Renewable energy tops 10 percent of U.S. production

PG&E Drum Fire Cause identified as a power line failure in Santa Barbara County, with arcing electricity igniting vegetation near Buellton on Drum Canyon Road; 696 acres burned as investigators and CPUC review PG&E safety.

Key Points

A failed PG&E power line sparked the 696-acre Drum Fire near Buellton; the utility is conducting its own probe.

✅ Power line failed between poles, arcing ignited vegetation.

✅ 696 acres burned; no structures damaged or injuries.

✅ PG&E filed CPUC incident report; ongoing investigation.

A downed Pacific Gas and Electric Co. power line was the cause of the Drum fire that broke out June 14 on Drum Canyon Road northwest of Buellton, a reminder that a transformer explosion can also spark multiple fires, the Santa Barbara County Fire Department announced Thursday.

The fire broke out about 12:50 p.m. north of Highway 246 and burned about 696 acres of wildland before firefighters brought it under control, although no structures were damaged or mass outages like the Los Angeles power outage occurred, according to an incident summary.

A team of investigators pinpointed the official cause as a power line that failed between two utility poles and fell to the ground, and as downed line safety tips emphasize, arcing electricity ignited the surrounding vegetation, said County Fire Department spokesman Capt. Daniel Bertucelli.

In response, a PG&E spokesman said the utility is conducting its own investigation and does not have access to whatever data investigators used, and, as the ATCO regulatory penalty illustrates, such matters can draw significant oversight, but he noted the company filed an electric incident report on the wire with the California Public Utilities Commission on June 14.

"We are grateful to the first responders who fought the 2020 Drum fire in Santa Barbara County and helped make sure that there were no injuries or fatalities, outcomes not always seen in copper theft incidents, and no reports of structures damaged or burned," PG&E spokesman Mark Mesesan said.

"While we are continuing to conduct our own investigation into the events that led to the Drum fire, and as the Site C watchdog inquiry shows, oversight bodies can seek more transparency, PG&E does not have access to the Santa Barbara County Fire Department's report."

He said PG&E remains focused on reducing wildfire risk across its service area while limiting the scope and duration of public safety power shutoffs, including strategies like line-burying decisions adopted by other utilities, and that the safety of customers and communities it serves are its most important responsibility.

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Bitcoin Energy Debate examines electricity usage, mining costs, environmental impact, and blockchain efficiency, weighing renewable power, carbon footprint, scalability, and transaction throughput to clarify stakeholder claims from Tesla, Square, academics, and policymakers.

Key Points

Debate on Bitcoin mining's power use, environmental impact, efficiency, and scalability versus alternative blockchains.

✅ Compares energy intensity with transaction throughput and system outputs.

✅ Weighs renewables, stranded power, and carbon footprint in mining.

✅ Assesses PoS blockchains, stablecoins, and scalability tradeoffs.

There is a great debate underway about the electricity required to process Bitcoin transactions. The debate is significant, the stakes are high, the views are diverse, and there are smart people on both sides. Bitcoin generates a lot of emotion, thereby producing too much heat and not enough light. In this post, I explain the importance of identifying the key issues in the debate, and of understanding the nature and extent of disagreement about how much electrical energy Bitcoin consumes.

Consider the background against which the debate is taking place. Because of its unstable price, Bitcoin cannot serve as a global mainstream medium of exchange. The instability is apparent. On January 1, 2021, Bitcoin’s dollar price was just over $29,000. Its price rose above $63,000 in mid-April, and then fell below $35,000, where it has traded recently. Now the financial media is asking whether we are about to experience another “cyber winter” as the prices of cryptocurrencies continue their dramatic declines.

Central banks warns of bubble on bitcoins as it skyrockets
As bitcoins skyrocket to more than $12 000 for one BTC, many central banks as ECB or US Federal ... [+] NURPHOTO VIA GETTY IMAGES
Bitcoin is a high sentiment beta asset, and unless that changes, Bitcoin cannot serve as a global mainstream medium of exchange. Being a high sentiment beta asset means that Bitcoin’s market price is driven much more by investor psychology than by underlying fundamentals.

As a general matter, high sentiment beta assets are difficult to value and difficult to arbitrage. Bitcoin qualifies in this regard. As a general matter, there is great disagreement among investors about the fair values of high sentiment beta assets. Bitcoin qualifies in this regard.

One major disagreement about Bitcoin involves the very high demand for electrical power associated with Bitcoin transaction processing, an issue that came to light several years ago. In recent months, the issue has surfaced again, in a drama featuring disagreement between two prominent industry leaders, Elon Musk (from Tesla and SpaceX) and Jack Dorsey (from Square).

On one side of the argument, Musk contends that Bitcoin’s great need for electrical power is detrimental to the environment, especially amid disruptions in U.S. coal and nuclear power that increase supply strain.  On the other side, Dorsey argues that Bitcoin’s electricity profile is a benefit to the environment, in part because it provides a reliable customer base for clean electric power. This might make sense, in the absence of other motives for generating clean power; however, it seems to me that there has been a surge in investment in alternative technologies for producing electricity that has nothing to do with cryptocurrency. So I am not sure that the argument is especially strong, but will leave it there. In any event, this is a demand side argument.

A supply side argument favoring Bitcoin is that the processing of Bitcoin transactions, known as “Bitcoin mining,” already uses clean electrical power, power which has already been produced, as in hydroelectric plants at night, but not otherwise consumed in an era of flat electricity demand across mature markets.

Both Musk and Dorsey are serious Bitcoin investors. Earlier this year, Tesla purchased $1.5 billion of Bitcoin, agreed to accept Bitcoin as payment for automobile sales, and then reversed itself. This reversal appears to have pricked an expanding Bitcoin bubble. Square is a digital transaction processing firm, and Bitcoin is part of its long-term strategy.

Consider two big questions at the heart of the digital revolution in finance. First, to what degree will blockchain replace conventional transaction technologies? Second, to what degree will competing blockchain based digital assets, which are more efficient than Bitcoin, overcome Bitcoin’s first mover advantage as the first cryptocurrency?

To gain some insight about possible answers to these questions, and the nature of the issues related to the disagreement between Dorsey and Musk, I emailed a series of academics and/or authors who have expertise in blockchain technology.

David Yermack, a financial economist at New York University, has written and lectured extensively on blockchains. In 2019, Yermack wrote the following: “While Bitcoin and successor cryptocurrencies have grown remarkably, data indicates that many of their users have not tried to participate in the mainstream financial system. Instead they have deliberately avoided it in order to transact in black markets for drugs and other contraband … or evade capital controls in countries such as China.” In this regard, cyber-criminals demanding ransom for locking up their targets information systems often require payment in Bitcoin. Recent examples of cyber-criminal activity are not difficult to find, such as incidents involving Kaseya and Colonial Pipeline.

David Yermack continues: “However, the potential benefits of blockchain for improving data security and solving moral hazard problems throughout the financial system have become widely apparent as cryptocurrencies have grown.” In his recent correspondence with me, he argues that the electrical power issue associated with Bitcoin “mining,” is relatively minor because Bitcoin miners are incentivized to seek out cheap electric power, and patterns shifted as COVID-19 changed U.S. electricity consumption across sectors.

Thomas Philippon, also a financial economist at NYU, has done important work characterizing the impact of technology on the resource requirements of the financial sector. He has argued that historically, the financial sector has comprised about 6-to-7% of the economy on average, with variability over time. Unit costs, as a percentage of assets, have consistently been about 2%, even with technological advances. In respect to Bitcoin, he writes in his correspondence with me that Bitcoin is too energy inefficient to generate net positive social benefits, and that energy crisis pressures on U.S. electricity and fuels complicate the picture, but acknowledges that over time positive benefits might be possible.

Emin Gün Sirer is a computer scientist at Cornell University, whose venture AVA Labs has been developing alternative blockchain technology for the financial sector. In his correspondence with me, he writes that he rejects the argument that Bitcoin will spur investment in renewable energy relative to other stimuli. He also questions the social value of maintaining a fairly centralized ledger largely created by miners that had been in China and are now migrating to other locations such as El Salvador.

Bob Seeman is an engineer, lawyer, and businessman, who has written a book entitled Bitcoin: The Mother of All Scams. In his correspondence with me, he writes that his professional experience with Bitcoin led him to conclude that Bitcoin is nothing more than unlicensed gambling, a point he makes in his book.

David Gautschi is an academic at Fordham University with expertise in global energy. I asked him about studies that compare Bitcoin’s use of energy with that of the U.S. financial sector. In correspondence with me, he cautioned that the issues are complex, and noted that online technology generally consumes a lot of power, with electricity demand during COVID-19 highlighting shifting load profiles.

My question to David Gautschi was prompted by a study undertaken by the cryptocurrency firm Galaxy Digital. This study found that the financial sector together with the gold industry consumes twice as much electrical power as Bitcoin transaction processing. The claim by Galaxy is that Bitcoin’s electrical power needs are “at least two times lower than the total energy consumed by the banking system as well as the gold industry on an annual basis.”

Galaxy’s analysis is detailed and bottom up based. In order to assess the plausibility of its claims, I did a rough top down analysis whose results were roughly consistent with the claims in the Galaxy study. For sake of disclosure, I placed the heuristic calculations I ran in a footnote.1 If we accept the Galaxy numbers, there remains the question of understanding the outputs produced by the electrical consumption associated with both Bitcoin mining and U.S. banks’ production of financial services. I did not see that the Galaxy study addresses the output issue, and it is important.

Consider some quick statistics which relate to the issue of outputs. The total market for global financial services was about $20 trillion in 2020. The number of Bitcoin transactions processed per day was about 330,000 in December 2020, and about 400,000 in January 2021. The corresponding number for Bitcoin’s digital rival Ethereum during this time was about 1.1 million transactions per day. In contrast, the global number of credit card transactions per day in 2018 was about 1 billion.2

Bitcoin Value Falls
LONDON, ENGLAND - NOVEMBER 20: A visual representation of the cryptocurrencies Bitcoin and Ethereum ... [+] GETTY IMAGES
These numbers tell us that Bitcoin transactions comprise a small share, on the order of 0.04%, of global transactions, but use something like a third of the electricity needed for these transactions. That said, the associated costs of processing Bitcoin transactions relate to tying blocks of transactions together in a blockchain, not to the number of transactions. Nevertheless, even if the financial sector does indeed consume twice as much electrical power as Bitcoin, the disparity between Bitcoin and traditional financial technology is striking, and the experience of Texas grid reliability underscores system constraints when it comes to output relative to input.  This, I suggest, weakens the argument that Bitcoin’s electricity demand profile is inconsequential because Bitcoin mining uses slack electricity.

A big question is how much electrical power Bitcoin mining would require, if Bitcoin were to capture a major share of the transactions involved in world commerce. Certainly much more than it does today; but how much more?

Given that Bitcoin is a high sentiment beta asset, there will be a lot of disagreement about the answers to these two questions. Eventually we might get answers.

At the same time, a high sentiment beta asset is ill suited to being a medium of exchange and a store of value. This is why stablecoins have emerged, such as Diem, Tether, USD Coin, and Dai. Increased use of these stable alternatives might prevent Bitcoin from ever achieving a major share of the transactions involved in world commerce.

We shall see what the future brings. Certainly El Salvador’s recent decision to make Bitcoin its legal tender, and to become a leader in Bitcoin mining, is something to watch carefully. Just keep in mind that there is significant downside to experiencing foreign exchange rate volatility. This is why global financial institutions such as the World Bank and IMF do not support El Salvador’s decision; and as I keep saying, Bitcoin is a very high sentiment beta asset.

In the past I suggested that Bitcoin bubble would burst when Bitcoin investors conclude that its associated processing is too energy inefficient. Of course, many Bitcoin investors are passionate devotees, who are vulnerable to the psychological bias known as motivated reasoning. Motivated reasoning-based sentiment, featuring denial,3 can keep a bubble from bursting, or generate a series of bubbles, a pattern we can see from Bitcoin’s history.

I find the argument that Bitcoin is necessary to provide the right incentives for the development of clean alternatives for generating electricity to be interesting, but less than compelling. Are there no other incentives, such as evolving utility trends, or more efficient blockchain technologies? Bitcoin does have a first mover advantage relative to other cryptocurrencies. I just think we need to be concerned about getting locked into an technologically inferior solution because of switching costs.

There is an argument to made that decisions, such as how to use electric power, are made in markets with self-interested agents properly evaluating the tradeoffs. That said, think about why most of the world adopted the Windows operating system in the 1980s over the superior Mac operating system offered by Apple. Yes, we left it to markets to determine the outcome. People did make choices; and it took years for Windows to catch up with the Mac’s operating system.

My experience as a behavioral economist has taught me that the world is far from perfect, to expect to be surprised, and to expect people to make mistakes. We shall see what happens with Bitcoin going forward.

As things stand now, Bitcoin is well suited as an asset for fulfilling some people’s urge to engage in high stakes gambling. Indeed, many people have a strong need to engage in gambling. Last year, per capita expenditure on lottery tickets in Massachusetts was the highest in the U.S. at over $930.

High sentiment beta assets offer lottery-like payoffs. While Bitcoin certainly does a good job of that, it cannot simultaneously serve as an effective medium of exchange and reliable store of value, even setting aside the issue at the heart of the electricity debate.

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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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Ukraine Power Grid Attacks disrupt critical infrastructure as missiles and drones strike power plants, substations, and lines, causing blackouts. Emergency repairs, international aid, generators, and renewables bolster resilience and keep hospitals and water running.

Key Points

Russian strikes on Ukraine's power infrastructure cause blackouts; repairs and aid sustain hospitals and water.

✅ Missile and drone strikes target plants, substations, and lines.

✅ Crews restore power under fire; air defenses protect sites.

✅ Allies supply equipment, generators, and grid repair expertise.

Ukraine is facing an ongoing battle to maintain its electrical grid in the wake of relentless Russian attacks targeting power plants and energy infrastructure. These attacks, which have intensified in the last year, are part of Russia's broader strategy to weaken Ukraine's ability to function amid the ongoing war. Power plants, substations, and energy lines have become prime targets, with Russian forces using missiles and drones to destroy critical infrastructure, as western Ukraine power outages have shown, leaving millions of Ukrainians without electricity and heating during harsh winters.

The Ukrainian government and energy companies are working tirelessly to repair the damage and prevent total blackouts, while also trying to ensure that civilians have access to vital services like hospitals and water supplies. Ukraine has received support from international allies in the form of technical assistance and equipment to help strengthen its power grid, and electricity reserve updates suggest outages can be avoided if no new strikes occur. However, the ongoing nature of the attacks and the complexity of repairing such extensive damage make the situation extraordinarily difficult.

Despite these challenges, Ukraine's resilience is evident, even as winter pressures on the battlefront intensify operations. Energy workers are often working under dangerous conditions, risking their lives to restore power and prevent further devastation. The Ukrainian government has prioritized the protection of energy infrastructure, with military forces being deployed to safeguard workers and critical assets.

Meanwhile, the international community continues to support Ukraine through financial and technical aid, though some U.S. support programs have ended recently, as well as providing temporary power solutions, like generators, to keep essential services running. Some countries have even sent specialized equipment to help repair damaged power lines and energy plants more quickly.

The humanitarian consequences of these attacks are severe, as access to electricity means more than just light—it's crucial for heating, cooking, and powering medical equipment. With winter temperatures often dropping below freezing, plans to keep the lights on are vital to protect vulnerable communities, and the lack of reliable energy has put many lives at risk.

In response to the ongoing crisis, Ukraine has also focused on enhancing its energy independence, seeking alternatives to Russian-supplied energy. This includes exploring renewable energy sources, such as solar and wind power, and new energy solutions adopted by communities to overcome winter blackouts, which could help reduce reliance on traditional energy grids and provide more resilient options in the future.

The battle for energy infrastructure in Ukraine illustrates the broader struggle of the country to maintain its sovereignty and independence in the face of external aggression. The destruction of power plants is not only a military tactic but also a psychological one—meant to instill fear and disrupt daily life. However, the unwavering spirit of the Ukrainian people, alongside international support, including Ukraine's aid to Spain during blackouts as one example, continues to ensure that the fight to "keep the lights on" is far from over.

As Ukraine works tirelessly to repair its energy grid, it also faces the challenge of preparing for the long-term impact of these attacks. The ongoing war has highlighted the importance of securing energy infrastructure in modern conflicts, and the world is watching as Ukraine's resilience in this area could serve as a model for other nations facing similar threats.

Ukraine’s energy struggle is far from over, but its determination to keep the lights on remains a beacon of hope and defiance in the face of ongoing adversity.

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Electricity Grid Flow Prediction leverages big data, machine learning, and weather analytics to forecast power flows across smart grids, enhancing reliability, reducing blackouts and curtailment, and optimizing renewable integration under EU Horizon 2020 innovation.

Key Points

Short-term forecasting of power flows using big data, weather inputs, and machine learning to stabilize smart grids.

✅ Uses big data, weather, and ML for 6-hour forecasts

✅ Improves reliability, cuts blackouts and energy waste

✅ Supports smart grids, renewables, and grid balancing

Three European prediction specialists have won prizes worth €2 million for developing the most accurate predictions of electricity flow through a grid

The three winners of the Big Data Technologies Horizon Prize received their awards at a ceremony on 12th November in Austria.

The first prize of €1.2 million went to Professor José Vilar from Spain, while Belgians Sofie Verrewaere and Yann-Aël Le Borgne came in joint second place and won €400,000 each.

The challenge was open to individuals groups and organisations from countries taking part in the EU’s research and innovation programme, Horizon 2020.

Carlos Moedas, Commissioner for Research, Science and Innovation, said: “Energy is one of the crucial sectors that are being transformed by the digital grid worldwide.

“This Prize is a good example of how we support a positive transformation through the EU’s research and innovation programme, Horizon 2020.

“For the future, we have designed our next programme, Horizon Europe, to put even more emphasis on the merger of the physical and digital worlds across sectors such as energy, transport and health.”

The challenge for the applicants was to create AI-driven software that could predict the likely flow of electricity through a grid taking into account a number of factors including the weather and the generation source (i.e. wind turbines, solar cells, etc).

Using a large quantity of data from electricity grids, EU smart meters, combined with additional data such as weather conditions, applicants had to develop software that could predict the flow of energy through the grid over a six-hour period.

Commissioner for Digital Economy and Society Mariya Gabriel said: “The wide range of possible applications of these winning submissions could bring tangible benefits to all European citizens, including efforts to tackle climate change with machine learning across sectors.”

The decision to focus on energy grids for this particular prize was driven by a clear market need, including expanding HVDC technology capabilities.

Today’s energy is produced at millions of interconnected and dispersed unpredictable sites such as wind turbines, solar cells, etc., so it is harder to ensure that electricity supply matches the demand at all times.

This complexity means that huge amounts of data are produced at the energy generation sites, in the grid and at the place where the energy is consumed.

Being able to make accurate, short-term predictions about power grid traffic is therefore vital to reduce the risks of blackouts or, by enabling utilities to use AI for energy savings, limit waste of energy.

Reliable predictions can also be used in fields such as biology and healthcare. The predictions can help to diagnose and cure diseases as well as to allocate resources where they are most needed.

Ultimately, the winning ideas are set to be picked up by the energy sector in the hopes of creating smarter electricity infrastructure, more economic and more reliable power grids.

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OEB Hydro One Rate Decision 2023-2027 sets approved transmission and distribution rates in Ontario, with a settlement reducing revenue requirement, modest bill impacts, higher productivity factors, inflation certainty, DVA credits, and First Nations participation measures.

Key Points

OEB-approved Hydro One 2023-2027 transmission and distribution rates settlement, lowering costs and limiting bill impacts.

✅ $482.7M revenue reductions vs. original proposal

✅ Avg bill impact: +$0.69 trans., +$2.43 distr. per month

✅ Faster DVA refunds; productivity and efficiency incentives

The Ontario Energy Board (OEB) issued its Decision and Order on an application filed by Hydro One Networks Inc. (Hydro One) on August 5, 2021 seeking approval for changes to the rates it charges for electricity transmission and distribution, beginning January 1, 2023 and for each subsequent year through to December 31, 2027. 

The proceeding resulted in the filing of a settlement proposal that the OEB has now approved after concluding that it is in the public interest. 

The negotiated reductions in Hydro One's transmission and distribution revenue requirements over the 2023 to 2027 period total $482.7 million compared to the requests made by Hydro One in its application.

The OEB found that the reductions in Hydro One's proposed capital expenditure and operating, maintenance and administration costs were reasonable, and should not compromise the safety and reliability of Hydro One's transmission and distribution systems. It also concluded that the estimated bill impacts for both transmission and distribution customers are reasonable, and that the January 1, 2023 implementation and effective date of the new rates is appropriate.

In the broader Canadian context, pressures on utility finances at other companies, such as Manitoba Hydro's debt provide additional background for stakeholders.

Bill Impacts

This proceeding related to both transmission and distribution operations.

Transmission

The new transmission revenue requirement will affect Ontario electricity consumers across the province because it will be incorporated into updated transmission rates, which are paid by electricity distributors and other large consumers connected directly to the transmission system, and distributors then pass this cost on to their customers.

As a result of the settlement approved on the transmission portion of the application, it is estimated that for a typical Hydro One residential customer with a monthly consumption of 750 kWh, the total bill impact averaged over the 2023-2027 period will be an increase of $0.69 per month or 0.5%, which follows the 2021 electricity rate reductions that affected many businesses.

Distribution

The new OEB-approved distribution rates will affect Hydro One's distribution customers, including areas served through acquisitions such as the Peterborough Distribution sale which expanded its customer base.

As a result of the settlement reached on the distribution portion of the application, it is estimated that for a typical residential distribution customer of Hydro One with a monthly consumption of 750 kWh, the total bill impact averaged over the 2023-2027 period will be an increase of $2.43 per month or 1.5%.
This proceeding included 24 approved intervenors representing a wide variety of customer classes and other interests. Representatives of 18 of those intervenors participated in the settlement conference. Having this diversity of perspective enriches the already thorough examination of evidence and argument that the OEB routinely undertakes when considering an application.

Other features of the settlement proposal include:

• A commitment by Hydro One to include, in future operational and capital investment plans, a discussion of how the proposed spending will directly support the achievement of Hydro One's climate change policy.
• Eliminating further updates to reflect changes to inflation in 2022 and 2023 as originally proposed, to provide Hydro One's customers with greater certainty as to the potential impacts of inflation on their bills.
• Increases in the productivity factors and supplemental stretch factors for both the distribution and transmission business segments which will provide Hydro One with additional incentives to achieve greater efficiencies during the 2023 to 2027 period.
• Undertaking certain measures to seek economic participation or equity investment opportunities from First Nations.
• Disposition of net credit balances in deferral and variance accounts (DVAs) owed to customers will be returned over a shorter period of time:
• Transmission DVA – $22.5M over a one-year period in 2023 (versus five years)
• Distribution DVA – $85.9M over a three-year period – 2023-2025 (versus five years)
• Undertaking certain measures to continue examining cost-effective transmission and distribution line losses
• In the decision, the OEB acknowledged the efforts involved by parties to participate in this entire proceeding, including the settlement conference, considering the number of participants, the complexity of the issues, and the challenging logistics of a "virtual" proceeding. The OEB commended the parties and OEB staff for achieving a comprehensive settlement on all issues.

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