Developer signs 30 MW of wind deals in Ontario

Rooftop Solar Battery Backup helps Californians keep lights on during PG&E blackouts, combining home energy storage with grid-tied systems for wildfire prevention, outage resilience, and backup power when solar panels cannot supply nighttime demand.

Key Points

A home battery paired with rooftop solar, providing backup power and blackout resilience when the grid is down.

✅ Works when grid is down; panels alone stop for safety.

✅ Requires home battery storage; market adoption is growing.

✅ Supports wildfire mitigation and PG&E outage preparedness.

Californians have embraced rooftop solar panels more than anyone in the U.S., but amid California's solar boom many are learning the hard way the systems won’t keep the lights on during blackouts.

That’s because most panels are designed to supply power to the grid -- not directly to houses, though emerging peer-to-peer energy models may change how neighbors share power in coming years. During the heat of the day, solar systems can crank out more juice than a home can handle, a challenge also seen in excess solar risks in Australia today. Conversely, they don’t produce power at all at night. So systems are tied into the grid, and the vast majority aren’t working this week as PG&E Corp. cuts power to much of Northern California to prevent wildfires, even as wildfire smoke can dampen solar output during such events.

The only way for most solar panels to work during a blackout is pairing them with solar batteries that store excess energy. That market is just starting to take off. Sunrun Inc., the largest U.S. rooftop solar company, said some of its customers are making it through the blackouts with batteries, but it’s a tiny group -- countable in the hundreds.

“It’s the perfect combination for getting through these shutdowns,” Sunrun Chairman Ed Fenster said in an interview. He expects battery sales to boom in the wake of the outages, as the state has at times reached a near-100% renewables mark that heightens the need for storage.

And no, trying to run appliances off the power in a Tesla Inc. electric car won’t work, at least without special equipment, and widespread U.S. power-outage risks are a reminder to plan for home backup.

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Central Asia power shortages strain grids across Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan, and Turkmenistan, driven by drought-hit hydropower, aging coal and gas plants, rising demand, cryptomining loads, and winter peak consumption risks.

Key Points

Regionwide blackouts from drought, aging plants and grids, rising demand, and winter peaks stressing Central Asia.

✅ Drought slashes hydropower in Kyrgyzstan, Tajikistan, Uzbekistan

✅ Aging coal and gas TPPs and weak grids cause frequent outages

✅ Cryptomining loads and winter heating spike demand and stress supply

Central Asians from western Kazakhstan to southern Tajikistan are suffering from power and energy shortages that have caused hardship and emergency situations affecting the lives of millions of people.

On October 14, several units at three power plants in northeastern Kazakhstan were shut down in an emergency that resulted in a loss of more than 1,000 megawatts (MW) of electricity.

It serves as an example of the kind of power failures that plague the region 30 years after the Central Asian countries gained independence and despite hundreds of millions of dollars being invested in energy infrastructure and power grids, and echo risks seen in other advanced markets such as Japan's near-blackouts during recent cold snaps.

Some of the reasons for these problems are clear, but with all the money these countries have allocated to their energy sectors and financial help they have received from international financial institutions, it is curious the situation is already so desperate with winter officially still weeks away.

The Current Problems
Three power plants were affected in the October 14 shutdowns of units: Ekibastuz-1, Ekibastuz-2, and the Aksu power plant.

Ekibastuz-1 is the largest power plant in Kazakhstan, capable of generating some 4,000 MW, roughly 13 percent of Kazakhstan’s total power output.

The Kazakhstan Electricity Grid Operating Company (KEGOC) explained the problems resulted partially from malfunctions and repair work, but also from overuse of the system that the government would later say was due to cryptominers, a large number of whom have moved to Kazakhstan recently from China after Beijing banned the mining needed by Bitcoin and other cryptocurrencies, amid its own China's power cuts across several provinces in 2021.

But between November 8 and 9, rolling blackouts were reported in the East Kazakhstan, North Kazakhstan, and Kyzylorda provinces, as well as the area around Almaty, Kazakhstan’s biggest city, and Shymkent, its third largest city.

People in Uzbekistan say they, too, are facing blackouts that the Energy Ministry described as “short-term outages,” even as authorities have looked to export electricity to Afghanistan to support regional demand, though it has been clear for several weeks that the country will have problems with natural gas supplies this winter.

Power lines in Uzbekistan
Kyrgyz President Sadyr Japarov continues to say there won't be any power rationing in Kyrgyzstan this winter, but at the end of September the National Energy Holding Company ordered “restrictions on the lighting of secondary streets, advertisements, and facades of shops, cafes, and other nonresidential customers.”

Many parts of Tajikistan are already experiencing intermittent supplies of electricity.

Even in Turkmenistan, a country with the fourth-largest reserves of natural gas in the world, there were reports of problems with electricity and heating in the capital, Ashgabat.

What Is Going On?
The causes of some of these problems are easy to see.

The population of the region has grown significantly, with the population of Central Asia when the Soviet Union collapsed in late 1991 being some 50 million and today about 75 million.

Kyrgyzstan and Tajikistan are mountainous countries that have long been touted for their hydropower potential and some 90 percent of Kyrgyzstan’s domestically produced electricity and 98 percent of Tajikistan’s come from hydropower.

But a severe drought that struck Central Asia this year has resulted in less hydropower and, in general, less energy for the region, similar to constraints seen in Europe's reduced hydro and nuclear output this year.

Tajik authorities have not reported how low the water in the country’s key reservoirs is, but Kyrgyzstan has reported the water level in the reservoir at its Toktogul hydropower plant (HPP) is 11.8 billion cubic meters (bcm), the lowest level in years and far less than the 14.7 bcm of water it had in November 2020.

The Toktogul HPP, with an installed capacity of 1,200 MW, provides some 40 percent of the country's domestically produced electricity, but operating the HPP this winter to generate desperately needed energy brings the risk of leaving water levels at the reservoir critically low next spring and summer when the water is also needed for agricultural purposes.

This year’s drought is something Kyrgyzstan and Tajikistan will have to take into consideration as they plan how to provide power for their growing populations in the future. Hydropower is a desirable option but may be less reliable with the onset of climate change, prompting interest in alternatives such as Ukraine's wind power to diversify generation.

Uzbekistan is also feeling the effects of this year’s drought, and, like the South Caucasus where Georgia's electricity imports have increased, supply shortfalls are testing grids.

According to the International Energy Agency, HPPs account for some 12 percent of Uzbekistan’s generating capacity.

Uzbekistan’s Energy Ministry attributed low water levels at HPPs that have caused a 23 percent decrease in hydropower generation this year.

A reservoir in Kyrgyzstan
Kazakhstan and Uzbekistan are the most populous Central Asian countries, and both depend on thermal power plants (TPP) for generating most of their electricity.

Most of the TPPs in Kazakhstan are coal-fired, while most of the TPPs in Uzbekistan are gas-fired.

Kazakhstan has 68 power plants, 80 percent of which are coal-fired TPPs, and most are in the northern part of the country where the largest deposits of coal are located. Kazakhstan has the world's 10th largest reserves of coal.

About 88 percent of Uzbekistan’s electricity comes from TTPs, most of which use natural gas.

Uzbekistan’s proven reserves are some 800 billion cubic meters, but gas production in Uzbekistan has been decreasing.

In December 2020, Uzbek President Shavkat Mirziyoev ordered a halt to the country’s gas exports and instructed that gas to be redirected for domestic use. Mirziyoev has already given similar instructions for this coming winter.

How Did It Come To This?
The biggest problem with the energy infrastructure in Central Asia is that it is generally very old. Nearly all of its power plants date back to the Soviet era -- and some well back into the Soviet period.

The use of power plants and transmission lines that some describe as “obsolete” and a few call “decrepit” has unfortunately been a necessity in Central Asia, even as regional players pursue new interconnections like Iran's plan to transmit electricity to Europe as a power hub.

Reporting on Kazakhstan in September 2016, the Asian Development Bank (ADB) said, “70 percent of the power generation infrastructure is in need of rehabilitation.”

The Ekibastuz-1 TPP is relatively new by the power-plant standards of Central Asia. The first unit of the eight units of the TPP was commissioned in 1980.

The first unit at the AKSU TPP was commissioned in 1968, and the first unit of the gas- and fuel-fired TPP in southern Kazakhstan’s Zhambyl Province was commissioned in 1967.

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Work From Home Energy Consumption is driving higher electricity bills as residential usage rises. Smart meter data, ISO-New-England trends, and COVID-19 telecommuting show stronger power demand and sensitivity to utility rates across regions.

Key Points

Higher household electricity use from telecommuting, shifting load to residences and raising utility bills.

✅ Smart meters show 5-22 percent residential usage increases.

✅ Commercial demand fell as home cooling and IT loads rose.

✅ Utility rates and AC use drive bill spikes during summer.

Don't be surprised if your electric bills are looking higher than usual, with a sizable increase in the amount of power that you have used.

Summer traditionally is a peak period for electricity usage because of folks' need to run fans and air-conditioners to cool their homes or run that pool pump. But the arrival of the coronavirus and people working from home is adding to amount of power people are using.

Under normal conditions, those who work in their employer's offices might not be cooling their homes as much during the middle of the day or using as much electricity for lights and running computers.

For many, that's changed.

Estimates on how much of an increase residential electric customers are seeing as result of working from home vary widely.

ISO-New England, the regional electric grid operator, has seen a 3 percent to 5 percent decrease in commercial and industrial power demand, even as the grid overseer issued pandemic warnings nationally. The expectation is that much of that decrease translates into a corresponding increase in residential electricity usage.

But other estimates put the increase in residential electricity usage much higher. A Washington state company that makes smart electric meters, Itron, estimates that American households are using 5 percent to 10 percent more electricity per month since March, when many people began working from home as part of an effort to prevent the spread of the coronavirus.

Another smart metering company, Cambridge, Mass.-based Sense, found that average home electricity usage increased 22 percent in April compared to the same period in 2019, a reflection of people using more electricity while they stayed home. Based on its analysis of data from 5,000 homes across 30 states, Sense officials said a typical customer's monthly electric bill increased by between $22 and $25, with a larger increase for consumers in states with higher electricity rates.

Connecticut-specfic data is harder to come by.

Officials with Orange-based United Illuminating declined to provide any customer usage data, though, like others in the power industry, they did acknowledge that residential customers are using more electricity. And the state's other large electric distribution utility, Eversource, was unable to provide any recent data on residential electric usage. The company did tell Connecticut utility regulators there was a 3 percent increase in residential power usage for the week of March 21 compared to the week before.

Over the same time period, Eversource officials saw a 3 percent decrease in power usage by commercial and industrial customers.

Separately, nuclear plant workers raised concerns about pandemic precautions at some facilities, reflecting operational strains.

Alan Behm of Cheshire said he normally uses 597 kilowatt hours of electricity during an average month. But in April of this year, the amount of electricity he used rose by nearly 51 percent.

With many offices closed, the expense of heating, cooking and lighting is being shifted from employer to employee, and some utilities such as Manitoba Hydro have pursued unpaid days off to trim costs during the pandemic. And one remote work expert believes some companies are recognizing the burden those added costs are placing on workers -- and are trying to do something about it.

Technology giant Google announced in late May that it was giving employees who work from home $1,000 allowances to cover equipment costs and other expenses associated with establishing a home office.

Moe Vela, chief transparency officer for the New York City-based computer software company TransparentBusiness, said the move by Google executives is a savvy one.

"Google is very smart to have figured this out," Vela said. "This is what employees want, especially millenials. People are so much happier to be working remotely, getting those two to three hours back per day that some people spend getting to and from work is so much more important than a stipend."

Vela predicted that even after a vaccine is found for the corona virus, one of the key worklife changes is likely to be a broader acceptance of telework and working from home.

Beyond the immediate shifts, more young Canadians would work in electricity if awareness improved, pointing to future talent pipelines.

"I think that's where we're headed," he said. "I think it will make an employer more attractive as they try to attract talent from around the world."

Vela said employers save an average of $11,000 per year for each employee they have working from home.

"It would be a brilliant move if a company were to share some of that amount with employees," he said. "I wouldn't do it if it's going to cause a company to not be there (in business) though."

The idea of a company sharing whatever savings it achieves by having employees work from home wasn't well received by many Connecticut residents who responded to questions posed via social media by Hearst Connecticut Media. More than 100 people responded and an overwhelming number of people spoke out against the idea.

"You are saving on gas and other travel related expenses, so the small increase in your electric bill shouldn't really be a concern," said Kathleen Bennett Charest of Wallingford.

Jim Krupp, also of Wallingford, said, "to suggest that the employers compensate the employees makes as much sense as suggesting that the employees should take a pay cut due to their reduced expenses for travel, day care, and eating lunch at work."

"Employers must still maintain their offices and incur all of the fixed expenses involved, including basic utilities, taxes and insurance," Krupp said. "The cost savings (for employers) that are realized are also offset by increased costs of creating and maintaining IT networks that allow employees to access their work sites from home and the costs of monitoring and managing the work force."

Kiki Nichols Nugent of Cheshire said she was against the idea of an employee trying to get their employer to pay for the increased electricity costs associated with working from home.

"I would not nickle and dime," Nugent said. "If companies are saving on electricity now, maybe employers will give better raises next year."

New Haven resident Chris Smith said he is "just happy to have a job where I am able to telecommute."

"When teleworking becomes more the norm, either now or in the future, we may see increased wages for teleworkers either for the lower cost to the employer or for the increase in productivity it brings," Smith said.

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Clean Power Plan Rollback signals EPA's shift to inside-the-fence efficiency at coal plants, emphasizing heat-rate improvements over sector-wide decarbonization, renewables, natural gas switching, demand-side efficiency, and carbon capture under Clean Air Act constraints.

Key Points

A policy shift by the EPA to replace broad emissions rules with plant-level efficiency standards, limiting CO2 cuts.

✅ Inside-the-fence heat-rate improvements at coal units

✅ Potential CO2 cuts limited to about 6% per plant

✅ Alternatives: fuel switching, renewables, carbon capture

President Barack Obama’s signature plan to reduce carbon dioxide emissions from electrical generation took years to develop and touched every aspect of power production and use, from smokestacks to home insulation.

The Trump administration is moving to scrap that plan and has signaled that any alternative it might adopt would take a much less expansive approach, possibly just telling utilities to operate their plants more efficiently.

That’s a strategy environmentalists say is almost certain to fall short of what’s needed.

The Trump administration is making "a wholesale retreat from EPA’s legal, scientific and moral obligation to address the threats of climate change," said former Environmental Protection Agency head Gina McCarthy, the architect of Obama’s Clean Power Plan.

President Donald Trump promised to rip up the initiative, echoing an end to the 'war on coal' message from his campaign, which mandated that states change their overall power mix, displacing coal-fired electricity with that from wind, solar and natural gas. The EPA is about to make it official, arguing the prior administration violated the Clean Air Act by requiring those broad changes to the electricity sector, according to a draft obtained by Bloomberg.

Possible Replacements

Later, the agency will also ask the public to weigh in on possible replacements. The administration will ask whether the EPA can or should develop a replacement rule -- and, if so, what actions can be mandated at individual power plants, though some policymakers favor a clean electricity standard to drive broader decarbonization.

Follow the Trump Administration’s Every Move

Such changes -- such as adding automation or replacing worn turbine seals -- would yield at most a 6 percent gain in efficiency, along with a corresponding fall in greenhouse gas emissions, according to earlier modeling by the Environmental Protection Agency and other analysts. That compares to the 32 percent drop in emissions by 2030 under Obama’s Clean Power Plan.

"In these existing plants, there’s only so many places to look for savings," said John Larsen, a director of the Rhodium Group, a research firm. "There’s only so many opportunities within a big spinning machine like that."

EPA Administrator Scott Pruitt outlined such an "inside-the-fence-line" approach in 2014, later embodied in the Affordable Clean Energy rule that industry groups backed, when he served as Oklahoma’s attorney general. Under his blueprint, states would set emissions standards after a detailed unit-by-unit analysis, looking at what reductions are possible given "the engineering limits of each facility."

The EPA has not decided whether it will promulgate a new rule at all, though it has also proposed new pollution limits for coal and gas plants in separate actions. In a forthcoming advanced notice of proposed rulemaking, the EPA will ask "what inside-the-fence-line options are legal, feasible and appropriate," according to a document obtained by Bloomberg.

Increased efficiency at a coal plant -- known as heat-rate improvement -- translates into fewer carbon-dioxide emissions per unit of electric power generated.

Under Obama, the EPA envisioned utilities would make some straightforward efficiency improvements at coal-fired power plants as the first step to comply with the Clean Power Plan. But that was expected to coincide with bigger, broader changes -- such as using more cleaner-burning natural gas, adding more renewable power projects and simply encouraging customers to do a better job turning down their thermostats and turning off their lights.

Obama’s EPA didn’t ask utilities to wring every ounce of efficiency they could out of coal-fired power plants because they saw the other options as cheaper. A plant-specific approach "would be grossly insufficient to address the public health and environmental impacts from CO2 emissions," Obama’s EPA said.

That approach might yield modest emissions reductions and, in a perverse twist, might event have the opposite effect. If utilities make coal plants more efficient -- thereby driving down operating costs -- they also make them more competitive with natural gas and renewables, "so they might run more and pollute more," said Conrad Schneider, advocacy director for the Clean Air Task Force.  

In a competitive market, any improvement in emissions produced for each unit of energy could be overwhelmed by an increase in electrical output, and debates over changes to electricity pricing under Trump and Perry added further uncertainty.

"A very minor heat rate improvement program would very likely result in increased emissions," Schneider said. "It might be worse than nothing."

Power companies want to get as much electricity as possible from every pound of coal, so they already have an incentive to keep efficiency high, said Jeff Holmstead, a former assistant EPA administrator now at Bracewell LLP. But an EPA regulation known as “new source review” has discouraged some from making those changes, for fear of triggering other pollution-control requirements, he said.

"If EPA’s replacement rule allows companies to improve efficiency without triggering new source review, it would make a real difference in terms of reducing carbon-dioxide emissions," Holmstead said.

Modest Impact

A plant-specific approach doesn’t have to mean modest impact.

"If you’re thinking about what can be done at the power plants by themselves, you don’t stop at efficiency tune-ups," said David Doniger, director of the Natural Resources Defense Council’s climate and clean air program. "You look at things like switching to natural gas or installing carbon capture and storage."

Requirements that facilities use carbon capture technology or swap in natural gas for coal could actually come close to hitting the same goals as in Obama’s Clean Power Plan -- if not go even further, Schneider said. They just would cost more.

The benefit of the Clean Power Plan "is that it enabled states to create programs and enabled companies to find a reduction strategy that was the most efficient and made the most sense for their own content," said Kathryn Zyla, deputy director of the Georgetown Climate Center. "And that flexibility was really important for the states and companies."

Some utilities, including Houston-based Calpine Corp., PG&E Corp. and Dominion Resources Inc., backed the Obama-era approach. And they are still pushing the Trump administration to be creative now.

"The Clean Power Plan achieved a thoughtful, balanced approach that gave companies and states considerable flexibility on how best to pursue that goal," said Melissa Lavinson, vice president of federal affairs and policy for PG&E’s Pacific Gas and Electric utility. “We look forward to working with the administration to devise an alternative plan for decarbonizing the U.S. economy."

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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.”

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Hourly Electricity Emissions Tracking maps grid balancing areas, embodied emissions, and imports/exports, revealing carbon intensity shifts across PJM, ERCOT, and California ISO, and clarifying renewable energy versus coal impacts on health and climate.

Key Points

An hourly method tracing generation, flows, and embodied emissions to quantify carbon intensity across US balancing areas.

✅ Hourly traces of imports/exports and generation mix

✅ Consumption-based carbon intensity by balancing area

✅ Policy insights for renewables, coal, health costs

In the United States, electricity generation accounts for nearly 30% of our carbon emissions. Some states have responded to that by setting aggressive renewable energy standards; others are hoping to see coal propped up even as its economics get worse. Complicating matters further is the fact that many regional grids are integrated, and as America goes electric the stakes grow, meaning power generated in one location may be exported and used in a different state entirely.

Tracking these electricity exports is critical for understanding how to lower our national carbon emissions. In addition, power from a dirty source like coal has health and environment impacts where it's produced, and the costs of these aren't always paid by the parties using the electricity. Unfortunately, getting reliable figures on how electricity is produced and where it's used is challenging, even for consumers trying to find where their electricity comes from in the first place, leaving some of the best estimates with a time resolution of only a month.

Now, three Stanford researchers—Jacques A. de Chalendar, John Taggart, and Sally M. Benson—have greatly improved on that standard, and they have managed to track power generation and use on an hourly basis. The researchers found that, of the 66 grid balancing areas within the United States, only three have carbon emissions equivalent to our national average, and they have found that imports and exports of electricity have both seasonal and daily changes. de Chalendar et al. discovered that the net results can be substantial, with imported electricity increasing California's emissions/power by 20%.

Hour by hour
To figure out the US energy trading landscape, the researchers obtained 2016 data for grid features called balancing areas. The continental US has 66 of these, providing much better spatial resolution on the data than the larger grid subdivisions. This doesn't cover everything—several balancing areas in Canada and Mexico are tied in to the US grid—and some of these balancing areas are much larger than others. The PJM grid, serving Pennsylvania, New Jersey, and Maryland, for example, is more than twice as large as Texas' ERCOT, in a state that produces and consumes the most electricity in the US.

Despite these limitations, it's possible to get hourly figures on how much electricity was generated, what was used to produce it, and whether it was used locally or exported to another balancing area. Information on the generating sources allowed the researchers to attach an emissions figure to each unit of electricity produced. Coal, for example, produces double the emissions of natural gas, which in turn produces more than an order of magnitude more carbon dioxide than the manufacturing of solar, wind, or hydro facilities. These figures were turned into what the authors call "embodied emissions" that can be traced to where they're eventually used.

Similar figures were also generated for sulfur dioxide and nitrogen oxides. Released by the burning of fossil fuels, these can both influence the global climate and produce local health problems.

Huge variation
The results were striking. "The consumption-based carbon intensity of electricity varies by almost an order of magnitude across the different regions in the US electricity system," the authors conclude. The low is the Bonneville Power grid region, which is largely supplied by hydropower; it has typical emissions below 100kg of carbon dioxide per megawatt-hour. The highest emissions come in the Ohio Valley Electric region, where emissions clear 900kg/MW-hr. Only three regional grids match the overall grid emissions intensity, although that includes the very large PJM (where capacity auction payouts recently fell), ERCOT, and Southern Co balancing areas.

Most of the low-emissions power that's exported comes from the Pacific Northwest's abundant hydropower, while the Rocky Mountains area exports electricity with the highest associated emissions. That leads to some striking asymmetries. Local generation in the hydro-rich Idaho Power Company has embodied emissions of only 71kg/MW-hr, while its imports, coming primarily from Rocky Mountain states, have a carbon content of 625kg/MW-hr.

The reliance on hydropower also makes the asymmetry seasonal. Local generation is highest in the spring as snow melts, but imports become a larger source outside this time of year. As solar and wind can also have pronounced seasonal shifts, similar changes will likely be seen as these become larger contributors to many of these regional grids. Similar things occur daily, as both demand and solar production (and, to a lesser extent, wind) have distinct daily profiles.

The Golden State
California's CISO provides another instructive case. Imports represent less than 30% of its total electric use in 2016, yet California electricity imports provided 40% of its embodied emissions. Some of these, however, come internally from California, provided by the Los Angeles Department of Water and Power. The state itself, however, has only had limited tracking of imported emissions, lumping many of its sources as "other," and has been exporting its energy policies to Western states in ways that shape regional markets.

Overall, the 2016 inventory provides a narrow picture of the US grid, as plenty of trends are rapidly changing our country's emissions profile, including the rise of renewables and the widespread adoption of efficiency measures and other utility trends in 2017 that continue to evolve. The method developed here can, however, allow for annual updates, providing us with a much better picture of trends. That could be quite valuable to track things like how the rapid rise in solar power is altering the daily production of clean power.

More significantly, it provides a basis for more informed policymaking. States that wish to promote low-emissions power can use the information here to either alter the source of their imports or to encourage the sites where they're produced to adopt more renewable power. And those states that are exporting electricity produced primarily through fossil fuels could ensure that the locations where the power is used pay a price that includes the health costs of its production.

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