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Canadian Softwood Lumber Tariffs challenge British Columbia's forestry sector, strain U.S.-Canada trade, and risk redirecting critical minerals and energy resources, threatening North American supply chains, manufacturing, and energy security across integrated markets.

Key Points

Duties imposed by the U.S. on Canadian lumber, affecting BC forestry, trade flows, and North American energy security.

✅ U.S. duties strain BC forestry and cross-border supply chains

✅ Risks redirecting critical minerals and energy exports

✅ Tariff rollback could bolster North American energy security

British Columbia Premier David Eby has raised concerns that U.S. tariffs on Canadian softwood lumber are prompting the province to redirect its critical minerals and energy resources, while B.C. challenges Alberta's electricity export restrictions domestically, away from the United States. In a recent interview, Eby emphasized the broader implications of these tariffs, suggesting they could undermine North American energy security and put electricity exports at risk across the border.

Since 2017, the U.S. Department of Commerce has imposed tariffs on Canadian softwood lumber imports, alleging that Canadian producers benefit from unfair subsidies. These duties have been a persistent source of tension between the two nations, coinciding with Canadian support for energy and mineral tariffs and significantly impacting British Columbia's forestry sector—a cornerstone of the province's economy.

Premier Eby highlighted that the financial strain imposed by these tariffs not only jeopardizes the Canadian forestry industry but also has unintended repercussions for the United States. He pointed out that the economic challenges faced by Canadian producers might lead them to seek alternative markets for their critical minerals and energy resources, as tariff threats boost support for Canadian energy projects domestically, thereby reducing the supply to the U.S. British Columbia is endowed with an abundance of critical minerals essential for various industries, including technology and defense.

The potential redirection of these resources could have significant consequences for American industries that depend on a stable and affordable supply of critical minerals and energy. Eby suggested that the tariffs might incentivize Canadian producers to explore other international markets, even as experts advise against cutting Quebec's energy exports amid the tariff dispute, diminishing the availability of these vital resources to the U.S.

In light of these concerns, Premier Eby has advocated for a reassessment of the tariffs, urging a more cooperative approach between Canada and the United States. He contends that eliminating the tariffs would be mutually beneficial, aligning with views that Biden is better for Canada's energy sector and cross-border collaboration, ensuring a consistent supply of critical resources and fostering economic growth in both countries.

The issue of U.S. tariffs on Canadian softwood lumber remains complex and contentious, with far-reaching implications for trade relations and resource distribution between the two nations. As discussions continue, stakeholders on both sides of the border are closely monitoring the situation, noting that Ford has threatened to cut U.S. electricity exports amid trade tensions, recognizing the importance of collaboration in addressing shared economic and security challenges.

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IESO Fictitious Demand Error inflated HOEP in the Ontario electricity market, after embedded generation was mis-modeled; the OEB says double-counted load lifted wholesale prices and shifted costs via the Global Adjustment.

Key Points

An IESO modeling flaw that double-counted load, inflating HOEP and charges in Ontario's wholesale market.

✅ Double-counted unmetered load from embedded generation

✅ Inflated HOEP; shifted costs via Global Adjustment

✅ OEB flagged transparency; exporters paid more

For almost a year, the operator of Ontario’s electricity system erroneously counted enough phantom demand to power a small city, causing prices to spike and hundreds of millions of dollars in extra charges to consumers, according to the provincial energy regulator.

The Independent Electricity System Operator (IESO) also failed to tell anyone about the error once it noticed and fixed it.

The error likely added between $450 million and $560 million to hourly rates and other charges before it was fixed in April 2017, according to a report released this month by the Ontario Energy Board’s Market Surveillance Panel.

It did this by adding as much as 220 MW of “fictitious demand” to the market starting in May 2016, when the IESO started paying consumers who reduced their demand for power during peak periods. This involved the integration of small-scale embedded generation (largely made up of solar) into its wholesale model for the first time.

The mistake assumed maximum consumption at such sites without meters, and double-counted that consumption.

The OEB said the mistake particularly hurt exporters and some end-users, who did not benefit from a related reduction of a global adjustment rate applicable to other customers.

“The most direct impact of the increase in HOEP (Hourly Ontario Energy Price) was felt by Ontario consumers and exporters of electricity, who paid an artificially high HOEP, to the benefit of generators and importers,” the OEB said.

The mix-up did not result in an equivalent increase in total system costs, because changes to the HOEP are offset by inverse changes to a electricity cost allocation mechanism such as the Global Adjustment rate, the OEB noted.

A chart from the OEB's report shows the time of day when fictitious demand was added to the system, and its influence on hourly rates.

Peak time spikes
The OEB said that the fictitious demand “regularly inflated” the hourly price of energy and other costs calculated as a direct function of it.

For almost a year, Ontario's electricity system operator @IESO_Tweets erroneously counted enough phantom demand to power a small city, causing price spikes and hundreds of millions in charges to consumers, @OntEnergyBoard says. @5thEstate reports.

It estimated the average increase to the HOEP was as much as $4.50/MWh, but that price spikes, compounded by scheduled OEB rate changes, would have been much higher during busier times, such as the mid-morning and early evening.

“In times of tight supply, the addition of fictitious demand often had a dramatic inflationary impact on the HOEP,” the report said.

That meant on one summer evening in 2016 the hourly rate jumped to $1,619/MWh, it said, which was the fourth highest in the history of the Ontario wholesale electricity market.

“Additional demand is met by scheduling increasingly expensive supply, thus increasing the market price. In instances where supply is tight and the supply stack is steep, small increases in demand can cause significant increases in the market price.

The OEB questioned why, as of September this year, the IESO had failed to notify its customers or the broader public, amid a broader auditor-regulator dispute that drew political attention, about the mistake and its effect on prices.

“It's time for greater transparency on where electricity costs are really coming from,” said Sarah Buchanan, clean energy program manager at Environmental Defence.

“Ontario will be making big decisions in the coming years about whether to keep our electricity grid clean, or burn more fossil fuels to keep the lights on,” she added. “These decisions need to be informed by the best possible evidence, and that can't happen if critical information is hidden.”

In a response to the OEB report on Monday, the IESO said its own initial analysis found that the error likely pushed wholesale electricity payments up by $225 million. That calculation assumed that the higher prices would have changed consumer behaviour, while upcoming electricity auctions were cited as a way to lower costs, it said.

In response to questions, a spokesperson said residential and small commercial consumers would have saved $11 million in electricity costs over the 11-month period, even as a typical bill increase loomed province-wide, while larger consumers would have paid an extra $14 million.

That is because residential and small commercial customers pay some costs via time-of-use rates, including a temporary recovery rate framework, the IESO said, while larger customers pay them in a way that reflects their share of overall electricity use during the five highest demand hours of the year.

The IESO said it could not compensate those that had paid too much, given the complexity of the system, and that the modelling error did not have a significant impact on ratepayers.

While acknowledging the effects of the mistake would vary among its customers, the IESO said the net market impact was less than $10 million, amid ongoing legislation to lower electricity rates in Ontario.

It said it would improve testing of its processes prior to deployment and agreed to publicly disclose errors that significantly affect the wholesale market in the future.

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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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EU-UK Coal Power Decline 2020 underscores Covid-19's impact on power generation, with renewables rising, carbon emissions falling, and electricity demand down, revealing resilient grids and accelerating the energy transition across European markets.

Key Points

Covid-19's impact on EU-UK power: coal down, renewables up, lower emissions intensity and reduced electricity demand.

✅ Coal generation down 25.5% EU-UK; 29% in March 10-April 10 period

✅ Renewables share up to 46%; grids remained stable and flexible

✅ Electricity demand fell 10%; emissions intensity dropped 19.5%

Coal based power generation has fallen by over a quarter (25.5%) across the European Union (EU) and United Kingdom (UK) in the first three months of 2020, compared to 2019, as a result of the response to Covid-19, with renewable energy reaching a 43% share, as wind and solar outpaced gas across the EU, according to new analysis by the technology group Wärtsilä.

The impact is even more stark in the last month, with coal generation collapsing by almost one third (29%) between March 10 and April 10 compared to the same period in 2019, making up only 12% of total EU and UK generation. By contrast, renewables delivered almost half (46%) of generation – an increase of 8% compared to 2019.

In total, demand for electricity across the continent is down by one tenth (10%), mirroring global demand declines of around 15%, due to measures taken to combat Covid-19, the biggest drop in demand since the Second World War. The result is an unprecedented fall in carbon emissions from the power sector, with emission intensity falling by 19.5% compared to the same March 10-April 10 period last year. The analysis comes from the Wärtsilä Energy Transition Lab, a new free-to-use data platform developed by Wärtsilä to help the industry, policy makers and the public understand the impact of Covid-19 on European electricity markets and analyse what this means for the future design and operation of its energy systems. The goal is to help accelerate the transition to 100% renewables.

Björn Ullbro, Vice President for Europe & Africa at Wärtsilä Energy Business, said: “The impact of the Covid-19 crisis on European energy systems is extraordinary. We are seeing levels of renewable electricity that some people believed would cause systems to collapse, yet they haven’t – in fact they are coping well. The question is, what does this mean for the future?”

“What we can see today is how our energy systems cope with much more renewable power – knowledge that will be invaluable, aligning with IAEA low-carbon insights, to accelerate the energy transition. We are making this new platform freely available to support the energy industry to adapt and use the momentum this tragic crisis has created to deliver a better, cleaner energy system, faster.”

The figures mark a dramatic shift in Europe’s energy mix – one that was not anticipated to occur until the end of the decade. The impact of the Covid-19 crisis has effectively accelerated the energy transition in the short-term, even as later lockdowns saw power demand hold firm in parts of Europe, providing a unique opportunity to see how energy systems function with far higher levels of renewables.

Ullbro added: “Electricity demand across Europe has fallen due to the lockdown measures applied by governments to stop the spread of the coronavirus. However, total renewable generation has remained at pre-crisis levels with low electricity prices, combined with renewables-friendly policy measures, crowding out gas and fossil fuel power generation, especially coal. This sets the scene for the next decade of the energy transition.”

These Europe-wide impacts are mirrored at a national level, for example:

• In the UK, renewables now have a 43% share of generation, following a stall in low-carbon progress in 2019 (up 10% on the same March 10-April 10 period in 2019) with coal power down 35% and gas down 24%.
• Germany has seen the share of renewables reach 60% (up 12%) and coal generation fall 44%, resulting in a fall in the carbon intensity of its electricity of over 30%.
• Spain currently has 49% renewables with coal power down by 41%.
• Italy has seen the steepest fall in demand, down 21% so far.

An industry first, the Wärtsilä Energy Transition Lab has been specifically developed as an open-data platform for the energy industry to understand the impact of Covid-19 and help accelerate the energy transition. The tool provides detailed data on electricity generation, demand and pricing for all 27 EU countries and the UK, combining Entso-E data in a single, easy to use platform. It will also allow users to model how systems could operate in future with higher renewables, as global power demand surpasses pre-pandemic levels, helping pinpoint problem areas and highlight where to focus policy and investment.

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New Mexico Energy Transition Act advances zero-carbon electricity, mandating public utilities deliver carbon-free electricity by 2045, with renewable targets of 50 percent by 2030 and 80 percent by 2040 to accelerate grid decarbonization.

Key Points

A state law requiring utilities to deliver carbon-free electricity by 2045, with 2030 and 2040 renewable targets.

✅ 100 percent carbon-free power from utilities by 2045

✅ Interim renewable targets: 50 percent by 2030, 80 percent by 2040

✅ Aligns with clean energy commitments in HI, CA, and DC

The New Mexico House of Representatives passed the Energy Transition Act Tuesday afternoon, sending the carbon-free electricity bill, a move aligned with proposals for a Clean Electricity Standard at the federal level, to Gov. Michelle Lujan Grisham.

Her opinions on it are known: she campaigned on raising the share of renewable energy, a priority echoed in many state renewable ambitions nationwide, and endorsed the ETA in a recent column.

"The governor will sign the bill as quickly as possible — we're hoping it is enrolled and engrossed and sent to her desk by Friday," spokesperson Tripp Stelnicki said in an email Tuesday afternoon.

Once signed, the legislation will commit the state to achieving zero-carbon electricity from public utilities by 2045. The bill also imposes interim renewable energy targets of 50 percent by 2030 and 80 percent by 2040, similar to Minnesota's 2040 carbon-free bill in its timeline.

The Senate passed the bill last week, 32-9. The House passed it 43-22.

The legislation would enter New Mexico into the company of Hawaii, California, where climate risks to grid reliability are shaping policy, and Washington, D.C., which have committed to eliminating carbon emissions from their grids. A dozen other states have proposed similar goals. Meanwhile, the Green New Deal resolution has prompted Congress to discuss the bigger task of decarbonizing the nation overall.

Though grid decarbonization has surged in the news cycle in recent months, even as some states consider moves in the opposite direction, such as a Wyoming bill restricting clean energy that would limit utility choices, New Mexico's bill arose from a years-long effort to rally stakeholders within the state's close-knit political community.

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Estonia energy prices 2021 show sharp electricity hikes versus the EU average, mixed natural gas trends, kWh tariffs on Nord Pool spiking, and VAT, taxes, and support measures shaping household bills.

Key Points

EU-high electricity growth, early gas dip, then Nord Pool spikes; taxes, VAT, and subsidies shaped energy bills.

✅ Electricity up 7% on year; EU average 2.8% in H1 2021.

✅ Gas fell 1% in H1; later spiked with global market.

✅ VAT, taxes, excise and aid impacted household costs.

Estonia saw one of the highest rates in growth of electricity prices in the first half of 2021, compared with the same period in key trends in 2020 across Europe. These figures were posted before the more recent, record level of electricity and natural gas prices; the latter actually dropped slightly in Estonia in the first half of the year.

While electricity prices rose 7 percent on year in the first half of 2021 in Estonia, the average for the EU as a whole, where energy prices drove inflation across the bloc, stood at 2.8 percent over the same period, BNS reports.

Hungary (€10 per 100 Kwh) and Bulgaria (€10.20 per 100 Kwh) saw the lowest electricity prices EU-wide, while at €31.9 per KWH, Germany's power prices posted the most expensive rate, while Denmark, Belgium and Ireland also had high prices, in excess of €25 per Kwh.

Slovenia saw the highest electricity price rise, at 15 percent, and even the United States' electricity prices saw their steepest rise in decades during the same era, while Estonia was in third place, joint with Romania at 7 percent as noted, and behind Poland (8 percent).

Lithuania, on the other hand, experienced the third highest electricity price fall over the first half of 2021, compared with the same period in 2020, at 6 percent, behind only Cyprus (7 percent) and the Netherlands (10 percent, largely due to a tax cut).

Urmas Reinsalu: VAT on electricity, gas and heating needs to be lowered
The EU average price of electricity was €21.9 percent per Kwh, with taxes and excise accounting for 39 percent of this, even as prices in Spain surged across the day-ahead market.

Estonia has also seen severe electricity price rises in the second half of the year so far, with records set and then promptly broken several times earlier in October, while an Irish electricity provider raised prices amid similar pressures, and a support package for low income households rolled out for the winter season (October to March next year). The price on the Nord Pool market as of €95.01 per Kwh; a day earlier it had stood at €66.21 per Kwh, while on October 19 the price was €140.68 per Kwh.

Gas prices
Natural gas prices to household, meanwhile, dropped in Estonia over the same period, at a sharper rate (1 percent) than the EU average (0.5 percent), according to Eurostat.

Gas prices across the EU were lowest in Lithuania (€2.8 per 100 Kwh) and highest in the Netherlands (€9.6 per KWH), while the highest growth was seen in Denmark (19 percent), in the first half of 2021.

Natural gas prices dropped in 20 member states, however, with the largest drop again coming in Lithuania (23 percent).

The average price of natural gas EU-side in the first half of 2021 was €6.4, and taxes and excise duties accounted on average for 36 percent of the total.

The second half of the year has seen steep gas price rises in Estonia, largely the result of increases on the world market, though European gas benchmarks later fell to pre-Ukraine war levels.

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