14/08/2025 09:10
W Energy Brings Advanced AI Energy Forecasting Back to Australia in Partnership with Simble
SYDNEY, AUSTRALIA - Media OutReach Newswire - 14 August 2025 - Australian clean energy innovation takes a leap forward as W Energy, a new energy technology company, teams up with long-established ASX-listed Simble Solutions (ASX: SIS) to deploy AI-driven energy forecasting and management solutions nationwide. Simble has also formally engaged Yongxin Sun, W Energy's founder and former AI Clean Energy GLOBAL lead, to provide technical support and strategic guidance. Mr. Sun combines expertise in finance, large-scale energy project modelling, and applied AI technology.
W Energy's AI forecasting platform originated in Australia to enhance solar and battery performance predictions while integrating financial modelling for investors and operators. Due to limited local data early on, the system was trialed in Southeast Asia across Cambodia, Vietnam, and the Philippines. These deployments delivered diverse climate and grid datasets, mature near real-time forecasting capabilities, and proven commercial benefits such as reduced investment risk and optimized storage dispatch.
Now commercially mature, W Energy and Simble will begin rolling out projects in New South Wales, expanding to Queensland and Victoria. The partnership leverages W Energy's predictive AI for generation, demand, and pricing optimization alongside Simble's established market presence and energy monitoring tools. Together, they will serve commercial buildings, industrial precincts, and regional grid networks, supporting virtual power plants, dynamic pricing response, and grid resilience.
This collaboration aligns with Australia's energy transition goals, using AI to boost renewable penetration and grid flexibility. The platform integrates real-time IoT sensor data with historical weather and market information, applies adaptive algorithms for storage dispatch, and incorporates financial scenario modelling to assess project returns under varying conditions—all secured to comply with Australian data standards.
Key benefits include higher forecasting accuracy across diverse weather conditions, direct integration of financial metrics into operational decisions, and scalability from small commercial sites to utility-scale assets. Potential applications range from energy cost reductions for commercial customers to enhanced stability in high-renewable regions.
W Energy and Simble plan initial deployments in NSW commercial and industrial sites while collaborating with universities and research institutions to refine the AI platform using local data, further improving its accuracy, adaptability, and security.
Hashtag: #WEnergy
W Energy's AI forecasting platform originated in Australia to enhance solar and battery performance predictions while integrating financial modelling for investors and operators. Due to limited local data early on, the system was trialed in Southeast Asia across Cambodia, Vietnam, and the Philippines. These deployments delivered diverse climate and grid datasets, mature near real-time forecasting capabilities, and proven commercial benefits such as reduced investment risk and optimized storage dispatch.
Now commercially mature, W Energy and Simble will begin rolling out projects in New South Wales, expanding to Queensland and Victoria. The partnership leverages W Energy's predictive AI for generation, demand, and pricing optimization alongside Simble's established market presence and energy monitoring tools. Together, they will serve commercial buildings, industrial precincts, and regional grid networks, supporting virtual power plants, dynamic pricing response, and grid resilience.
This collaboration aligns with Australia's energy transition goals, using AI to boost renewable penetration and grid flexibility. The platform integrates real-time IoT sensor data with historical weather and market information, applies adaptive algorithms for storage dispatch, and incorporates financial scenario modelling to assess project returns under varying conditions—all secured to comply with Australian data standards.
Key benefits include higher forecasting accuracy across diverse weather conditions, direct integration of financial metrics into operational decisions, and scalability from small commercial sites to utility-scale assets. Potential applications range from energy cost reductions for commercial customers to enhanced stability in high-renewable regions.
W Energy and Simble plan initial deployments in NSW commercial and industrial sites while collaborating with universities and research institutions to refine the AI platform using local data, further improving its accuracy, adaptability, and security.
Hashtag: #WEnergy
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source: W Energy