Wind Power Plant Storage Control for Forecasted Grid Events

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Solution Overview

Problem

Wind power plants face challenges in dynamically controlling their output to match varying grid demands and wind conditions, while also ensuring adequate energy storage to handle critical grid events.

Innovation Solution

A method and control system that process grid data to determine probability forecasts for future grid states and wind conditions, enabling optimized control of energy storage device charging and discharging to meet dynamic grid requirements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If energy storage device capacity is increased to handle critical grid events, then reliability is improved, but device complexity and cost increase

Engineering Contradiction:

Improveability to handle critical grid eventsVSAvoidenergy storage system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The control system performs preliminary forecasting of grid events and wind conditions to proactively manage energy storage charging/discharging schedules. By predicting future grid events and wind patterns, the system prepares energy storage in advance, ensuring adequate capacity is available when needed without requiring excessive over-provisioning of storage capacity.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors actual grid events and wind conditions, comparing them against forecasts to refine future predictions. This feedback loop enables the control system to learn from past performance and improve forecasting accuracy, allowing for more precise energy storage management that balances reliability with reduced storage capacity requirements.

Inventive Principle:

Principle #23Feedback

2Productivity

If energy storage is charged when electricity prices are low to increase revenue, then productivity is improved, but the state of charge decreases when prices are high

Engineering Contradiction:

Improverevenue generation from energy storageVSAvoidstate of charge availability for grid events

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The control system forecasts future electricity prices, grid events, and wind conditions to determine optimal charging schedules in advance. By predicting when prices will be low and when grid events are likely, the system proactively charges energy storage during low-price periods while ensuring sufficient charge remains for predicted high-value grid events, maximizing revenue without compromising reliability.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The energy storage management strategy dynamically adjusts charging/discharging schedules based on real-time and forecasted conditions. The system flexibly modifies its operation to respond to changing price signals, grid event probabilities, and wind forecasts, optimizing the balance between revenue generation and maintaining adequate charge for critical events.

Inventive Principle:

Principle #15Dynamics

3Productivity

If wind power plant output is increased to meet grid demand, then productivity is improved, but the ability to provide virtual inertia decreases

Engineering Contradiction:

Improvepower output to gridVSAvoidvirtual inertia provision

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The control system forecasts future grid events and wind conditions to proactively manage the balance between power output and virtual inertia provision. By predicting when high power output is needed versus when virtual inertia will be required for grid stability, the system can pre-position energy storage charge levels to meet both demands appropriately.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts the operating mode of energy storage between charging, discharging for power output augmentation, and discharging for virtual inertia provision. Based on real-time grid conditions, forecasted events, and wind patterns, the control system flexibly switches between these modes to simultaneously maximize power delivery and maintain virtual inertia capabilities when needed.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS12224590B2Method of controlling a wind power plant

Publication Date: 2025.02.11 VESTAS WIND SYSTEMS AS

AI summary

A method of controlling a wind power plant including an energy storage device, the wind power plant being connected to a power grid and comprising one or more wind turbine generators that produce electrical power for delivery to the power grid, the method comprising: processing grid data related to the power grid to determine a probability forecast for a future state of the grid; and controlling charging and discharging of the energy storage device in accordance with the probability forecast.