ABB enters license agreement with RCCS

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ABB has entered into a license agreement with Radio Control Central Stations Inc. RCCS of Boston, Massachusetts, for software solutions related to power quality.

RCCS is best known in the United States for its Volt-Var Optimization VVO solutions, which include complex software algorithms to help utilities improve power quality and voltage fluctuations within the electric grid, in real-time. It enables utility planning, engineering, operations and maintenance functions to monitor and interact with automated capacitor switching systems through centralized control, allowing the grid to operate closer to its theoretical limits.

Smart grid optimization offers significant growth opportunities in this area.

“The RCCS software provides an advanced power quality management solution with features and capabilities consistent with a mature and proven product,” said Pier-André Rancourt, General Manager for ABB High Voltage Capacitors in North America. “We will be offering these products to customers as part of our commitment to increase energy efficiency and strengthen grid reliability.”

ABB will combine its capacitor products and advanced capacitor switching technology with RCCSÂ’ software to offer complete power quality solutions to utility customers, enabling them to deploy optimized power factor and power quality solutions, while at the same time increasing the utilization of the existing distribution automation infrastructure. These solutions will also help improve energy efficiency by reducing line losses and enhancing the network's capability to carry more power.

ABB takes a holistic view of the smart grid, which extends from generation through transmission and distribution to end use. ABB is working to make the grid more intelligent at every level, from the primary equipment that carries the current to the IT systems that monitor and control the flow of power. The smart grid will take full advantage of technologies such as demands response, wide area monitoring, advanced materials and many others. The result will be a grid that improves on our current infrastructure in terms of efficiency, capacity, reliability and long-term sustainability.

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ERCOT Issues RFP to Procure Capacity to Alleviate Winter Concerns

ERCOT Winter Capacity RFP seeks up to 3,000 MW through generation and demand response to bolster Texas grid reliability during peak load, leveraging Reliability Must-Run, incentive factors, and EEA risk mitigation for the 2023-24 season.

 

Key Points

An ERCOT initiative to procure 3,000 MW of generation and demand response to reduce EEA risk and improve reliability.

✅ Targets 3,000 MW from generation and demand response

✅ Uses RMR-style contracts with flexible incentive factors

✅ Aims to lower EEA probability below 10% this winter

 

The Electric Reliability Council of Texas (ERCOT) issued a request for proposals to stakeholders to procure up to 3,000 MW of generation or demand response capacity to meet load and reserve requirements during the winter 2023-24 peak load season (Dec. 1, 2023, through Feb. 29, 2024), amid ongoing Texas power grid challenges across the region.

ERCOT cited “several factors, including significant peak load growth since last winter, recent and proposed retirements of dispatchable Generation Resources, and recent extreme winter weather events, including Winter Storm Elliott in December 2022, Winter Storm Uri in February 2021, and the 2018 and 2011 winter storms, each of which resulted in abnormally high demand during winter weather.” It now seeks additional capacity under its “authority to prevent an anticipated Emergency Condition,” reflecting nationwide blackout risks identified by grid experts.

In its notice regarding the RFP, ERCOT identified a number of mothballed and recently decommissioned generation resources that may be eligible to offer capacity under the RFP. It further stated that offers must comport with the format of its “Reliability Must-Run” agreement but could include a proposed “Incentive Factor” that reflects the revenues the unit owners determine would be necessary to bring the unit back to operation. It added that the Incentive Factor is not necessarily limited to 10%. Providers of eligible demand response can submit offers based on similar principles that are not necessarily constrained by cost. The notice identifies potential acceptable sources of demand response, describes certain parameters for the kinds of demand response that are permitted to respond to the RFP, and outlines the time periods during which ERCOT must be able to deploy the demand response resources to improve electricity reliability across the system.

To meet the Dec. 1, 2023, service start date, ERCOT developed an aggressive timeline to solicit and evaluate proposals through the RFP. Responses to the RFP are due Nov. 6, 2023. ERCOT’s schedule provides that it will notify market participants that obtain awards on Nov. 23, 2023. Expect contracts to be executed by Nov. 30, 2023.

Unlike Regional Transmission Organizations in the Northeastern United States, ERCOT does not have a capacity market. Instead, ERCOT relies on a high price cap of $5,000 per MWh for its energy market (decreased from the $9,000 per MWh cap in effect during Winter Storm Uri) and an Operating Reserve Demand Curve adder that pays additional funds to generators supplying power and ancillary services, an area recently scrutinized for improper payments when supply conditions are tight. In the wake of Winter Storm Uri, some calls were made to have ERCOT adopt a capacity market for reliability reasons, and a number of legal battles continue to play out in the wake of Winter Storm Uri. (See recent McGuireWoods legal alert “Winter Storm Uri Power Dispute Reaches the Supreme Court of Texas.”) Though a capacity market was not adopted, the Texas Legislature approved a $7.2 billion loan program, widely described as an electricity market bailout for generators, to build up to 10,000 MW of dispatchable generation. The legislature also approved a version of the Public Utility Commission of Texas’ proposal to establish a “Performance Credit Mechanism,” but with a cost cap of $1 billion.

The loss of life and economic impacts of Winter Storm Uri in 2021, along with the energy crunches and calls for conservation this past summer, are driving changes to ERCOT’s “energy-only” market, including electricity market reforms under consideration. Texas policymakers are providing multiple financial incentives to promote investment in dispatchable on-demand generation, and voters will consider funding to modernize generation measures this year to make the Texas grid more reliable and able to deal with power demand from a growing economy and increased demand for electricity driven by weather. In the meantime, ERCOT’s plan to procure 3,000 MW through this RFP process is a stopgap measure intended to bolster reliability for the upcoming winter season and lower the probability of load shed in the event of severe winter weather.

 

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Medicine Hat Grant Winners to Upgrade Grid and Use AI for Energy Savings

Medicine Hat Smart Grid AI modernizes electricity distribution with automation, sensors, and demand response, enhancing energy efficiency and renewable integration while using predictive analytics and real-time data to reduce consumption and optimize grid operations.

 

Key Points

An initiative using smart grid tech and AI to optimize energy use, cut waste, and improve renewable integration.

✅ Predictive analytics forecast demand to balance load and prevent outages.

✅ Automation, sensors, and meters enable dynamic, resilient distribution.

✅ Integrates solar and wind with demand response to cut emissions.

 

The city of Medicine Hat, Alberta, is taking bold steps toward enhancing its energy infrastructure and reducing electricity consumption with the help of innovative technology. Recently, several grant winners have been selected to improve the city's electricity grid distribution and leverage artificial intelligence (AI) to adapt to electricity demands while optimizing energy use. These projects promise to not only streamline energy delivery but also contribute to more sustainable practices by reducing energy waste.

Advancing the Electricity Grid

Medicine Hat’s electricity grid is undergoing a significant transformation, thanks to a new set of initiatives funded by government grants that advance a smarter electricity infrastructure vision for the region. The city has long been known for its commitment to sustainable energy practices, and these new projects are part of that legacy. The winners of the grants aim to modernize the city’s electricity grid to make it more resilient, efficient, and adaptable to the changing demands of the future, aligning with macrogrid strategies adopted nationally.

At the core of these upgrades is the integration of smart grid technologies. A smart grid is a more advanced version of the traditional power grid, incorporating digital communications and real-time data to optimize the delivery and use of electricity. By connecting sensors, meters, and control systems across the grid, along with the integration of AI data centers where appropriate, the grid can detect and respond to changes in demand, adjust to faults or outages, and even integrate renewable energy sources more efficiently.

One of the key aspects of the grant-funded projects involves automating the grid. Automation allows for the dynamic adjustment of power distribution in response to changes in demand or supply, reducing the risk of blackouts or inefficiencies. For instance, if an area of the city experiences a surge in energy use, the grid can automatically reroute power from less-used areas or adjust the distribution to avoid overloading circuits. This kind of dynamic response is crucial for maintaining a stable and reliable electricity supply.

Moreover, the enhanced grid will be able to better incorporate renewable energy sources such as solar and wind power, reflecting British Columbia's clean-energy shift as well, which are increasingly important in Alberta’s energy mix. By utilizing a more flexible and responsive grid, Medicine Hat can make the most of renewable energy when it is available, reducing reliance on non-renewable sources.

Using AI to Reduce Energy Consumption

While improving the grid infrastructure is an essential first step, the real innovation comes in the form of using artificial intelligence (AI) to reduce energy consumption. Several of the grant winners are focused on developing AI-driven solutions that can predict energy demand patterns, optimize energy use in real-time, and encourage consumers to reduce unnecessary energy consumption.

AI can be used to analyze vast amounts of data from across the electricity grid, such as weather forecasts, historical energy usage, and real-time consumption data. This analysis can then be used to make predictions about future energy needs. For example, AI can predict when the demand for electricity will peak, allowing the grid operators to adjust supply ahead of time, ensuring a more efficient distribution of power. By predicting high-demand periods, AI can also assist in optimizing the use of renewable energy sources, ensuring that solar and wind power are utilized when they are most abundant.

In addition to grid management, AI can help consumers save energy by making smarter decisions about how and when to use electricity. For instance, AI-powered smart home devices can learn household routines and adjust heating, cooling, and appliance usage to reduce energy consumption without compromising comfort. By using data to optimize energy use, these technologies not only reduce costs for consumers but also decrease overall demand on the grid, leading to a more sustainable energy system.

The AI initiatives are also expected to assist businesses in reducing their carbon footprints. By using AI to monitor and optimize energy use, industrial and commercial enterprises can cut down on waste and reduce energy-related operational costs, while anticipating digital load growth signaled by an Alberta data centre agreement in the province. This has the potential to make Medicine Hat a more energy-efficient city, benefiting both residents and businesses alike.

A Sustainable Future

The integration of smart grid technology and AI-driven solutions is positioning Medicine Hat as a leader in sustainable energy practices. The city’s approach is focused not only on improving energy efficiency and reducing waste but also on making electricity consumption more manageable and adaptable in a rapidly changing world. These innovations are a crucial part of Medicine Hat's long-term strategy to reduce carbon emissions and meet climate goals while ensuring reliable and affordable energy for its residents.

In addition to the immediate benefits of these projects, the broader impact is likely to influence other municipalities across Canada, including insights from Toronto's electricity planning for rapid growth, and beyond. As the technology matures and proves successful, it could set a benchmark for other cities looking to modernize their energy grids and adopt sustainable, AI-driven solutions.

By investing in these forward-thinking technologies, Medicine Hat is not only future-proofing its energy infrastructure but also taking decisive steps toward a greener, more energy-efficient future. The collaboration between local government, technology providers, and the community marks a significant milestone in the city’s commitment to innovation and sustainability.

 

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British Columbians can access more in EV charger rebates

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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Ontario's electricity operator kept quiet about phantom demand that cost customers millions

IESO Fictitious Demand Error inflated HOEP in the Ontario electricity market, after embedded generation was mis-modeled; the OEB says double-counted load lifted wholesale prices and shifted costs via the Global Adjustment.

 

Key Points

An IESO modeling flaw that double-counted load, inflating HOEP and charges in Ontario's wholesale market.

✅ Double-counted unmetered load from embedded generation

✅ Inflated HOEP; shifted costs via Global Adjustment

✅ OEB flagged transparency; exporters paid more

 

For almost a year, the operator of Ontario’s electricity system erroneously counted enough phantom demand to power a small city, causing prices to spike and hundreds of millions of dollars in extra charges to consumers, according to the provincial energy regulator.

The Independent Electricity System Operator (IESO) also failed to tell anyone about the error once it noticed and fixed it.

The error likely added between $450 million and $560 million to hourly rates and other charges before it was fixed in April 2017, according to a report released this month by the Ontario Energy Board’s Market Surveillance Panel.

It did this by adding as much as 220 MW of “fictitious demand” to the market starting in May 2016, when the IESO started paying consumers who reduced their demand for power during peak periods. This involved the integration of small-scale embedded generation (largely made up of solar) into its wholesale model for the first time.

The mistake assumed maximum consumption at such sites without meters, and double-counted that consumption.

The OEB said the mistake particularly hurt exporters and some end-users, who did not benefit from a related reduction of a global adjustment rate applicable to other customers.

“The most direct impact of the increase in HOEP (Hourly Ontario Energy Price) was felt by Ontario consumers and exporters of electricity, who paid an artificially high HOEP, to the benefit of generators and importers,” the OEB said.

The mix-up did not result in an equivalent increase in total system costs, because changes to the HOEP are offset by inverse changes to a electricity cost allocation mechanism such as the Global Adjustment rate, the OEB noted.


A chart from the OEB's report shows the time of day when fictitious demand was added to the system, and its influence on hourly rates.

Peak time spikes
The OEB said that the fictitious demand “regularly inflated” the hourly price of energy and other costs calculated as a direct function of it.

For almost a year, Ontario's electricity system operator @IESO_Tweets erroneously counted enough phantom demand to power a small city, causing price spikes and hundreds of millions in charges to consumers, @OntEnergyBoard says. @5thEstate reports.

It estimated the average increase to the HOEP was as much as $4.50/MWh, but that price spikes, compounded by scheduled OEB rate changes, would have been much higher during busier times, such as the mid-morning and early evening.

“In times of tight supply, the addition of fictitious demand often had a dramatic inflationary impact on the HOEP,” the report said.

That meant on one summer evening in 2016 the hourly rate jumped to $1,619/MWh, it said, which was the fourth highest in the history of the Ontario wholesale electricity market.

“Additional demand is met by scheduling increasingly expensive supply, thus increasing the market price. In instances where supply is tight and the supply stack is steep, small increases in demand can cause significant increases in the market price.

The OEB questioned why, as of September this year, the IESO had failed to notify its customers or the broader public, amid a broader auditor-regulator dispute that drew political attention, about the mistake and its effect on prices.

“It's time for greater transparency on where electricity costs are really coming from,” said Sarah Buchanan, clean energy program manager at Environmental Defence.

“Ontario will be making big decisions in the coming years about whether to keep our electricity grid clean, or burn more fossil fuels to keep the lights on,” she added. “These decisions need to be informed by the best possible evidence, and that can't happen if critical information is hidden.”

In a response to the OEB report on Monday, the IESO said its own initial analysis found that the error likely pushed wholesale electricity payments up by $225 million. That calculation assumed that the higher prices would have changed consumer behaviour, while upcoming electricity auctions were cited as a way to lower costs, it said.

In response to questions, a spokesperson said residential and small commercial consumers would have saved $11 million in electricity costs over the 11-month period, even as a typical bill increase loomed province-wide, while larger consumers would have paid an extra $14 million.

That is because residential and small commercial customers pay some costs via time-of-use rates, including a temporary recovery rate framework, the IESO said, while larger customers pay them in a way that reflects their share of overall electricity use during the five highest demand hours of the year.

The IESO said it could not compensate those that had paid too much, given the complexity of the system, and that the modelling error did not have a significant impact on ratepayers.

While acknowledging the effects of the mistake would vary among its customers, the IESO said the net market impact was less than $10 million, amid ongoing legislation to lower electricity rates in Ontario.

It said it would improve testing of its processes prior to deployment and agreed to publicly disclose errors that significantly affect the wholesale market in the future.

 

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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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TCS Partners with Schneider Electric Marathon de Paris to Boost AI and Technology

TCS AI Partnership Paris Marathon integrates predictive analytics, digital twin simulations, real-time runner tracking, and sustainability solutions to elevate logistics, athlete performance, and immersive spectator engagement across the Schneider Electric Marathon de Paris ecosystem.

 

Key Points

AI-driven TCS partnership enhancing Paris logistics, performance, engagement, and sustainability for three years.

✅ Predictive analytics and digital twins optimize race-day ops

✅ Real-time runner tracking and health insights

✅ Sustainable resource management and waste reduction

 

Tata Consultancy Services (TCS) has officially become the AI & Technology Partner for the Schneider Electric Marathon de Paris, marking the start of a three-year collaboration with one of the world’s most prestigious running events. This partnership, announced on April 1, 2025, aims to revolutionize the marathon experience by integrating cutting-edge technology, artificial intelligence (AI), and data analytics, and modern AI data centers to power scalable capabilities, enhancing both the runner's journey and the spectator experience.

The Schneider Electric Marathon de Paris, which attracts over 55,000 runners from across the globe, is a renowned event that not only challenges athletes but also captivates a worldwide audience. As the Official AI & Technology Partner, TCS is set to bring its deep expertise in AI, digital innovation, and data-driven insights to this iconic event, drawing on adjacent domains such as substation automation training to strengthen operations. With more than 30 years of presence in France and its significant partnerships with French corporations, TCS is uniquely positioned to merge its global technology capabilities with local knowledge, thus adding immense value to this prestigious marathon.

The collaboration will primarily focus on enhancing the race logistics, improving athlete performance, and creating a personalized experience for both runners and spectators. Using advanced AI tools, predictive analytics, and digital twin technologies, TCS will streamline various aspects of the event. For example, AI-powered predictive models, reflecting progress recognized by European electricity prediction specialists in forecasting, will be used to track and monitor runners in real-time, providing insights into their performance and well-being during the race. Additionally, the implementation of digital twin technology will enable TCS to create accurate virtual models of the event, improving logistics and supporting better decision-making.

One of the key goals of the partnership is to improve the sustainability of the marathon. By utilizing advanced AI solutions, including AI for energy savings approaches, TCS will help optimize race-day operations, ensuring efficient management of resources, reducing waste, and minimizing environmental impact. This aligns with the growing trend of incorporating sustainability into large-scale events, ensuring that such iconic marathons not only provide an exceptional experience for participants but also contribute to global environmental goals.

TCS’s PacePort™ innovation hub in Paris will play a pivotal role in the collaboration. This innovation center will serve as the testing ground for new AI-powered solutions and tools aimed at improving runner performance and creating a more engaging race experience. Early priorities for the project include the development of personalized AI-based training programs for runners, real-time tracking systems for athlete health monitoring, and advanced analytics to support better training and recovery strategies, drawing on insights from EU smart meter analytics to inform personalization.

Additionally, TCS will introduce new technologies to enhance spectator engagement. Digital experiences, such as virtual race tracking and immersive content, will bring spectators closer to the event, even if they are not physically present at the marathon. This will allow fans worldwide to engage with the race in more interactive ways, enhancing the global reach and excitement surrounding the event.

TCS’s role in the Schneider Electric Marathon de Paris is part of its broader strategy to leverage technology in the realm of sports. The company already supports several major global marathons, including those in New York, London, where projects like the London electricity tunnel showcase infrastructure innovation, and Mumbai, contributing to their operational success and social impact. In fact, marathons supported by TCS raised nearly $280 million for charitable causes in 2024 alone, demonstrating the company’s commitment to blending innovation with social responsibility.

The strategic partnership with the Paris marathon also underscores TCS’s continued commitment to its French operations, and aligns with Schneider Electric’s Notre Dame restoration initiatives that highlight local impact, reinforcing its role as a leader in AI and digital technology. Through this collaboration, TCS aims to not only support the marathon’s logistical and technological needs but also to contribute to the broader development of digital sports experiences.

This partnership promises to deliver a more dynamic, sustainable, and engaging marathon experience, benefiting runners, spectators, and the broader event ecosystem. With TCS’s cutting-edge technology and commitment to enhancing the marathon, the Schneider Electric Marathon de Paris is poised to set new standards for global sports events, blending athletic performance with digital innovation in unprecedented ways.

 

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