New regulations could cost coal plant $2.8B

Powering Ontario's Growth accelerates clean electricity, pairing solar, wind, and hydro with energy storage, efficiency investments, and new nuclear, including SMRs, to meet rising demand and net-zero goals while addressing supply planning across the province.

Key Points

Ontario's clean energy plan adds renewables, storage, efficiency, and nuclear to meet rising electricity demand.

✅ Over $1B for energy-efficiency programs through 2030+

✅ Largest clean power procurement in Canadian history

✅ Mix of solar, wind, hydro, storage, nuclear, and SMRs

Energy Minister Todd Smith has announced a new plan that outlines the actions the government is taking to address the province's growing demand for electricity.

The government is investing over a billion dollars in "energy-efficiency programs" through 2030 and beyond, Smith said in Windsor.

Experts at Ontario's Independent Electricity System recommended the planning start early to meet demand they predict will require the province to be able to generate 88,000 megawatts (MW) in 20 years.

"That means all of our current supply ... would need to double to meet the anticipated demand by 2050," he said during the announcement.

"While we may not need to start building today, government and those in the energy sector need to start planning immediately, so we have new clean, zero emissions projects ready to go when we need them."

The project is called Powering Ontario's Growth and will advance new clean energy generation from a number of sources, including solar, hydroelectric and wind.

He said this would be the biggest acquisition of clean energy in Canada's history.

Smith made the announcement at Hydro One's Keith Transmission Station.

He said the new planned procurement of green power will pair well with recent energy storage procurements, so that power generated by solar panels, for example, can be stored and injected into the system when needed.

NDP Opposition Leader Marit Stiles said Monday's announcement lacks specifics.

"It's light on details, including key questions of cost, climate impact, waste management and financial risk," said Stiles.

"Ford's Conservatives should be playing catch-up after undermining clean energy in their first term. Instead, they're offering generalities and a vague sense of what they might do."

The Green Party criticized the move Monday afternoon, noting that clean, affordable electricity remains a key Ontario election issue today.

"Ontario is facing an energy crunch – and the Ford government is making it worse by choosing more expensive, dirtier options," said MPP for Guelph Mike Schreiner in the statement.

He said Premier Doug Ford has "grossly" mismanaged the province's energy supply by cancelling 750 renewable energy projects and slashing efficiency programs.

"Now, faced with an opportunity to become a leader in a world that's rapidly embracing renewable energy, this government has chosen to funnel taxpayer dollars into polluting fossil gas plants and expensive new nuclear that will take decades to come online," said Schreiner.

Smith announced last week the plan for three more small modular reactors at the site of the Darlington nuclear power plant. The province also shared its intention to add a third nuclear generating station to Bruce Power near Kincardine. 

"With this backwards approach, the Ford government is squandering a once-in-a-generation opportunity to make Ontario a global leader in attracting investment dollars and creating better jobs in the trillion-dollar clean energy sector," said Schreiner.

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Quinone-mediated fuel cell uses a bio-inspired organic shuttle to carry electrons and protons to a nearby cobalt catalyst, improving hydrogen conversion, cutting platinum dependence, and raising efficiency while lowering costs for clean electricity.

Key Points

An affordable, bio-inspired fuel cell using an organic quinone shuttle and cobalt catalyst to move electrons efficiently

✅ Organic quinone shuttles electrons to a separate cobalt catalyst

✅ Reduces platinum use, lowering cost of hydrogen power

✅ Bio-inspired design aims to boost efficiency and durability

Fuel cells have long been viewed as a promising power source. But most fuel cells are too expensive, inefficient, or both. In a new approach, inspired by biology, a team has designed a fuel cell using cheaper materials and an organic compound that shuttles electrons and protons.

Fuel cells have long been viewed as a promising power source. These devices, invented in the 1830s, generate electricity directly from chemicals, such as hydrogen and oxygen, and produce only water vapor as emissions. But most fuel cells are too expensive, inefficient, or both.

In a new approach, inspired by biology and published today (Oct. 3, 2018) in the journal Joule, a University of Wisconsin-Madison team has designed a fuel cell using cheaper materials and an organic compound that shuttles electrons and protons.

In a traditional fuel cell, the electrons and protons from hydrogen are transported from one electrode to another, where they combine with oxygen to produce water. This process converts chemical energy into electricity. To generate a meaningful amount of charge in a short enough amount of time, a catalyst is needed to accelerate the reactions.

Right now, the best catalyst on the market is platinum -- but it comes with a high price tag, and while advances like low-cost heat-to-electric materials show promise, they address different conversion pathways. This makes fuel cells expensive and is one reason why there are only a few thousand vehicles running on hydrogen fuel currently on U.S. roads.

Shannon Stahl, the UW-Madison professor of chemistry who led the study in collaboration with Thatcher Root, a professor of chemical and biological engineering, says less expensive metals can be used as catalysts in current fuel cells, but only if used in large quantities. "The problem is, when you attach too much of a catalyst to an electrode, the material becomes less effective," he says, "leading to a loss of energy efficiency."

The team's solution was to pack a lower-cost metal, cobalt, into a reactor nearby, where the larger quantity of material doesn't interfere with its performance. The team then devised a strategy to shuttle electrons and protons back and forth from this reactor to the fuel cell.

The right vehicle for this transport proved to be an organic compound, called a quinone, that can carry two electrons and protons at a time. In the team's design, a quinone picks up these particles at the fuel cell electrode, transports them to the nearby reactor filled with an inexpensive cobalt catalyst, and then returns to the fuel cell to pick up more "passengers."

Many quinones degrade into a tar-like substance after only a few round trips. Stahl's lab, however, designed an ultra-stable quinone derivative. By modifying its structure, the team drastically slowed down the deterioration of the quinone. In fact, the compounds they assembled last up to 5,000 hours -- a more than 100-fold increase in lifetime compared to previous quinone structures.

"While it isn't the final solution, our concept introduces a new approach to address the problems in this field," says Stahl. He notes that the energy output of his new design produces about 20 percent of what is possible in hydrogen fuel cells currently on the market. On the other hand, the system is about 100 times more effective than biofuel cells that use related organic shuttles.

The next step for Stahl and his team is to bump up the performance of the quinone mediators, allowing them to shuttle electrons more effectively and produce more power. This advance would allow their design to match the performance of conventional fuel cells, but with a lower price tag.

"The ultimate goal for this project is to give industry carbon-free options for creating electricity, including thermoelectric materials that harvest waste heat," says Colin Anson, a postdoctoral researcher in the Stahl lab and publication co-author. "The objective is to find out what industry needs and create a fuel cell that fills that hole."

This step in the development of a cheaper alternative could eventually be a boon for companies like Amazon and Home Depot that already use hydrogen fuel cells to drive forklifts in their warehouses.

"In spite of major obstacles, the hydrogen economy, with efforts such as storing electricity in pipelines in Europe, seems to be growing," adds Stahl, "one step at a time."

Financial support for this project was provided by the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, and by the Wisconsin Alumni Research Foundation (WARF) through the WARF Accelerator Program.

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Electricity Market Competition drives lower wholesale prices, stable retail rates, better grid reliability, and faster emissions cuts as deregulation and renewables adoption pressure utilities, improve efficiency, and enhance consumer choice in power markets.

Key Points

Electricity market competition opens supply to rivals, lowering prices, improving reliability, and reducing emissions.

✅ Wholesale prices fell faster in competitive markets

✅ Retail rates rose less than in monopoly states

✅ Fewer outages, shorter durations, improved reliability

By Bernard L. Weinstein

Electricity used to be boring.  Public utilities that provided power to homes and businesses were regulated monopolies and, by law, guaranteed a fixed rate-of-return on their generation, transmission, and distribution assets. Prices per kilowatt-hour were set by utility commissions after lengthy testimony from power companies, wanting higher rates, and consumer groups, wanting lower rates.

About 25 years ago, the electricity landscape started to change as economists and others argued that competition could lead to lower prices and stronger grid reliability. Opponents of competition argued that consumers weren’t knowledgeable enough about power markets to make intelligent choices in a competitive pricing environment. Nonetheless, today 20 states have total or partial competition for electricity, allowing independent power generators to compete in wholesale markets and retail electric providers (REPs) to compete for end-use customers, a dynamic echoed by the Alberta electricity market across North America. (Transmission, in all states, remains a regulated natural monopoly).

A recent study by the non-partisan Pacific Research Institute (PRI) provides compelling evidence that competition in power markets has been a boon for consumers. Using data from the U.S. Energy Information Administration (EIA), PRI’s researchers found that wholesale electricity prices in competitive markets have been generally declining or flat, prompting discussions of free electricity business models, over the last five years. For example, compared to 2015, wholesale power prices in New England have dropped more than 44 percent, those in most Mid-Atlantic States have fallen nearly 42 percent, and in New York City they’ve declined by nearly 45 percent. Wholesale power costs have also declined in monopoly states, but at a considerably slower rate.

As for end-users, states that have competitive retail electricity markets have seen smaller price increases, as consumers can shop for electricity in Texas more cheaply than in monopoly states. Again, using EIA data, PRI found that in 14 competitive jurisdictions, retail prices essentially remained flat between 2008 and 2020. By contrast, retail prices jumped an average of 21 percent in monopoly states.  The ten states with the largest retail price increases were all monopoly-based frameworks. A 2017 report from the Retail Energy Supply Association found customers in states that still have monopoly utilities saw their average energy prices increase nearly 19 percent from 2008 to 2017 while prices fell 7 percent in competitive markets over the same period.

The PRI study also observed that competition has improved grid reliability, the recent power disruptions in California and Texas, alongside disruptions in coal and nuclear sectors across the U.S., notwithstanding. Looking at two common measures of grid resiliency, PRI’s analysis found that power interruptions were 10.4 percent lower in competitive states while the duration of outages was 6.5 percent lower.

Citing data from the EIA between 2008 and 2018, PRI reports that greenhouse gas emissions in competitive states declined on average 12.1 percent compared to 7.3 percent in monopoly states. This result is not surprising, and debates over whether Israeli power supply competition can bring cheaper electricity mirror these dynamics.  In a competitive wholesale market, independent power producers have an incentive to seek out lower-cost options, including subsidized renewables like wind and solar. By contrast, generators in monopoly markets have no such incentive as they can pass on higher costs to end-users. Perhaps the most telling case is in the monopoly state of Georgia where the cost to build nuclear Plant Vogtle has doubled from its original estimate of $14 billion 12 years ago. Overruns are estimated to cost Georgia ratepayers an average of $854, and there is no definite date for this facility to come on line. This type of mismanagement doesn’t occur in competitive markets.

Unfortunately, some critics are attempting to halt the momentum for electricity competition and have pointed to last winter’s “deep freeze” in Texas that left several million customers without power for up to a week. But this example is misplaced. Power outages in February were the result of unprecedented and severe weather conditions affecting electricity generation and fuel supply, and numerous proposals to improve Texas grid reliability have focused on weatherization and fuel resilience; the state simply did not have enough access to natural gas and wind generation to meet demand. Competitive power markets were not a factor.

The benefits of wholesale and retail competition in power markets are incontrovertible. Evidence shows that households and businesses in competitive states are paying less for electricity while grid reliability has improved. The facts also suggest that wholesale and retail competition can lead to faster reductions in greenhouse gas emissions. In short, competition in power markets is good for consumers and good for the environment.

Bernard L. Weinstein is emeritus professor of applied economics at the University of North Texas, former associate director of the Maguire Energy Institute at Southern Methodist University, and a fellow of Goodenough College, London. He wrote this for InsideSources.com.

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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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UK Energy Networks Coronavirus Contingency outlines ESO's lockdown electricity demand forecast, reduced industrial and commercial load, rising domestic use, Ofgem guidance needs, grid resilience, control rooms, mutual aid, and backup centers.

Key Points

A coordinated plan with ESO forecasts, safeguards, and mutual aid to keep power and gas services during a lockdown.

✅ ESO forecasts lower industrial use, higher domestic demand

✅ Control rooms protected; backup sites and cross-trained staff

✅ Mutual aid and Ofgem coordination bolster grid resilience

National Grid ESO is predicting a reduction in electricity demand, consistent with residential use trends observed during the pandemic, in the case of the coronavirus spread prompting a lockdown across the country.

Its analysis shows the reduction in commercial and industrial use would outweigh an upsurge in domestic demand, mirroring Ontario demand data seen as people stayed home, according to similar analyses.

The prediction was included in an update from the Energy Networks Association (ENA), in which it sought to reassure the public that contingency plans are in place, reflecting utility disaster planning across electric and gas networks, to ensure services are unaffected by the coronavirus spread.

The body, which represents the UK's electricity and gas network companies, said "robust measures" had been put in place to protect control rooms and contact centres, similar to staff lockdown protocols considered by other system operators, to maintain resilience. To provide additional resilience, engineers have been trained across multiple disciplines and backup centres exist should operations need to be moved if, for example, deep cleaning is required, the ENA said.

Networks also have industry-wide mutual aid arrangements, similar to grid response measures outlined in the U.S., for people and the equipment needed to keep gas and electricity flowing.

ENA chief executive, David Smith, said, echoing system reliability assurances from other markets: "The UK's electricity and gas network is one of the most reliable in the world and network operators are working with the authorities to ensure that their contingency plans are reviewed and delivered in accordance with the latest expert advice. We are following this advice closely and reassuring customers that energy networks are continuing to operate as normal for the public."

Utility Week spoke to a senior figure at one of the networks who reiterated the robust measures in place to keep the lights on, even as grid alerts elsewhere highlight the importance of contingency planning. However, they pleaded for more clarity from Ofgem and government on how its workers will be treated if the coronavirus spread becomes a pandemic in the UK.

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EU Nuclear Reactor Life Extension focuses on energy security, carbon-free electricity, and safety as ageing reactors face gas shortages, high power prices, and regulatory approvals across the UK and EU amid winter supply risks.

Key Points

EU Nuclear Reactor Life Extension is the policy to keep ageing reactors safely generating affordable, low-carbon power.

✅ Extends reactor operation via inspections and component upgrades

✅ Addresses gas shortages, price volatility, and winter supply risks

✅ Requires national regulator approval and cost-benefit analysis

Shaken by the loss of Russian natural gas since the invasion of Ukraine, European countries are questioning whether they can extend the lives of their ageing nuclear reactors to maintain the supply of affordable, carbon-free electricity needed for net-zero across the bloc — but national regulators, companies and governments disagree on how long the atomic plants can be safely kept running.

Europe avoided large-scale blackouts last winter despite losing its largest supplier of natural gas, and as Germany temporarily extended nuclear operations to bolster stability, but industry is still grappling with high electricity prices and concerns about supply.

Given warnings from the International Energy Agency that the coming winters will be particularly at risk from a global gas shortage, governments have turned their attention to another major energy source — even as some officials argue nuclear would do little to solve the gas issue in the near term — that would exacerbate the problem if it too is disrupted: Europe’s ageing fleet of nuclear power plants.

Nuclear accounts for nearly 10% of energy consumed in the European Union, with transport, industry, heating and cooling traditionally relying on coal, oil and natural gas.

Historically nuclear has provided about a quarter of EU electricity and 15% of British power, even as Germany shut down its last three nuclear plants recently, underscoring diverging national paths.

Taken together, the UK and EU have 109 nuclear reactors running, even as Europe is losing nuclear power in several markets, most of which were built in the 1970s and 1980s and were commissioned to last about 30 years.

That means 95 of those reactors — nearly 90% of the fleet — have passed or are nearing the end of their original lifespan, igniting debates over how long they can safely continue to be granted operating extensions, with some arguing it remains a needed nuclear option for climate goals despite age-related concerns.

Regulations differ across borders, with some countries such as Germany turning its back on nuclear despite an ongoing energy crisis, but life extension discussions are usually a once-a-decade affair involving physical inspections, cost/benefit estimates for replacing major worn-out parts, legislative amendments, and approval from the national nuclear safety authority.

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