Aggregated Electrolysis Plant Modeling for Grid Code Verification
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Solution Overview
Problem
Current simulation methods for large-scale electrolysis plants with multiple electrolysis systems require excessive processor time and may introduce artificial instabilities, making it difficult to meet grid code compliance requirements and potentially leading to unnecessary equipment oversizing and costs.
Innovation Solution
A computer-implemented method using an aggregated model of electrolysis systems, characterized by scaled parameter values, to simulate grid code compliance without interface algorithms, representing the cumulative behavior of parallel electrolysis systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed EMT simulation models are used for each electrolysis system, then grid code compliance verification accuracy is improved, but processor time requirements and computational resources increase excessively
Solution Approach 1:
Multiple individual electrolysis systems are merged into a single aggregated electrolysis system that represents the cumulative behavior of all parallel systems. The aggregated model combines the electrical characteristics of individual systems while reducing computational complexity, enabling grid code compliance verification without excessive processor time requirements.
Solution Approach 2:
The model parameters are scaled to represent the aggregated behavior of multiple electrolysis systems. By changing the parameter representation from individual system values to scaled aggregated values, the simulation maintains accuracy for grid code compliance verification while reducing the number of computational elements.
2Productivity
If interface algorithms are used to aggregate electrolysis systems, then computational resources are reduced, but artificial instabilities are introduced in the simulation
Solution Approach 1:
The interface algorithm that causes artificial instabilities is removed from the simulation model. Instead of using complex interface algorithms to connect aggregated systems, the invention directly models the aggregated electrolysis system with scaled parameters, eliminating the source of simulation instability while maintaining computational efficiency.
3Manufacturing precision
If individual system simulations are performed for dozens or hundreds of electrolysis systems, then detailed grid compliance testing is achieved, but CPU resource demands become unmanageable
Solution Approach 1:
Dozens or hundreds of individual electrolysis system simulations are merged into a single aggregated simulation. The aggregated model preserves the detailed grid compliance testing capability by maintaining accurate electrical characteristics while reducing CPU resource demands through consolidation of computational elements.
Solution Approach 2:
Individual system parameters are transformed into aggregated parameters that represent the cumulative behavior of multiple systems. This parameter transformation enables detailed grid compliance testing with reduced computational complexity by working with scaled aggregate values rather than individual system values.
Data Source
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AI summary
A computer-implemented method 100 for verifying a grid code compliance of an electrolysis plant is provided, wherein the electrolysis plant comprises a plurality of essentially identical electrolysis systems connected in parallel to a same AC power grid. The method comprises determining 104 a model of the AC power grid and at least one grid compliance requirement, determining 106 a model of the electrolysis plant, and verifying 108 a grid code compliance of the electrolysis plant by performing a simulated grid compliance test with respect to the at least one grid compliance requirement, for the model of the electrolysis plant connected to the model of the AC power grid, wherein the step of determining 106 a model of the electrolysis plant comprises determining 110 a first set of parameter values characterizing a first electrolysis system of the plurality of essentially identical electrolysis systems and a scaling factor corresponding to a size of the plurality of essentially identical electrolysis systems, and determining 112 an aggregated set of parameter values characterizing the electrolysis plant as the first set of parameter values scaled depending on said scaling factor.