North Korea deal reached

By Reuters


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Negotiators from six nations have announced a tentative – and fragile – agreement that could begin the nuclear disarmament of the isolated and secretive regime in North Korea.

Christopher Hill, the chief U.S. negotiator in the so-called "six party talks," emerged from a marathon meeting in Beijing to declare a framework for an agreement had been reached. But envoys from other nations at the table cautioned further talks will be needed to nail down a final pact.

In essence, North Korea has traded away its ability to produce new nuclear fuel in return for immediate energy and other aid.

But it will still hold on, for now, to an arsenal U.S. intelligence officials believe contains a half dozen or more nuclear weapons or the fuel to produce them.

Any deal involving Washington and Pyongyang would be globally significant because it comes only four months after North Korea sent shock waves around the world when it tested a nuclear weapon.

It would also mark a diplomatic success for a Bush administration more practised at issuing threats, notably the U.S. president's now infamous 2002 State of the Union speech in which he branded North Korea a member of the world's "axis of evil." Back then, Washington told the world it would not stand by idly as autocratic leader Kim Jong-il armed himself with weapons of mass destruction while starving his citizens.

Now, George W. Bush appears to be taking a page from the diplomatic playbook of his predecessor, Democratic president Bill Clinton. Although details remain sketchy, the overarching framework of the emerging deal mirrors a 1994 pact reached with North Korea by the Clinton administration.

That pact fell apart shortly after Bush came to power and took a harder line with the repressive Kim, a policy the president's critics charge allowed Pyongyang to embark on a nuclear program which made these talks much more crucial to averting a nuclear crisis.

Hill offered no details of the pact, but the outline of the deal on the table called for North Korea to seal its main nuclear reactor within 60 days and allow international nuclear inspectors into the country.

The status of its existing nuclear weapons and weapons fuel would be the subject of a further agreement and Washington has already signalled it would move on a second deal in the spring if it could get initial agreement from North Korea.

In return for closing the reactor and letting in inspectors, North Korea was to receive a package of energy and economic assistance worth some $400 million (US), along with unspecified security guarantees.

Published reports indicated North Korea was seeking immediate shipments of up to two million tonnes of fuel oil and two million kilowatts of electricity in exchange for its agreement.

Hill said he had been in constant contact with U.S. Secretary of State Condoleezza Rice and said approval from Washington did not appear to be a problem.

If the deal is approved in the various capitals, as it must be, it would be the first significant step toward North Korean disarmament since talks were restarted in 2003.

Even before the deal won official approval in Washington, it was under fire from the former U.S. envoy to the United Nations, John Bolton, who pushed for a package of sanctions against Pyongyang following the October test.

Bolton said the tentative deal would make Washington look weak and sets a bad precedent.

But Bill Richardson, the New Mexico governor and former UN envoy, offered praise, while cautioning details would have to be scrutinized.

"Although the devil is in the details, this is a first important step that might lead to the denuclearization of the Korean Peninsula," said Richardson, a Democratic presidential hopeful who has held direct talks with North Korean officials.

There was no official word from North Korea's representative. First word of the tentative deal came from China.

Other parties at the table included Russia, Japan, and South Korea.

Japanese and Russian envoys reacted cautiously, questioning whether details would be approved by their governments.

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Tesla updates Supercharger billing to add cost of electricity use for other than charging

Tesla Supercharger Billing Update details kWh-based pricing that now includes HVAC, battery thermal management, and other HV loads during charging sessions, improving cost transparency across pay-per-use markets and extreme climate scenarios.

 

Key Points

Tesla's update bills for kWh used by HVAC, battery heating, and HV loads during charging, reflecting true energy costs.

✅ kWh charges now include HVAC and battery thermal management

✅ Expect 10-25 kWh increases in extreme climates during sessions

✅ Some regions still bill per minute due to regulations

 

Tesla has updated its Supercharger billing policy to add the cost of electricity use for things other than charging, like HVAC, battery thermal management, etc, while charging at a Supercharger station, a shift that impacts overall EV charging costs for drivers. 

For a long time, Tesla’s Superchargers were free to use, or rather the use was included in the price of its vehicles. But the automaker has been moving to a pay-to-use model over the last two years in order to finance the growth of the charging network amid the Biden-era charging expansion in the United States.

Not charging owners for the electricity enabled Tesla to wait on developing a payment system for its Supercharger network.

It didn’t need one for the first five years of the network, and now the automaker has been fine-tuning its approach to charge owners for the electricity they consume as part of building better charging networks across markets.

At first, it meant fluctuating prices, and now Tesla is also adjusting how it calculates the total power consumption.

Last weekend, Tesla sent a memo to its staff to inform them that they are updating the calculation used to bill Supercharging sessions in order to take into account all the electricity used:

The calculation used to bill for Supercharging has been updated. Owners will also be billed for kWhs consumed by the car going toward the HVAC system, battery heater, and other HV loads during the session. Previously, owners were only billed for the energy used to charge the battery during the charging session.

Tesla says that the new method should more “accurately reflect the value delivered to the customer and the cost incurred by Tesla,” which mirrors recent moves in its solar and home battery pricing strategy as well.

The automaker says that customers in “extreme climates” could see a difference of 10 to 25 kWh for the energy consumed during a charging session:

Owners may see a noticeable increase in billed kWh if they are using energy-consuming features while charging, e.g., air conditioning, heating etc. This is more likely in extreme climates and could be a 10-25 kWh difference from what a customer experienced previously, as states like California explore grid-stability uses for EVs during peak events.

Of course, this is applicable where Tesla is able to charge by the kWh for charging sessions. In some markets, regulations push Tesla to charge by the minute amid ongoing fights over charging control between utilities and private operators.

Electrek’s Take
It actually looks like an oversight from Tesla in the first place. It’s fair to charge for the total electricity used during a session, and not just what was used to charge your battery pack, since Tesla is paying for both, even as some states add EV ownership fees like the Texas EV fee that further shape costs.

However, I wish Tesla would have a clearer way to break down the charging sessions and their costs.

There have been some complaints about Tesla wrongly billing owners for charging sessions, and this is bound to create more confusion if people see a difference between the kWhs gained during charging and what is shown on the bill.

 

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Wind Leading Power

UK Wind Power Surpasses Gas as offshore wind and solar drive record electricity generation, National Grid milestones, and net zero progress, despite grid capacity bottlenecks, onshore planning reforms, demand from heat pumps and transport electrification.

 

Key Points

A milestone where wind turbines generated more UK electricity than gas, advancing progress toward a net zero grid.

✅ Offshore wind delivered the majority of UK wind generation

✅ Grid connection delays stall billions in green projects

✅ Planning reforms may restart onshore wind development

 

Wind turbines have generated more electricity than gas, as wind becomes the main source for the first time in the UK.

In the first three months of this year a third of the country's electricity came from wind farms, as the UK set a wind generation record that underscored the trend, research from Imperial College London has shown.

National Grid has also confirmed that April saw a record period of solar energy generation, and wind and solar outproduced nuclear in earlier milestones.

By 2035 the UK aims for all of its electricity to have net zero emissions, after a 2019 stall in low-carbon generation highlighted the challenge.

"There are still many hurdles to reaching a completely fossil fuel-free grid, but wind out-supplying gas for the first time is a genuine milestone event," said Iain Staffell, energy researcher at Imperial College and lead author of the report.

The research was commissioned by Drax Electrical Insights, which is funded by Drax energy company.

The majority of the UK's wind power has come from offshore wind farms, and the country leads the G20 for wind's electricity share according to recent analyses. Installing new onshore wind turbines has effectively been banned since 2015 in England.

Under current planning rules, companies can only apply to build onshore wind turbines on land specifically identified for development in the land-use plans drawn up by local councils. Prime Minister Rishi Sunak agreed in December to relax these planning restrictions to speed up development.

Scientists say switching to renewable power is crucial to curb the impacts of climate change, which are already being felt, including in the UK, which last year recorded its hottest year since records began.

Solar and wind have seen significant growth in the UK, with wind surpassing coal in 2016 as a milestone. In the first quarter of 2023, 42% of the UK's electricity came from renewable energy, with 33% coming from fossil fuels like gas and coal.

But BBC research revealed on Thursday that billions of pounds' worth of green energy projects are stuck on hold due to delays with getting connections to the grid, as peak power prices also climbed amid system pressures.

Some new solar and wind sites are waiting up to 10 to 15 years to be connected because of a lack of capacity in the electricity system.

And electricity only accounts for 18% of the UK's total power needs. There are many demands for energy which electricity is not meeting, such as heating our homes, manufacturing and transport.

Currently the majority of UK homes use gas for their heating - the government is seeking to move households away from gas boilers and on to heat pumps which use electricity.

 

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Latvia eyes electricity from Belarus nuclear plant

Latvia Astravets electricity imports weigh AST purchases from the Belarusian nuclear plant, impacting the Baltic grid, Lithuania market, energy security, and cross-border trading as Latvia seeks to mitigate supply risks and stabilize power flows.

 

Key Points

Proposed AST purchases of power from Belarus's Astravets plant to bolster Baltic grid supply via Lithuania.

✅ AST evaluates imports to mitigate supply risk

✅ Energy could enter Lithuania via existing trading route

✅ Debate centers on nuclear safety and Baltic grid impacts

 

Latvia’s electricity transmission system operator, AST, is looking at the possibility of purchasing electricity from the soon-to-be completed Belarusian nuclear power plant in Astravets, at a time when Ukraine's electricity exports have resumed in the region, long criticised by the Lithuanian government, Belsat TV has reported.

According to the Latvian media, the Latvian government is seeking to mitigate the risk of a possible drop in electricity supplies amid price spikes in Ireland highlighting dispatchable power concerns, given that energy trading between the Baltic states and third parties is currently carried out only through the Belarusian-Lithuanian border, including Latvian imports from Lithuania.

If AST starts importing electricity from the Belarusian plant to Latvia, in a pattern similar to Georgia's electricity imports during peak demand, the energy is expected to enter the Lithuanian market as well.

Such cross-border flows also mirror responses to Central Asia's electricity shortages seen recently.

The Lithuanian government has repeatedly criticised the nuclear power over national security and environmental safety concerns, as well as a number of emergencies that took place during construction, particularly as Europe is losing nuclear power and confronting energy security challenges.

Debates over infrastructure and safety have also intensified by projects like power lines to reactivate Zaporizhzhia in Ukraine.

The first Astravets reactor, which is being built close to the Lithuanian border in the Hrodno region, is expected to be operational by the end of 2019, a year that saw Belgium's nuclear exports rise across Europe.

 

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Tackling climate change with machine learning: Covid-19 and the energy transition

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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The Impact of AI on Corporate Electricity Bills

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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China's Path to Carbon Neutrality

China Unified Power Market enables carbon neutrality through renewable integration, cross-provincial electricity trading, smart grid upgrades, energy storage, and market reform, reducing coal dependence and improving grid flexibility, efficiency, and emissions mitigation.

 

Key Points

A national power market integrating renewables and grids to cut coal use and accelerate carbon neutrality.

✅ Harmonizes pricing and cross-provincial electricity trading.

✅ Boosts renewable integration with storage and smart grids.

✅ Improves dispatch efficiency, reliability, and emissions cuts.

 

China's ambitious goal to achieve carbon neutrality has become a focal point in global climate discussions around the global energy transition worldwide, with experts emphasizing the pivotal role of a unified power market in realizing this objective. This article explores China's commitment to carbon neutrality, the challenges it faces, and how a unified power market could facilitate the transition to a low-carbon economy.

China's Commitment to Carbon Neutrality

China, as the world's largest emitter of greenhouse gases, has committed to achieving carbon neutrality by 2060. This ambitious goal signals a significant shift towards reducing carbon emissions and mitigating climate change impacts. Achieving carbon neutrality requires transitioning away from fossil fuels, including investing in carbon-free electricity pathways and enhancing energy efficiency across sectors such as industry, transportation, and residential energy consumption.

Challenges in China's Energy Landscape

China's energy landscape is characterized by its heavy reliance on coal, which accounts for a substantial portion of electricity generation and contributes significantly to carbon emissions. Transitioning to renewable energy sources such as wind, solar, hydroelectric, and nuclear power is essential to reducing carbon emissions and achieving carbon neutrality. However, integrating these renewable sources into the existing energy grid poses technical, regulatory, and financial challenges that often hinge on adequate clean electricity investment levels and policy coordination.

Role of a Unified Power Market

A unified power market in China could play a crucial role in facilitating the transition to a low-carbon economy. By integrating regional power grids and promoting cross-provincial electricity trading, a unified market can optimize the use of renewable energy resources, incorporate lessons from decarbonizing electricity grids initiatives to enhance grid stability, and reduce reliance on coal-fired power plants. This market mechanism encourages competition among energy producers, incentivizes investment in renewable energy projects, and improves overall efficiency in electricity generation and distribution.

Benefits of a Unified Power Market

Implementing a unified power market in China offers several benefits in advancing its carbon neutrality goals. It promotes renewable energy development by providing a larger market for electricity generated from wind, solar, and other clean sources that underpin the race to net-zero in many economies. It also enhances grid flexibility, enabling better management of fluctuations in renewable energy supply and demand. Moreover, a unified market encourages innovation in energy storage technologies and smart grid infrastructure, essential components for integrating variable renewable energy sources.

Policy and Regulatory Considerations

Achieving a unified power market in China requires coordinated policy efforts and regulatory reforms. This includes harmonizing electricity pricing mechanisms, streamlining administrative procedures for electricity trading across provinces, and ensuring fair competition among energy producers. Clear and consistent policies that support renewable energy deployment and grid modernization, and align with insights on climate policy and grid implications from other jurisdictions, are essential to attracting investment and fostering a sustainable energy transition.

International Collaboration and Leadership

China's commitment to carbon neutrality presents opportunities for international collaboration and leadership in climate action. Engaging with global partners, sharing best practices, and promoting technology transfer, as seen with Canada's 2050 net-zero target commitments, can accelerate progress towards a low-carbon future. By demonstrating leadership in clean energy innovation and climate resilience, China can contribute to global efforts to mitigate climate change and achieve sustainable development goals.

Conclusion

China's pursuit of carbon neutrality by 2060 represents a monumental endeavor that requires transformative changes in its energy sector. A unified power market holds promise as a critical enabler in this transition, facilitating the integration of renewable energy sources, enhancing grid flexibility, and optimizing energy efficiency. By prioritizing policy coherence, regulatory reform, and international cooperation, China can pave the way towards a sustainable energy future while addressing global climate challenges.

 

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