AREVA and China strengthen links

EV Grid Capacity Management shows how smart charging, load balancing, and off-peak pricing align with utility demand response, DC fast charging networks, and renewable integration to keep national electricity infrastructure reliable as EV adoption scales

Key Points

EV Grid Capacity Management schedules charging and balances load to keep EV demand within utility capacity.

✅ Off-peak pricing and time-of-use tariffs shift charging demand.

✅ Smart chargers enable demand response and local load balancing.

✅ Gradual EV adoption allows utilities to plan upgrades efficiently.

One of the most frequent concerns you will see from electric vehicle haters is that the electricity grid can’t possibly cope with all cars becoming EVs, or that EVs will crash the grid entirely. However, they haven’t done the math properly. The grids in most developed nations will be just fine, so long as the demand is properly management. Here’s how.

The biggest mistake the social media keyboard warriors make is the very strange assumption that all cars could be charging at once. In the UK, there are currently 32,697,408 cars according to the UK Department of Transport. The UK national grid had a capacity of 75.8GW in 2020. If all the cars in the UK were EVs and charging at the same time at 7kW (the typical home charger rate), they would need 229GW – three times the UK grid capacity. If they were all charging at 50kW (a common public DC charger rate), they would need 1.6TW – 21.5 times the UK grid capacity. That sounds unworkable, and this is usually the kind of thinking behind those who claim the UK grid can't cope with EVs.

What they don’t seem to realize is that the chances of every single car charging all at once are infinitesimally low. Their arguments seem to assume that nobody ever drives their car, and just charges it all the time. If you look at averages, the absurdity of this position becomes particularly clear. The distance each UK car travels per year has been slowly dropping, and was 7,400 miles on average in 2019, again according to the UK Department of Transport. An EV will do somewhere between 2.5 and 4.5 miles per kWh on average, so let’s go in the middle and say 3.5 miles. In other words, each car will consume an average of 2,114kWh per year. Multiply that by the number of cars, and you get 69.1TWh. But the UK national grid produced 323TWh of power in 2019, so that is only 21.4% of the energy it produced for the year. Before you argue that’s still a problem, the UK grid produced 402TWh in 2005, which is more than the 2019 figure plus charging all the EVs in the UK put together. The capacity is there, and energy storage can help manage EV-driven peaks as well.

Let’s do the same calculation for the USA, where an EV boom is about to begin and planning matters. In 2020, there were 286.9 million cars registered in America. In 2020, while the US grid had 1,117.5TW of utility electricity capacity and 27.7GW of solar, according to the US Energy Information Administration. If all the cars were EVs charging at 7kW, they would need 2,008.3TW – nearly twice the grid capacity. If they charged at 50kW, they would need 14,345TW – 12.8 times the capacity.

However, in 2020, the US grid generated 4,007TWh of electricity. Americans drive further on average than Brits – 13,500 miles per year, according to the US Department of Transport’s Federal Highway Administration. That means an American car, if it were an EV, would need 3,857kWh per year, assuming the average efficiency figures above. If all US cars were EVs, they would need a total of 1,106.6TWh, which is 27.6% of what the American grid produced in 2020. US electricity consumption hasn’t shrunk in the same way since 2005 as it has in the UK, but it is clearly not unfeasible for all American cars to be EVs. The US grid could cope too, even as state power grids face challenges during the transition.

After all, the transition to electric isn’t going to happen overnight. The sales of EVs are growing fast, with for example more plug-ins sold in the UK in 2021 so far than the whole of the previous decade (2010-19) put together. Battery-electric vehicles are closing in on 10% of the market in the UK, and they were already 77.5% of new cars sold in Norway in September 2021. But that is new cars, leaving the vast majority of cars on the road fossil fuel powered. A gradual introduction is essential, too, because an overnight switchover would require a massive ramp up in charge point installation, particularly devices for people who don’t have the luxury of home charging. This will require considerable investment, but could be served by lots of chargers on street lamps, which allegedly only cost £1,000 ($1,300) each to install, usually with no need for extra wiring.

This would be a perfectly viable way to provide charging for most people. For example, as I write this article, my own EV is attached to a lamppost down the street from my house. It is receiving 5.5kW costing 24p (32 cents) per kWh through SimpleSocket, a service run by Ubitricity (now owned by Shell) and installed by my local London council, Barnet. I plugged in at 11am and by 7.30pm, my car (which was on about 28% when I started) will have around 275 miles of range – enough for a couple more weeks. It will have cost me around £12 ($16) – way less than a tank of fossil fuel. It was a super-easy process involving the scanning of a QR code and entering of a credit card, very similar to many parking systems nowadays. If most lampposts had one of these charging plugs, not having off-street parking would be no problem at all for owning an EV.

With most EVs having a range of at least 200 miles these days, and the average mileage per day being 20 miles in the UK (the 7,400-mile annual figure divided by 365 days) or 37 miles in the USA, EVs won’t need charging more than once a week or even every week or two. On average, therefore, the grids in most developed nations will be fine. The important consideration is to balance the load, because if too many EVs are charging at once, there could be a problem, and some regions like California are looking to EVs for grid stability as part of the solution. This will be a matter of incentivizing charging during off-peak times such as at night, or making peak charging more expensive. It might also be necessary to have the option to reduce charging power rates locally, while providing the ability to prioritize where necessary – such as emergency services workers. But the problem is one of logistics, not impossibility.

There will be grids around the world that are not in such a good place for an EV revolution, at least not yet, and some critics argue that policies like Canada's 2035 EV mandate are unrealistic. But to argue that widespread EV adoption will be an insurmountable catastrophe for electricity supply in developed nations is just plain wrong. So long as the supply is managed correctly to make use of spare capacity when it’s available as much as possible, the grids will cope just fine.

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Saudi Arabia Wind Power Market set to lead the Middle East, driven by Vision 2030 renewables goals, REPDO tenders, and PIF backing, adding 6.2GW wind capacity by 2028 alongside solar PV diversification.

Key Points

It is the emerging national segment leading Middle East wind growth, targeting 6.2GW by 2028 under Vision 2030 policies.

✅ Adds 6.2GW, 46% of regional wind capacity by 2028

✅ REPDO tenders and PIF funding underpin pipeline

✅ Targets: 16GW wind, 40GW solar under Vision 2030

Saudi Arabia will become a regional heavyweight in the Middle East's wind power market adding over 6GW in the next 10 years, according to new research by Wood Mackenzie Power & Renewables.

The report – 'Middle East Wind Power Market Outlook, 2019-2028’ – said developers will build 6.2GW of wind capacity in the country or 46% of the region’s total wind capacity additions between 2019 and 2028.

Wood Mackenzie Power & Renewables senior analyst Sohaib Malik said: “The integration of renewables in Vision 2030’s objectives underlines strong political commitment within Saudi Arabia.

“The level of Saudi ambition for wind and solar PV varies significantly, despite the cost parity between both technologies during the first round of tenders in 2018.”

Saudi Arabia has set a 16GW target for wind by 2030 and 40GW for solar, plans to solicit 60 GW of clean energy over the next decade, Wood Mackenzie added.

“Moving forward, the Renewable Energy Project Development Office will award 850MW of wind capacity in 2019, which is expected to be commissioned in 2021-2022, and increase the local content requirement in future tendering rounds,” Malik said.

However, Saudi Arabia will fall short of its current 2030 renewables target, despite growth projections and regional leadership, the report said.

Some 70% of the renewables capacity target is to be supported by the Public Investment Fund (PIF), the Saudi sovereign wealth fund, while the remaining capacity is to be awarded through REPDO.

“A central concern is the PIF’s lack of track record in the renewables sector and its limited in-house sectoral expertise,” said Malik

“REPDO, on the other hand, completed two renewables request for proposals after pre-developing the sites,” he said.

PIF is estimated to have $230bn of assets – targeted to reach $2 trillion under Vision 2030 – driven by investments in a variety of sectors ranging from electric vehicles to public infrastructure, Wood Mackenzie said.

“There is little doubt about the fund’s financial muscle, however, its past investment strategy focused on established firms in traditional industries,” Malik added.

“Aspirations to develop a value chain for wind and PV technologies locally is a different ball game and requires the PIF to acquire new capabilities for effective oversight of these ventures,” he said.

The report noted that regional volatility is expected to remain, with strong positive growth, driven by Jordan and Iran in 2018 expected to reverse in 2019, and policy shifts, as in Canada’s scaled-back projections, can influence outcomes.

Post-2020 Wood Mackenzie Power & Renewables sees regional demand returning to steady growth as global renewables set more records elsewhere.

“In 2018, developers added 185MW and 63MW of wind capacity in Jordan and Iran, respectively, compared to 53MW of capacity across the entire region in 2017, following a record year for renewables in 2016,” said Malik.

“The completion of the 89MW Al Fujeij and the 86MW Al Rajef projects in 2018 indicates that Jordan has 375MW of the region’s operational 675MW wind capacity.

“Iran followed with 278MW of installed capacity at the end of 2018. A slowdown in 2019 is expected, as project development activity softens in Iran.

“Additionally, delays in awarding the 400MW Dumat Al Jandal project in Saudi Arabia will limit annual capacity additions to 184MW.”

He added that a maturing project pipeline in the region supports the 2020-2021 outlook, even as wind power grew despite Covid-19 globally.

“Saudi Arabian demand serves as the foundation for regional demand. Regional demand diversification is also occurring, with Lebanon set to add 200-400MW to its existing permitted capacity pipeline of 202MW in 2019,” he said

“These developments pave the way for the addition of 2GW of wind capacity between 2019 and 2021.”

Wood Mackenzie Power & Renewables added that the outlook for solar in the region is “much more positive” than wind.

“Compared to only 6GW of wind power capacity, developers will add 53GW of PV capacity through 2024,” said Malik.

He added: “Solar PV, supported by trends such as China’s rapid PV growth in 2016, has become a natural choice for many countries in the region, which is endowed with world class solar energy resources.

“The increased focus on solar energy is demonstrated by ambitious PV targets across the region.”

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Ontario CEAP Program provides one-time electricity bill relief for residential consumers via local utilities, supports low-income households, aligns with COVID-19 recovery rates, and complements time-of-use pricing options and the winter disconnection ban.

Key Points

A one-time electricity bill credit for eligible Ontario households affected by COVID-19, available via local utilities.

✅ Apply through your local distribution company or utility

✅ One-time credit for overdue electricity bills from COVID-19

✅ Complements TOU options, OER, and winter disconnection ban

Applications for the CEAP program for Ontario residential consumers has opened. Residential customers across the province can now apply for funding through their local distribution company/utility.

On June 1st, our government announced a suite of initiatives to support Ontario’s electricity consumers amid changes for electricity consumers during the pandemic, including a $9 million investment to support low-income Ontarians through the COVID-19 Energy Assistance Program (CEAP). CEAP will provide a one-time payment to Ontarians who are struggling to pay down overdue electricity bills incurred during the COVID-19 outbreak.

These initiatives include:

• $9 million for the COVID-19 Energy Assistance Program (CEAP) to support consumers struggling to pay their energy bills during the pandemic. CEAP will provide one-time payments to consumers to help pay down any electricity bill debt incurred over the COVID19 period. Applications will be available through local utilities in the upcoming months;
• $8 million for the COVID-19 Energy Assistance Program for Small Business (CEAP-SB) to provide support to businesses struggling with bill payments as a result of the outbreak; and
• An extension of the Ontario Energy Board’s winter disconnection ban until July 31, 2020 to ensure no one is disconnected from their natural gas or electricity service during these uncertain times.

More information about applications for the CEAP for Small Business will be coming later this summer, as electricity rates are about to change across Ontario for many customers.

In addition, the government recently announced that it will continue the suspension of time-of-use (TOU) electricity rates and, starting on June 1, 2020, customers will be billed based on a new fixed COVID-19 hydro rate of 12.8 cents per kilowatt hour. The COVID-19 Recovery Rate, which some warned in analysis could lead to higher hydro bills will be in place until October 31, 2020.

Later in the pandemic, Ontario set electricity rates at the off-peak price until February 7 to provide additional relief.

“Starting November 1, 2020, our government has announced Ontario electricity consumers will have the option to choose between time-of-use and tiered electricity pricing plan, following the Ontario Energy Board’s new rate plan prices and support thresholds announcement. We are proud to soon offer Ontarians the ability to choose an electricity plan that best suits for their lifestyle,” said Jim McDonell, MPP for Stormont–Dundas–South Glengarry.

The government will continue to subsidize electricity bills by 31.8 per cent through the Ontario Electricity Rebate.

The government is providing approximately $5.6 billion in 2020-21 as part of its existing electricity cost relief programs and conservation initiatives such as the Peak Perks program to help ensure more affordable electricity bills for eligible residential, farm and small business consumers.

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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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Rural Electrification Poverty Impact examines energy access, grid connections, and reliability, testing economic development claims via randomized trials; findings show minimal gains without appliances, reliable supply, and complementary services like education and job creation initiatives.

Key Points

Study of household grid connections showing modest poverty impact without reliable power and appliances.

✅ Randomized grid connections showed no short-term income gains.

✅ Low reliability and few appliances limited electricity use.

✅ Complementary investments in jobs, education, health may be needed.

The head of Swedfund, the development finance group, recently summarized a widely-held belief: “Access to reliable electricity drives development and is essential for job creation, women’s empowerment and combating poverty.” This view has been the driving force behind a number of efforts to provide electricity to the 1.1 billion people around the world living in energy poverty, such as India's village electrification initiatives in recent years.

But does electricity really help lift households out of poverty? My co-authors and I set out to answer this question. We designed an experiment in which we first identified a sample of “under grid” households in Western Kenya—structures that were located close to but not connected to a grid. These households were then randomly divided into treatment and control groups. In the treatment group, we worked closely with the rural electrification agency to connect the households to the grid for free or at various discounts. In the control group, we made no changes. After eighteen months, we surveyed people from both groups and collected data on an assortment of outcomes, including whether they were employed outside of subsistence agriculture (the most common type of work in the region) and how many assets they owned. We even gave children basic tests, as a frequent assertion is that electricity helps children perform better in school since they are able to study at night.

When we analyzed the data, we found no differences between the treatment and control groups. The rural electrification agency had spent more than $1,000 to connect each household. Yet eighteen months later, the households we connected seemed to be no better off. Even the children’s test scores were more or less the same. The results of our experiment were discouraging, and at odds with the popular view that supplying households with access to electricity will drive economic development. Lifting people out of poverty may require a more comprehensive approach to ensure that electricity is not only affordable (with some evidence that EV growth can benefit all customers in mature markets), but is also reliable, useable, and available to the whole community, paired with other important investments.

For instance, in many low-income countries, the grid has frequent blackouts and maintenance problems, making electricity unreliable, as seen in Nigeria's electricity crisis in recent years. Even if the grid were reliable, poor households may not be able to afford the appliances that would allow for more than just lighting and cell phone charging. In our data, households barely bought any appliances and they used just 3 kilowatt-hours per month. Compare that to the U.S. average of 900 kilowatt-hours per month, a figure that could rise as EV adoption increases electricity demand over time.

There are also other factors to consider. After all, correlation does not equal causation. There is no doubt that the 1.1 billion people without power are the world’s poorest citizens. But this is not the only challenge they face. The poor may also lack running water, basic sanitation, consistent food supplies, quality education, sufficient health care, political influence, and a host of other factors that may be harder to measure but are no less important to well-being. Prioritizing investments in some of these other factors may lead to higher immediate returns. Previous work by one of my co-authors, for example, shows substantial economic gains from government spending on treatment for intestinal worms in children.

It’s possible that our results don’t generalize. They certainly don’t apply to enhancing electricity services for non-residential customers, like factories, hospitals, and schools, and electric utilities adapting to new load patterns. Perhaps the households we studied in Western Kenya are particularly poor (although measures of well-being suggest they are comparable to rural households across Sub-Saharan Africa) or politically disenfranchised. Perhaps if we had waited longer, or if we had electrified an entire region, the household impacts we measured would have been much greater. But others who have studied this question have found similar results. One study, also conducted in Western Kenya, found that subsidizing solar lamps helped families save on kerosene, but did not lead children to study more. Another study found that installing solar-powered microgrids in Indian villages resulted in no socioeconomic benefits.

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US Power Grid Blackouts highlight aging infrastructure, rising outages, and declining reliability per DOE and NERC data, with weather-driven failures, cyberattack risk, and underinvestment stressing utilities, transmission lines, and modernization efforts.

Key Points

US power grid blackouts are outages caused by aging grid assets, severe weather, and cyber threats reducing reliability.

✅ DOE and NERC data show rising outage frequency and duration.

✅ Weather now drives 68-73% of major failures since 2008.

✅ Modernization, hardening, and cybersecurity investments are critical.

The United States power grid has more blackouts than any other country in the developed world, according to new data and U.S. blackout warnings that spotlight the country’s aging and unreliable electric system.

The data by the Department of Energy (DOE) and the North American Electric Reliability Corporation (NERC) shows that Americans face more power grid failures lasting at least an hour than residents of other developed nations.

And it’s getting worse.

Going back three decades, the US grid loses power 285 percent more often than it did in 1984, when record keeping began, International Business Times reported. The power outages cost businesses in the United States as much as $150 billion per year, according to the Department of Energy.

Customers in Japan lose power for an average of 4 minutes per year, as compared to customers in the US upper Midwest (92 minutes) and upper Northwest (214), University of Minnesota Professor Massoud Amin told the Times. Amin is director of the Technological Leadership Institute at the school.

#google#

The grid is becoming less dependable each year, he said.

“Each one of these blackouts costs tens of hundreds of millions, up to billions, of dollars in economic losses per event,” Amin said. “… We used to have two to five major weather events per year [that knocked out power], from the ‘50s to the ‘80s. Between 2008 and 2012, major outages caused by weather, reflecting extreme weather trends, increased to 70 to 130 outages per year. Weather used to account for about 17 to 21 percent of all root causes. Now, in the last five years, it’s accounting for 68 to 73 percent of all major outages.”

As previously reported by Off The Grid News, the power grid received a “D+” grade on its power grid report card from the American Society of Civil Engineers (ASCE) in 2013. The power grid grade card rating means the energy infrastructure is in “poor to fair condition and mostly below standard, with many elements approaching the end of their service life.” It further means a “large portion of the system exhibits significant deterioration” with a “strong risk of failure.”

“America relies on an aging electrical grid and pipeline distribution systems, some of which originated in the 1880s,” the 2013 ASCE report read. “Investment in power transmission has increased since 2005, but ongoing permitting issues, weather events, and limited maintenance have contributed to an increasing number of failures and power interruptions.”

As The Times noted, the US power grid as it exists today was built shortly after World War II, with the design dating back to Thomas Edison. While Edison was a genius, he and his contemporaries could not have envisioned all the strains the modern world would place upon the grid and the multitude of tech gadgets many Americans treat as an extension of their body. While the drain on the grid has advanced substantially, the infrastructure itself has not.

There are approximately 5 million miles of electrical transmission lines throughout the United States, and thousands of power generating plants dot the landscape. The electrical grid is managed by a group of 3,300 different utilities and serve about 150 million customers, The Times said. The entire power grid system is currently valued at $876 billion.

Many believe the grid is vulnerable to an attack on substations and other threats.

Former Department of Homeland Security Secretary Janet Napolitano once said that a power grid cyber attack is a matter of “when” not “if,” as Russians hacked utilities incidents have shown.

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