Optimizing Hybrid Batteries for Grid-Connected Wind Power Systems

This patent describes a detailed method to figure out the best size and type of hybrid energy storage systems for wind farms connected to the power grid, aiming to cut costs and reliably deliver power.

What it covers

This method helps wind farms decide the best way to combine different energy storage technologies, like batteries and supercapacitors, when connected to the main power grid. First, it analyzes past wind power data by breaking it down into fast and slow changes (frequency domain decomposition) to determine the storage system's initial power rating (Claim 1). Next, it creates a mathematical model that considers the entire lifespan of the wind farm, aiming to both minimize the total cost over time and maximize how consistently the farm can meet its power delivery goals (Claim 1). The method groups typical daily wind patterns using a clustering algorithm to feed into this model (Claim 1). Finally, a multi-objective optimization algorithm solves this model to find the ideal mix and size of energy storage components, which then guides how the wind power system operates (Claim 1). For example, it could determine that a wind farm needs a 10 MWh battery for slow energy shifts and a 2 MW supercapacitor for rapid power fluctuations, ensuring stable grid supply while minimizing replacement costs over 20 years.

What it doesn't cover

• —Does not cover optimal configuration methods for energy storage systems that are not connected to a power grid.
• —Does not cover energy storage optimization for power generation systems other than wind, such as solar or hydroelectric.
• —Does not cover methods that determine energy storage capacity without first performing frequency domain decomposition on historical power output.
• —Does not cover optimization models that do not simultaneously minimize annual cost and maximize a target satisfaction rate of output.
• —Does not cover simple sizing calculations for energy storage that do not involve a multi-objective optimization algorithm for a full life cycle.

The clever bit

The cleverness lies in combining detailed analysis of wind power's fast and slow changes with a sophisticated optimization model that balances long-term costs and consistent power delivery across the entire lifespan of a wind farm. This ensures the hybrid storage system is perfectly tailored to handle wind's variability efficiently.

Why it matters

Wind power is a clean energy source, but its output can fluctuate, making it challenging to integrate reliably into the power grid. This patent provides a systematic way to size and configure hybrid energy storage, which can smooth out these fluctuations. By doing so, it helps make wind farms more reliable and cost-effective, which is crucial for increasing the amount of renewable energy on the grid and ensuring stable power delivery to homes and businesses.

Real-world examples

• 1.Large-scale wind farms integrating battery energy storage systems (BESS)
• 2.Grid operators planning for increased renewable energy penetration
• 3.Hybrid energy storage projects combining batteries and supercapacitors
• 4.Microgrid systems that incorporate wind power and grid connection