Power System Stabilizer Frequency Prediction Renewable Energy
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Solution Overview
Problem
Existing power system stabilizers fail to accurately reflect the control effect and influence of renewable energy resources, leading to frequency destabilization due to inappropriate main control amounts and increased correction control, especially with increasing renewable energy interconnection and weather-dependent output fluctuations.
Innovation Solution
A power system stabilizer that includes a correction data generation unit predicting frequency fluctuations based on a renewable energy resources model, a predicted frequency generation unit, and a control amount computation unit, which computes and adjusts control amounts to stabilize the power system frequency during accidents, considering virtual inertia and other control factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional frequency stabilization methods are used without considering renewable energy control effects, then the control system is simple, but the frequency stabilization accuracy deteriorates due to inability to reflect virtual inertia and other control influences
Solution Approach 1:
The system pre-generates correction data by simulating frequency responses under various renewable energy control conditions (virtual inertia, frequency feedback, voltage control, reactive power control, power factor control) before actual frequency stabilization events occur. This preliminary action stores the control effects in a lookup table, allowing the frequency prediction to incorporate these effects without real-time calculation complexity.
Solution Approach 2:
The system creates a simplified representation of complex renewable energy control effects by generating correction data that copies the essential frequency response characteristics. Instead of modeling the full complexity of virtual inertia and other controls in real-time, the system uses pre-simulated correction data that replicates these effects, enabling accurate frequency prediction with reduced computational burden.
2Adaptability or versatility
If renewable energy resources are increased in the power system, then the system adaptability improves, but the frequency stability deteriorates due to weather-dependent output fluctuations and lack of inertia
Solution Approach 1:
The system incorporates frequency feedback function as one of the renewable energy control types in the correction data generation. By simulating and storing the frequency response characteristics of renewable energy resources under feedback control, the system can predict and compensate for frequency deviations caused by renewable energy fluctuations, thereby maintaining frequency stability despite increased renewable energy penetration.
Solution Approach 2:
The system changes the parameters used for frequency prediction by incorporating correction data that accounts for different renewable energy control modes (virtual inertia, frequency feedback, voltage control, etc.). This allows the frequency stabilization system to adapt to varying renewable energy conditions and maintain stability despite parameter changes in the power system composition.
3Measurement precision
If pre-generation of correction data for various renewable energy control types is performed, then the frequency prediction accuracy improves, but the data processing complexity increases
Solution Approach 1:
The system performs the computationally intensive task of generating correction data in advance, during system initialization or offline simulation, rather than in real-time during frequency events. The pre-generated correction data is stored in a lookup table structured by renewable energy control types and system conditions, enabling fast retrieval and application during actual frequency stabilization without real-time processing complexity.
Data Source
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AI summary
There is provided a power system stabilizer including a correction data generation unit that pre-generates correction data related to prediction of a frequency of a power system including a renewable energy resources power supply, based on a renewable energy resources power supply model that models an output of the renewable energy resources power supply and control system data of the renewable energy resources power supply; a predicted frequency generation unit that generates a frequency at the time of occurrence of an accident as a predicted frequency using the correction data; and a control amount computation unit that computes a control amount with respect to the power system using the predicted frequency that corresponds to the occurred accident at the time of occurrence of an accident.