Wind Plant Storage Control Using Probability Forecasts

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Solution Overview

Problem

The challenge in managing wind power plants is the stochastic nature of wind conditions and grid demands, which requires dynamic control of energy storage devices to balance power output and grid requirements, while accounting for varying electricity prices and grid events.

Innovation Solution

A method and system that utilize probability forecasts to optimize the charging and discharging of energy storage devices in wind power plants, incorporating chance-constrained model predictive control to manage uncertainties and enhance flexibility and efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If energy storage devices are used to provide virtual inertia and absorb power spikes, then the wind power plant can meet grid requirements and provide stability, but the state of charge must be carefully managed which reduces operational flexibility

Engineering Contradiction:

Improvegrid requirement complianceVSAvoidoperational flexibility

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent implements dynamic state of charge setpoint adjustment based on real-time probability forecasts of wind conditions and grid events. The control system continuously adapts the energy storage device's operating parameters, transitioning from static to dynamic control to simultaneously ensure grid compliance and maintain operational flexibility.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the key parameter of state of charge setpoint based on probabilistic forecasts of future wind conditions and grid events. By adjusting this parameter dynamically according to predicted scenarios, the system optimizes the balance between providing virtual inertia for grid stability and maintaining flexibility for revenue optimization.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If the state of charge is increased to compensate for power production drops during grid events, then reliability is improved, but the ability to maximize revenue through energy arbitrage is reduced

Engineering Contradiction:

Improvepower production stabilityVSAvoidrevenue opportunity

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The control system performs preliminary actions by charging the energy storage device before anticipated grid events or low wind periods, based on probability forecasts. This advance preparation ensures power stability is maintained while minimizing revenue loss, as the system proactively manages state of charge rather than reactively responding to events.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system incorporates feedback loops that continuously monitor actual wind conditions and grid events against predicted scenarios, adjusting the state of charge setpoint in real-time. This feedback mechanism allows the system to learn from deviations and optimize the balance between reliability and revenue maximization over time.

Inventive Principle:

Principle #23Feedback

3Device complexity

If deterministic predictions are used for wind conditions and grid events, then the control strategy is simple to implement, but accuracy is insufficient due to the stochastic nature of these inputs

Engineering Contradiction:

Improvecontrol strategy simplicityVSAvoidprediction accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent introduces probability forecasts as an intermediary between raw wind/grid data and control decisions. Instead of directly using deterministic predictions or raw stochastic data, the system processes inputs through probabilistic modeling to generate forecast distributions, which then guide the control strategy. This intermediary layer bridges the gap between simplicity and accuracy.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system replaces traditional mechanical/deterministic control approaches with a probabilistic control framework. By substituting deterministic prediction mechanisms with probability-based forecasting and chance-constrained optimization, the system achieves higher accuracy in handling the stochastic nature of wind and grid conditions while maintaining computational tractability.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12463425B2Method of controlling a wind power plant according to a probability forecast

Publication Date: 2025.11.04 VESTAS WIND SYSTEMS AS

AI summary

A method of controlling a wind power plant is disclosed. The wind power plant includes an energy storage device and is connected to a power grid. The wind power plant also includes one or more wind turbine generators that produce electrical power for delivery to the power grid. The method includes: processing input data related to one or more inputs to the wind power plant to determine a probability forecast for each input; and controlling charging and discharging of the energy storage device in accordance with each probability forecast and a prescribed probability of violating one or more grid requirements.