In recent years, the global energy landscape has undergone a significant transformation driven by the rapid adoption of renewable energy sources. Distributed photovoltaic (PV) systems, particularly those integrated into medium and low voltage distribution networks, have seen exponential growth. However, the high penetration of distributed solar power introduces critical challenges, such as voltage violations and increased operational uncertainties. Traditional voltage control methods, including network reconfiguration, on-load tap changers, and capacitor banks, often fall short in addressing these issues due to their slow response times and limited coverage in low voltage areas. In this context, solar inverters emerge as a pivotal solution, offering both active and reactive power control capabilities to enhance voltage stability. This paper proposes a hierarchical coordination control strategy that leverages solar inverter adjustments to mitigate voltage quality problems in distribution networks with high proportions of distributed PV.
The integration of distributed solar power has transformed distribution networks from passive to active systems, leading to bidirectional power flows and frequent voltage fluctuations. Solar inverters, which convert DC power from PV panels to AC, can provide additional grid services by adjusting their active and reactive power outputs. Unlike conventional devices, solar inverters can respond rapidly to voltage changes, making them ideal for real-time control. This paper explores the potential of solar inverters in voltage regulation, focusing on a partitioned voltage interval control method and a two-stage hierarchical control architecture for medium and low voltage networks. The proposed strategy aims to minimize network losses, reduce voltage deviations, and maximize the utilization of distributed solar power, ensuring the secure and stable operation of active distribution networks.
Voltage control in distribution networks has evolved from centralized to decentralized approaches, with solar inverters playing a crucial role. Traditional methods, such as tap changer adjustments and capacitor switching, are effective but lack the granularity needed for low voltage networks. In contrast, solar inverters can be deployed at various points in the network, providing localized voltage support. The reactive power capability of a solar inverter is determined by its apparent power rating and the instantaneous active power output. For instance, the available reactive power \( Q_{PV} \) from a solar inverter can be expressed as:
$$ Q_{PV} = \sqrt{S_{PV}^2 – P_{PV}^2} $$
where \( S_{PV} \) is the inverter’s rated apparent power, and \( P_{PV} \) is the active power output. This equation highlights that the reactive power capacity increases when the active power output decreases, allowing solar inverters to inject or absorb reactive power as needed. Two primary control strategies are commonly used: power factor control (\( \cos \phi(P) \)) and voltage-dependent reactive power control (\( Q(U) \)). The \( \cos \phi(P) \) strategy maintains a constant power factor based on the active power output, while the \( Q(U) \) strategy adjusts reactive power in response to voltage measurements. The latter is more flexible and can be tailored to specific voltage thresholds, as shown in the following control curve.
In addition to reactive power control, solar inverters can also regulate active power to prevent overvoltage conditions. Under normal operation, solar inverters operate in maximum power point tracking (MPPT) mode to maximize energy harvest. However, when the grid voltage exceeds permissible limits, the inverters can curtail active power output according to a predefined voltage-active power curve. This approach reduces reverse power flow and alleviates voltage rise issues. The combined use of active and reactive power control enables solar inverters to provide comprehensive voltage support, enhancing the resilience of distribution networks.
Building on these concepts, we propose a voltage interval partitioning method for solar inverters, which divides the voltage range into five distinct zones. Each zone corresponds to specific control actions, ensuring optimal inverter response under varying grid conditions. The voltage thresholds are defined as follows: \( U_{L1} \) (lower voltage limit), \( U_{L0} \) (optimal lower limit), \( U_{U0} \) (optimal upper limit), and \( U_{U1} \) (upper voltage limit). The control strategies for each zone are summarized in Table 1.
| Voltage Zone | Control Action |
|---|---|
| \( U \leq U_{L1} \) | Zone III: Inverter reaches maximum capability; external control required. |
| \( U_{L1} < U \leq U_{L0} \) | Zone II: Reactive power control via Q(U) curve. |
| \( U_{L0} < U \leq U_{U0} \) | Zone I: No action needed; voltage within optimal range. |
| \( U_{U0} < U < U_{U1} \) | Zone IV: Prioritize reactive power control; if insufficient, activate active power curtailment. |
| \( U \geq U_{U1} \) | Zone V: Inverter disconnects from grid due to overvoltage. |
This partitioned control method ensures that solar inverters respond appropriately to voltage deviations, minimizing the need for centralized interventions and improving the overall efficiency of the distribution network. The use of solar inverters for voltage control is particularly beneficial in networks with high PV penetration, where traditional methods may be inadequate.
To implement a coordinated voltage control strategy across medium and low voltage networks, we propose a two-stage hierarchical architecture. The first stage focuses on medium voltage control, while the second stage addresses low voltage adjustments, with iterative coordination between the two layers. This architecture leverages the communication capabilities of smart devices, such as intelligent terminals in low voltage areas, to exchange data and control signals. The medium voltage control layer collects operational parameters from low voltage areas, including three-phase voltages and net power flows, and optimizes the setpoints for distributed solar inverters and capacitor banks. The optimization model aims to minimize network losses, voltage deviations, and maximize distributed generation hosting capacity. The objective function is formulated as:
$$ \min f = w_1 P_{loss}^* + w_2 U_D^* – w_3 P_{DG}^* $$
where \( P_{loss}^* \), \( U_D^* \), and \( P_{DG}^* \) are the per-unit values of network losses, voltage deviation, and distributed generation output, respectively. The weights \( w_1 \), \( w_2 \), and \( w_3 \) sum to 1 and reflect the relative importance of each objective. For instance, in areas with frequent voltage violations, \( w_2 \) can be set higher to prioritize voltage stability. The constraints include power flow equations, branch current limits, voltage boundaries, and inverter capacity limits. The power flow constraints are expressed as:
$$ \sum_{j \in i} (P_i – U_i U_j (G_{ij} \cos \theta_{ij} + B_{ij} \sin \theta_{ij})) + P_{DG,i} = 0 $$
$$ \sum_{j \in i} (Q_i – U_i U_j (G_{ij} \sin \theta_{ij} – B_{ij} \cos \theta_{ij})) = 0 $$
where \( P_i \) and \( Q_i \) are the active and reactive power injections at node i, \( U_i \) and \( U_j \) are voltage magnitudes, \( G_{ij} \) and \( B_{ij} \) are the conductance and susceptance of the line between nodes i and j, and \( \theta_{ij} \) is the phase angle difference. The branch current and voltage constraints are:
$$ I_{ij,min} \leq I_{ij} \leq I_{ij,max} $$
$$ U_{min} \leq U_i \leq U_{max} $$
Additionally, the solar inverter outputs are constrained by:
$$ P_{DG,min} \leq P_{DG} \leq P_{DG,max} $$
$$ Q_{DG,min} \leq Q_{DG} \leq Q_{DG,max} $$
The low voltage control layer performs localized optimization based on the setpoints received from the medium voltage layer. It adjusts the outputs of residential solar inverters and other controllable devices to meet the power and voltage targets. The control process is iterative, with the low voltage layer feedbacking its adjustable power range to the medium voltage layer for further optimization. This hierarchical approach reduces computational burden and enhances scalability, making it suitable for large-scale distribution networks.
The effectiveness of the proposed strategy is validated through simulations on the IEEE 33-node system and a real distribution network. In the IEEE 33-node case, the network is modified to include distributed solar inverters at various nodes, and two optimization scenarios are compared: one using only reactive power control and another employing the proposed hierarchical strategy. The results demonstrate that the hierarchical approach reduces total losses by 3.79% and voltage deviation by 27.29% compared to the initial state. The objective function values for different scenarios are summarized in Table 2.
| Scenario | Losses (kW) | Voltage Deviation (%) | DG Utilization (kW) | Objective Value |
|---|---|---|---|---|
| Initial | 372.71 | 16.71 | 6675.80 | 0.40 |
| Reactive Control Only | 372.71 | 15.84 | 6675.80 | 0.37 |
| Hierarchical Control | 358.57 | 12.15 | 6475.07 | 0.25 |
In the real distribution network case, which includes multiple medium and low voltage areas with high PV penetration, the proposed strategy is tested against traditional methods like tap changer adjustments and reactive power control. The results show that the hierarchical control reduces losses by 36.33% and voltage deviation by 62.59%, while also mitigating reverse power flow. The comparative performance metrics are presented in Table 3.
| Scenario | Losses (kW) | Voltage Deviation (%) | DG Utilization (kW) | Objective Value |
|---|---|---|---|---|
| Initial | 119.09 | 18.15 | 6890.22 | 0.40 |
| Tap Changer Adjustment | 119.09 | 10.82 | 6890.22 | 0.19 |
| Reactive Control Only | 128.91 | 8.65 | 6890.22 | 0.15 |
| Hierarchical Control | 75.82 | 6.79 | 5955.16 | 0.06 |
The simulation results underscore the advantages of the proposed hierarchical control strategy, which efficiently coordinates solar inverter adjustments across voltage levels. The use of solar inverters for both active and reactive power control provides a versatile solution to voltage management, outperforming traditional methods in terms of loss reduction and voltage stability. Furthermore, the partitioned voltage control method ensures that solar inverters operate within safe limits, enhancing the reliability of the distribution network.
In conclusion, the integration of high proportions of distributed solar power necessitates advanced voltage control strategies to maintain grid stability. Solar inverters, with their inherent control capabilities, offer a promising avenue for addressing voltage violations and optimizing network performance. The proposed hierarchical coordination control strategy, combined with voltage interval partitioning, provides a comprehensive framework for managing medium and low voltage distribution networks. By leveraging solar inverter adjustments, this approach minimizes losses, reduces voltage deviations, and maximizes solar power utilization, contributing to the sustainable operation of active distribution systems. Future work could explore the integration of energy storage systems and machine learning techniques to further enhance the adaptability and intelligence of voltage control strategies.
The deployment of solar inverters in voltage control is not without challenges, such as communication delays and inverter compatibility issues. However, with standardized protocols and advanced monitoring systems, these challenges can be mitigated. The continuous evolution of solar inverter technologies will likely expand their role in grid services, paving the way for more resilient and efficient distribution networks. As the energy transition accelerates, the importance of innovative control strategies, such as the one proposed in this paper, cannot be overstated. Solar inverters are poised to become integral components of smart grids, enabling the seamless integration of renewable energy sources and supporting the global shift toward a sustainable energy future.