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Multi-Feature Dynamic Reconstruction of Photovoltaic Systems with Battery Storage for Real-Time Grid Monitoring
Tao Xia1, Mingqi Lu1, Ziyan Ding1
1School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China.
Sensors (Basel, Switzerland)
|July 28, 2026
Summary
A new Multi-Feature Dynamic Reconstruction (MFDR) method enhances real-time grid monitoring for photovoltaic (PV) systems with battery storage. This approach significantly reduces computational load while maintaining accurate voltage, current, and power state tracking.
Area of Science:
- Electrical Engineering
- Renewable Energy Systems
- Computational Simulation
Background:
- Real-time grid monitoring of photovoltaic (PV) systems with battery storage necessitates continuous access to electrical states.
- Traditional simulation models face scalability limitations due to the computational demands of calculating switching events for real-time analysis.
Purpose of the Study:
- To introduce and validate a novel Multi-Feature Dynamic Reconstruction (MFDR) method for efficient real-time grid monitoring of PV systems with battery storage.
- To reduce the computational burden of real-time simulations without compromising the accuracy of critical electrical parameters.
Main Methods:
- The MFDR method integrates environmental inputs (irradiance, temperature), averaged converter states, and frequency-domain electrical variables.
- PV output is calculated from environmental data; bidirectional battery converters use low-frequency reconstruction; grid-connected inverters are modeled using dynamic phasors and frequency-domain Norton equivalents.
- Controller hardware-in-the-loop tests were performed under various operating conditions to evaluate the method's performance.
Main Results:
- Tracking errors for transient quantities remained below 3% in peak and normalized values.
- In a large-scale test case (IEEE 118-bus), average CPU utilization decreased from 70.43% to 41.08%, and maximum step execution time reduced from 38 μs to 27 μs.
- The MFDR model, despite having 1069 state variables, operated within a 50 μs simulation step.
Conclusions:
- The MFDR method effectively reduces computational demand for real-time grid monitoring of PV systems with battery storage.
- The approach successfully preserves the accuracy of voltage, current, and power responses essential for grid stability and control.
- MFDR offers a scalable and efficient solution for advanced real-time monitoring applications in power systems.
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