Pumped Storage Load Rejection Test Optimization
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Solution Overview
Problem
Existing load rejection tests for pumped storage groups are inadequate in accurately reflecting actual working conditions due to random fluctuations in hydraulic and mechanical parameters, making it difficult to determine optimal decision contents for the test.
Innovation Solution
A method and device that utilize probability distribution models, semi-invariants, and objective functions to determine the combination of decision contents for an optimal load rejection test, incorporating random variable analysis and risk assessment to account for fluctuations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If only several representative load points are selected for test, then the test complexity is reduced and operation is simplified, but the measurement precision and reliability of reflecting actual working conditions deteriorates
Solution Approach 1:
The patent transforms the static selection of fixed load points into a dynamic optimization process. By using probability distribution models and semi-invariants to represent the random fluctuations of hydraulic and mechanical parameters, the system dynamically determines the optimal number and distribution of load points based on statistical characteristics rather than fixed representative values, thereby improving measurement precision while maintaining operational feasibility
Solution Approach 2:
The patent changes the parameter representation from deterministic fixed load points to probabilistic distributions characterized by semi-invariants. This parameter transformation allows the test design to account for random fluctuations in guide vane opening, water head, and flow rate, converting a simplified but inaccurate approach into a more precise method that still manages test complexity through mathematical modeling
2Reliability
If more load points are selected to reflect actual working conditions, then the measurement precision and reliability improve, but the device complexity and test difficulty increase
Solution Approach 1:
The patent replaces the mechanical approach of increasing the number of physical test points with a mathematical substitution using probability distribution models and semi-invariants. Instead of physically implementing numerous load points to capture random parameter variations, the system uses statistical modeling to represent and analyze these variations, thereby improving reliability without proportionally increasing system complexity
Solution Approach 2:
The patent introduces semi-invariants as an intermediary between the random parameters and the test design. These semi-invariants serve as a mathematical mediator that captures the essential statistical characteristics of parameter fluctuations without requiring direct measurement or implementation of every possible parameter combination, thus bridging the gap between accuracy requirements and system complexity
Data Source
AI summary
A method and device for a load rejection test for a pumped storage group, an apparatus and a medium. The method includes: determining a probability distribution model of at least one known random variable corresponding to a target pumped storage group, and determining an origin moment of the target random variable based on each probability distribution model; determining semi-invariants of the target random variable based on the origin moment of the target random variable; determining a probability density function of the target random variable based on the semi-invariants, and determining an overall offset risk value of the target random variable; determining an objective function based on the overall offset risk value, and determining a combination of target decision contents in the load rejection test for the target pumped storage group, so as to perform the load rejection test on the target pumped storage group.