South Carolina nuke plant back at full power

Ontario Nuclear Power Costs highlight LCOE, capex, refurbishment outlays, and waste management, compared with renewables, grid reliability, and emissions targets, informing Australia and Peter Dutton on feasibility, timelines, and electricity prices.

Key Points

They include high capex and LCOE from refurbishments and waste, offset by reliable, low-emission baseload.

✅ Refurbishment and maintenance drive lifecycle and LCOE variability.

✅ High capex and long timelines affect consumer electricity prices.

✅ Low emissions, but waste and safety compliance add costs.

Australian opposition leader Peter Dutton recently lauded Canada’s use of nuclear power as a model for Australia’s energy future. His praise comes as part of a broader push to incorporate nuclear energy into Australia’s energy strategy, which he argues could help address the country's energy needs and climate goals. However, the question arises: Is Ontario’s experience with nuclear power as cost-effective as Dutton suggests?

Dutton’s endorsement of Canada’s nuclear power strategy highlights a belief that nuclear energy could provide a stable, low-emission alternative to fossil fuels. He has pointed to Ontario’s substantial reliance on nuclear power, and the province’s exploration of new large-scale nuclear projects, as an example of how such an energy mix might benefit Australia. The province’s energy grid, which integrates a significant amount of nuclear power, is often cited as evidence that nuclear energy can be a viable component of a diversified energy portfolio.

The appeal of nuclear power lies in its ability to generate large amounts of electricity with minimal greenhouse gas emissions. This characteristic aligns with Australia’s climate goals, which emphasize reducing carbon emissions to combat climate change. Dutton’s advocacy for nuclear energy is based on the premise that it can offer a reliable and low-emission option compared to the fluctuating availability of renewable sources like wind and solar.

However, while Dutton’s enthusiasm for the Canadian model reflects its perceived successes, including recent concerns about Ontario’s grid getting dirtier amid supply changes, a closer look at Ontario’s nuclear energy costs raises questions about the financial feasibility of adopting a similar strategy in Australia. Despite the benefits of low emissions, the economic aspects of nuclear power remain complex and multifaceted.

In Ontario, the cost of nuclear power has been a topic of considerable debate. While the province benefits from a stable supply of electricity due to its nuclear plants, studies warn of a growing electricity supply gap in coming years. Ontario’s experience reveals that nuclear power involves significant capital expenditures, including the costs of building reactors, maintaining infrastructure, and ensuring safety standards. These expenses can be substantial and often translate into higher electricity prices for consumers.

The cost of maintaining existing nuclear reactors in Ontario has been a particular concern. Many of these reactors are aging and require costly upgrades and maintenance to continue operating safely and efficiently. These expenses can add to the overall cost of nuclear power, impacting the affordability of electricity for consumers.

Moreover, the development of new nuclear projects, as seen with Bruce C project exploration in Ontario, involves lengthy and expensive construction processes. Building new reactors can take over a decade and requires significant investment. The high initial costs associated with these projects can be a barrier to their economic viability, especially when compared to the rapidly decreasing costs of renewable energy technologies.

In contrast, the cost of renewable energy has been falling steadily, even as debates over nuclear power’s trajectory in Europe continue, making it a more attractive option for many jurisdictions. Solar and wind power, while variable and dependent on weather conditions, have seen dramatic reductions in installation and operational costs. These lower costs can make renewables more competitive compared to nuclear energy, particularly when considering the long-term financial implications.

Dutton’s praise for Ontario’s nuclear power model also overlooks some of the environmental and logistical challenges associated with nuclear energy. While nuclear power generates low emissions during operation, it produces radioactive waste that requires long-term storage solutions. The management of nuclear waste poses significant environmental and safety concerns, as well as additional costs for safe storage and disposal.

Additionally, the potential risks associated with nuclear power, including the possibility of accidents, contribute to the complexity of its adoption. The safety and environmental regulations surrounding nuclear energy are stringent and require continuous oversight, adding to the overall cost of maintaining nuclear facilities.

As Australia contemplates integrating nuclear power into its energy mix, it is crucial to weigh these financial and environmental considerations. While the Canadian model provides valuable insights, the unique context of Australia’s energy landscape, including its existing infrastructure, energy needs, and the costs of scrapping coal-fired electricity in comparable jurisdictions, must be taken into account.

In summary, while Peter Dutton’s endorsement of Canada’s nuclear power model reflects a belief in its potential benefits for Australia’s energy strategy, the cost-effectiveness of Ontario’s nuclear power experience is more nuanced than it may appear. The high capital and maintenance costs associated with nuclear energy, combined with the challenges of managing radioactive waste and ensuring safety, present significant considerations. As Australia evaluates its energy future, a comprehensive analysis of both the benefits and drawbacks of nuclear power will be essential to making informed decisions about its role in the country’s energy strategy.

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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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Washington State Hybrid-Electric Ferries advance green maritime transit with battery-diesel propulsion, lower emissions, and fleet modernization, integrating charging infrastructure and reliable operations across WSF routes to meet climate goals and reduce fuel consumption.

Key Points

New WSF vessels using diesel-battery propulsion to cut emissions, improve efficiency, and sustain reliable ferry service.

✅ Hybrid diesel-battery propulsion reduces fuel use and CO2

✅ Larger vessels with efficient batteries and charging upgrades

✅ Compatible with WSF docks, maintenance, and safety standards

Washington State is embarking on an ambitious update to its ferry fleet, introducing hybrid-electric boats that represent a significant leap toward greener and more sustainable transportation. The state’s updated plans reflect a commitment to reducing carbon emissions and enhancing environmental stewardship while maintaining the efficiency and reliability of its vital ferry services.

The Washington State Ferries (WSF) system, one of the largest in the world, has long been a critical component of the state’s transportation network, linking various islands and coastal communities with the mainland. Traditionally powered by diesel engines, the ferries are responsible for significant greenhouse gas emissions. In response to growing environmental concerns and legislative pressure, WSF is now turning to hybrid-electric technology similar to battery-electric high-speed ferries seen elsewhere to modernize its fleet and reduce its carbon footprint.

The updated plans for the hybrid-electric boats build on earlier efforts to introduce cleaner technologies into the ferry system. The new designs incorporate advanced hybrid-electric propulsion systems that combine traditional diesel engines with electric batteries. This hybrid approach allows the ferries to operate on electric power during certain segments of their routes, reducing reliance on diesel fuel and cutting emissions as electric ships on the B.C. coast have demonstrated during similar operations.

One of the key features of the updated plans is the inclusion of larger and more capable hybrid-electric ferries, echoing BC Ferries hybrid ships now entering service in the region. These vessels are designed to handle the demanding operational requirements of the Washington State Ferries system while significantly reducing environmental impact. The new boats will be equipped with state-of-the-art battery systems that can store and utilize electric power more efficiently, leading to improved fuel economy and lower overall emissions.

The transition to hybrid-electric ferries is driven by both environmental and economic considerations. On the environmental side, the move aligns with Washington State’s broader goals to combat climate change and reduce greenhouse gas emissions, including programs like electric vehicle rebate program that encourage cleaner travel across the state. The state has set ambitious targets for reducing carbon emissions across various sectors, and upgrading the ferry fleet is a crucial component of achieving these goals.

From an economic perspective, hybrid-electric ferries offer the potential for long-term cost savings. Although the initial investment in new technology can be substantial, with financing models like CIB support for B.C. electric ferries helping spur adoption and reduce barriers for agencies, the reduced fuel consumption and lower maintenance costs associated with hybrid-electric systems are expected to lead to significant savings over the lifespan of the vessels. Additionally, the introduction of greener technology aligns with public expectations for more sustainable transportation options.

The updated plans also emphasize the importance of integrating hybrid-electric technology with existing infrastructure. Washington State Ferries is working to ensure that the new vessels are compatible with current docking facilities and maintenance practices. This involves updating docking systems, as seen with Kootenay Lake electric-ready ferry preparations, to accommodate the specific needs of hybrid-electric ferries and training personnel to handle the new technology.

Public response to the hybrid-electric ferry initiative has been largely positive, with many residents and environmental advocates expressing support for the move towards greener transportation. The new boats are seen as a tangible step toward reducing the environmental impact of one of the state’s most iconic transportation services. The project also highlights Washington State’s commitment to innovation and leadership in sustainable transportation, alongside global examples like Berlin's electric flying ferry that push the envelope in maritime transit.

However, the transition to hybrid-electric ferries is not without its challenges. Implementing new technology requires careful planning and coordination, including addressing potential technical issues and ensuring that the vessels meet all safety and operational standards. Additionally, there may be logistical challenges associated with integrating the new ferries into the existing fleet and managing the transition without disrupting service.

Despite these challenges, the updated plans for hybrid-electric boats represent a significant advancement in Washington State’s efforts to modernize its transportation system. The initiative reflects a growing trend among transportation agencies to embrace sustainable technologies and address the environmental impact of traditional transportation methods.

In summary, Washington State’s updated plans for hybrid-electric ferries mark a crucial step towards a more sustainable and environmentally friendly transportation network. By incorporating advanced hybrid-electric technology, the state aims to reduce carbon emissions, improve fuel efficiency, and align with its broader climate goals. While challenges remain, the initiative demonstrates a commitment to innovation and underscores the importance of transitioning to greener technologies in the quest for a more sustainable future.

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Global Renewable LCOE Trends reveal offshore wind costs down 32%, with 10MW turbines, lower CAPEX and OPEX, and parity for solar PV and onshore wind in Europe, China, and California, per BloombergNEF analysis.

Key Points

Benchmarks showing falling LCOE for offshore wind, onshore wind, and solar PV, driven by larger turbines and lower CAPEX

✅ Offshore wind LCOE $78/MWh; $53-64/MWh in DK/NL excl. transmission

✅ Onshore wind $47/MWh; solar PV $51/MWh, best $26-36/MWh

✅ Cost drivers: 10MW turbines, lower CAPEX/OPEX, weak China demand

World offshore wind costs have fallen 32% from just a year ago and 12% compared with the first half of 2019, according to a BNEF long-term outlook from BloombergNEF.

In its latest Levelized Cost of Electricity (LCOE) Update, BloombergNEF said its current global benchmark LCOE estimate for offshore wind is $78 a megawatt-hour.

“New offshore wind projects throughout Europe, including the UK's build-out, now deploy turbines with power ratings up to 10MW, unlocking CAPEX and OPEX savings,” BloombergNEF said.

In Denmark and the Netherlands, it expects the most recent projects financed to achieve $53-64/MWh excluding transmission.

New solar and onshore wind projects have reached parity with average wholesale power prices in California and parts of Europe, while in China levelised costs are below the benchmark average regulated coal price, according to BloombergNEF.

The company's global benchmark levelized cost figures for onshore wind and PV projects financed in the last six months are at $47 and $51 a megawatt-hours, underscoring that renewables are now the cheapest new electricity option in many regions, down 6% and 11% respectively compared with the first half of 2019.

BloombergNEF said for wind this is mainly down to a fall in the price of turbines – 7% lower on average globally compared with the end of 2018.

In China, the world’s largest solar market, the CAPEX of utility-scale PV plants has dropped 11% in the last six months, reaching $0.57m per MW.

“Weak demand for new plants in China has left developers and engineering, procurement and construction firms eager for business, and this has put pressure on CAPEX,” BloombergNEF said.

It added that estimates of the cheapest PV projects financed recently – in India, Chile and Australia – will be able to achieve an LCOE of $27-36/MWh, assuming competitive returns for their equity investors.

Best-in-class onshore wind farms in Brazil, India, Mexico and Texas can reach levelized costs as low as $26-31/MWh already, the research said.

Programs such as the World Bank wind program are helping developing countries accelerate wind deployment as costs continue to drop.

BloombergNEF associate in the energy economics team Tifenn Brandily said: “This is a three- stage process. In phase one, new solar and wind get cheaper than new gas and coal plants on a cost-of- energy basis.

“In phase two, renewables reach parity with power prices. In phase three, they become even cheaper than running existing thermal plants.

“Our analysis shows that phase one has now been reached for two-thirds of the global population.

“Phase two started with California, China and parts of Europe. We expect phase three to be reached on a global scale by 2030.

“As this all plays out, thermal power plants will increasingly be relegated to a balancing role, looking for opportunities to generate when the sun doesn’t shine or the wind doesn’t blow.”

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Hydro One Avista Takeover faces Washington UTC scrutiny as regulators deny approval; companies plan a reconsideration petition, citing acquisition terms, governance concerns, merger risks, EPS dilution, and balance sheet impacts across regulated utility operations.

Key Points

A $6.7B bid by Hydro One to buy Avista, denied by Washington UTC on governance risk, under reconsideration petition.

✅ UTC denied over potential provincial interference.

✅ Petition for reconsideration due by Dec. 17.

✅ Deal seen diluting EPS, weakening balance sheet.

Hydro One Ltd. and Avista Corp. say they plan to formally request that the Washington Utilities and Transportation Commission reconsider its order last week denying approval of the $6.7-billion takeover, which previously received U.S. antitrust clearance from federal regulators, of the U.S.-based energy utility.

The two companies say they will file a petition no later than Dec. 17 but haven't indicated on what grounds they are making the request, even as investor concerns about Hydro One persist.

Under Washington State law, the UTC has 20 days to consider the petition, otherwise it is deemed to be denied.

If it reconsiders its decision, the UTC can modify the prior order or take any actions it deems appropriate, similar to provincial rulings such as the OEB decision on Hydro One's first combined T&D rates, including extending deliberations.

Washington State regulators said they would not allow Ontario's largest utility to buy Avista for fear the provincial government, which owns 47 per cent of Hydro One's shares and recently prompted a CEO and board exit at the utility, might meddle in Avista's operations.

Hydro One's shares have risen since the order because the deal, announced in July 2017, would have eroded earnings per share and weakened Hydro One's balance sheet, according to analysts, even as the company reported a one-time-boosted Q2 profit earlier this year.

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Ontario Global Adjustment Appeal spotlights Ontario's electricity fee, regulatory charge vs tax debate, FIT contracts, green energy policy, and constitutional challenge as National Steel Car contests soaring power costs before the Ontario Superior Court.

Key Points

Court challenge over Ontario's global adjustment fee, disputing its status as a regulatory charge instead of a tax.

✅ Challenges classification of global adjustment as tax vs regulatory charge.

✅ Focuses on FIT contracts, renewable energy payments, power cost impacts.

✅ Appeals Ontario ruling; implications for ratepayers and policy.

A manufacturer of steel rail cars is pursuing an appeal after its lawsuit challenging the constitutionality of a major Ontario electricity fee was struck down earlier this year.

Lawyers for Hamilton, Ont.-based National Steel Car Ltd. filed a notice of appeal in July after Ontario Superior Court Justice Wendy Matheson ruled in June that an electricity fee known as the global adjustment charge was a regulatory charge, and not an unconstitutional tax used to finance policy goals, as National Steel Car alleges.

The company, the decision noted, began its legal crusade last year after seeing its electricity bills had “increased dramatically” since the Ontario government passed green energy legislation nearly a decade ago, and amid concerns that high electricity rates are hurting Ontario manufacturers.

Under that legislation, the judge wrote, “private suppliers of renewable energy were paid to ’feed in’ energy into Ontario’s electricity grid.” The contracts for these so-called “feed-in tariff” contracts, or FIT contracts, were the “primary focus” of the lawsuit.

“The applicant seeks a declaration that part of the amount it has paid for electricity is an unconstitutional tax rather than a valid regulatory charge,” the judge added. “More specifically, it challenges part of the Global Adjustment, which is a component of electricity pricing and incorporates obligations under FIT contracts.”

Chiefly representing the difference between Ontario’s market price for power and the guaranteed price owed to generators, global adjustment now makes up the bulk of the commodity cost of electricity in the province. The fee has risen over the past decade, amid calls to reject steep Nova Scotia rate hikes as well — costing electricity customers $37 billion in global adjustment from 2006 to 2014, according to the province’s auditor general — because of investments in the electricity grid and green-energy contracts, among other reasons.

National Steel Car argued the global adjustment is a tax, and an unconstitutional one at that because it violated a section of the Constitution Act requiring taxes to be authorized by the legislature. The company also said the imposition of the global adjustment broke an Ontario law requiring a referendum to be held for new taxes.

The province, Justice Matheson wrote, had argued “that it is plain and obvious that these applications will fail.” In a decision released in June, the judge granted motions to strike out National Steel Car’s applications.

“The Global Adjustment,” she added, “is not a tax because its purpose, in pith and substance, is not to tax, and it is a regulatory charge and therefore, again, not a tax.”

Now, National Steel Car is arguing that the judge erred in several ways, including in fact, “by finding that the FIT contracts must be paid, when they can be cancelled.”

There has been a change in government at Queen’s Park since National Steel Car first filed its lawsuit last year, and that change has put green energy contracts under fire. The Progressive Conservative government of new Premier Doug Ford has already made a number of decisions on the electricity file, such as moving to cancel and wind down more than 750 renewable energy contracts, as well as repealing the province’s Green Energy Act.

The Tories also struck a commission of inquiry into the province’s finances that warned the global adjustment “may be struck down as unconstitutional,” a warning delivered amid cases where Nova Scotia's regulator approved a 14% rate hike in a high-profile decision.

“There is a risk that a court may find the global adjustment is not a valid regulatory charge if shifting costs over a longer period of time inadvertently results in future ratepayers cross-subsidizing today’s ratepayers,” the commission’s report said.

A spokesperson for Ontario’s Ministry of Energy, Northern Development and Mines said in an email that it would be “inappropriate to comment about the specifics of any case before the courts or currently under arbitration.”

National Steel Car is also prepared to fight its case all the way up to the Supreme Court of Canada, according to its lawyer.

“What is clear from our proceeding with the appeal is National Steel Car has every intention of seeing that lawsuit through to its conclusion if this government isn’t interested or prepared to reasonably settle it,” Jerome Morse said.

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