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Watch: Oil Prices Are Rebounding

Recently released government data showed a less-than-expected bump in US crude stockpiles. A weak US dollar and strong economic growth had propped up oil markets, but today’s news has caused oil prices to rebound. American crude inventories came up short of expectations by about 1 million barrels last week, though gas inventories beat forecasts. As…

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Watch: Oil Prices Are Rebounding

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Recently released government data showed a less-than-expected bump in US crude stockpiles. A weak US dollar and strong economic growth had propped up oil markets, but today’s news has caused oil prices to rebound. American crude inventories came up short of expectations by about 1 million barrels last week, though gas inventories beat forecasts. As OPEC attempts to reduce supply following a January deal, a leap in US production has undermined the project. Will US production alone sustain bearish oil prices or will OPEC achieve its goal?

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Importers paid roughly $75 billion for Chinese batteries and grid equipment in 2026's first seven months

Importers paid roughly $75 billion for Chinese batteries and grid equipment in 2026's first seven months

Importers spent about $75 billion on Chinese batteries and grid equipment from January to July 2026, versus about $19.4 billion on Chinese solar imports. As more markets hit sunny-day surpluses, spending is shifting toward storage and grid upgrades. Europe led purchases at about $31.1 billion, followed by Asia at $22 billion.

  • 01In the first seven months of 2026, global importers paid roughly $75 billion for Chinese energy storage batteries and grid equipment, compared with about $19.4 billion for solar imports so far in 2026, according to Ember data.
  • 02Lower spending on Chinese solar imports doesn’t necessarily mean solar is declining: import dollars track spending on Chinese equipment, not installations. In markets already seeing midday solar surpluses, utilities are shifting budgets toward batteries, transmission lines and grid upgrades to manage swings in output.

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Disconnected data can delay recognizing fuel-quality issues, Titan Cloud says

Disconnected data can delay recognizing fuel-quality issues, Titan Cloud says

This article draws on a Titan Cloud presentation. Its operational examples and product claims reflect the vendor’s account and should not be read as findings from a representative industry survey. Titan Cloud describes a scenario in which disconnected tank, delivery and maintenance records delay recognition of a fuel-quality problem until a customer reports it. The presentation argues that connecting those records can help operators investigate earlier and reduce operational disruption.

  • 01Disconnected data can delay fuel-quality alerts, Titan Cloud says.
  • 02The linked client video is the source for the vendor’s account; its claims are not independent industry benchmarks.
  • 03Buyers can ask for demonstrations using their own asset categories and request examples of how discrepancies are identified, investigated, and followed through to resolution.

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Titan Cloud describes organized fuel theft across multiple sites

Titan Cloud describes organized fuel theft across multiple sites

This article draws on a Titan Cloud presentation. Its operational examples and product claims reflect the vendor’s account and should not be read as findings from a representative industry survey. Michael Lewis, identified in the presentation as leading Titan Cloud’s international solutions consultancy team, describes coordinated fuel-theft scenarios involving multiple sites. His examples include dispenser manipulation, delivery losses and product adulteration. The scale described is the speaker’s account, not a measured industry-wide rate.

  • 01Titan Cloud describes organized fuel theft across multiple sites.
  • 02The Titan Cloud presentation is the source for the vendor’s account; its claims are not independent industry benchmarks.
  • 03Titan Cloud’s presenters argue that detecting coordinated theft and slow leaks requires cleaner data (including addressing gauge/calibration noise), more frequent reconciliation, and looking for patterns across the network rather than ranking sites by raw loss volume.

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