Amid the wave of green energy development, how communities can access energy storage benefits at low cost has become a key issue. Recently, an international study led by researchers from the Dutch National Research Institute for Mathematics and Computer Science (CWI) has proposed an innovative solution: communities can lease capacity from large commercial batteries without bearing high upfront costs or technical challenges, thereby reducing electricity bills and sharing storage advantages.

The study was conducted collaboratively by CWI researchers, Dutch leading grid-connected battery operator GIGA Storage, the University of Glasgow in the UK, and Princeton University in the US. The team developed a method to precisely determine the battery capacity that energy communities should lease and a fair leasing price, ensuring economic benefits for both communities and battery operators. The findings were published in the journal Applied Energy and tested using real data from a community of 200 households with wind turbines. Results showed that even after deducting leasing costs, communities could still achieve substantial savings.

Currently, rooftop solar panels and small wind turbines are increasingly common in residential areas, but many households face challenges in storing excess electricity. Meanwhile, commercial battery operators need stable revenue sources in volatile energy markets. This study's win-win approach comes at the perfect time.

The core idea is straightforward: battery operators lease part of their large grid-connected batteries to energy communities. The batteries store energy when electricity prices are low and release it when demand and prices rise. Using mathematical models, the researchers identified the "optimal balance" for leased capacity, charging, and discharging times based on market prices, electricity rates, and community energy needs.

Moreover, the team addressed practical challenges—how to control grid-connected batteries without excessive wear. Project lead researcher Professor Valentin Robu explained: "We explored various techniques to improve linear optimization algorithms, aiming to enhance long-term economic benefits from battery capacity utilization while reducing charge-discharge cycles to extend remaining battery life."

The method has been validated using GIGA Storage battery data, as well as energy demand and wind power data from the UK and Netherlands. It has broad applicability across different countries, market environments, and community models. This achievement represents a solid step toward enabling energy communities to utilize more local renewable energy, improving the financial viability of community energy projects, and reducing dependence on large utility companies. It is expected to promote widespread adoption and development of green energy at the community level.