Multi-Inverter Voltage Coordination Without Grid Models
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Solution Overview
Problem
Traditional dynamic voltage control methods for power grids with high-penetration renewable energy fail to consider multi-inverter coordination and rely on accurate system models, which are difficult to obtain, leading to inadequate voltage support and instability.
Innovation Solution
A model-free adaptive dynamic voltage control method using a data-driven dynamic linearization model updated in real-time through block update recursive least squares, enabling iterative coordination control among multiple inverters to track voltage reference values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional model-based voltage control methods are used, then control accuracy may be improved, but system adaptability deteriorates due to difficulty in obtaining accurate system models
Solution Approach 1:
The patent replaces traditional model-based control methods with a data-driven dynamic linearization model. Instead of relying on accurate physical system models that are difficult to obtain, the invention uses measured input-output data to construct and continuously update a dynamic linearization model, substituting mechanical/model-based approaches with data-driven approaches to achieve both accuracy and adaptability.
Solution Approach 2:
The system performs self-updating of its control model through the block update recursive least squares method. The dynamic linearization model automatically adapts to changing system conditions by continuously learning from new measurement data without requiring external model updates or manual intervention, enabling the system to serve itself in maintaining optimal control performance.
2Device complexity
If single-inverter dynamic voltage control is implemented, then control simplicity is improved, but voltage support capability deteriorates due to insufficient reactive power output
Solution Approach 1:
The patent merges multiple inverters into a coordinated control system. Instead of treating each inverter independently, the invention combines their reactive power outputs through a unified dynamic voltage control framework, enabling the inverter cluster to provide sufficient voltage support capability while maintaining manageable control complexity through modular implementation.
Solution Approach 2:
The control method developed for multi-inverter coordination is designed to be universally applicable to different inverter configurations and grid conditions. The data-driven dynamic linearization model can adapt to various system scales and topologies, making the solution multi-functional and broadly applicable beyond specific single configurations.
3Adaptability or versatility
If frequent system parameter changes are accommodated, then system adaptability is improved, but control stability deteriorates due to dynamic operating conditions
Solution Approach 1:
The patent implements a dynamic linearization model that continuously adapts to changing system conditions. Instead of using fixed static models, the invention creates a dynamic model that evolves with operating conditions through continuous data updates, allowing the system to maintain stability while accommodating frequent parameter changes in renewable energy generation and load demands.
Solution Approach 2:
The block update recursive least squares method incorporates continuous feedback from measured system data. The model uses real-time measurement data to update and refine its parameters, creating a closed-loop adaptive system that automatically adjusts to changing conditions while maintaining control stability through continuous correction based on actual system behavior.
Data Source
AI summary
The present disclose provides a model-free adaptive dynamic voltage control method considering multi-inverter coordination, relates to a technology field of power system operation. The method includes: constructing a data-driven dynamic linearization model for dynamic voltage control of a new energy cluster; acquiring online measurement data through a measurement apparatus of the new energy cluster, and updating the data-driven dynamic linearization model in real time based on the online measurement data through a block update recursive least squares method; and generating, based on the data-driven dynamic linearization model updated in real time, a dynamic coordination control instruction for a coordination controller of the new energy cluster in an iterative form, and performing adaptive dynamic voltage control based on the dynamic coordination control instruction generated iteratively. With the technical solution of the present disclosure, adaptive dynamic voltage control on the power system is realized.