Assets

Balancing the power grid

Flexibility is key for transitioning to a renewable-powered grid. Our value-stacking AI algorithms empower assets to stabilize the grid while boosting revenues.

Qurrent’s platform optimizes renewable resources and battery storage solutions for the best of the resource owner and the grid at large.

Battery storage

Battery storage systems are essential for enhancing long-term grid stability and reliability. Operating independently, these batteries can charge, discharge, or remain idle as needed. This flexibility allows them to participate in frequency regulation markets (e.g. FCR, FFR) and contribute to grid stability. Additionally, they can help mitigate imbalances and enable spot price arbitrage, providing economic returns while ensuring a more resilient and adaptable grid. Our platform unlocks the full potential of the asset.

mFRR cap mFRR FCR-N FCR-D Peak shaving Intraday Day-Ahead FFR

Solar

Solar power is currently the fastest growing energy source, fueled by falling costs and rising demand for renewable energy. Beyond clean energy production, solar can actively contribute to grid stability by downregulating production at times of excess supply. Leveraging solar energy for downregulation ancillary services, we can optimize the use of renewable resources, enhance grid stability and improve returns. Our real-time regulation capabilities ensure that solar production is precisely adjusted to meet grid needs, maximizing both efficiency and returns.

Day-Ahead (curtilment)mFRR cap mFRR FCR-D

Wind

Wind power is a crucial source of clean, renewable energy. Wind turbines can dynamically adjust their output to provide frequency regulation services, such as downregulation at times of oversupply. This capability allows wind power to contribute to grid stability whilst producing renewable energy. Wind power is eligible for participation in ancillary services and reserve markets.

Day-Ahead (curtilment)mFRR cap mFRR FCR-D

Use-cases

Co-Location

Battery + solar

Combining battery storage systems with solar parks at a shared grid connection offers significant opportunities for added value. This scenario is becoming increasingly common, as permitting is often simpler when integrating a battery into an existing facility.

By co-locating batteries and solar, operators shift production from times of low demand (and lower prices) to periods of higher demand and cost. This added strategy enhances profitability while also retaining the options to deploy the strategies that solar and battery systems offer when deployed independently.

A common challenge with co-location is the limitation of the grid connection. To maximize the potential of a co-located site, Qurrent’s advanced algorithm continuously monitors and forecasts available grid capacity, adjusting energy bids in real-time to ensure optimal utilization.

Battery + EV charging

One of the primary challenges for EV charging infrastructure today is obtaining approvals for grid connections, especially for larger stations that require megawatt-level power output. Grid operators often struggle to approve these high-capacity connections.

However, most charging stations operate well below full capacity, meaning the average load is much lower than the peak demand.

By integrating battery systems, EV charging sites can store energy during periods of low demand and discharge it during peak times. This helps balance the load and reduces the need for oversized grid connections. Qurrent collaborates with these sites to optimize battery usage, allowing the system to participate in various energy markets when not in use for EV charging, further enhancing the financial viability for operators.

Battery + Site loads

In Commercial & Industrial (C&I) settings, it’s common to have multiple types of loads competing for capacity on the grid connection.

While battery systems are valuable for peak shaving, optimizing their use becomes more complex when both energy consumption and on-site production need to be managed.

Qurrent's advanced algorithms leverage historical production and consumption data to continuously forecast available grid capacity. This allows for more precise battery system optimization, ensuring efficient energy management and maximized performance in even the most dynamic environments.

FAQS

Frequently asked questions

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