Abengoa Solar to build the worldÂ’s largest plant

Barakah Unit 4 Cold Hydrostatic Testing validates reactor coolant system integrity at the Barakah Nuclear Energy Plant in Abu Dhabi, UAE, confirming safety, quality, and commissioning readiness under ENEC and KEPCO oversight.

Key Points

Pressure test of Unit 4's reactor coolant system, confirming integrity and safety for commissioning at Barakah.

✅ 25% above normal operating pressure verified.

✅ Welds, joints, and high-pressure components inspected.

✅ Supports safe, reliable, emissions-free baseload power.

The Emirates Nuclear Energy Corporation (ENEC) has successfully completed Cold Hydrostatic Testing (CHT) at Unit 4 of the Barakah Nuclear Energy Plant, the Arab world’s first nuclear energy plant being built in the Al Dhafra region of Abu Dhabi, UAE. The testing incorporated the lessons learned from the previous three units and is a crucial step towards the completion of Unit 4, the final unit of the Barakah plant.

As a part of CHT, the pressure inside Unit 4’s systems was increased to 25 per cent above what will be the normal operating pressure, demonstrating, as seen across global nuclear projects, the quality and robust nature of the Unit’s construction. Prior to the commencement of CHT, Unit 4’s Nuclear Steam Supply Systems were flushed with demineralised water, and the Reactor Pressure Vessel Head and Reactor Coolant Pump Seals were installed. During the Cold Hydrostatic Testing, the welds, joints, pipes and components of the reactor coolant system and associated high-pressure systems were verified.

Mohammed Al Hammadi, Chief Executive Officer of ENEC said: “I am proud of the continued progress being made at Barakah despite the circumstances we have all faced in relation to COVID-19. The UAE leadership’s decisive and proactive response to the pandemic supported us in taking timely, safety-led actions to protect the health and safety of our workforce and our plant. These actions, alongside the efforts of our talented and dedicated workforce, have enabled the successful completion of CHT at Unit 4, which was completed in adherence to the highest standards of safety, quality, and security.

“With this accomplishment, we move another step closer to achieving our goal of supplying up to a quarter of our nation’s electricity needs through the national grid and powering its future growth with safe, reliable, and emissions-free electricity,” he added.

By the end of 2019, ENEC and Korea Electric Power Corporation (KEPCO), working with Korea Hydro & Nuclear Power (KHNP) on the project, had successfully completed all major construction work including major concrete pouring, installation of the Turbine Generator, and the internal components of the Reactor Pressure Vessel (RPV) of Unit 4, which paved the way for the commencement of testing and commissioning.

The testing at Unit 4 represents a significant achievement in the development of the UAE Peaceful Nuclear Energy Program, following the successful completion of fuel assembly loading into Unit 1 in March 2020, confirming that the UAE has officially become a peaceful nuclear energy operating nation. Preparations are now in the final stages for the safe start-up of Unit 1, which subsequently reached 100% power ahead of commercial operations, in the coming months.

ENEC is currently in the final stages of construction of units 2, 3 and 4 of the Barakah Nuclear Energy Plant, as China’s nuclear program continues its steady development globally. The overall construction of the four units is more than 94% complete. Unit 4 is more than 84 per cent, Unit 3 is more than 92 per cent and Unit 2 is more than 95 per cent. The four units at Barakah will generate up to 25 per cent of the UAE’s electricity demand by producing 5,600 MW of clean baseload electricity, as projects such as new reactors in Georgia take shape, and preventing the release of 21 million tons of carbon emissions each year – the equivalent of removing 3.2 million cars off the roads annually.

Related News

• Electricity Forum News

• Power Generation News

US Power Grid Blackouts highlight aging infrastructure, rising outages, and declining reliability per DOE and NERC data, with weather-driven failures, cyberattack risk, and underinvestment stressing utilities, transmission lines, and modernization efforts.

Key Points

US power grid blackouts are outages caused by aging grid assets, severe weather, and cyber threats reducing reliability.

✅ DOE and NERC data show rising outage frequency and duration.

✅ Weather now drives 68-73% of major failures since 2008.

✅ Modernization, hardening, and cybersecurity investments are critical.

The United States power grid has more blackouts than any other country in the developed world, according to new data and U.S. blackout warnings that spotlight the country’s aging and unreliable electric system.

The data by the Department of Energy (DOE) and the North American Electric Reliability Corporation (NERC) shows that Americans face more power grid failures lasting at least an hour than residents of other developed nations.

And it’s getting worse.

Going back three decades, the US grid loses power 285 percent more often than it did in 1984, when record keeping began, International Business Times reported. The power outages cost businesses in the United States as much as $150 billion per year, according to the Department of Energy.

Customers in Japan lose power for an average of 4 minutes per year, as compared to customers in the US upper Midwest (92 minutes) and upper Northwest (214), University of Minnesota Professor Massoud Amin told the Times. Amin is director of the Technological Leadership Institute at the school.

#google#

The grid is becoming less dependable each year, he said.

“Each one of these blackouts costs tens of hundreds of millions, up to billions, of dollars in economic losses per event,” Amin said. “… We used to have two to five major weather events per year [that knocked out power], from the ‘50s to the ‘80s. Between 2008 and 2012, major outages caused by weather, reflecting extreme weather trends, increased to 70 to 130 outages per year. Weather used to account for about 17 to 21 percent of all root causes. Now, in the last five years, it’s accounting for 68 to 73 percent of all major outages.”

As previously reported by Off The Grid News, the power grid received a “D+” grade on its power grid report card from the American Society of Civil Engineers (ASCE) in 2013. The power grid grade card rating means the energy infrastructure is in “poor to fair condition and mostly below standard, with many elements approaching the end of their service life.” It further means a “large portion of the system exhibits significant deterioration” with a “strong risk of failure.”

“America relies on an aging electrical grid and pipeline distribution systems, some of which originated in the 1880s,” the 2013 ASCE report read. “Investment in power transmission has increased since 2005, but ongoing permitting issues, weather events, and limited maintenance have contributed to an increasing number of failures and power interruptions.”

As The Times noted, the US power grid as it exists today was built shortly after World War II, with the design dating back to Thomas Edison. While Edison was a genius, he and his contemporaries could not have envisioned all the strains the modern world would place upon the grid and the multitude of tech gadgets many Americans treat as an extension of their body. While the drain on the grid has advanced substantially, the infrastructure itself has not.

There are approximately 5 million miles of electrical transmission lines throughout the United States, and thousands of power generating plants dot the landscape. The electrical grid is managed by a group of 3,300 different utilities and serve about 150 million customers, The Times said. The entire power grid system is currently valued at $876 billion.

Many believe the grid is vulnerable to an attack on substations and other threats.

Former Department of Homeland Security Secretary Janet Napolitano once said that a power grid cyber attack is a matter of “when” not “if,” as Russians hacked utilities incidents have shown.

Related News

• Electricity Forum News

• Grid Technologies News

AI Load Forecasting for Utilities leverages machine learning, smart meters, and predictive analytics to balance energy demand during COVID-19 disruptions, optimize grid reliability, support demand response, and stabilize rates for residential and commercial customers.

Key Points

AI predicts utility demand with ML and smart meters to improve reliability and reduce costs.

✅ Adapts to rapid demand shifts with accurate short term forecasts

✅ Optimizes demand response and distributed energy resources

✅ Reduces outages risk while lowering procurement and operating costs

The spread of the novel coronavirus that causes COVID-19 has prompted state and local governments around the U.S. to institute shelter-in-place orders and business closures. As millions suddenly find themselves confined to their homes, the shift has strained not only internet service providers, streaming platforms, and online retailers, but the utilities supplying power to the nation’s electrical grid, which face longer, more frequent outages as well.

U.S. electricity use on March 27, 2020 was 3% lower than it was on March 27, 2019, a loss of about three years of sales growth. Peter Fox-Penner, director of the Boston University Institute for Sustainable Energy, asserted in a recent op-ed that utility revenues will suffer because providers are halting shutoffs and deferring rate increases. Moreover, according to research firm Wood Mackenzie, the rise in household electricity demand won’t offset reduced business electricity demand, mainly because residential demand makes up just 40% of the total demand across North America.

Some utilities are employing AI and machine learning for the energy transition to address the windfalls and fluctuations in energy usage resulting from COVID-19. Precise load forecasting could ensure that operations aren’t interrupted in the coming months, thereby preventing blackouts and brownouts. And they might also bolster the efficiency of utilities’ internal processes, leading to reduced prices and improved service long after the pandemic ends.

Innowatts
Innowatts, a startup developing an automated toolkit for energy monitoring and management, counts several major U.S. utility companies among its customers, including Portland General Electric, Gexa Energy, Avangrid, Arizona Public Service Electric, WGL, and Mega Energy. Its eUtility platform ingests data from over 34 million smart energy meters across 21 million customers in more than 13 regional energy markets, while its machine learning algorithms analyze the data to forecast short- and long-term loads, variances, weather sensitivity, and more.

Beyond these table-stakes predictions, Innowatts helps evaluate the effects of different rate configurations by mapping utilities’ rate structures against disaggregated cost models. It also produces cost curves for each customer that reveal the margin impacts on the wider business, and it validates the yield of products and cost of customer acquisition with models that learn the relationships between marketing efforts and customer behaviors (like real-time load).

Innowwatts told VentureBeat that it observed “dramatic” shifts in energy usage between the first and fourth weeks of March. In the Northeast, “non-essential” retailers like salons, clothing shops, and dry cleaners were using only 35% as much energy toward the end of the month (after shelter-in-place orders were enacted) versus the beginning of the month, while restaurants (excepting pizza chains) were using only 28%. In Texas, conversely, storage facilities were using 142% as much energy in the fourth week compared with the first.

Innowatts says that throughout these usage surges and declines, its clients took advantage of AI-based load forecasting to learn from short-term shocks and make timely adjustments. Within three days of shelter-in-place orders, the company said, its forecasting models were able to learn new consumption patterns and produce accurate forecasts, accounting for real-time changes.

Innowatts CEO Sid Sachdeva believes that if utility companies had not leveraged machine learning models, demand forecasts in mid-March would have seen variances of 10-20%, significantly impacting operations.

“During these turbulent times, AI-based load forecasting gives energy providers the ability to … develop informed, data-driven strategies for future success,” Sachdeva told VentureBeat. “With utilities and energy retailers seeing a once-in-a-lifetime 30%-plus drop in commercial energy consumption, accurate forecasting has never been more important. Without AI tools, utilities would see their forecasts swing wildly, leading to inaccuracies of 20% or more, placing an enormous strain on their operations and ultimately driving up costs for businesses and consumers.”

Autogrid
Autogrid works with over 50 customers in 10 countries — including Energy Australia, Florida Power & Light, and Southern California Edison — to deliver AI-informed power usage insights. Its platform makes 10 million predictions every 10 minutes and optimizes over 50 megawatts of power, which is enough to supply the average suburb.

Flex, the company’s flagship product, predicts and controls tens of thousands of energy resources from millions of customers by ingesting, storing, and managing petabytes of data from trillions of endpoints. Using a combination of data science, machine learning, and network optimization algorithms, Flex models both physics and customer behavior, automatically anticipating and adjusting for supply and demand patterns through virtual power plants that coordinate distributed assets.

Autogrid also offers a fully managed solution for integrating and utilizing end-customer installations of grid batteries and microgrids. Like Flex, it automatically aggregates, forecasts, and optimizes capacity from assets at sub-stations and transformers, reacting to distribution management needs while providing capacity to avoid capital investments in system upgrades.

Autogrid CEO Dr. Amit Narayan told VentureBeat that the COVID-19 crisis has heavily shifted daily power distribution in California, where it’s having a “significant” downward impact on hourly prices in the energy market. He says that Autogrid has also heard from customers about transformer failures in some regions due to overloaded circuits, which he expects will become a problem in heavily residential and saturated load areas during the summer months (as utilities prepare for blackouts across the U.S. when air conditioning usage goes up).

“In California, [as you’ll recall], more than a million residents faced wildfire prevention-related outages in PG&E territory in 2019,” Narayan said, referring to the controversial planned outages orchestrated by Pacific Gas & Electric last summer. “The demand continues to be high in 2020 in spite of the COVID-19 crisis, as residents prepare to keep the lights on and brace for a similar situation this summer. If a 2019 repeat happens again, it will be even more devastating, given the health crisis and difficulty in buying groceries.”

AI making a difference
AI and machine learning isn’t a silver bullet for the power grid — even with predictive tools at their disposal, utilities are beholden to a tumultuous demand curve and to mounting climate risks across the grid. But providers say they see evidence the tools are already helping to prevent the worst of the pandemic’s effects — chiefly by enabling them to better adjust to shifted daily and weekly power load profiles.

“The societal impact [of the pandemic] will continue to be felt — people may continue working remotely instead of going into the office, they may alter their commute times to avoid rush hour crowds, or may look to alternative modes of transportation,” Schneider Electric chief innovation officer Emmanuel Lagarrigue told VentureBeat. “All of this will impact the daily load curve, and that is where AI and automation can help us with maintenance, performance, and diagnostics within our homes, buildings, and in the grid.”

Related News

• Electricity Forum News

• Grid Technologies News

US SF6 Emissions Decline as NOAA analysis and EPA mitigation show progress, with atmospheric measurements and Greenhouse Gas Reporting verifying reductions from the electric power grid; sulfur hexafluoride's extreme global warming potential underscores inventory improvements.

Key Points

A documented drop in US sulfur hexafluoride emissions, confirmed by NOAA atmospheric data and EPA reporting reforms.

✅ NOAA towers and aircraft show 2007-2018 decline

✅ EPA reporting and utility mitigation narrowed inventory gaps

✅ Winter leaks and servicing signal further reduction options

A new NOAA analysis shows U.S. emissions of the super-potent greenhouse gas sulfur hexafluoride (SF6) have declined between 2007-2018, likely due to successful mitigation efforts by the Environmental Protection Agency (EPA) and the electric power industry, with attention to SF6 in the power industry across global markets. 

At the same time, significant disparities that existed previously between NOAA’s estimates, which are based on atmospheric measurements, and EPA’s estimates, which are based on a combination of reported emissions and industrial activity, have narrowed following the establishment of the EPA's Greenhouse Gas Reporting Program. The findings, published in the journal Atmospheric Chemistry and Physics, also suggest how additional emissions reductions might be achieved. 

SF6 is most commonly used as an electrical insulator in high-voltage equipment that transmits and distributes electricity, and its emissions have been increasing worldwide as electric power systems expand, even as regions hit milestones like California clean energy surpluses in recent years. Smaller amounts of SF6 are used in semiconductor manufacturing and in magnesium production. 

SF6 traps 25,000 times more heat than carbon dioxide over a 100-year time scale for equal amounts of emissions, and while CO2 emissions flatlined in 2019 globally, that comparison underscores the potency of SF6. That means a relatively small amount of the gas can have a significant impact on climate warming. Because of its extremely large global warming potential and long atmospheric lifetime, SF6 emissions will influence Earth’s climate for thousands of years.

In this study, researchers from NOAA’s Global Monitoring Laboratory, as record greenhouse gas concentrations drive demand for better data, working with colleagues at EPA, CIRES, and the University of Maryland, estimated U.S. SF6 emissions for the first time from atmospheric measurements collected at a network of tall towers and aircraft in NOAA’s Global Greenhouse Gas Reference Network. The researchers provided an estimate of SF6 emissions independent from the EPA’s estimate, which is based on reported SF6 emissions for some industrial facilities and on estimated SF6 emissions for others.

“We observed differences between our atmospheric estimates and the EPA’s activity-based estimates,” said study lead author Lei Hu, a Global Monitoring Laboratory researcher who was a CIRES scientist at the time of the study. “But by closely collaborating with the EPA, we were able to identify processes potentially responsible for a significant portion of this difference, highlighting ways to improve emission inventories and suggesting additional emission mitigation opportunities, such as forthcoming EPA carbon capture rules for power plants, in the future.” 

In the 1990s, the EPA launched voluntary partnerships with the electric power, where power-sector carbon emissions are falling as generation shifts, magnesium, and semiconductor industries to reduce SF6 emissions after the United States recognized that its emissions were significant. In 2011, large SF6 -emitting facilities were required to begin tracking and reporting their emissions under the EPA Greenhouse Gas Reporting Program. 

Hu and her colleagues documented a decline of about 60 percent in U.S. SF6 emissions between 2007-2018, amid global declines in coal-fired power in some years—equivalent to a reduction of between 6 and 20 million metric tons of CO2 emissions during that time period—likely due in part to the voluntary emission reduction partnerships and the EPA reporting requirement. A more modest declining trend has also been reported in the EPA’s national inventories submitted annually under the United Nations Framework Convention on Climate Change. 

Examining the differences between the NOAA and EPA independent estimates, the researchers found that the EPA’s past inventory analyses likely underestimated SF6 emissions from electrical power transmission and distribution facilities, and from a single SF6 production plant in Illinois. According to Hu, the research collaboration has likely improved the accuracy of the EPA inventories. The 2023 draft of the EPA’s U.S. Greenhouse Gas Emissions and Sinks: 1990-2021 used the results of this study to support revisions to its estimates of SF6 emissions from electrical transmission and distribution. 

The collaboration may also lead to improvements in the atmosphere-based estimates, helping NOAA identify how to expand or rework its network to better capture emitting industries or areas with significant emissions, according to Steve Montzka, senior scientist at GML and one of the paper’s authors.

Hu and her colleagues also found a seasonal variation in SF6 emissions from the atmosphere-based analysis, with higher emissions in winter than in summer. Industry representatives identified increased servicing of electrical power equipment in the southern states and leakage from aging brittle sealing materials in the equipment in northern states during winter as likely explanations for the enhanced wintertime emissions—findings that suggest opportunities for further emissions reductions.

“This is a great example of the future of greenhouse gas emission tracking, where inventory compilers and atmospheric scientists work together to better understand emissions and shed light on ways to further reduce them,” said Montzka.

Related News

• Electricity Forum News

• Climate Change News

Alberta wind power surpasses coal as AESO reports record renewable energy feeding the grid, with natural gas conversions, solar growth, energy storage, and decarbonization momentum lowering carbon intensity across Alberta's electricity system.

Key Points

AESO data shows wind surpassing coal in Alberta, driven by coal retirements, gas conversions, and growing renewables.

✅ AESO reports wind output above coal several times this week

✅ Coal units retire or convert to natural gas, boosting renewables

✅ Carbon intensity falls; storage and solar improve grid reliability

Marking a significant shift in Alberta energy history, wind generation trends provided more power to the province's energy grid than coal several times this week.

According to data from the Alberta Energy System Operator (AESO) released this week, wind generation units contributed more energy to the grid than coal at times for several days. On Friday afternoon, wind farms contributed more than 1,700 megawatts of power to the grid, compared to around 1,260 megawatts from coal stations.

"The grid is going through a period of transformative change when we look at the generation fleet, specifically as it relates to the coal assets in the province," Mike Deising, AESO spokesperson, told CTV News in an interview.

The shift in electricity generation comes as more coal plants come offline in Alberta, or transition to cleaner energy through natural gas generation, including the last of TransAlta's units at the Keephills Plant west of Edmonton.

Only three coal generation stations remain online in the province, at the Genesee plant southwest of Edmonton, as the coal phase-out timeline advances. Less available coal power, means renewable energy like wind and solar make up a greater portion of the grid.

EVOLUTION OF THE GRID
"Our grid is changing, and it's evolving," Deising said, adding that more units have converted to natural gas and companies are making significant investments into solar and wind energy.

For energy analyst Kevin Birn with IHS Markit, that trend is only going to continue.

"What we've seen for the last 24 to 36 months is a dramatic acceleration in ambition, policy, and projects globally around cleaner forms of energy or lower carbon forms of energy," Birn said.

Birn, who is also chief analyst of Canadian Oil Markets, added that not only has the public appetite for cleaner energy helped fuel the shift, but technological advancements have made renewables like wind and solar more cost-efficient.

"Alberta was traditionally heavily coal-reliant," he said. "(Now) western Canada has quite a diverse energy base."

LESS CARBON-INTENSIVE
According to Birn, the shift in energy production marks a significant reduction in carbon emissions as Alberta progresses toward its last coal plant closure milestone.

Ten years ago, IHS Markit estimates that Alberta's grid contributed about 900 kilograms of carbon dioxide equivalent per megawatt-hour of energy generation.

"That (figure is) really representing the dominance and role of coal in that grid," Birn said.

Current estimates show that figure is closer to 600 kilograms of CO2 equivalent.

"That means the power you and I are using is less carbon-intensive," Birn said, adding that figure will continue to fall over the next couple of years.

RENEWABLES HERE TO STAY
While many debate whether Alberta's energy is getting clean enough fast enough, Birn believes change is coming.

"It's been a half-decade of incredible price volatility in the oil market which had really dominated this sector and region," the analyst said.

"When I think of the future, I see the power sector building on large-scale renewables, which means decarbonization, and that provides an opportunity for those tech companies looking for clean energy places to land facilities."

Coal and natural gas are considered baseline assets by the AESO, where generation capacity does not shift dramatically, though some utilities report declining coal returns in other markets.

"Wind is a variable resource. It will generate when the wind is blowing, and it obviously won't when the wind is not," Deising said. "Wind and solar can ramp quickly, but they can drop off quite quickly, and we have to be prepared.

"We factor that into our daily planning and assessments," he added. "We follow those trends and know where the renewables are going to show up on the system, how many renewables are going to show up."

Deising says one wind plant in Alberta currently has an energy storage capacity to preserve renewably generated electricity during summer demand records and peak hours as needed. As the technology becomes more affordable, he expects more plants to follow suit.

"As a system operator, our job is to make sure as (the grid) is evolving we can continue to provide reliable power to Albertans at every moment every day," Deising said. "We just have to watch the system more carefully." 

Related News

• Electricity Forum News

• Power Generation News

Near-Field Thermophotovoltaics captures radiated energy across a nanoscale gap, using thin-film photovoltaic cells and indium gallium arsenide to boost power density and efficiency, enabling compact Army portable power from emitters via radiative heat transfer.

Key Points

A nanoscale TPV method capturing near-field photons for higher power density at lower emitter temperatures.

✅ Nanoscale gap boosts radiative transfer and usable photon flux

✅ Thin-film InGaAs cells recycle sub-band-gap photons via reflector

✅ Achieved ~5 kW/m2 power density with higher efficiency

With the addition of sensors and enhanced communication tools, providing lightweight, portable power has become even more challenging, with concepts such as power from falling snow illustrating how diverse new energy-harvesting approaches are. Army-funded research demonstrated a new approach to turning thermal energy into electricity that could provide compact and efficient power for Soldiers on future battlefields.

Hot objects radiate light in the form of photons into their surroundings. The emitted photons can be captured by a photovoltaic cell and converted to useful electric energy. This approach to energy conversion is called far-field thermophotovoltaics, or FF-TPVs, and has been under development for many years; however, it suffers from low power density and therefore requires high operating temperatures of the emitter.

The research, conducted at the University of Michigan and published in Nature Communications, demonstrates a new approach, where the separation between the emitter and the photovoltaic cell is reduced to the nanoscale, enabling much greater power output than what is possible with FF-TPVs for the same emitter temperature.

This approach, which enables capture of energy that is otherwise trapped in the near-field of the emitter is called near-field thermophotovoltaics or NF-TPV and uses custom-built photovoltaic cells and emitter designs ideal for near-field operating conditions, alongside emerging smart solar inverters that help manage conversion and delivery.

This technique exhibited a power density almost an order of magnitude higher than that for the best-reported near-field-TPV systems, while also operating at six-times higher efficiency, paving the way for future near-field-TPV applications, including remote microgrid deployments in extreme environments, according to Dr. Edgar Meyhofer, professor of mechanical engineering, University of Michigan.

"The Army uses large amounts of power during deployments and battlefield operations and must be carried by the Soldier or a weight constrained system," said Dr. Mike Waits, U.S. Army Combat Capabilities Development Command's Army Research Laboratory. "If successful, in the future near-field-TPVs could serve as more compact and higher efficiency power sources for Soldiers as these devices can function at lower operating temperatures than conventional TPVs."

The efficiency of a TPV device is characterized by how much of the total energy transfer between the emitter and the photovoltaic cell is used to excite the electron-hole pairs in the photovoltaic cell, where insights from near-light-speed conduction research help contextualize performance limits in semiconductors. While increasing the temperature of the emitter increases the number of photons above the band-gap of the cell, the number of sub band-gap photons that can heat up the photovoltaic cell need to be minimized.

"This was achieved by fabricating thin-film TPV cells with ultra-flat surfaces, and with a metal back reflector," said Dr. Stephen Forrest, professor of electrical and computer engineering, University of Michigan. "The photons above the band-gap of the cell are efficiently absorbed in the micron-thick semiconductor, while those below the band-gap are reflected back to the silicon emitter and recycled."

The team grew thin-film indium gallium arsenide photovoltaic cells on thick semiconductor substrates, and then peeled off the very thin semiconductor active region of the cell and transferred it to a silicon substrate, informing potential interfaces with home battery systems for distributed use.

All these innovations in device design and experimental approach resulted in a novel near-field TPV system that could complement distributed resources in virtual power plants for resilient operations.

"The team has achieved a record ~5 kW/m2 power output, which is an order of magnitude larger than systems previously reported in the literature," said Dr. Pramod Reddy, professor of mechanical engineering, University of Michigan.

Researchers also performed state-of-the-art theoretical calculations to estimate the performance of the photovoltaic cell at each temperature and gap size, informing hybrid designs with backup fuel cell solutions that extend battery life, and showed good agreement between the experiments and computational predictions.

"This current demonstration meets theoretical predictions of radiative heat transfer at the nanoscale, and directly shows the potential for developing future near-field TPV devices for Army applications in power and energy, communication and sensors," said Dr. Pani Varanasi, program manager, DEVCOM ARL that funded this work.

Related News

• Electricity Forum News

• Power Generation News