(IN BRIEF) AI is crucial in scaling up the renewable energy industry, with Lightsource bp leveraging AI to address challenges like grid stability and asset protection. AI supports accurate forecasting, risk mitigation from extreme weather, and optimized site design. Lightsource bp’s culture of innovation and in-house AI team empower their operations, driving efficiency and growth.
(PRESS RELEASE) LONDON, 29-Jun-2024 — /EuropaWire/ — Artificial intelligence (AI) is increasingly pivotal in the renewable energy industry, supporting companies like Lightsource bp in scaling up their operations. As these companies drive the global energy transition, AI is helping to address significant challenges, from maintaining grid stability to protecting assets against extreme weather.
AI is enabling faster, smarter solutions to emerging challenges.
Utilizing Machine Learning for Solar Power Integration Weather significantly impacts power grids, balancing supply and demand for heating, cooling, and accommodating low-cost green energy on sunny days. Unpredictable weather patterns complicate these decisions. With the rise in renewable energy, grids need advanced tools to manage variable power generation from wind and solar sources.
AI provides highly accurate short-term forecasts, offering grid operators precise production estimates to maintain network stability. Local conditions and topography play crucial roles as renewables increase their share in electricity generation. At Lightsource bp, a two-step process enhances forecasting. In Australia, for example, machine learning forecasts short-term solar irradiance by combining historical data with real-time sky images from on-site cameras. This forecast then predicts power generation with industry-leading accuracy, improving grid stability.
AI-Enhanced Weather Forecasting for Asset Protection In the US, growing hailstorm frequency poses a challenge to solar assets. To mitigate this risk, Lightsource bp initiated ‘Project Whiskeyball,’ a program to protect plant modules from damaging hail. Trackers mounted on solar modules can be angled to reduce the impact of hail.
AI determines when to initiate these interventions, despite the unpredictable nature of hailstorms. Since the project’s inception, over 200 interventions have been made based on daily weather forecasts, effectively reducing damage.
Optimizing Renewable Energy Site Design with AI AI is also instrumental in site selection for renewable energy projects, analyzing land availability, resource potential, environmental impact, grid connection, and economic viability. It helps optimize system designs to maximize performance and value.
This is particularly beneficial for battery energy storage, where AI matches battery specifications to local market dynamics and grid needs. Lightsource bp’s in-house AI tool assesses multiple variables to analyze energy storage system designs, significantly accelerating project evaluation.
Empowering Teams with AI AI empowers Lightsource bp’s teams to navigate the rapidly changing industry. “Our innovation is fuelled by our people,” says Adele Ara, Chief Technology Officer at Lightsource bp. “Our Applied AI & Digital Products team is characterized by curiosity and determination; they talk about all of our projects constantly, successful and failed, so that we can continuously learn and improve.”
Lightsource bp’s culture of innovation encourages bottom-up contributions, allowing the Applied AI and Digital Products team to develop AI solutions for emerging renewable energy challenges, enhancing overall efficiency and scalability.
Read Part One of this series to learn more about AI deployment in the broader renewable energy sector.
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First published in this link of EuropaWIRE.
