Power Plant Control Using Lifetime and Environmental Forecast Modeling
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Solution Overview
Problem
Conventional control methods for power plants with renewable energy systems and energy storage devices fail to optimize overall performance, as they disregard interactions between different energy devices and control features.
Innovation Solution
A method that involves obtaining operating data and estimated environmental data to model residual lifetime, energy production, and power demand satisfaction for renewable energy systems, allowing for adjustment of operating modes to maximize desired characteristics such as lifetime and energy production, while considering interactions between systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional control methods are used for each energy system individually, then each system can be controlled based on its own conditions, but the overall performance of the power plant cannot be optimized due to disregarded interactions between different energy devices
Solution Approach 1:
The patent merges individual control systems into a centralized control system that manages multiple energy systems (wind turbines, solar plants, energy storage devices) as an integrated power plant. The centralized controller receives operating data from all systems and coordinates their operation to optimize overall performance while considering interactions between different energy devices.
Solution Approach 2:
The centralized control system performs multiple functions: it monitors operating data from various energy systems, predicts future operating conditions using environmental data, models different operating modes, and adjusts control parameters across all systems. This universal control approach replaces multiple individual control systems while enhancing overall plant performance.
2Adaptability or versatility
If individual control is applied to each energy system, then local conditions can be considered, but interactions between different energy devices and control features are disregarded
Solution Approach 1:
The control system continuously receives operating data from all energy systems and uses this feedback to adjust control parameters. The system monitors actual performance versus modeled predictions and refines its control strategy accordingly, ensuring both local conditions are considered and overall plant optimization is achieved.
Solution Approach 2:
The system obtains estimated environmental data (wind speeds, solar radiation, temperature) and uses this preliminary information to predict future operating conditions before they occur. This allows the control system to proactively adjust operating modes of energy systems in anticipation of changing conditions, optimizing performance while considering both local and system-wide interactions.
3Productivity
If operating modes are modified to maximize energy production, then energy output increases, but residual lifetime of energy systems may be reduced
Solution Approach 1:
The control system dynamically adjusts operating modes of energy systems based on real-time conditions and future predictions. Rather than using fixed control strategies, the system continuously modifies control parameters to optimize the balance between energy production and lifetime consumption, adapting to changing environmental conditions and system states.
Solution Approach 2:
The system models multiple operating modes with different parameter settings (power output levels, operational intensity) and selects the optimal mode by changing key operating parameters. This allows flexible adjustment between maximizing energy production and preserving system lifetime depending on current conditions and future forecasts.
Data Source
AI summary
A method of controlling the operation of a power plant is provided. The power plant includes plural energy systems, the plural energy systems including plural renewable energy generating systems, wherein the plural energy systems are coupled to a power grid. The method includes obtaining operating data of at least the renewable energy generating systems, the operating data being at least indicative of a lifetime consumption of the renewable energy generating systems; obtaining estimated environmental data that estimates one or more future environmental conditions; and modeling at least one of residual lifetime, energy production, or power demand satisfaction for a power demand for the energy systems. The modeling is based on the obtained operating data and is performed for a future period of time. The modeling considers a modification of operating modes. Based on the modeling, the operation of the power plant is adjusted.