Electro-Thermal Virtual Power Plant Aggregation Using SVM Equivalence
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Solution Overview
Problem
Existing model-driven approaches for equivalent aggregation of electro-thermal coupled virtual power plants are inaccurate due to uncertainties in heating section model parameters, leading to power deviations that do not meet aggregation assessment requirements.
Innovation Solution
A method that uses a support vector machine to obtain an equivalence model in the heating section, establishing and solving a computing model for equivalent aggregation, combining data-driven and model-driven approaches to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a model-driven approach is used for equivalent aggregation, then the theoretical framework is complete, but the aggregation accuracy deteriorates due to parameter uncertainties
Solution Approach 1:
The patent introduces a data-driven intermediary layer (support vector machine model) between the theoretical physical model and the actual heating section parameters. This intermediary learns the mapping relationship from operational data, compensating for the inaccuracies in theoretical model parameters without requiring direct measurement of difficult-to-obtain parameters like pipe wall thickness and thermal conductivity.
Solution Approach 2:
The patent transforms the aggregation problem from relying on fixed theoretical parameters to using adaptive data-driven parameters. The support vector machine model continuously adjusts its parameters based on historical operational data, allowing the aggregation accuracy to improve over time while the underlying physical model remains unchanged.
2Productivity
If theoretical model parameters are used, then the calculation process is simplified, but the power deviation increases and fails to meet assessment requirements
Solution Approach 1:
The patent performs preliminary data collection and model training offline before the actual aggregation calculation. Historical operational data is collected and used to train the support vector machine model in advance, so that during real-time aggregation, only the trained model needs to be applied, maintaining high calculation efficiency while improving power deviation control.
Solution Approach 2:
The patent creates a data-driven copy (support vector machine model) of the complex heating section behavior. Instead of directly measuring difficult parameters or performing complex theoretical calculations, the system creates a virtual replica that mimics the heating section's response based on historical data, simplifying the aggregation process while improving accuracy.
Data Source
AI summary
The present disclosure provides an equivalent aggregation method and an apparatus for an electro-thermal coupled virtual power plant. The method includes: obtaining an equivalence model in a heating section of the electro-thermal coupled virtual power plant by training a support vector machine; establishing a computing model for equivalent aggregation of the electro-thermal coupled virtual power plant; and realizing the equivalent aggregation of the electro-thermal coupled virtual power plant by solving the computing model for the equivalent aggregation of the electro-thermal coupled virtual power plant.