The model was validated using real-world data from a 200-home community powered in part by a wind turbine. Even after factoring in battery rental costs, the findings revealed significant energy cost savings for the community.
As more households adopt rooftop solar panels and wind turbines, storing surplus power remains a challenge. Simultaneously, battery operators are seeking reliable income streams in unpredictable energy markets. This research outlines a mutually beneficial framework: communities rent a portion of a grid-connected commercial battery, storing energy when it's cheap and drawing it during peak prices.
The innovation hinges on a mathematical model that calculates ideal battery capacity and charge/discharge schedules based on fluctuating electricity prices, tariffs, and demand patterns. The approach aligns profitability with sustainability.
The team also addressed battery longevity. Lead researcher Professor Valentin Robu noted, "Our work explores a number of techniques for modifying linear optimization algorithms. The goal is to increase long-term financial gains from using the battery capacity, while reducing the number of charge/discharge cycles, which can lead to a reduction of the battery's remaining useful lifetime."
Using datasets from GIGA Storage and energy profiles from both the UK and Netherlands, the solution is designed to scale across various countries and regulatory environments. The research supports more effective use of locally generated renewable energy, enhances the viability of community-led power projects, and reduces reliance on centralized utilities.
Research Report:Optimal sizing and control of a grid-connected battery in a stacked revenue model including an energy community
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