Dynamic Power System Sensitivity for Overload Stabilization
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Solution Overview
Problem
Existing power system stabilization methods fail to adequately account for voltage fluctuations and propagation delays, leading to potential instability during overload conditions and cascade failures.
Innovation Solution
A power system stabilization system that uses dynamic system sensitivity calculations, incorporating measurement data and neural networks to generate sensitivity functions, which account for voltage fluctuations and propagation delays, enabling more accurate and timely overload resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional sensitivity coefficient calculation methods are used, then the calculation is simple and fast, but voltage fluctuations and propagation delays are not accounted for, leading to potential instability
Solution Approach 1:
The patent transforms the static sensitivity coefficient calculation into a dynamic approach by incorporating voltage fluctuations and propagation delays. The sensitivity coefficient is recalculated based on real-time system states, making it adaptive to changing conditions while maintaining computational feasibility through structured calculation methods.
Solution Approach 2:
The patent implements feedback mechanisms by using measured voltage and power data to continuously update the sensitivity coefficient calculations. This feedback loop ensures that the sensitivity coefficients reflect actual system conditions, improving reliability while managing complexity through iterative refinement.
2Reliability
If real-time sensitivity analysis is performed to account for voltage fluctuations and propagation delays, then power system stability is improved, but calculation time and computational resources increase
Solution Approach 1:
The patent performs preliminary calculations by pre-computing certain sensitivity components and system parameters that can be updated less frequently. This allows the main sensitivity analysis to focus only on the critical real-time variables, reducing calculation time while maintaining accuracy in overload resolution.
Solution Approach 2:
The sensitivity calculation is divided into multiple segments: static sensitivity components that change slowly, and dynamic components that require real-time updates. This segmentation allows the system to allocate computational resources efficiently, performing detailed calculations only where and when necessary.
Data Source
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AI summary
Operations for stabilizing a power system are more appropriately supported. A system stabilization system (1) that supports stabilization of a power system includes a dynamic system sensitivity generation unit (2), a system abnormality resolution procedure generation unit (3), and an output unit (6). The dynamic system sensitivity generation unit (2) generates dynamic system sensitivity (D2) of the power system by using measurement data (D1) obtained by a measurement unit installed in the power system and a sensitivity calculation parameter (D7) as inputs. The system abnormality resolution procedure generation unit (3) uses the dynamic system sensitivity (D2), a controllable device list (D3) indicating a controllable device in the power system, and a system abnormality resolution procedure generation policy (D8) as inputs, to generate a system abnormality resolution procedure (D6) with which the power system is operated with the controllable device controlled to resolve a system abnormality in the power system. The output unit (6) outputs the system abnormality resolution procedure (D6).