to increase axial flow velocity and/or staging combustion to combat the wide flame speed ranges between NG and H₂. 

Heating Value

Heating value is a measure of the amount of energy contained in a specific volume (or mass) of fuel, and the heating value of H₂ is significantly different than that of NG. It is the impact of the low density of H₂ that makes the comparison with NG heating values a topic which can lead to incorrect conclusions.  Figure 1 compares the heating values of H₂ and NG in mass and volume bases. 

Performance and Emissions

An increase of H₂ content in the fuel gas will result in a performance and efficiency impact (in a positive direction) on the gas turbine; however, not due to volumetric- or mass-based heating value impacts.  The impact is related to the exchange of CO₂ emissions for H₂O emissions with H₂. As CO₂ decreases in the exhaust, the concentrations of other constituents, namely oxygen and water, increase. Figure 2 shows the general trend of exhaust products with increasing H₂. 

The change in exhaust products results in an exhaust with a higher energy content relative to its temperature (specific heat, c_p).  This results in more work for the same temperature and/or higher efficiency of the gas turbine, depending on the type of control used.  This nominal trend in efficiency, performance, and CO₂ reduction with increasing H₂ is shown in Figure 3. Note that this is shown for a nominal turbine and specific benefits will be model specific.  

KEY takeaways

Major project team members

System design modifications

A temporary blending system was added to the NG supply to introduce specific concentrations of H₂ gas to the fuel gas sufficiently upstream of the gas turbine to ensure adequate mixing, as shown in Figure 4.

Safety and code compliance

The importance of safety during the design and execution phases of the project cannot be overstated.  All team members served critical roles in ensuring that all applicable design codes and regulations were reviewed and complied with.  Systems constructed specifically for hydrogen service were designed or modified in accordance with current ASME B31.12 piping and pipeline code and other relevant standards and/or recommended practices. Functional testing, final inspection, and review of quality documents was performed in person by qualified personnel from each member organization.  While the project itself was intended to operate for only for the duration of the test program, the systems were designed to comply with industry codes and standards applicable to permanent installations. 

Summary and conclusions

Overall, the Georgia Power, Southern Company, EPRI, and Mitsubishi Power consortium successfully operated a M501G with H₂ blending up to ~20.9% by volume. The results of the preparation and testing execution exhibit the feasibility of utilizing H₂ on-site with an existing DLN gas turbine asset while maintaining emissions compliance.  This project constitutes the first of a kind in blending large volume flows of H₂ in an advanced, high efficiency gas turbine operating in combined cycle mode.  Testing results show the promise that H₂ blending holds in the Energy Transformation to a low- to zero-carbon future.

About the authors:

Bobby Noble is the program manager of Gas Turbine R&D at EPRI and a Fellow of American Society of Mechanical Engineers. He is a key global leader in gas turbine combustion and diagnostics, authoring a number of EPRI reports and conference papers on GT hydrogen combustion.

Jim Harper is a Principle Technical Leader in the Gas Turbine programs at EPRI and has extensive Gas Turbine design, control, testing and fleet experience.  In addition to Gas Turbines he has automotive and EV battery thermal systems design experience. He has authored over 10 patents in Gas Turbine Design and Gas Turbine as well as EV Control architectures.

Michael Gagliano is a Technical Executive at EPRI executing material-based research for the Low Carbon Resources Initiative.  He has a Ph.D in Materials Science and Engineering and has expertise in boiler materials, low and high temperature degradation mechanisms, and metallurgical failure analysis.

Dr. Robert Steele is a Technical Executive for Gas Turbine Advanced Components and Technologies at EPRI and has 35 years of experience in gas turbine combustion research, development and testing, and electric power generation industry technologies including carbon capture, compression, and sequestration. 

[1] Douglas, C. M., Shaw, S. L., Martz, T. D., Steele, R. C., Noble, D. R., Emerson, B. L., and Lieuwen, T. C. (July 28, 2022). “Pollutant Emissions Reporting and Performance Considerations for Hydrogen–Hydrocarbon Fuels in Gas Turbines.” ASME. J. Eng. Gas Turbines Power. September 2022; 144(9): 091003. https://doi.org/10.1115/1.4054949

[2] Noble, D., Wu, D., Emerson, B., Sheppard, S., Lieuwen, T., and Angello, L. (February 9, 2021). “Assessment of Current Capabilities and Near-Term Availability of Hydrogen-Fired Gas Turbines Considering a Low-Carbon Future.” ASME. J. Eng. Gas Turbines Power. April 2021; 143(4): 041002. https://doi.org/10.1115/1.4049346

[3] Emerson, B., Lieuwen, T., Noble, B., and Espinoza, N. “Hydrogen substitution for natural gas in turbines: Opportunities, issues, and challenges,” Power Engineering, June 18, 2021. https://www.power-eng.com/gas/hydrogen-substitution-for-natural-gas-in-turbines-opportunities-issues-and-challenges/#gref

The New York Power Authority (NYPA) said a recently completed demonstration showed reduced CO2 emissions when blending hydrogen with natural gas to generate power at NYPA’s Brentwood Small Clean Power Plant on Long Island.

The demonstration project, led by NYPA, the Electric Power Research Institute (EPRI), GE and Airgas, is the first retrofit of an existing NYPA facility that enabled use of hydrogen blended with natural gas.

The project took place between Fall 2021 to Spring 2022 and also included the Electric Power Research Institute (EPRI), GE and Airgas. The demonstration used blends of 5%-44% hydrogen to identify and document any resulting impacts on GE’s LM-6000 combustion turbine engine and plant operations.

The results found that following expected trends, carbon emissions decreased as the amount of hydrogen increased.

In addition, at steady state conditions, the exhaust stack NOx, CO, and ammonia slip levels showed that emissions could be maintained below the New York State Department of Environmental Conservation (DEC) Title V Regulatory Permit using existing post-combustion emissions reduction systems, with no known detrimental effects on gas turbine operations.

The 45 MW Brentwood plant consists of a GE LM6000 GT equipped with single annular combustion (SAC) technology. SAC is not a dry-low emissions combustor technology and requires water injection for NOx control. The plant is also equipped with post-combustion catalyst systems for NOx and CO control. The plant’s location and layout, along with its relatively low capacity factor as a peaking unit, facilitated the temporary modifications required for this demonstration project.

Here are some specific findings:

• CO₂ (carbon dioxide) mass emission rates (ton/hr) decreased as hydrogen fuel percentages increased. At 47 MWg (megawatt gross), CO₂ mass emission rates were reduced by approximately 14% when using 35% hydrogen cofiring.
• At steady water injection conditions, other emissions including NOx (nitrogen oxides), CO (carbon monoxide) and ammonia levels were maintained below regulatory operating permit limits, using the existing SCR (selective catalytic reduction) and CO catalyst post-combustion control systems.
• Engine control was stable throughout the duration of the test and combustion equipment was in good condition before, during and after the test.

The report also details several challenges that would prevent ongoing plant operation using the blend, including volume of hydrogen required, little industry experience with blending and restrictive code requirements.

The test represents the first utility-scale hydrogen blending project in New York, which is mandating a zero-emission electricity sector by 2040.

A summary of the demonstration findings can be found here. The full report is available on EPRI’s website here.

By Lea Boche and Bobby Noble, Electric Power Research Institute

Generation dispatch decisions are made every day with the goal of optimizing revenue from power while reducing operating costs. In simple terms, dispatch determines when to run generating assets and how much power each should produce.

In practice, determining how to dispatch generating assets to meet grid demand involves many disciplines. The generating capacity of the asset must be predicted, and the financial risk-reward equations must be balanced. Owners and operators express a degree of control over these two areas; however, external factors also exert influence.

The weather is a primary factor working against operators, especially in the summer months. Higher temperatures mean increased demand and reduced output from air-breathing assets, such as gas turbines. Accurate weather forecasts are also hard to come by, as anyone who has ventured out on a spring day can attest.

All of this leads to uncertainty in just how much power a generating asset can produce at a given cost. There is also asset-to-asset variation. As gas turbines age, they go through upgrade and maintenance cycles which means two gas turbines that were identical at commissioning may have measurably different performance 10 years later.

These uncertainties lead to assumptions in performance that can lead to reduced operating margins. Better quantification of variation in gas turbine performance, due to internal and external factors, will provide more precise information for dispatch decisions.

EPRI is working with gas turbine owners and operators to develop a software solution aimed at improving the ease and efficiency of making dispatch decisions. Through discussions with gas turbine operators, the team found two key areas where gross oversimplifications are often made: characterizing asset performance and estimating the impacts of variable weather on potential output.

Gas Turbine Performance Prediction for the New Age

The traditional method for predicting gas turbine performance uses correction curves. Most engineers have used these curves, which are often supplied at commissioning and provide estimates to performance vs. inlet temperature, pressure, and humidity.

The reality is that these curves, while presumably accurate at the first commercial operation date, are not updated often enough to accurately represent current performance. This can lead to misestimation of asset performance, which can have financial implications due to over- or under-committing to grid needs.

Figure 1 shows a comparison between correction curves from a gas turbine’s commissioning date and the current day performance. As the plant has aged its characteristics have shifted. Heat rate is underpredicted by the correction curve and the power output vs. inlet temperature has a different slope. While the changes are subtle, the ever-increasing uncertainty of renewables means those that can better quantify their gas turbine asset capabilities will be able to increase their margins in the marketplace.

To be fair, many operators do update performance curves but are often limited in resources and ability to process the noisy and incomplete data that is typical of real-world power plants. Many engineers also lack the training to properly curate, filter, and denoise performance data to extract a good performance model. EPRI and Turbine Logic have worked to leverage modern AI toolsets enabling an automated performance model.

Working with engineers at power plants led to the realization that most want to use AI, but do not want to be bogged down by IT and math. But the team has found a way to fuse physics-based models and AI to let operators perform a ‘click-one-button’ analysis that can accurately capture gas turbine simple and combined cycle performance.

Figure 2 shows the resulting accuracy of the model over an entire year compared to using static correction curves. Using a physics-informed AI model allows for good accuracy and can be used by non-experts in engineering and AI.

What About Weather?

If your performance model is good, weather will have the largest impact on your predicted performance over the day. Being off by 10 degrees ambient temperature can mean a 5% change in potential power output. How accurate is your forecast? Have you ever actually thought about it? Or do you flip on the news every morning and take it at face value?

Finding reliable historical forecast accuracy information is challenging, if not downright impossible, so EPRI and Turbine Logic started tracking forecast accuracy in key locations. They found that the forecast accuracy varies in two repeatable ways. Error in the weather forecast was consistent with the wall-clock time of day and the number of days out from today.

Figure 3 shows the historical forecast accuracy for air temperature for Atlanta over a 3-month period. Obviously, the forecast is less accurate the further into the future you look, but it’s also less accurate from around 11 AM to 8 PM (20h), when afternoon thunderstorms can roll in. Predicting the time of arrival of storms is hard, but the drastic temperature swings can cause large variations in gas turbine output. Pressure and humidity follow similar trends. Better calculation of that +/- can help provide critical risk information to the groups responsible for dispatch commitments.

Bringing It Together

Even if you don’t have commercial dispatch optimization software, there are some basic things you can do now to better quantify the uncertainty in your performance predictions due to inaccurate weather forecasting. Quantifying error is a major first step and involves systematic, purposeful record keeping.

Typically, once a forecast is made, no one ever goes back and checks the accuracy and then uses that information to further improve the next forecast. EPRI and Turbine Logic have suggested some simple steps you can take to see where you stand. From there you can decide if you need to improve your modeling capabilities

Step 1 – Calculate your trade factors

If you have correction curves, figure out the sensitivity to inlet temperature and pressure. If you don’t have correction curves, filter your performance data to base load, and use a spreadsheet to fit a line. If properly filtered, your data should look similar to the data in Figure 2, but appropriate to your range of operations. If you want very rough estimates, you can use the following trade factors.

Table 1: Generic Gas Turbine Trade Factors

These trade factors are used to estimate a change in power output per change in operating conditions relative to the rated conditions of the gas turbine. For example, when your gas turbine is rated at 59 degrees F and 14.7 psia; you want to estimate the power output at 78 degrees and 14.4 psia using the generic factors above:

Change in temperature from rated = 78 – 59 = 19 deg F

Change in pressure from rated = 14.4 – 14.7 = -0.3

Estimated power output = (1 + -0.0035 x 19) x (1 + 0.0068 x -0.3) = 0.931

This means that you should expect to produce 93.1% of the power relative to the rated condition.

Step 2 – Record your weather forecast uncertainty

This should give you something to do during that morning coffee break. Every day, preferably at the same time of the day, start your weather app and record the forecasted temperature and pressure each hour for the next 24-168 hours (1-7 days). It’s your choice on how much to record. If you’ve got a clever intern or access to a forecasting API, you can also use those resources to pull the forecast every day. It’s best to structure the data in a spreadsheet as shown Table 2. Each day:

1. Record ‘today’s date’
2. Record the forecast times
3. Calculate the number of days ahead the forecast is relative to ‘today’
4. Extract the time (hour) of day)
5. Record the forecast for the next 1-7 days
6. Every day go back and fill in what actually happened yesterday for the recording date
7. Calculate the difference between the forecast and the recorded weather

Table 2: Tracking Your Weather Forecast

Step 3 – Calculate the Forecast Uncertainty

Once you’ve collected a month or so of forecast data you can calculate the forecast uncertainty by the time of day or days ahead. If you’re using a spreadsheet program just calculate the standard deviation by day-ahead or time of day for the errors. It might look something like the below.

Table 3: Recorded Forecast Error

Step 4 – Calculate Impact on Performance (You can also skip right to this step!)

Once you’ve done the hard part of calculating your forecast error, you can plug it into the equation below to figure out the impact on power output. Or, if you think you know how bad your forecast is, you can just plug in different levels of forecast error to see the resulting impact.

So, for our example, on day 5 in the future and using our generic performance factors:

This means uncertainty in the forecast is leading to an error in predicted power output of about 2.8% This number may seem small, but considering a 500 MW combined cycle, this can be 15MW. Also, keep in mind that this represents the error that will occur less than 68% of the time. That means 1/3^rd of the time your prediction will be even more inaccurate. Add on uncertainty in asset performance and there could be a significant mismatch between required and possible generation.

Evaluate the impact of your forecast errors on predicting asset capabilities and decide if it’s time to improve your processes.

About the Authors:

Dr. Lea Boche is a senior technical leader at EPRI. She is a plant monitoring and diagnostics specialist and has authored a number of EPRI reports and conference papers on data science and digital twin applications.

Chris Perullo is the Director of Engineering for Turbine Logic. He leads day to day development of customized monitoring and diagnostic solutions and services for natural gas and renewable energy assets.

Bobby Noble is the gas turbine programs manager at EPRI and a Fellow of American Society of Mechanical Engineers. He is a key global leader in gas turbine diagnostics, and has authored a number of EPRI reports and conference papers on GT digital twin utilization case studies.

WEC Energy Group (WEC), Wärtsilä, the Electric Power Research Institute (EPRI) and Burns & McDonnell will partner to carry out hydrogen fuel testing in reciprocating engines at the A.J. Mihm power plant in Michigan.

WEC’s 55 MW plant currently operates with three Wärtsilä 50SG engines that run on natural gas. It was placed into service in March 2019.

The parties will aim for testing fuel blends of up to 25% hydrogen volume mixed with natural gas.

Wärtsilä said the engines can operate with this level of hydrogen blend with little or no modifications needed.

One engine will be selected for the test program and will continue to deliver power to the grid. The hydrogen content in the fuel will be gradually increased to 25%, with measurements of the engine’s performance made throughout the testing.

Wärtsilä said it has already hydrogen blending tests at facilities in Vaasa, Finland and Bermeo, Spain.

The project aims to support WEC’s goal of reducing carbon emissions 60% (from 2005 levels) from its generating fleet by the end of 2025. It could also inform similar hydrogen blending efforts in other reciprocating engines.

Each of Wärtsilä’s three engines at A.J. Mihm has its own 65-foot stack and are cooled by 24 radiator fans that reject heat from a closed-loop circulating antifreeze (coolant) system.

Fueled with natural gas, each engine is shaft-coupled to an electric generator. The units are housed inside a building with an exterior resembling a warehouse. The exhaust system is located outside the building and includes silencers, air quality control systems and stacks.

The plant uses selective catalytic reduction with urea injection for control of nitrogen oxides and an oxidation catalyst for control of carbon monoxide, volatile organic compounds and hazardous air pollutants.

“These hydrogen tests reinforce the viability of the internal combustion engine as a future-proof technology that plays a key role in decarbonizing the power industry,” said Jon Rodriguez, director for engine power plants at Wärtsilä North America.

The past 12 months have been positively electric for the Electric Power Research Institute (EPRI). From working with the U.S. Department of Energy to develop a national EV charging infrastructure blueprint to speaking at COP26 about numerous EPRI-led decarbonization research initiatives, it has been a whirlwind of a year.

Let’s hop in our electric-powered DeLorean and take a trip back to revisit 2021.

Among EPRI’s highlights for the year:

• In April, the U.S. government announced plans to reduce U.S.-economy-wide carbon emissions by around 50 percent by 2030. Because other sectors, such as transportation, buildings, and industry, could largely reduce carbon emissions through electrification, the power sector will play a crucial role in achieving the administration’s 2030 economy-wide goal. On Earth Day, the government announced that DOE, in partnership with EPRI, will develop a national EV charging infrastructure blueprint, including fast charging and grid interaction. The blueprint would assess needs in terms of connectivity, communication, and protocols from the utility down to the vehicle, to support electrification of the full vehicle fleet. EPRI also informed consumers through a new, interactive Electric Vehicle Consumer Guide, providing a searchable database for battery-electric and plug-in hybrid vehicles by make, model, electric range, and MSRP.
• Also, in April, EPRI announced its resource adequacy initiative to help ensure the ongoing ability to meet electricity demand by better anticipating and assessing risks to power supply resources due to extreme weather and other hazards. The project brings together grid operators, utilities, researchers, and other key stakeholders from across the electric power industry to accelerate the evolution of resource adequacy processes and tools. 
• In June, EPRI published a preview of an important analysis, “Rethinking Deployment Scenarios to Enable Large-Scale, Demand-Driven Non-Electricity Markets for Advanced Reactors.” The preview and forthcoming analysis examine four possible deployment scenarios that reimagine nuclear’s role in meeting global energy needs into the future. These scenarios will include shipyard-based manufacturing and floating nuclear facilities, as well as hydrogen production at large scale. A full analysis is scheduled to be published shortly.
• In September, EPRI issued five Grand Challenges to accelerate the adoption of artificial intelligence technologies in high-value areas: advancing grid-interactive smart communities; lessening environmental impacts; strengthening energy system resiliency; enabling intelligent and autonomous power plants; and enhancing cybersecurity. The future power system will involve millions of variable, distributed resources working in concert to reliably meet customers’ energy needs. AI holds the potential to greatly improve system operations, flexibly integrate distributed energy resources, and improve time-consuming tasks such as inspections. 
• Continued progress on the Low-Carbon Resources Initiative (LCRI), launched in 2020 with EPRI and Gas Technology Institute. LCRI is focused on accelerating development and demonstration of low- and zero-carbon energy technologies. LCRI has nearly 50 industry sponsors and in October, kicked off its first demonstration project with the New York Power Authority, General Electric and Airgas to test blending renewable hydrogen with natural gas in a turbine at the Brentwood Power Station. The project could be used as a blueprint throughout New York — which aims to reduce emissions 85% below 1990 levels by 2050 — and the country, helping to further decarbonize the energy sector.
• Speaking at COP26 in Glasgow in November, EPRI announced it was partnering with the World Economic Forum and Accenture to accelerate the transition of industrial clusters towards net zero. Industrial clusters are geographic regions comprised of co-located energy supply and demand companies. Industrial clusters account for approximately 15% to 20% of global CO2 emissions, making them an attractive target for impactful emissions reductions. The initiative aims to have more than 100 industrial clusters engaged by 2024, and four clusters from Australia, the UK and Spain have already joined, with a collective CO2 emissions reduction profile equivalent to that of Denmark.

EPRI accomplished these and many projects in 2021, but we expect an even busier 2022. It’s going to take all sectors of the economy working together to meet collective decarbonization targets. EPRI will help to lead the way to ensure the clean energy transition is equitable and sustainable, while keeping electricity accessible, affordable, and reliable for consumers in the U.S. and around the world.