Energy Storage System Control for Wind Power Fluctuation Mitigation

Wind energy, while a key pillar of global decarbonisation, is inherently intermittent, posing challenges to grid stability as turbines inject variable power. Energy storage systems (ESS) have emerged as effective buffers, absorbing short-term surges and supplying deficits to smooth output and maintain power quality. Control strategies span simple low-pass filtering to advanced predictive and adaptive algorithms. Their objectives are to align storage actions with anticipated wind variations, reduce reliance on conventional reserves and mitigate grid frequency deviations. Hybrid configurations, combining batteries with supercapacitors or dual battery banks, leverage complementary response times to address fluctuations across multiple time scales. Real-time coordination between turbine operation and storage dispatch optimises energy capture while meeting grid codes. As wind penetration rises globally, finely tuned ESS control not only secures operational stability but also enhances system economics by trimming storage capacity requirements and extending equipment lifespan.

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Research from all publishers

Recent studies have introduced novel adaptive control and optimisation schemes for battery-based storage in wind farms. One approach employs a master-slave adaptive linear neuron model to track a target power waveform, achieving precise smoothing and reducing required storage capacity in a 99 MW installation. Another development applies model predictive control to a dual-battery system, optimising charge–discharge schedules to improve dispatchability, limit cycling and extend battery life. Field-driven operational analysis of a 1 MW/1.29 MWh battery installation in Brazil has demonstrated effective active-power smoothing and power-factor correction, highlighting the value of real-time data in refining control parameters. Collectively, these works focus on predictive and adaptive frameworks that tailor storage response to both forecasted and observed wind variability, delivering enhanced grid integration and cost-effectiveness.

Energy Storage System Control for Wind Power Fluctuation Mitigation publication trend

The graph below shows the total number of articles in energy storage system control for wind power fluctuation mitigation across all publications each year (not limited to Nature Index journals).

Technical terms

Battery Energy Storage System (BESS): An electrochemical storage unit that absorbs and delivers electrical energy through charge and discharge cycles.

Model Predictive Control (MPC): A control technique that uses a dynamic model to forecast future system behaviour and optimise control actions over a prediction horizon.

State of Charge (SOC): The available energy in a storage device expressed as a percentage of its total capacity.

Hybrid Energy Storage System (HESS): A storage architecture combining two or more technologies (e.g. batteries and supercapacitors) to exploit their complementary power and energy characteristics.

References

1. A master-slave adaptive linear neuron-based approach for cost-effective use of battery energy storage systems in wind farms. Results in Engineering (2024).
2. Dispatching of a Wind Farm Incorporated With Dual-Battery Energy Storage System Using Model Predictive Control. IEEE Access (2020).
3. Operational Data Analysis of a Battery Energy Storage System to Support Wind Energy Generation. Energies (2023).