Britain Prepares for High Winter Heating and Electricity Costs

Covid-19 Energy Transition and Machine Learning reshape climate change policy, electricity planning, and grid operations, from demand forecasting and decarbonization strategies in Europe to scalable electrification modeling and renewable integration across Africa.

Key Points

How the pandemic reshapes energy policy and how ML improves planning, demand forecasts, and grid reliability in Africa.

✅ Pandemic-driven demand shifts strain grid operations and markets

✅ Policy momentum risks rollback; favor future-oriented decarbonization

✅ ML boosts demand prediction, electrification, and grid reliability in Africa

The impact of Covid-19 on the energy system was discussed in an online climate change workshop that also considered how machine learning can help electricity planning in Africa.

This year’s International Conference on Learning Representations event included a workshop held by the Climate Change AI group of academics and artificial intelligence industry representatives, which considered how machine learning can help tackle climate change and highlighted advances by European electricity prediction specialists working in this field.

Bjarne Steffen, senior researcher at the energy politics group at ETH Zürich, shared his insights at the workshop on how Covid-19 and the accompanying economic crisis are affecting recently introduced ‘green’ policies. “The crisis hit at a time when energy policies were experiencing increasing momentum towards climate action, especially in Europe, and in proposals to invest in smarter electricity infrastructure for long-term resilience,” said Steffen, who added the coronavirus pandemic has cast into doubt the implementation of such progressive policies.

The academic said there was a risk of overreacting to the public health crisis, as far as progress towards climate change goals was concerned.

Lobbying

“Many interest groups from carbon-intensive industries are pushing to remove the emissions trading system and other green policies,” said Steffen. “In cases where those policies are having a serious impact on carbon-emitting industries, governments should offer temporary waivers during this temporary crisis, instead of overhauling the regulatory structure.”

However, the ETH Zürich researcher said any temptation to impose environmental conditions to bail-outs for carbon-intensive industries should be resisted. “While it is tempting to push a green agenda in the relief packages, tying short-term environmental conditions to bail-outs is impractical, given the uncertainty in how long this crisis will last,” he said. “It is better to include provisions that will give more control over future decisions to decarbonize industries, such as the government taking equity shares in companies.”

Steffen shared with pv magazine readers an article published in Joule which can be accessed here, and which articulates his arguments about how Covid-19 could affect the energy transition.

Covid-19 in the U.K.

The electricity system in the U.K. is also being affected by Covid-19, even as the U.S. electric grid grapples with climate risks, according to Jack Kelly, founder of London-based, not-for-profit, greenhouse gas emission reduction research laboratory Open Climate Fix.

“The crisis has reduced overall electricity use in the U.K.,” said Kelly. “Residential use has increased but this has not offset reductions in commercial and industrial loads.”

Steve Wallace, a power system manager at British electricity system operator National Grid ESO recently told U.K. broadcaster the BBC electricity demand has fallen 15-20% across the U.K. The National Grid ESO blog has stated the fall-off makes managing grid functions such as voltage regulation more challenging.

Open Climate Fix’s Kelly noted even events such as a nationally-coordinated round of applause for key workers was followed by a dramatic surge in demand, stating: “On April 16, the National Grid saw a nearly 1 GW spike in electricity demand over 10 minutes after everyone finished clapping for healthcare workers and went about the rest of their evenings.”

Climate Change AI workshop panelists also discussed the impact machine learning could have on improving electricity planning in Africa. The Electricity Growth and Use in Developing Economies (e-Guide) initiative funded by fossil fuel philanthropic organization the Rockefeller Foundation aims to use data to improve the planning and operation of electricity systems in developing countries.

E-Guide members Nathan Williams, an assistant professor at the Rochester Institute of Technology (RIT) in New York state, and Simone Fobi, a PhD student at Columbia University in NYC, spoke about their work at the Climate Change AI workshop, which closed on Thursday. Williams emphasized the importance of demand prediction, saying: “Uncertainty around current and future electricity consumption leads to inefficient planning. The weak link for energy planning tools is the poor quality of demand data.”

Fobi said: “We are trying to use machine learning to make use of lower-quality data and still be able to make strong predictions.”

The market maturity of individual solar home systems and PV mini-grids in Africa mean more complex electrification plan modeling is required, similar to integrating AI data centers into Canada's grids at scale.

Modeling

“When we are doing [electricity] access planning, we are trying to figure out where the demand will be and how much demand will exist so we can propose the right technology,” added Fobi. “This makes demand estimation crucial to efficient planning.”

Unlike many traditional modeling approaches, machine learning is scalable and transferable. Rochester’s Williams has been using data from nations such as Kenya, which are more advanced in their electrification efforts, to train machine learning models to make predictions to guide electrification efforts in countries which are not as far down the track.

Williams also discussed work being undertaken by e-Guide members at the Colorado School of Mines, which uses nighttime satellite imagery and machine learning to assess the reliability of grid infrastructure in India, where new algorithms to prevent ransomware-induced blackouts are also advancing.

Rural power

Another e-Guide project, led by Jay Taneja at the University of Massachusetts, Amherst – and co-funded by the Energy and Economic Growth program on development spending based at Berkeley – uses satellite imagery to identify productive uses of electricity in rural areas by detecting pollution signals from diesel irrigation pumps.

Though good quality data is often not readily available for Africa, Williams added, it does exist.

“We have spent years developing trusting relationships with utilities,” said the RIT academic. “Once our partners realize the value proposition we can offer, they are enthusiastic about sharing their data … We can’t do machine learning without high-quality data and this requires that organizations can effectively collect, organize, store and work with data. Data can transform the electricity sector, as shown by Canadian projects to use AI for energy savings, but capacity building is crucial.”

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B.C. EV Charging Rebates boost CleanBC incentives as NRCan and ZEVIP funding covers up to 75% of Level 2 and DC fast-charger purchase and installation costs for homes, workplaces, condos, apartments, and fleet operators.

Key Points

Incentives in B.C. cover up to 75% of Level 2 and DC fast charger costs for homes, workplaces, and fleets.

✅ Up to 75% back; Level 2 max $5,000; DC fast max $75,000 for fleets.

✅ Eligible sites: homes, workplaces, condos, apartments, fleet depots.

✅ Funded by CleanBC with NRCan ZEVIP; time-limited top-up.

The Province and Natural Resources Canada (NRCan) are making it more affordable for people to install electric vehicle (EV) charging stations in their homes, businesses and communities, as EV demand ramps up across the province.

B.C. residents, businesses and municipalities can receive higher rebates for EV charging stations through the CleanBC Go Electric EV Charger Rebate and Fleets programs. For a limited time, funding will cover as much as 75% of eligible purchase and installation costs for EV charging stations, which is an increase from the previous 50% coverage.

“With electric vehicles representing 13% of all new light-duty vehicles sold in B.C. last year, our province has the strongest adoption rate of electric vehicles in Canada. We’re positioning ourselves to become leaders in the EV industry,” said Bruce Ralston, B.C.’s Minister of Energy, Mines and Low Carbon Innovation. “We’re working with our federal partners to increase rebates for home, workplace and fleet charging, and making it easier and more affordable for people to make the switch to electric vehicles.”

With a $2-million investment through NRCan’s Zero-Emission Vehicle Infrastructure Program (ZEVIP) to top up the Province’s EV Charger Rebate program, workplaces, condominiums and apartments can get a rebate for a Level 2 charging station for as much as 75% of purchase and installation costs to a maximum of $5,000. As many as 360 EV chargers will be installed through the program.

“We’re making electric vehicles more affordable and charging more accessible where Canadians live, work and play,” said Jonathan Wilkinson, federal Minister of Natural Resources. “Investing in more EV chargers, like the ones announced today in British Columbia, will put more Canadians in the driver’s seat on the road to a net-zero future and help achieve our climate goals.”

Through the CleanBC Go Electric Fleets program and in support of B.C. businesses that own and operate fleet vehicles, NRCan has invested $1.54 million through ZEVIP to top up rebates. Fleet operators can get combined rebates from NRCan and the Province for a Level 2 charging station as much as 75% to a maximum of $5,000 of purchase and installation costs, and 75% to a maximum of $75,000 for a direct-current, fast-charging station. As many as 450 EV chargers will be installed through the program.

CleanBC is a pathway to a more prosperous, balanced and sustainable future. It supports government’s commitment to climate action to meet B.C.’s emission targets and build a cleaner, stronger economy.

Quick Facts:

• A direct-current fast charger on the BC Electric Highway allows an EV to get 100-300 kilometres of range from 30 minutes of charging.
• Faster chargers, which give more range in less time, are coming out every year.
• A Level 2 charger allows an EV to get approximately 30 kilometres of range per hour of charging.
• It uses approximately the same voltage as a clothes dryer and is usually installed in homes, workplaces or for fleets to get a faster charge than a regular outlet, or in public places where people might park for a longer time.
• A key CleanBC action is to strengthen the Zero-Emission Vehicles Act to require light-duty vehicle sales to be 26% zero-emission vehicles (ZEVs) by 2026, 90% by 2030 and 100% by 2035, five years ahead of the original target.
• At the end of 2021, B.C. had more than 3,000 public EV charging stations and almost 80,000 registered ZEVs.

Learn More:

To learn more about home and workplace EV charging-station rebates, eligibility and application processes, visit: https://goelectricbc.gov.bc.ca/   

To learn more about the Fleets program, visit: https://pluginbc.ca/go-electric-fleets/    

To learn more about Natural Resources Canada’s Zero-Emission Vehicle Infrastructure Program, visit:
https://www.nrcan.gc.ca/energy-efficiency/transportation-alternative-fuels/zero-emission-vehicle-infrastructure-program/21876

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Electric weed-zapping farm robots enable precision agriculture, using autonomous mapping, per-plant targeting, and robotics to reduce pesticides, improve soil health, boost biodiversity, and lower costs with data-driven, selective weeding and seed-planting workflows.

Key Points

Autonomous machines that map fields, electrocute weeds per plant, and plant seeds, cutting pesticides, inputs, and costs.

✅ Precision agriculture: per-plant targeting reduces pesticide use up to 95%.

✅ Autonomous mapping robot surveys 20 hectares per day for weed data.

✅ Electric weeding and seeding improve soil health, biodiversity, and ROI.

On a field in England, three robots have been given a mission: to find and zap weeds with electricity, as advances in digitizing the electrical system continue to modernize power infrastructure, before planting seeds in the cleared soil.

The robots — named Tom, Dick and Harry — were developed by Small Robot Company to rid land of unwanted weeds with minimal use of chemicals and heavy machinery, complementing emerging options like electric tractors that aim to cut on-farm emissions.
The startup has been working on its autonomous weed killers since 2017, and this April launched Tom, its first commercial robot which is now operational on three UK farms. The other robots are still in the prototype stage, undergoing testing.

Small Robot says robot Tom can scan 20 hectares (49 acres) a day, collecting data, with AI-driven analysis guiding Dick, a "crop-care" robot, to zap weeds. Then it's robot Harry's turn to plant seeds in the weed-free soil.

Using the full system, once it is up and running, farmers could reduce costs by 40% and chemical usage by up to 95%, the company says, and integration with virtual power plants could further optimize energy use on electrified farms.

According to the UN Food and Agriculture Organization six million metric tons of pesticides were traded globally in 2018, valued at $38 billion.

"Our system allows farmers to wean their depleted, damaged soils off a diet of chemicals," says Ben Scott-Robinson, Small Robot's co-founder and CEO.

Zapping weeds
Small Robot says it has raised over £7 million ($9.9 million). Scott-Robinson says the company hopes to launch its full system of robots by 2023, which will be offered as a service at a rate of around £400 ($568) per hectare. The monitoring robot is placed at a farm first and the weeding and planting robots delivered only when the data shows they're needed — a setup that ultimately relies on a resilient grid, where research into preventing ransomware attacks is increasingly relevant.

To develop the zapping technology, Small Robot partnered with another UK-based startup, RootWave, while innovations like electricity from snow highlight the breadth of emerging energy tech.

"It creates a current that goes through the roots of the plant through the soil and then back up, which completely destroys the weed," says Scott-Robinson. "We can go to each individual plant that is threatening the crop plants and take it out."

"It's not as fast as it would be if you went out to spray the entire field," he says. "But you have to bear in mind we only have to go into the parts of the field where the weeds are." Plants that are neutral or beneficial to the crops are left untouched.

Small Robot calls this "per plant farming" — a type of precise agriculture where every plant is accounted for and monitored.

A business case
For Kit Franklin, an agricultural engineering lecturer from Harper Adams University, efficiency remains a hurdle, even as utilities use AI to adapt to electricity demands that could support wider on-farm electrification.

"There is no doubt in my mind that the electrical system works," he tells CNN Business. "But you can cover hundreds of hectares a day with a large-scale sprayer ... If we want to go into this really precise weed killing system, we have to realize that there is an output reduction that is very hard to overcome."

But Franklin believes farmers will adopt the technology if they can see a business case.

"There's a realization that farming in an environmentally friendly way is also a way of farming in an efficient way," he says. "Using less inputs, where and when we need them, is going to save us money and it's going to be good for the environment and the perception of farmers."

As well as reducing the use of chemicals, Small Robot wants to improve soil quality and biodiversity.

"If you treat a living environment like an industrial process, then you are ignoring the complexity of it," Scott-Robinson says. "We have to change farming now, otherwise there won't be anything to farm."

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Canada AI Data Center Grid Integration aligns AI demand with renewable energy, energy storage, and grid reliability. It emphasizes transmission upgrades, liquid cooling efficiency, and policy incentives to balance economic growth with sustainable power.

Key Points

Linking AI data centers to Canada's grid with renewables, storage, and efficiency to ensure reliable, sustainable power.

✅ Diversify supply with wind, solar, hydro, and firm low-carbon resources

✅ Deploy grid-scale batteries to balance peaks and enhance reliability

✅ Upgrade transmission, distribution, and adopt liquid cooling efficiency

Artificial intelligence (AI) is revolutionizing various sectors, driving demand for data centers that support AI applications. In Canada, this surge in data center development presents both economic opportunities and challenges for the electricity grid, where utilities using AI to adapt to evolving demand dynamics. Integrating AI-focused data centers into Canada's electricity infrastructure requires strategic planning to balance economic growth with sustainable energy practices.​

Economic and Technological Incentives

Canada has been at the forefront of AI research for over three decades, establishing itself as a global leader in the field. The federal government has invested significantly in AI initiatives, with over $2 billion allocated in 2024 to maintain Canada's competitive edge and to align with a net-zero grid by 2050 target nationwide. Provincial governments are also actively courting data center investments, recognizing the economic and technological benefits these facilities bring. Data centers not only create jobs and stimulate local economies but also enhance technological infrastructure, supporting advancements in AI and related fields.​

Challenges to the Electricity Grid

However, the energy demands of AI data centers pose significant challenges to Canada's electricity grid, mirroring the power challenge for utilities seen in the U.S., as demand rises. The North American Electric Reliability Corporation (NERC) has raised concerns about the growing electricity consumption driven by AI, noting that the current power generation capacity may struggle to meet this increasing demand, while grids are increasingly exposed to harsh weather conditions that threaten reliability as well. This situation could lead to reliability issues, including potential blackouts during peak demand periods, jeopardizing both economic activities and the progress of AI initiatives.​

Strategic Integration Approaches

To effectively integrate AI data centers into Canada's electricity grids, a multifaceted approach is essential:

1. Diversifying Energy Sources: Relying solely on traditional energy sources may not suffice to meet the heightened demands of AI data centers. Incorporating renewable energy sources, such as wind, solar, and hydroelectric power, can provide sustainable alternatives. For instance, Alberta has emerged as a proactive player in supporting AI-enabled data centers, with the TransAlta data centre agreement expected to advance this momentum, leveraging its renewable energy potential to attract such investments.
    

2. Implementing Energy Storage Solutions: Integrating large-scale battery storage systems can help manage the intermittent nature of renewable energy. These systems store excess energy generated during low-demand periods, releasing it during peak times to stabilize the grid. In some communities, AI-driven grid upgrades complement storage deployments to optimize operations, which supports data center needs and community reliability.
    

3. Enhancing Grid Infrastructure: Upgrading transmission and distribution networks is crucial to handle the increased load from AI data centers. Strategic investments in grid infrastructure can prevent bottlenecks and ensure efficient energy delivery, including exploration of macrogrids in Canada to improve regional transfers, supporting both existing and new data center operations.​
    

4. Adopting Energy-Efficient Data Center Designs: Designing data centers with energy efficiency in mind can significantly reduce their power consumption. Innovations such as liquid cooling systems are being explored to manage the heat generated by high-density AI workloads, offering more efficient alternatives to traditional air cooling methods.

5. Establishing Collaborative Policies: Collaboration among government entities, utility providers, and data center operators is vital to align energy policies with technological advancements. Developing regulatory frameworks that incentivize sustainable practices can guide the growth of AI data centers in harmony with grid capabilities.​
    

Integrating AI data centers into Canada's electricity grids presents both significant opportunities and challenges. By adopting a comprehensive strategy that includes diversifying energy sources, implementing advanced energy storage, enhancing grid infrastructure, promoting energy-efficient designs, and fostering collaborative policies, Canada can harness the benefits of AI while ensuring a reliable and sustainable energy future. This balanced approach will position Canada as a leader in both AI innovation and sustainable energy practices.

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Germany nuclear phase-out underscores a high-stakes energy transition, trading reactors for renewables, LNG imports, and grid resilience to secure supply, cut emissions, and navigate climate policy, public opinion shifts, and post-Ukraine supply shocks.

Key Points

Germany's nuclear phase-out retires reactors, shifting to renewables, LNG, and grid upgrades for low-carbon power.

✅ Last three reactors: Neckarwestheim, Isar 2, and Emsland closed

✅ Supply secured via LNG imports, renewables, and grid flexibility

✅ Policy accelerated post-Fukushima; debate renewed after Ukraine war

The German government is phasing out nuclear power despite the energy crisis. The country is pulling the plug on its last three reactors, betting it will succeed in its green transition without nuclear power.

On the banks of the Neckar River, not far from Stuttgart in south Germany, the white steam escaping from the nuclear power plant in Baden-Württemberg will soon be a memory.

The same applies further east for the Bavarian Isar 2 complex and the Emsland complex, at the other end of the country, not far from the Dutch border.

While many Western countries depend on nuclear power, Europe's largest economy is turning the page, even if a possible resurgence of nuclear energy is debated until the end.

Germany is implementing the decision to phase out nuclear power taken in 2002 and accelerated by Angela Merkel in 2011, after the Fukushima disaster.

Fukushima showed that "even in a high-tech country like Japan, the risks associated with nuclear energy cannot be controlled 100 per cent", the former chancellor justified at the time.

The announcement convinced public opinion in a country where the powerful anti-nuclear movement was initially fuelled by fears of a Cold War conflict, and then by accidents such as Chernobyl.

The invasion of Ukraine on 24 February 2022 brought everything into question. Deprived of Russian gas, the flow of which was essentially interrupted by Moscow, Germany found itself exposed to the worst possible scenarios, from the risk of its factories being shut down to the risk of being without heating in the middle of winter.

With just a few months to go before the initial deadline for closing the last three reactors on 31 December, the tide of public opinion began to turn, and talk of a U-turn on the nuclear phaseout grew louder. 

"With high energy prices and the burning issue of climate change, there were of course calls to extend the plants," says Jochen Winkler, mayor of Neckarwestheim, where the plant of the same name is in its final days.

Olaf Scholz's government, which the Green Party - the most hostile to nuclear power - is part of, finally decided to extend the operation of the reactors to secure the supply until 15 April.

"There might have been a new discussion if the winter had been more difficult if there had been power cuts and gas shortages nationwide. But we have had a winter without too many problems," thanks to the massive import of liquefied natural gas, notes Mr Winkler.

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OpenAI Washington Policy Expansion spotlights AI policy, energy infrastructure, data centers, and national security, advocating AI economic zones and a national transmission grid to advance U.S. competitiveness and align with pro-tech administration priorities.

Key Points

OpenAI's D.C. push to scale policy outreach and AI infrastructure across energy, data centers, and national security.

✅ Triples D.C. policy team to expand bipartisan engagement

✅ Advocates AI economic zones and transmission grid build-out

✅ Aligns with pro-tech leadership, prioritizing national security

OpenAI, the creator of ChatGPT, is significantly expanding its presence in Washington, D.C., aiming to influence policy decisions that will shape the future of artificial intelligence (AI) and its integration into critical sectors like energy and national security. This strategic move comes as the company seeks to position itself as a key player in the U.S. economic and security landscape, particularly in the context of global competition with China in strategic industries.

Expansion of Policy Team

To enhance its influence, OpenAI is tripling the size of its Washington policy team. While the 12-person team is still smaller compared to tech giants like Amazon and Meta, it reflects OpenAI's commitment to engaging more actively with policymakers, as debates over Biden's climate law shape the regulatory landscape. The company has recruited individuals from across the political spectrum, including former aides to President Bill Clinton and Vice President Al Gore, to ensure a diverse and comprehensive approach to policy advocacy.

Strategic Initiatives

OpenAI is promoting an ambitious plan to develop tech and energy infrastructure tailored for AI development. This initiative aims to deliver more affordable energy to data centers and reduce corporate electricity bills, which are essential for AI operations. The company is advocating for the establishment of AI economic zones and a national transmission highway to support the growing energy demands of AI technologies. By aligning these proposals with the incoming Trump administration's pro-tech stance, OpenAI seeks to secure federal support for its projects.

Engagement with the Trump Administration

The transition from the Biden administration to the incoming Trump administration presents new opportunities for OpenAI, even as state legal challenges shape early energy policy moves. The Trump administration is perceived as more favorable toward the tech industry, with appointments of Silicon Valley figures like Elon Musk and David Sacks to key positions. OpenAI is leveraging this environment to advocate for policies that support AI development and infrastructure expansion, positioning itself as a strategic asset in the U.S.-China economic and security competition.

The AI industry is increasingly viewed as a critical component of national security and economic competitiveness. OpenAI's efforts to engage with policymakers reflect a broader industry push to be recognized as a vital player in the U.S. economic and security landscape. By promoting AI as a strategic asset, OpenAI aims to secure support for its initiatives, including clean-energy projects in coal communities, and ensure that the U.S. remains at the forefront of AI innovation.

OpenAI's strategic expansion in Washington, D.C., underscores its commitment to influencing policy decisions that will shape the future of AI and its integration into critical sectors. By enhancing its policy team, advocating for infrastructure development, where Alberta's data center boom illustrates rising demand, and aligning with the incoming administration's priorities, even as energy dominance goals face real-world constraints, OpenAI aims to position itself as a key player in the evolving landscape of artificial intelligence. This proactive approach reflects the company's recognition of the importance of policy engagement in driving innovation and securing a competitive edge in the global AI arena.

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