Communication-Less Power Sharing Strategy for Microgrids Using Oscillations Generated by Inertia-Enabled Power Sources
Abstract
1. Introduction
- Avoiding communication links when controlling an MG due to their known disadvantages;
- Identifying the DGSs that are connected to an MG using only local measurements that contain the electromechanical oscillations generated by each DGS after a disturbance;
- Computing the load power of an MG using an (off-line-trained) ANN fed by only local measurements;
- Finally adjusting the slope coefficients of the droop controller in each DGS and enhancing the power sharing ratio of an MG.
- The oscillation frequency of each synchronverter-based DGS in an MG can be fixed to a desired value. This allows a different oscillation frequency to be selected for each DGS to prevent them from being near one another, effectively having a distinctive and identifiable frequency fingerprint for each DGS, even if they are similarly rated. The recognition of patterns in electrical waveforms after a change in the operating conditions of an MG has been reported, for example, by Díaz N. L. et al. [37], but these patterns are based on the charge/discharge characteristics of ESSs that degrade over time and can introduce uncertainty, as well as by Serban E. et al. [40], but these are based on intentional variation in the system frequency, where other phenomena that cause frequency deviations can introduce uncertainty into the information obtained, and by Baldwin, M.W. et al. [42] for detecting the natural oscillation frequency of generators and determining whether these are connected to an electric network, but the oscillation frequency is fixed, which results in similarly rated generators with a similar natural oscillation frequency. On the other hand, in this work, the oscillatory patterns depend on the controller parameters of a synchronverter algorithm that can be set to specific values, which makes it easier to discriminate among DGSs.
- The droop controller coefficients are adjusted. This changes the slope of the droop controller of each DGS to enhance the voltage and frequency regulation and the power sharing ratio among DGSs. Adjusting coefficients has also been reported, for example, by Khayat Y. et al. [39], who propose adjusting the controller, but the focus is only on frequency regulation, whereas in this work, the voltage, frequency, and power sharing ratio are enhanced.
- The DGSs connected to an MG can be detected. This allows the controller to be adapted to meet the requirements. Other authors have proposed adaptive controllers; for example, Belgana S. et al. [41] use an adaptive neural network droop control strategy and particle swarm optimization to generate optimal voltage references that compensate for line effects and load variations; however, the results do not consider whether a DGS is connected or disconnected from the MG, which has a great impact on voltage, frequency, and power sharing.
2. Synchronverter Controller Based on the Droop Scheme
2.1. Droop Controller
2.2. Synchronverter Controller
3. Electromechanical Oscillations as Information Carrying Signals
4. Generation and Load Assessment Using Local Measurements
4.1. Detection of the DGS Through Electromechanical Oscillations
4.2. Load Estimator
4.3. Slope Coefficient Calculator
5. Simulation Results
5.1. Full Renewable Energy Power Injection
5.2. Increasing the Imported Energy of an MG to Aid in Load Supply
6. Discussion
6.1. Quality of the Voltage Magnitude and Frequency and Its Relation to Stability of the Droop Controller
6.2. Operation Under Short Circuits
6.3. DGSs Reaching Their Power Limit
6.4. Constantly Changing Load Power
6.5. Occurrence of Subsynchronous Oscillations
6.6. Non-Fourier-Based Algorithm for Detecting Oscillations
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
ANN | Artificial Neural Network |
CCU | Central Control Unit |
DGS | Distributed Generation Source |
EPS | Electric Power System |
ESS | Energy Storage System |
FCPB | Frequency Control Proportional Band |
ICU | Individual Control Unit |
MG | Microgrid |
RE | Renewable Energy |
SG | Synchronous Generator |
VCPB | Voltage Control Proportional Band |
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Value | Description | Appears in | |
---|---|---|---|
Microgrid data | Line impedance of all sources | Figure 4 | |
Controller data | DGS voltage reference | Figure 3 | |
Load node voltage reference | Figure 3 | ||
Microgrid frequency of reference | Figure 3 | ||
Moment of inertia of | Figure 3 | ||
Moment of inertia of | Figure 3 | ||
Moment of inertia of | Figure 3 | ||
Moment of inertia of back-to-back | Figure 3 | ||
Integral constant of all | Figure 3 | ||
Inverter data | Switching frequency | Figure 2 | |
Inductor filter resistance | Figure 2 | ||
Filter inductance | Figure 2 | ||
Filter capacitance | Figure 2 |
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Gutierrez, M.; Zuniga, P.; del Puerto-Flores, D.; Uribe, F.; Barocio, E. Communication-Less Power Sharing Strategy for Microgrids Using Oscillations Generated by Inertia-Enabled Power Sources. Electricity 2025, 6, 59. https://doi.org/10.3390/electricity6040059
Gutierrez M, Zuniga P, del Puerto-Flores D, Uribe F, Barocio E. Communication-Less Power Sharing Strategy for Microgrids Using Oscillations Generated by Inertia-Enabled Power Sources. Electricity. 2025; 6(4):59. https://doi.org/10.3390/electricity6040059
Chicago/Turabian StyleGutierrez, Marco, Pavel Zuniga, Dunstano del Puerto-Flores, Felipe Uribe, and Emilio Barocio. 2025. "Communication-Less Power Sharing Strategy for Microgrids Using Oscillations Generated by Inertia-Enabled Power Sources" Electricity 6, no. 4: 59. https://doi.org/10.3390/electricity6040059
APA StyleGutierrez, M., Zuniga, P., del Puerto-Flores, D., Uribe, F., & Barocio, E. (2025). Communication-Less Power Sharing Strategy for Microgrids Using Oscillations Generated by Inertia-Enabled Power Sources. Electricity, 6(4), 59. https://doi.org/10.3390/electricity6040059