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Adani Electricity Mumbai Power Cuts follow non-payment rules, reflecting billing disputes, regulatory compliance, consumer impact, and affordability concerns, while prompting mitigation measures like flexible payment plans, assistance programs, and clearer communication for residents.

Key Points

AEML cutoffs for unpaid bills per rules, raising affordability worries, billing issues, and calls for flexible aid.

✅ Triggered by unpaid bills under regulatory guidelines

✅ Affordability and billing transparency concerns raised

✅ Mitigation: flexible plans, aid for low-income users

Adani Electricity Mumbai Limited (AEML) recently made headlines by cutting power supply to around 100 homes in Mumbai, sparking discussions about the reasons behind this action and its implications for consumers, especially as reports like the Northeast D.C. outage continue to surface.

Background of the Incident

The power supply disconnections by AEML were reportedly due to non-payment of electricity bills by the affected households. This action, although necessary under AEML's policies and in accordance with regulatory guidelines, has raised concerns about the impact on residents, particularly during challenging economic times when pandemic electricity shut-offs highlighted energy insecurity.

Reasons for Non-Payment

Non-payment of electricity bills can stem from various reasons, including financial hardships, disputes over billing accuracy, or unforeseen circumstances affecting household finances. In Mumbai, where the cost of living is high, utility bills constitute a significant portion of monthly expenses for many households, mirroring trends of rising electricity bills seen elsewhere.

Regulatory and Legal Framework

AEML's decision to disconnect power supply aligns with regulatory provisions governing utility services, which may include emergency disconnection moratoriums in other jurisdictions. Utility companies are mandated to enforce bill payments to maintain operational sustainability and ensure fair distribution of resources among consumers.

Consumer Impact and Response

The power disconnections have prompted reactions from affected residents and consumer advocacy groups, highlighting issues related to affordability, transparency in billing practices, and the need for supportive measures during times of economic distress amid heat-related electricity struggles that pressure vulnerable households.

Mitigation Measures

In response to such incidents, utility companies and regulatory authorities often implement mitigation measures. These may include flexible payment options, financial assistance programs for low-income households, and enhanced communication about billing procedures and payment deadlines, along with policy scrutiny such as utility spending oversight to curb unnecessary costs.

Future Considerations

As cities like Mumbai continue to grow and face challenges related to urbanization and infrastructure development, ensuring reliable and affordable access to essential services like electricity, including efforts to prevent summer power outages, remains a priority. Balancing the operational needs of utility providers with consumer welfare concerns requires ongoing dialogue and proactive measures from all stakeholders.

Conclusion

The power supply cuts by Adani Electricity in Mumbai underscore the complexities of managing utility services in urban centers. While necessary for financial viability and regulatory compliance, such actions also highlight broader issues of affordability and consumer protection. Moving forward, collaborative efforts between utility companies, regulatory authorities, and community stakeholders are essential in addressing these challenges and ensuring equitable access to essential services for all residents.

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PG&E Drum Fire Cause identified as a power line failure in Santa Barbara County, with arcing electricity igniting vegetation near Buellton on Drum Canyon Road; 696 acres burned as investigators and CPUC review PG&E safety.

Key Points

A failed PG&E power line sparked the 696-acre Drum Fire near Buellton; the utility is conducting its own probe.

✅ Power line failed between poles, arcing ignited vegetation.

✅ 696 acres burned; no structures damaged or injuries.

✅ PG&E filed CPUC incident report; ongoing investigation.

A downed Pacific Gas and Electric Co. power line was the cause of the Drum fire that broke out June 14 on Drum Canyon Road northwest of Buellton, a reminder that a transformer explosion can also spark multiple fires, the Santa Barbara County Fire Department announced Thursday.

The fire broke out about 12:50 p.m. north of Highway 246 and burned about 696 acres of wildland before firefighters brought it under control, although no structures were damaged or mass outages like the Los Angeles power outage occurred, according to an incident summary.

A team of investigators pinpointed the official cause as a power line that failed between two utility poles and fell to the ground, and as downed line safety tips emphasize, arcing electricity ignited the surrounding vegetation, said County Fire Department spokesman Capt. Daniel Bertucelli.

In response, a PG&E spokesman said the utility is conducting its own investigation and does not have access to whatever data investigators used, and, as the ATCO regulatory penalty illustrates, such matters can draw significant oversight, but he noted the company filed an electric incident report on the wire with the California Public Utilities Commission on June 14.

"We are grateful to the first responders who fought the 2020 Drum fire in Santa Barbara County and helped make sure that there were no injuries or fatalities, outcomes not always seen in copper theft incidents, and no reports of structures damaged or burned," PG&E spokesman Mark Mesesan said.

"While we are continuing to conduct our own investigation into the events that led to the Drum fire, and as the Site C watchdog inquiry shows, oversight bodies can seek more transparency, PG&E does not have access to the Santa Barbara County Fire Department's report."

He said PG&E remains focused on reducing wildfire risk across its service area while limiting the scope and duration of public safety power shutoffs, including strategies like line-burying decisions adopted by other utilities, and that the safety of customers and communities it serves are its most important responsibility.

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U.S. Electricity Trade by State, 2013-2017 highlights EIA grid patterns, interstate imports and exports, cross-border flows with Canada and Mexico, net exporters and importers, and market regions like ISOs and RTOs shaping consumption and generation.

Key Points

Brief EIA overview of interstate and cross-border power flows, ranking top net importers and exporters.

✅ Pennsylvania was the largest net exporter, averaging 59 million MWh.

✅ California was the largest net importer, averaging 77 million MWh.

✅ Top cross-border: NY, CA, VT, MN, MI imports; WA, TX, CA, NY, MT exports.

According to the U.S. Energy Information Administration (EIA) State Electricity Profiles, from 2013 to 2017, Pennsylvania was the largest net exporter of electricity, while California was the largest net importer.

Pennsylvania exported an annual average of 59 million megawatt-hours (MWh), while California imported an average of 77 million MWh annually.

Based on the share of total consumption in each state, the District of Columbia, Maryland, Massachusetts, Idaho and Delaware were the five largest power-importing states between 2013 and 2017, highlighting how some clean states import 'dirty' electricity as consumption outpaces local generation. Wyoming, West Virginia, North Dakota, Montana and New Hampshire were the five largest power-exporting states. Wyoming and West Virginia were net power exporting states between 2013 and 2017.

New York, California, Vermont, Minnesota and Michigan imported the most electricity from Canada or Mexico on average from 2013 to 2017, reflecting the U.S. look to Canada for green power during that period. Similarly, Washington, Texas, California, New York, and Montana exported the most electricity to Canada or Mexico, on average, during the same period.

Electricity routinely flows among the Lower 48 states and, to a lesser extent, between the United States and Canada and Mexico. From 2013 to 2017, Pennsylvania was the largest net exporter of electricity, sending an annual average of 59 million megawatthours (MWh) outside the state. California was the largest net importer, receiving an average of 77 million MWh annually.

Based on the share of total consumption within each state, the District of Columbia, Maryland, Massachusetts, Idaho, and Delaware were the five largest power-importing states between 2013 and 2017. Wyoming, West Virginia, North Dakota, Montana, and New Hampshire were the five largest power-exporting states. States with major population centers and relatively less generating capacity within their state boundaries tend to have higher ratios of net electricity imports to total electricity consumption, as utilities devote more to electricity delivery than to power production in many markets.

Wyoming and West Virginia were net power exporting states (they exported more power to other states than they consumed) between 2013 and 2017. Customers residing in these two states are not necessarily at an economic disadvantage or advantage compared with customers in neighboring states when considering their electricity bills and fees and market dynamics. However, large amounts of power trading may affect a state’s revenue derived from power generation.

Some states also import and export electricity outside the United States to Canada or Mexico, even as Canada's electricity exports face trade tensions today. New York, California, Vermont, Minnesota, and Michigan are the five states that imported the most electricity from Canada or Mexico on average from 2013 through 2017. Similarly, Washington, Texas (where electricity production and consumption lead the nation), California, New York, and Montana are the five states that exported the most electricity to Canada or Mexico, on average, for the same period.

Many states within the continental United States fall within integrated market regions, referred to as independent system operators or regional transmission organizations. These integrated market regions allow electricity to flow freely between states or parts of states within their boundaries.

EIA’s State Electricity Profiles provide details about the supply and disposition of electricity for each state, including net trade with other states and international imports and exports, and help you understand where your electricity comes from more clearly.

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BC Hydro Clean Energy Champions highlights Vancouver's Bloedel Conservatory electrification with a massive heat pump, clean electricity, LED lighting, deep energy efficiency, and 90% greenhouse gas reductions advancing climate action across buildings and industry.

Key Points

A BC Hydro program honoring clean electricity adoption in homes, transport, and industry to replace fossil fuels.

✅ Vancouver's Bloedel Conservatory cut GHGs by 90% with a heat pump

✅ LEDs and electrification boost efficiency, comfort, and reliability

✅ Nominations open for residents, businesses, and Indigenous groups

The City of Vancouver has been selected as BC Hydro’s first Clean Energy Champion for energy efficient upgrades made at the Bloedel Conservatory that cut greenhouse gas emissions by 90 per cent, a meaningful step given concerns about 2050 greenhouse gas targets in B.C.

BC Hydro’s Clean Energy Champions program is officially being launched today to recognize residents, businesses, municipalities, Indigenous and community groups across B.C. that have made the choice to switch from using fossil fuels to using clean electricity in three primary areas: homes and buildings, transportation, and industry, even as drought challenges power generation in B.C. The City of Vancouver is being recognized as the first champion for demonstrating its commitment to using clean energy, including power from projects like Site C's electricity, to fight climate change at its landmark Bloedel Conservatory.

Earlier this year, the City of Vancouver installed a large air source heat pump at Bloedel Conservatory – more than 50 times the size of a heat pump used in a typical B.C. home – that uses electricity instead of natural gas to heat and cool the dome's interior, which is home to more than 500 exotic plants and flowers, and 100 exotic birds, aligning with citywide debates such as Vancouver’s reversal on gas appliances policy. It is the biggest heat pump the City of Vancouver has ever installed, with 210 tonnes of cooling capacity.

A heat pump that provides cooling in the summer and heating in the winter, helping reduce reliance on wasteful air conditioning that can drive up energy bills, is ideal for the conservatory, as its dome is completely made of glass, which can be challenging for temperature regulation. While the dome experiences a lot of heat loss in the colder months, its need for cooling in warmer weather is even greater to ensure the safety of the wildlife and plants that call it home.

The clean energy upgrades do not end there though. All lighting in the building has been upgraded to energy-efficient LEDs, reflecting conservation themes highlighted by 2018 Earth Hour electricity use discussions, and outside colour-changing LEDs now surround the perimeter and light up the dome at night.

BC Hydro is calling for nominations from B.C. residents, businesses, municipalities or Indigenous and community groups that have taken steps to lower their carbon footprint and adopt new clean energy technologies, and continues to support customers through programs like its winter payment plan during colder months. If you or someone you know is a Clean Energy Champion, nominate them at bchydro.com/cleanenergychampions.

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Canada Wind Energy Costs are plunging as renewable energy auctions, CfD contracts, and efficient turbines drive prices to 2-4 cents/kWh across Alberta and Saskatchewan, outcompeting grid power via competitive bidding and improved capacity factors.

Key Points

Averaging 2-4 cents/kWh via auctions, CfD support, and bigger turbines, wind is now cost-competitive across Canada.

✅ Alberta CfD bids as low as 3.9 cents/kWh.

✅ Turbine outputs rose from 1 MW to 3.3 MW per tower.

✅ Competitive auctions cut costs ~70% over nine years.

It's taken a decade of technological improvement and a new competitive bidding process for electrical generation contracts, but wind may have finally come into its own as one of the cheapest ways to create power.

Ten years ago, Ontario was developing new wind power projects at a cost of 28 cents per kilowatt hour (kWh), the kind of above-market rate that the U.K., Portugal and other countries were offering to try to kick-start development of renewables. 

Now some wind companies say they've brought generation costs down to between 2 and 4 cents — something that appeals to provinces that are looking to significantly increase their renewable energy deployment plans.

The cost of electricity varies across Canada, by province and time of day, from an average of 6.5 cents per kWh in Quebec to as much as 15 cents in Halifax.

Capital Power, an Edmonton-based company, recently won a contract for the Whitla 298.8-megawatt (MW) wind project near Medicine Hat, Alta., with a bid of 3.9 cents per kWh, at a time when three new solar facilities in Alberta have been contracted at lower cost than natural gas, underscoring the trend. That price covers capital costs, transmission and connection to the grid, as well as the cost of building the project.

Jerry Bellikka, director of government relations, said Capital Power has been building wind projects for a decade, in the U.S., Alberta, B.C. and other provinces. In that time the price of wind generation equipment has been declining continually, while the efficiency of wind turbines increases.

Increased efficiency

"It used to be one tower was 1 MW; now each turbine generates 3.3 MW. There's more electricity generated per tower than several years ago," he said.

One wild card for Whitla may be steel prices — because of the U.S. and Canada slapping tariffs on one other's steel and aluminum products. Whitla's towers are set to come from Colorado, and many of the smaller components from China.

Canada introduces new surtaxes to curb flood of steel imports

"We haven't yet taken delivery of the steel. It remains to be seen if we are affected by the tariffs." Belikka said.

Another company had owned the site and had several years of meteorological data, including wind speeds at various heights on the site, which is in a part of southern Alberta known for its strong winds.

But the choice of site was also dependent on the municipality, with rural Forty Mile County eager for the development, Belikka said.

Alberta aims for 30% electricity from wind by 2030

Alberta wants 30 per cent of its electricity to come from renewable sources by 2030 and, as an energy powerhouse, is encouraging that with a guaranteed pricing mechanism in what is otherwise a market-bidding process.

While the cost of generating energy for the Alberta Electric System Operator (AESO) fluctuates hourly and can be a lot higher when there is high demand, the winners of the renewable energy contracts are guaranteed their fixed-bid price.

The average pool price of electricity last year in Alberta was 5 cents per kWh; in boom times it rose to closer to 8 cents. But if the price rises that high after the wind farm is operating, the renewable generator won't get it, instead rebating anything over 3.9 cents back to the government.

On the other hand, if the average or pool price is a low 2 cents kWh, the province will top up their return to 3.9 cents.

This contract-for-differences (CfD) payment mechanism has been tested in renewable contracts in the U.K. and other jurisdictions, including some U.S. states, according to AESO.

Competitive bidding in Saskatchewan

In Saskatchewan, the plan is to double its capacity of renewable electricity, to 50 per cent of generation capacity, by 2030, and it uses an open bidding system between the private sector generator and publicly owned SaskPower.

In bidding last year on a renewable contract, 15 renewable power developers submitted bids, with an average price of 4.2 cents per kWh.

One low bidder was Potentia with a proposal for a 200 MW project, which should provide electricity for 90,000 homes in the province, at less than 3 cents kWh, according to Robert Hornung of the Canadian Wind Energy Association.

"The cost of wind energy has fallen 70 per cent in the last nine years," he says. "In the last decade, more wind energy has been built than any other form of electricity."

Ontario remains the leading user of wind with 4,902 MW of wind generation as of December 2017, most of that capacity built under a system that offered an above-market price for renewable power, put in place by the previous Liberal government.

In June of last year, the new Conservative government of Doug Ford halted more than 700 renewable-energy projects, one of them a wind farm that is sitting half-built, even as plans to reintroduce renewable projects continue to advance.

The feed-in tariff system that offered a higher rate to early builders of renewable generation ended in 2016, but early contracts with guaranteed prices could last up to 20 years.

Hornung says Ontario now has an excess of generating capacity, as it went on building when the 2008-9 bust cut market consumption dramatically.

But he insists wind can compete in the open market, offering low prices for generation when Ontario needs new  capacity.

"I expect there will be competitive processes put in place. I'm quite confident wind projects will continue to go ahead. We're well positioned to do that."

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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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