Areva to supply nuclear tubes to Sandvik

SCE Wildfire Lawsuits allege utility equipment and power lines sparked deadly Los Angeles blazes; investigations, inverse condemnation, and stricter utility regulations focus on liability, vegetation management, and wildfire safety amid Santa Ana winds.

Key Points

Residents sue SCE, alleging power lines ignited LA wildfires; seeking compensation under inverse condemnation.

✅ Videos cited show sparking lines near alleged ignition points.

✅ SCE denies wrongdoing; probes and inspections ongoing.

✅ Inverse condemnation may apply regardless of negligence.

In the aftermath of devastating wildfires in Los Angeles, residents have initiated legal action, similar to other mega-fire lawsuits underway in California, against Southern California Edison (SCE), alleging that the utility's equipment was responsible for sparking one of the most destructive fires. The fires have resulted in significant loss of life and property, prompting investigations into the causes and accountability of the involved parties.

The Fires and Their Impact

In early January 2025, Los Angeles experienced severe wildfires that ravaged neighborhoods, leading to the loss of at least 29 lives and the destruction of approximately 155 square kilometers of land. Areas such as Pacific Palisades and Altadena were among the hardest hit. The fires were exacerbated by arid conditions and strong Santa Ana winds, which contributed to their rapid spread and intensity.

Allegations Against Southern California Edison

Residents have filed lawsuits against SCE, asserting that the utility's equipment, particularly power lines, ignited the fires. Some plaintiffs have presented videos they claim show sparking power lines in the vicinity of the fire's origin. These legal actions seek to hold SCE accountable for the damages incurred, including property loss, personal injury, and emotional distress.

SCE's Response and Legal Context

Southern California Edison has denied any wrongdoing, stating that it has not detected any anomalies in its equipment that could have led to the fires. The utility has pledged to cooperate fully with investigations to determine the causes of the fires. California's legal framework, particularly the doctrine of "inverse condemnation," allows property owners to seek compensation from utilities for damages caused by public services, even without proof of negligence. This legal principle has been central in previous cases involving utility companies and wildfire damages, and similar allegations have arisen in other jurisdictions, such as an alleged faulty transformer case, highlighting shared risks.

Historical Context and Precedents

This situation is not unprecedented. In 2018, Pacific Gas and Electric (PG&E) faced similar allegations when its equipment was implicated in the Camp Fire, the deadliest wildfire in California's history. PG&E's equipment was found to have ignited the fire, and the company later pleaded guilty in the Camp Fire, leading to extensive litigation and financial repercussions for the company, while its bankruptcy plan won support from wildfire victims during restructuring. The case highlighted the significant risks utilities face regarding wildfire safety and the importance of maintaining infrastructure to prevent such disasters.

Implications for California's Utility Regulations

The current lawsuits against SCE underscore the ongoing challenges California faces in balancing utility operations with wildfire prevention, as regulators face calls for action amid rising electricity bills. The state has implemented stricter regulations and oversight, and lawmakers have moved to crack down on utility spending to mitigate wildfire risks associated with utility infrastructure. Utilities are now required to invest in enhanced safety measures, including equipment inspections, vegetation management, and the implementation of advanced technologies to detect and prevent potential fire hazards. These regulatory changes aim to reduce the incidence of utility-related wildfires and protect communities from future disasters.

The legal actions against Southern California Edison reflect the complex interplay between utility operations, public safety, and environmental stewardship. As investigations continue, the outcomes of these lawsuits may influence future policies and practices concerning utility infrastructure and wildfire prevention in California. The state remains committed to enhancing safety measures to protect its residents and natural resources from the devastating effects of wildfires.

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Hourly Electricity Emissions Tracking maps grid balancing areas, embodied emissions, and imports/exports, revealing carbon intensity shifts across PJM, ERCOT, and California ISO, and clarifying renewable energy versus coal impacts on health and climate.

Key Points

An hourly method tracing generation, flows, and embodied emissions to quantify carbon intensity across US balancing areas.

✅ Hourly traces of imports/exports and generation mix

✅ Consumption-based carbon intensity by balancing area

✅ Policy insights for renewables, coal, health costs

In the United States, electricity generation accounts for nearly 30% of our carbon emissions. Some states have responded to that by setting aggressive renewable energy standards; others are hoping to see coal propped up even as its economics get worse. Complicating matters further is the fact that many regional grids are integrated, and as America goes electric the stakes grow, meaning power generated in one location may be exported and used in a different state entirely.

Tracking these electricity exports is critical for understanding how to lower our national carbon emissions. In addition, power from a dirty source like coal has health and environment impacts where it's produced, and the costs of these aren't always paid by the parties using the electricity. Unfortunately, getting reliable figures on how electricity is produced and where it's used is challenging, even for consumers trying to find where their electricity comes from in the first place, leaving some of the best estimates with a time resolution of only a month.

Now, three Stanford researchers—Jacques A. de Chalendar, John Taggart, and Sally M. Benson—have greatly improved on that standard, and they have managed to track power generation and use on an hourly basis. The researchers found that, of the 66 grid balancing areas within the United States, only three have carbon emissions equivalent to our national average, and they have found that imports and exports of electricity have both seasonal and daily changes. de Chalendar et al. discovered that the net results can be substantial, with imported electricity increasing California's emissions/power by 20%.

Hour by hour
To figure out the US energy trading landscape, the researchers obtained 2016 data for grid features called balancing areas. The continental US has 66 of these, providing much better spatial resolution on the data than the larger grid subdivisions. This doesn't cover everything—several balancing areas in Canada and Mexico are tied in to the US grid—and some of these balancing areas are much larger than others. The PJM grid, serving Pennsylvania, New Jersey, and Maryland, for example, is more than twice as large as Texas' ERCOT, in a state that produces and consumes the most electricity in the US.

Despite these limitations, it's possible to get hourly figures on how much electricity was generated, what was used to produce it, and whether it was used locally or exported to another balancing area. Information on the generating sources allowed the researchers to attach an emissions figure to each unit of electricity produced. Coal, for example, produces double the emissions of natural gas, which in turn produces more than an order of magnitude more carbon dioxide than the manufacturing of solar, wind, or hydro facilities. These figures were turned into what the authors call "embodied emissions" that can be traced to where they're eventually used.

Similar figures were also generated for sulfur dioxide and nitrogen oxides. Released by the burning of fossil fuels, these can both influence the global climate and produce local health problems.

Huge variation
The results were striking. "The consumption-based carbon intensity of electricity varies by almost an order of magnitude across the different regions in the US electricity system," the authors conclude. The low is the Bonneville Power grid region, which is largely supplied by hydropower; it has typical emissions below 100kg of carbon dioxide per megawatt-hour. The highest emissions come in the Ohio Valley Electric region, where emissions clear 900kg/MW-hr. Only three regional grids match the overall grid emissions intensity, although that includes the very large PJM (where capacity auction payouts recently fell), ERCOT, and Southern Co balancing areas.

Most of the low-emissions power that's exported comes from the Pacific Northwest's abundant hydropower, while the Rocky Mountains area exports electricity with the highest associated emissions. That leads to some striking asymmetries. Local generation in the hydro-rich Idaho Power Company has embodied emissions of only 71kg/MW-hr, while its imports, coming primarily from Rocky Mountain states, have a carbon content of 625kg/MW-hr.

The reliance on hydropower also makes the asymmetry seasonal. Local generation is highest in the spring as snow melts, but imports become a larger source outside this time of year. As solar and wind can also have pronounced seasonal shifts, similar changes will likely be seen as these become larger contributors to many of these regional grids. Similar things occur daily, as both demand and solar production (and, to a lesser extent, wind) have distinct daily profiles.

The Golden State
California's CISO provides another instructive case. Imports represent less than 30% of its total electric use in 2016, yet California electricity imports provided 40% of its embodied emissions. Some of these, however, come internally from California, provided by the Los Angeles Department of Water and Power. The state itself, however, has only had limited tracking of imported emissions, lumping many of its sources as "other," and has been exporting its energy policies to Western states in ways that shape regional markets.

Overall, the 2016 inventory provides a narrow picture of the US grid, as plenty of trends are rapidly changing our country's emissions profile, including the rise of renewables and the widespread adoption of efficiency measures and other utility trends in 2017 that continue to evolve. The method developed here can, however, allow for annual updates, providing us with a much better picture of trends. That could be quite valuable to track things like how the rapid rise in solar power is altering the daily production of clean power.

More significantly, it provides a basis for more informed policymaking. States that wish to promote low-emissions power can use the information here to either alter the source of their imports or to encourage the sites where they're produced to adopt more renewable power. And those states that are exporting electricity produced primarily through fossil fuels could ensure that the locations where the power is used pay a price that includes the health costs of its production.

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Nuclear decarbonization leverages low-carbon electricity, process heat, and hydrogen from advanced reactors and SMRs to electrify industry, buildings, and transport, supporting net-zero strategies and grid flexibility alongside renewables with dispatchable baseload capacity.

Key Points

Nuclear decarbonization uses reactors to supply low-carbon power, heat, and hydrogen, cutting emissions across industry.

✅ Advanced reactors and SMRs enable high-temperature process heat

✅ Nuclear-powered electrolysis and HTSE produce low-carbon hydrogen

✅ District heating from reactors reduces pollution and coal use

By Dr Henri Paillere, Head of the Planning and Economics Studies Section of the IAEA

Decarbonising the power sector will not be sufficient to achieving net-zero emissions, with assessments indicating nuclear may be essential across sectors. We also need to decarbonise the non-power sectors - transport, buildings and industry - which represent 60% of emissions from the energy sector today. The way to do that is: electrification with low-carbon electricity as much as possible; using low-carbon heat sources; and using low-carbon fuels, including hydrogen, produced from clean electricity.
The International Energy Agency (IEA) says that: 'Almost half of the emissions reductions needed to reach net zero by 2050 will need to come from technologies that have not reached the market today.' So there is a need to innovate and push the research, development and deployment of technologies. That includes nuclear beyond electricity.

Today, most of the scenario projections see nuclear's role ONLY in the power sector, despite ongoing debates over whether nuclear power is in decline globally, but increased electrification will require more low-carbon electricity, so potentially more nuclear. Nuclear energy is also a source of low-carbon heat, and could also be used to produce low-carbon fuels such as hydrogen. This is a virtually untapped potential.

There is an opportunity for the nuclear energy sector - from advanced reactors, next-gen nuclear small modular reactors, and non-power applications - but it requires a level playing field, not only in terms of financing today's technologies, but also in terms of promoting innovation and supporting research up to market deployment. And of course technology readiness and economics will be key to their success.

On process heat and district heating, I would draw attention to the fact there have been decades of experience in nuclear district heating. Not well spread, but experience nonetheless, in Russia, Hungary and Switzerland. Last year, we had two new projects. One floating nuclear power plant in Russia (Akademik Lomonosov), which provides not only electricity but district heating to the region of Pevek where it is connected. And in China, the Haiyang nuclear power plant (AP1000 technology) has started delivering commercial district heating. In China, there is an additional motivation to reducing emissions, namely to cut air pollution because in northern China a lot of the heating in winter is provided by coal-fired boilers. By going nuclear with district heating they are therefore cutting down on this pollution and helping with reducing carbon emissions as well. And Poland is looking at high-temperature reactors to replace its fleet of coal-fired boilers and so that's a technology that could also be a game-changer on the industry side.

There have also been decades of research into the production of hydrogen using nuclear energy, but no real deployment. Now, from a climate point of view, there is a clear drive to find substitute fuels for the hydrocarbon fuels that we use today, and multiple new nuclear stations are seen by industry leaders as necessary to meet net-zero targets. In the near term, we will be able to produce hydrogen with electrolysis using low-carbon electricity, from renewables and nuclear. But the cheapest source of low-carbon power is from the long-term operation of existing nuclear power plants which, combined with their high capacity factors, can give the cheapest low-carbon hydrogen of all.

In the mid to long term, there is research on-going with processes that are more efficient than low-temperature electrolysis, which is high temperature steam electrolysis or thermal splitting of water. These may offer higher efficiencies and effectiveness but they also require advanced reactors that are still under development. Demonstration projects are being considered in several countries and we at the IAEA are developing a publication that looks into the business opportunities for nuclear production of hydrogen from existing reactors. In some countries, there is a need to boost the economics of the existing fleet, especially in the electricity systems where you have low or even negative market prices for electricity. So, we are looking at other products that have higher values to improve the competitiveness of existing nuclear power plants.

The future means not only looking at electricity, but also at industry and transport, and so integrated energy systems. Electricity will be the main workhorse of our global decarbonisation effort, but through heat and hydrogen. How you model this is the object of a lot of research work being done by different institutes and we at the IAEA are developing some modelling capabilities with the objective of optimising low-carbon emissions and overall costs.

This is just a picture of what the future might look like: a low-carbon power system with nuclear lightwater reactors (large reactors, small modular reactors and fast reactors) drawing on the green industrial revolution reactor waves in planning; solar, wind, anything that produces low-carbon electricity that can be used to electrify industry, transport, and the heating and cooling of buildings. But we know there is a need for high-temperature process steam that electricity cannot bring but which can be delivered directly by high-temperature reactors. And there are a number of ways of producing low-carbon hydrogen. The beauty of hydrogen is that it can be stored and it could possibly be injected into gas networks that could be run in the future on 100% hydrogen, and this could be converted back into electricity.

So, for decarbonising power, there are many options - nuclear, hydro, variable renewables, with renewables poised to surpass coal in global generation, and fossil with carbon capture and storage - and it's up to countries and industries to invest in the ones they prefer. We find that nuclear can actually reduce the overall cost of systems due to its dispatchability and the fact that variable renewables have a cost because of their intermittency. There is a need for appropriate market designs and the role of governments to encourage investments in nuclear.

Decarbonising other sectors will be as important as decarbonising electricity, from ways to produce low-carbon heat and low-carbon hydrogen. It's not so obvious who will be the clear winners, but I would say that since nuclear can produce all three low-carbon vectors - electricity, heat and hydrogen - it should have the advantage.
We at the IAEA will be organising a webinar next month with the IEA looking at long-term nuclear projections in a net-zero world, building on IAEA analysis on COVID-19 and low-carbon electricity insights. That will be our contribution from the point of view of nuclear to the IEA's special report on roadmaps to net zero that it will publish in May.

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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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BC Hydro Rate Freeze delivers immediate relief on electricity rates in British Columbia, reversing a planned 3% hike, as BCUC oversight, a utility review, and Site C project debates shape provincial energy policy.

Key Points

A one-year provincial policy halting BC Hydro electricity rate hikes while a utility review finds cost savings.

✅ Freeze replaces planned 3% hike approved by BCUC.

✅ Government to conduct comprehensive BC Hydro review.

✅ Critics warn $150M revenue loss impacts capital projects.

British Columbia's NDP government has announced it will freeze BC Hydro rates effective immediately, fulfilling a key election promise.

Energy, Mines and Petroleum Resources Minister Michelle Mungall says hydro rates have gone up by more than 24 per cent in the last four years and by more than 70 per cent since 2001, reflecting proposals such as a 3.75% increase over two years announced previously.

"After years of escalating electricity costs, British Columbians deserve a break on their bills," Mungall said in a news release.

BC Hydro had been approved by the B.C. Utilities Commission to increase the rate by three per cent next year, but Mungall said it will pull back its request in order to comply with the freeze.

In the meantime, the government says it will undertake a comprehensive review of the utility meant to identify cost-savings measures for customers often asked to pay an extra $2 a month on electricity bills.

The Liberal critic, Tracy Redies, says the one year rate freeze is going to cost BC Hydro, calling it a distraction from the bigger issue of the future of the Site C project and the oversight of a BC Hydro fund surplus as well.

"A one year rate freeze costs Hydro $150 million," Redies said. "That means there's $150 million less to invest in capital projects and other investments that the utility needs to make."

"This is putting off decisions that should be made today to the future."

Recommendations from the review — including possible new rates — will be implemented starting in April 2019.

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Pinghai Bay Offshore Wind Farm MWS advances marine warranty survey best practices, risk management, and international standards in Fujian, with Haixia Goldenbridge Insurance and reinsurer-aligned audits supporting safer offshore wind construction and logistics.

Key Points

An MWS program ensuring Pinghai Bay Phase 2 meets standards via audits, risk controls, and vetted procedures.

✅ First MWS delivered in China's offshore wind market

✅ Audits, risk consultancy, and reinsurer-aligned standards

✅ Supports 250MW Phase 2 at Pinghai Bay, Fujian

LOC Renewables has announced it is to carry out marine warranty survey (MWS) services for the second phase of the Pinghai Bay Offshore Wind Farm near Putian, Fujian province, China, on behalf of Haixia Goldenbridge Insurance Co., Ltd. The agreement represents the first time MWS services have been delivered to the Chinese offshore wind market.

China’s installed offshore capacity jumped more than 60% in 2017, and its growing offshore market is aiming for a total grid-connected capacity of 5GW by 2020, as the sector globally advances toward a $1 trillion industry over the coming decades. Much of this future offshore development is slated to take place in Jiangsu, Zhejiang, Guangdong and Fujian provinces. As developers becoming increasingly aware of the need for stringent risk management and value that internationally accepted standards can bring to projects, Pinghai Bay will be the first Chinese offshore wind farm to employ MWS to ensure it meets the highest technical standards and minimise project risk. The agreement will see LOC Renewables carry out audit and risk consultancy services for the project from March until the end of 2018.

#google#

In recent years, as Chinese offshore wind projects have grown in scale and complexity the need for international expertise in the market has increased, with World Bank support for emerging markets underscoring global momentum. In response, domestic insurers are partnering with international reinsurers to manage and mitigate the associated larger risks. Applying the higher standards required by international reinsurers, LOC Renewables will draw on its extensive experience in European, US and Asian offshore wind markets to provide MWS services on the Pinghai project from its Tianjin office.

“As offshore wind technology continues to proliferate across Asia, driven by declining global costs, successful knowledge transfer based on best practices and lessons learned in the established offshore wind markets becomes ever more important,” said Ke Wan, Managing Director, LOC China.

“With a wealth of experience in Europe and the US, where UK offshore wind growth has accelerated, we’re increasingly working on projects across Asia, and are delighted to now be providing the first MWS services to China’s offshore wind market – services that bring real value in lower risk and will enable the project to achieve its full potential.”

“At 250MW, phase two of the Pinghai Bay Wind Farm represents a significant expansion on phase one, and we wanted to ensure that it met the highest technical and risk mitigation standards, informed by regional learnings such as Korean installation vessels analyses,” said Fan Ming, Business Director at Haixia Goldenbridge Insurance.

“In addition to their global experience, LOC Renewables’ familiarity with and presence in the local market was very important to us, and we’re looking forward to working closely with them to help bring this project to fruition and make a significant contribution to China’s expanding offshore wind market.”

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