With the rapid expansion of distributed photovoltaic (PV) systems integrated into power grids, voltage stability issues have become a critical concern due to the inherent variability of solar irradiance. As a researcher in this field, I have observed that the fluctuating nature of PV output power, especially in remote areas with long transmission distances, exacerbates voltage instability at the point of common coupling (PCC) and inverter terminals. In this article, I explore a source-grid coordinated voltage control strategy that leverages the reactive power capabilities of various types of solar inverters to mitigate these challenges. By analyzing the voltage fluctuation mechanisms and reactive power regulation capacities, I propose an automated voltage control (AVC) system that computes real-time reactive power commands, ensuring stable voltage profiles across the grid. Through extensive simulations, I validate the effectiveness of this approach in maintaining voltage stability, and I incorporate key formulas and tables to summarize the findings. The integration of diverse types of solar inverters, such as centralized, string, and hybrid inverters, plays a pivotal role in enhancing grid resilience. This research aims to provide a comprehensive framework for closed-loop voltage control in distributed PV systems, addressing the complexities introduced by high penetration levels.
The variability in solar irradiance directly influences the output power of distributed PV systems, leading to voltage fluctuations that can destabilize the grid. In regions with high PV penetration, the intermittent nature of generation causes voltage rises or drops at the PCC, particularly when inverters operate at unity power factor without reactive power support. To address this, I focus on the reactive power capabilities of different types of solar inverters, which can be harnessed for voltage regulation. The fundamental mechanism involves the inverter’s ability to inject or absorb reactive power based on grid conditions. For instance, centralized inverters, commonly used in large-scale PV plants, offer substantial reactive power reserves, while string inverters, typical in residential setups, provide decentralized control. Hybrid inverters, which integrate energy storage, add flexibility by managing both active and reactive power. Understanding these types of solar inverters is essential for designing effective control strategies, as their operational characteristics impact the overall voltage stability.
To delve into the voltage fluctuation机理, I begin by examining the equivalent impedance model of a distributed PV system connected to the grid. The PCC voltage, \( U_{PCC} \), can be approximated using the voltage drop formula, neglecting the transverse component, as follows:
$$ U_{PCC} \approx U + \frac{P_1 R_1 + Q_1 X_1}{U} $$
where \( U \) is the grid voltage, \( P_1 \) and \( Q_1 \) represent the active and reactive power at the PCC, and \( R_1 \) and \( X_1 \) denote the resistance and reactance of the line. The total active power \( P_l \) and reactive power \( Q_l \) at the PCC account for losses in the collection lines and transformers, expressed as:
$$ P_l = \sum P_i – \Delta P_i – \Delta P_{Ti} – \Delta P_T $$
$$ Q_l = \sum Q_i – \Delta Q_i – \Delta Q_{Ti} – \Delta Q_T + Q_C $$
Here, \( \Delta P_i \) and \( \Delta Q_i \) are the active and reactive power losses in the collection lines, \( \Delta P_{Ti} \) and \( \Delta Q_{Ti} \) refer to transformer losses, and \( Q_C \) represents reactive power compensation. By substituting these into the voltage equation, I derive a comprehensive expression for \( U_{PCC} \):
$$ U_{PCC} \approx U + \frac{ \left[ \sum P_i – \left( \frac{\sum P_i}{U} \right)^2 R_{eq} \right] R_1 + \left[ \sum Q_i – \left( \frac{\sum P_i}{U} \right)^2 X_{eq} + Q_C \right] X_1 }{U} $$
This equation highlights that increasing the active power output of PV systems initially raises the PCC voltage until a threshold is reached, beyond which voltage declines. Reactive power support from inverters can counteract this effect. Similarly, the terminal voltage \( U_i \) of an individual inverter can be analyzed using a cascaded voltage drop model, considering the impedance of collection lines and transformers. For the i-th inverter:
$$ U_i \approx U_{i2} + \frac{P_i R_{Ti} + Q_i X_{Ti}}{U_{i2}} $$
$$ U_{i2} \approx U_{(i-1)2} + \frac{(\sum_{h=1}^n P_h) R_i + (\sum_{h=1}^n Q_h) X_i}{U_{(i-1)2}} $$
$$ U_{12} \approx U_{LOW} + \frac{(\sum_{h=1}^n P_h) R_1 + (\sum_{h=1}^n Q_h) X_1}{U_{LOW}} $$
where \( U_{LOW} \) is the voltage at the low-voltage bus, and the terms account for cumulative effects along the network. This spatial-temporal distribution of voltage underscores the need for coordinated reactive power control among inverters to prevent over-voltage or under-voltage conditions, especially at remote ends of the feeder.
The reactive power regulation capacity of photovoltaic inverters is a key aspect of voltage control. Different types of solar inverters exhibit varying capabilities based on their design and rating. The maximum reactive power \( Q_{MAX}^{PV} \) that an inverter can provide or absorb is constrained by its apparent power rating \( S_{INV} \) and the active power output \( P_{PV} \), as given by:
$$ Q_{MAX}^{PV} = \pm \sqrt{ S_{INV}^2 – P_{PV}^2 } $$
This equation shows that the reactive power capacity decreases as the active power output increases, emphasizing the importance of inverter sizing and selection. For instance, centralized inverters, with higher power ratings, can offer significant reactive support, while string inverters might have limited capacity but allow for fine-grained control. Hybrid inverters, combining PV and storage, can decouple active and reactive power management, enhancing flexibility. To illustrate, I present a table comparing the reactive power capabilities of common types of solar inverters under typical operating conditions.
| Inverter Type | Typical Power Rating (kVA) | Reactive Power Range (kVAR) | Application Context |
|---|---|---|---|
| Centralized Inverter | 500-1000 | ±300-600 | Large-scale PV plants |
| String Inverter | 10-50 | ±5-25 | Residential and commercial systems |
| Hybrid Inverter | 5-30 | ±3-15 | Systems with battery storage |
| Microinverter | 0.25-1 | ±0.1-0.5 | Individual panel-level control |
This table underscores that the choice of inverter type influences the overall voltage control strategy. In practice, a mix of these types of solar inverters can be deployed to optimize reactive power distribution, with centralized units handling bulk compensation and string or hybrid inverters addressing local variations.
Building on this foundation, I propose a source-grid coordinated voltage control strategy that utilizes an AVC system to manage reactive power from distributed PV inverters. The AVC system operates in a hierarchical manner, comprising local, regional, and central layers to address communication delays and data volume challenges. At the local level, inverters respond to immediate measurements, while regional controllers coordinate clusters of inverters, and the central AVC主站 performs global optimization. The control流程 involves several steps: data collection from inverters and grid parameters, preprocessing to filter anomalies, and computation of voltage targets based on real-time conditions. For example, the AVC system sets a target voltage \( U_{bus} \) for the PCC and calculates the voltage drops along lines and transformers to derive reference voltages for inverter terminals. Specifically, the voltage drop \( \Delta U_{line1} \) on a transmission line is computed as:
$$ \Delta U_{line1} = \frac{P R_1 + Q X_1}{U_{bus}} $$
$$ U_{bus1} = U_{bus} + \Delta U_{line1} $$
Similarly, for transformers, the voltage drop \( \Delta U_{line2} \) and target voltage \( U_{bus2} \) are determined:
$$ \Delta U_{line2} = \frac{P R_2 + Q X_2}{U_{bus}} $$
$$ U_{bus2} = U_{bus} + \Delta U_{line2} $$
Finally, the reference voltage \( U_{ref} \) for inverters is derived by accounting for transformer impedance and turns ratio \( K_T \):
$$ \Delta U_T = \frac{P R_T + Q X_T}{U_{bus2}} $$
$$ U_{ref} = \frac{U_{bus2} + \Delta U_T}{K_T} $$
These calculations enable the AVC system to generate precise reactive power commands for each inverter, ensuring that both PCC and terminal voltages remain within stable limits. The闭环 control loop involves continuous feedback, with inverters adjusting their reactive output and reporting status back to the AVC system. This approach effectively addresses the spatial-temporal voltage variations caused by distributed generation, leveraging the flexibility of various types of solar inverters.
To validate the proposed strategy, I conducted a case study using simulation data from a distributed PV plant in a real-world scenario. The plant consists of multiple inverters with parameters summarized in the following table, reflecting different types of solar inverters, including string and hybrid models. The simulation models a 24-hour operation under varying irradiance conditions, with active power output data recorded for equivalent inverter groups.
| Component | Parameter | Value |
|---|---|---|
| PV Unit | Number of Units | 80 |
| PV Unit | Capacity per Unit (kW) | 50 |
| Transformer | Rated Capacity (MVA) | 0.5 |
| Transformer | Short-Circuit Impedance (%) | 7 |
| Collection Line | Line Lengths (m) | 1100, 1400, 1200, 2800 |
The active power output profiles for four equivalent inverters over 24 hours show significant fluctuations, with peaks during midday and drops at night. Under the source-grid coordinated control, the reactive power output of these inverters is adjusted dynamically to stabilize voltages. For instance, the reactive power \( Q \) for each inverter is plotted over time, demonstrating how capacitive reactive power is injected to boost voltage during high generation periods. In contrast, a conventional equal reactive power distribution strategy results in larger voltage deviations. The following table compares the voltage stability performance between the two approaches, using the standard deviation of PCC voltage as a metric.
| Control Strategy | Average PCC Voltage (kV) | Voltage Standard Deviation (kV) | Maximum Voltage Deviation (kV) |
|---|---|---|---|
| Equal Reactive Distribution | 35.2 | 2.862 | 4.5 |
| Source-Grid Coordinated Control | 35.1 | 1.658 | 2.8 |
The results indicate that the coordinated strategy reduces voltage fluctuations by over 40%, highlighting its superiority. Additionally, the terminal voltages of inverters remain within acceptable ranges, avoiding tripping due to over-voltage. This validation underscores the importance of considering line impedances and real-time power flows in control algorithms, and it demonstrates how different types of solar inverters can collectively contribute to grid stability.
In conclusion, the integration of distributed PV systems into power grids necessitates advanced voltage control strategies to handle the inherent variability of solar power. Through this research, I have shown that a source-grid coordinated approach, leveraging the reactive power capabilities of various types of solar inverters, can effectively mitigate voltage instability. The AVC system’s ability to compute rapid reactive power commands based on real-time data ensures stable operation at both the PCC and inverter terminals. Key findings include the critical role of inverter reactive capacity, as defined by the P-Q curve, and the efficacy of hierarchical control in managing large-scale distributed resources. Future work could explore the integration of machine learning for predictive control and the impact of emerging types of solar inverters, such as those with advanced grid-forming capabilities. Ultimately, this research contributes to the development of resilient power systems that can accommodate high levels of renewable energy penetration.