Review of Nunavut utility urged

Canada Power Grid Climate Resilience integrates extreme weather planning, microgrids, battery storage, renewable energy, vegetation management, and undergrounding to reduce outages, harden infrastructure, modernize utilities, and safeguard reliability during storms, ice events, and wildfires.

Key Points

Canada's grid resilience hardens utilities against extreme weather using microgrids, storage, renewables, and upgrades.

✅ Grid hardening: microgrids, storage, renewable integration

✅ Vegetation management reduces storm-related line contact

✅ Selective undergrounding where risk and cost justify

The increasing intensity of storms that lead to massive power outages highlights the need for Canada’s electrical utilities to be more robust and innovative, climate change scientists say.

“We need to plan to be more resilient in the face of the increasing chances of these events occurring,” University of New Brunswick climate change scientist Louise Comeau said in a recent interview.

The East Coast was walloped this week by the third storm in as many days, with high winds toppling trees and even part of a Halifax church steeple, underscoring the value of storm-season electrical safety tips for residents.

Significant weather events have consistently increased over the last five years, according to the Canadian Electricity Association (CEA), which has tracked such events since 2003.

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Nearly a quarter of total outage hours nationally in 2016 – 22 per cent – were caused by two ice storms, a lightning storm, and the Fort McMurray fires, which the CEA said may or may not be classified as a climate event.

“It (climate change) is putting quite a lot of pressure on electricity companies coast to coast to coast to improve their processes and look for ways to strengthen their systems in the face of this evolving threat,” said Devin McCarthy, vice president of public affairs and U.S. policy for the CEA, which represents 40 utilities serving 14 million customers.

The 2016 figures – the most recent available – indicate the average Canadian customer experienced 3.1 outages and 5.66 hours of outage time.

McCarthy said electricity companies can’t just build their systems to withstand the worst storm they’d dealt with over the previous 30 years. They must prepare for worse, and address risks highlighted by Site C dam stability concerns as part of long-term planning.

“There needs to be a more forward looking approach, climate science led, that looks at what do we expect our system to be up against in the next 20, 30 or 50 years,” he said.

Toronto Hydro is either looking at or installing equipment with extreme weather in mind, Elias Lyberogiannis, the utility’s general manager of engineering, said in an email.

That includes stainless steel transformers that are more resistant to corrosion, and breakaway links for overhead service connections, which allow service wires to safely disconnect from poles and prevents damage to service masts.

Comeau said smaller grids, tied to electrical systems operated by larger utilities, often utilize renewable energy sources such as solar and wind as well as battery storage technology to power collections of buildings, homes, schools and hospitals.

“Capacity to do that means we are less vulnerable when the central systems break down,” Comeau said.

Nova Scotia Power recently announced an “intelligent feeder” pilot project, which involves the installation of Tesla Powerwall storage batteries in 10 homes in Elmsdale, N.S., and a large grid-sized battery at the local substation. The batteries are connected to an electrical line powered in part by nearby wind turbines.

The idea is to test the capability of providing customers with back-up power, while collecting data that will be useful for planning future energy needs.

Tony O’Hara, NB Power’s vice-president of engineering, said the utility, which recently sounded an alarm on copper theft, was in the late planning stages of a micro-grid for the western part of the province, and is also studying the use of large battery storage banks.

“Those things are coming, that will be an evolution over time for sure,” said O’Hara.

Some solutions may be simpler. Smaller utilities, like Nova Scotia Power, are focusing on strengthening overhead systems, mainly through vegetation management, while in Ontario, Hydro One and Alectra are making major investments to strengthen infrastructure in the Hamilton area.

“The number one cause of outages during storms, particularly those with high winds and heavy snow, is trees making contact with power lines,” said N.S. Power’s Tiffany Chase.

The company has an annual budget of $20 million for tree trimming and removal.

“But the reality is with overhead infrastructure, trees are going to cause damage no matter how robust the infrastructure is,” said Matt Drover, the utility’s director for regional operations.

“We are looking at things like battery storage and a variety of other reliability programs to help with that.”

NB Power also has an increased emphasis on tree trimming and removal, and now spends $14 million a year on it, up from $6 million prior to 2014.

O’Hara said the vegetation program has helped drive the average duration of power outages down since 2014 from about three hours to two hours and 45 minutes.

Some power cables are buried in both Nova Scotia and New Brunswick, mostly in urban areas. But both utilities maintain it’s too expensive to bury entire systems – estimated at $1 million per kilometre by Nova Scotia Power.

The issue of burying more lines was top of mind in Toronto following a 2013 ice storm, but that’s city’s utility also rejected the idea of a large-scale underground system as too expensive – estimating the cost at around $15 billion, while Ontario customers have seen Hydro One delivery rates rise in recent adjustments.

“Having said that, it is prudent to do so for some installations depending on site specific conditions and the risks that exist,” Lyberogiannis said.

Comeau said lowering risks will both save money and disruption to people’s lives.

“We can’t just do what we used to do,” said Xuebin Zhang, a senior climate change scientist at Environment and Climate Change Canada.

“We have to build in management risk … this has to be a new norm.”

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Senate Renewable Energy Tax Credits face Finance Committee scrutiny, with Democrats urging action on tax extenders, clean energy incentives, and climate policy, while Republicans cite prior wins in wind, biodiesel, and EV credits.

Key Points

Legislative incentives debated in the Senate Finance Committee to extend and align clean energy tax benefits.

✅ Democrats press hearings and action on energy tax policy

✅ Focus on clean energy, EVs, wind, biodiesel, and resilience

✅ Grassley cites prior extenders; disputes push for bigger subsidies

A group of 27 Democratic senators is calling for action in the Senate Finance Committee on extending energy-related tax credits and examining new tax proposals, especially those that incentivize renewable energy projects and align with FERC action on aggregated DERs across the grid.

Sen. Ron Wyden, D-Ore., the ranking Democrat on the Senate Finance Committee, who recently introduced a wildfire-resilient grid bill with Sen. Merkley, led the group of Democrats in writing a letter Tuesday to Sen. Charles Grassley, R-Iowa, who chairs the committee.

“Despite numerous opportunities, including in the recent tax extenders package, the Finance Committee has failed to take action on the dozens of energy tax proposals pending before it,” they wrote. “It is critical that the Committee move to address these issues in a timely manner, along with much needed policy changes that heed warnings on regulatory rollbacks to combat the damage and growing dangers caused by global climate change.”

The number of Americans ages 65 and over is projected to nearly double by 2060. And most would prefer to age in place and hiresenior caregivers if needed.

They pointed out that the Senate Finance Committee hasn’t held a single hearing on energy tax policy during the previous congressional term, and has yet to hold one in the current one.

“The sole energy tax-related recommendation of the Committee’s temporary policy task forces was ignored in the tax extender legislation passed in December 2019, along with nearly all proposals put forward in members’ legislation this Congress,” they wrote. “This Committee must fulfill its role in examining members’ energy tax proposals and in bolstering our nation’s efforts to combat climate change, including a clean electricity standard approach that sets firm targets.”

They noted that In 2019, the global average temperature was the second highest ever recorded and the past decade was the hottest ever. The lawmakers pointed to raging wildfires and increased flooding in the western part of the U.S., as well as challenges in California’s power system during the transition, causing unprecedented destruction over the past several years. They called for tax incentives for renewable energy to help combat climate change.

“Gaps in the tax code have disadvantaged complementary technologies that could improve climate resiliency and provide additional emissions reductions,” they wrote. “While power sector emissions continue to decrease, emissions from transportation, heavy industry and agriculture have stayed level or increased over the past 10 years, even amid $5 gas not spurring a green shift in consumer behavior. The United States is not on pace to meet its international climate commitments, to say nothing of the reductions necessary to stave off the worst potential outcomes of global warming.”

Grassley reacted to the letter, noting that he had worked to get tax extenders legislation passed, even as some states consider bans on clean energy use by utilities. "I begged Democrats for a year to help me get an extenders package passed, about half of which were green energy policies, so this rings hollow," he said in a statement Tuesday. "We wouldn’t have a wind energy credit or a biodiesel credit but for me, let alone an extension of either. Democrats were holding up these green energy provisions in an attempt to get a big expansion of taxpayer subsidies for rich Tesla owners."

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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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National Grid power supply warning highlights electricity shortage risks amid low wind output, generator outages, and cold weather, reducing capacity margins and grid stability; considering demand response and reserve power to avoid blackout risk.

Key Points

An alert that reduced capacity from low wind and outages requires actions to maintain UK grid stability.

✅ Low wind output and generator outages reduce capacity margins

✅ ESO exploring demand response and reserve generation options

✅ Aim: maintain grid stability and avoid blackout risk

National Grid has warned that Britain’s electricity will be in short supply over the next few days after a string of unplanned power plant outages and unusually low wind speeds this week, as cheap wind power wanes across the system.

The electricity system operator said it will take action to “make sure there is enough generation” during the cold weather spell, including virtual power plants and other demand-side measures, to prevent a second major blackout in as many years.

“Unusually low wind output coinciding with a number of generator outages means the cushion of spare capacity we operate the system with has been reduced,” the company told its Twitter followers.

“We’re exploring measures and actions to make sure there is enough generation available to increase our buffer of capacity.”

A spokeswoman for National Grid said the latest electricity supply squeeze was not expected to be as severe as recorded last month, following reports that the government’s emergency energy plan was not going ahead, and added that the company did not expect to issue an official warning in the next 24 hours.

“We’re monitoring how the situation develops,” she said.

The warning is the second from the electricity system operator in recent weeks. In mid-September the company issued an official warning to the electricity market as peak power prices climbed, that its ‘buffer’ of power reserves had fallen below 500MW and it may need to call on more power plants to help prevent a blackout. The notice was later withdrawn.

Concerns over National Grid’s electricity supplies have been relatively rare in recent years. It was forced in November 2015 to ask businesses to cut their demand as a “last resort” measure to keep the lights on after a string of coal plant breakdowns.

But since then, National Grid’s greater challenge has been an oversupply of electricity, partly due to record wind generation, which has threatened to overwhelm the grid during times of low electricity demand.

National Grid has already spent almost £1bn on extra measures to prevent blackouts over the first half of the year by paying generators to produce less electricity during the coronavirus lockdown, as daily demand fell.

The company paid wind farms to turn off, and EDF Energy to halve the nuclear generation from its Sizewell B nuclear plant, to avoid overwhelming the grid when demand for electricity fell by almost a quarter from last year.

The electricity supply squeeze comes a little over a year after National Grid left large parts of England and Wales without electricity after the biggest blackout in a decade left a million homes in the dark. National Grid blamed a lightning strike for the widespread power failure.

Similar supply strains have recently caused power cuts in China, underscoring how weather and generation mix can trigger blackouts.

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ACCC energy underwriting guarantee proposes government-backed certainty for new generation, cutting electricity prices and supporting gas, pumped hydro, renewables, batteries, and potentially coal-fired power, addressing market failure without direct subsidies.

Key Points

A tech-neutral, government-backed plan underwriting new generation revenue to increase certainty and cut power prices.

✅ Government guarantee provides a revenue floor for new generators.

✅ Technology neutral: coal, gas, renewables, pumped hydro, batteries.

✅ Intended to reduce bills by up to $400 and address market failure.

Australian Taxpayers won't directly fund any new power plants despite some Coalition MPs seizing on a new report to call for a coal-fired power station.

The Australian Competition and Consumer Commission recommended the government give financial certainty to new power plants, guaranteeing energy will be bought at a cheap price if it can't be sold, as part of an electricity market plan to avoid threats to supply.

It's part of a bid to cut up to $400 a year from average household power prices.

Prime Minister Malcolm Turnbull said the finance proposal had merit, but he ruled out directly funding specific types of power generation.

"We are not in the business of subsidising one technology or another," he told reporters in Queensland today.

"We've done enough of that. Frankly, there's been too much of that."

Renewable subsidies, designed in the 1990s to make solar and wind technology more affordable, have worked and will end in 2020.

Some Coalition MPs claim the ACCC's recommendation to underwrite power generation is vindication for their push to build new coal-fired power plants.

But ACCC chair Rod Sims said no companies had proposed building new coal plants - instead they're trying to build new gas projects, pumped hydro or renewable projects.

Opposition Leader Bill Shorten said Mr Turnbull was offering solutions years away, having overseen a rise in power prices over the past year.

"You don't just go down to K-Mart and get a coal-fired power station off the shelf," Mr Shorten told reporters, admitting he had not read the ACCC report.

Energy Minister Josh Frydenberg said the recommendation to underwrite new power generators had a lot of merit, as it would address a market failure highlighted by AEMO warnings about reduced reserves.

"What they're saying is the government needs to step in here to provide some sort of assurance," Mr Frydenberg told 9NEWS today.

He said that could include coal, gas, renewable energy or battery storage.

Deputy Nationals leader Bridget McKenzie said science should determine which technology would get the best outcomes for power bills, with a scrapping coal report suggesting it can be costly.

Mr Turnbull said there was strong support for the vast majority of the ACCC's 56 recommendations, but the government would carefully consider the report, which sets out a blueprint to cut electricity bills by 25 percent.

Acting Greens leader Adam Bandt said Australia should exit coal-fired power in favour of renewable energy to cut pollution.

In contrast, Canada has seen the Stop the Shock campaign advocate a return to coal power in some provinces.

The Australian Energy Council, which represents 21 major energy companies, said the government should consult on changes to avoid "unintended consequences".

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AI Energy Consumption strains corporate electricity bills as data centers and HPC workloads run nonstop, driving carbon emissions. Efficiency upgrades, renewable energy, and algorithm optimization help control costs and enhance sustainability across industries.

Key Points

AI Energy Consumption is the power used by AI compute and data centers, impacting costs and sustainability.

✅ Optimize cooling, hardware, and workloads to cut kWh per inference

✅ Integrate on-site solar, wind, or PPAs to offset data center power

✅ Tune models and algorithms to reduce compute and latency

Artificial Intelligence (AI) is revolutionizing industries with its promise of increased efficiency and productivity. However, as businesses integrate AI technologies into their operations, there's a significant and often overlooked impact: the strain on corporate electricity bills.

AI's Growing Energy Demand

The adoption of AI entails the deployment of high-performance computing systems, data centers, and sophisticated algorithms that require substantial energy consumption. These systems operate around the clock, processing massive amounts of data and performing complex computations, and, much like the impact on utilities seen with major EV rollouts, contributing to a notable increase in electricity usage for businesses.

Industries Affected

Various sectors, including finance, healthcare, manufacturing, and technology, rely on AI-driven applications for tasks ranging from data analysis and predictive modeling to customer service automation and supply chain optimization, while manufacturing is influenced by ongoing electric motor market growth that increases electrified processes.

Cost Implications

The rise in electricity consumption due to AI deployments translates into higher operational costs for businesses. Corporate entities must budget accordingly for increased electricity bills, which can impact profit margins and financial planning, especially in regions experiencing electricity price volatility in Europe amid market reforms. Managing these costs effectively becomes crucial to maintaining competitiveness and sustainability in the marketplace.

Sustainability Challenges

The environmental impact of heightened electricity consumption cannot be overlooked. Increased energy demand from AI technologies contributes to carbon emissions and environmental footprints, alongside rising e-mobility demand forecasts that pressure grids, posing challenges for businesses striving to meet sustainability goals and regulatory requirements.

Mitigation Strategies

To address the escalating electricity bills associated with AI, businesses are exploring various mitigation strategies:

1. Energy Efficiency Measures: Implementing energy-efficient practices, such as optimizing data center cooling systems, upgrading to energy-efficient hardware, and adopting smart energy management solutions, can help reduce electricity consumption.

2. Renewable Energy Integration: Investing in renewable energy sources like solar or wind power and energy storage solutions to enhance flexibility can offset electricity costs and align with corporate sustainability initiatives.

3. Algorithm Optimization: Fine-tuning AI algorithms to improve computational efficiency and reduce processing times can lower energy demands without compromising performance.

4. Cost-Benefit Analysis: Conducting thorough cost-benefit analyses of AI deployments to assess energy consumption against operational benefits and potential rate impacts, informed by cases where EV adoption can benefit customers in broader electricity markets, helps businesses make informed decisions and prioritize energy-saving initiatives.

Future Outlook

As AI continues to evolve and permeate more aspects of business operations, the demand for electricity will likely intensify and may coincide with broader EV demand projections that increase grid loads. Balancing the benefits of AI-driven innovation with the challenges of increased energy consumption requires proactive energy management strategies and investments in sustainable technologies.

Conclusion

The integration of AI technologies presents significant opportunities for businesses to enhance productivity and competitiveness. However, the corresponding surge in electricity bills underscores the importance of proactive energy management and sustainability practices. By adopting energy-efficient measures, leveraging renewable energy sources, and optimizing AI deployments, businesses can mitigate cost impacts, reduce environmental footprints, and foster long-term operational resilience in an increasingly AI-driven economy.

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