High Photovoltaic Penetration Research Articles

Real-Time Power Regulation of Flexible User-Side Resources in Distribution Networks via Dual Ascent Method

Flexible user-side resources are of great potential in providing power regulation so as to effectively address the challenges of reverse power flow and overvoltage issues in distribution networks characterized by high photovoltaic (PV) penetration. However, existing distributed algorithms typically implement control signals after the convergence of the algorithms, making it difficult to track frequent and rapid fluctuations in PV power outputs in real time. Given this background, an online-distributed control algorithm for the real-time power regulation of flexible user-side resources is proposed in this paper. The objective of the established control model is to minimize network losses by dynamically adjusting active power outputs of flexible user-side resources and reactive power outputs of PV inverters while respecting branch power flow and voltage magnitude constraints. Furthermore, by deconstructing the centralized problem into a primal–dual one, a distributed control strategy based on the dual ascent method is implemented. With the proposed method, agents can achieve global optimality by exchanging limited information with their neighbors. The simulation results verify the good balance between economic efficiency and voltage control performance of the proposed method.

Optimal Economic Analysis of Battery Energy Storage System Integrated with Electric Vehicles for Voltage Regulation in Photovoltaics Connected Distribution System

The integration of photovoltaic and electric vehicles in distribution networks is rapidly increasing due to the shortage of fossil fuels and the need for environmental protection. However, the randomness of photovoltaic and the disordered charging loads of electric vehicles cause imbalances in power flow within the distribution system. These imbalances complicate voltage management and cause economic inefficiencies in power dispatching. This study proposes an innovative economic strategy utilizing battery energy storage system and electric vehicles cooperation to achieve voltage regulation in photovoltaic-connected distribution system. Firstly, a novel pelican optimization algorithm-XGBoost is introduced to enhance the accuracy of photovoltaic power prediction. To address the challenge of disordered electric vehicles charging loads, a wide-local area scheduling method is implemented using Monte Carlo simulations. Additionally, a scheme for the allocation of battery energy storage system and a novel slack management method are proposed to optimize both the available capacity and the economic efficiency of battery energy storage system. Finally, we recommend a day-ahead real-time control strategy for battery energy storage system and electric vehicles to regulate voltage. This strategy utilizes a multi-particle swarm algorithm to optimize economic power dispatching between battery energy storage system on the distribution side and electric vehicles on the user side during the day-ahead stage. At the real-time stage, the superior control capabilities of the battery energy storage system address photovoltaic power prediction errors and electric vehicle reservation defaults. This study models an IEEE 33 system that incorporates high-penetration photovoltaics, electric vehicles, and battery storage energy systems. A comparative analysis of four scenarios revealed significant financial benefits. This approach ensures economic cooperation between devices on both the user and distribution system sides for effective voltage management. Additionally, it encourages trading activities of these devices in the power market and establishes a foundation for economic cooperation between devices on both the user and distribution system sides.

Adaptive reactive power control for voltage rise mitigation on distribution network with high photovoltaic penetration

This research addresses the challenge of voltage rise on low voltage distribution networks with high photovoltaic penetration. The proliferation of distributed generators, particularly small-scale PV systems, has raised concerns about voltage stability and power quality in these networks. Existing reactive power control techniques, such as fixed power factor and voltage-based methods (Q(V)), have limitations in effectively mitigating voltage rise while considering load variations and network sensitivity. To overcome these limitations, an adaptive reactive power control technique is proposed in this research. The technique combines both PV active power injection and network voltage considerations in real-time to dynamically adjust reactive power output. Unlike traditional methods, which directly link reactive power reference to PV active power or voltage, the adaptive technique calculates the change in reactive power reference (ΔQ) based on both factors. This dynamic approach enables more responsive and accurate voltage regulation. The effectiveness of the adaptive technique is demonstrated through MATLAB simulations on a representative low voltage distribution network. The results show that the adaptive technique outperforms existing methods, providing better voltage regulation and reduced losses. The technique's adaptability to different scenarios and variations is also highlighted. However, it is noted that the adaptive technique may have a slightly slower response time compared to existing methods due to its dynamic nature.

Voltage regulation and energy loss minimization for distribution networks with high photovoltaic penetration and EV charging stations using dual-stage model predictive control

The widespread integration of photovoltaic (PV) units and controllable loads like electric vehicles (EVs) might cause uncertain voltage fluctuations quite frequently. The reactive power from distributed generation (DG) units and EV charging stations (EVCSs) can effectively be used along with conventional devices like on-load tap changer (OLTC) to successfully control network voltages in real-time, with multi-time scale coordination. However, the control of a large number of available resources, with reliable communication among them becomes a complex task. Moreover, the substantial real-time data set amassed through the deployment of measurement devices across the network increases both cost and computational intricacies. This paper presents a novel approach, employing a time decomposition-based dual-stage model predictive control (MPC) with a reduced model control framework for voltage control and energy loss minimization in active distribution networks (ADNs), by significantly reducing the number of measuring devices. A minimum global set of available control resources is identified for real-time control, aiming to mitigate control complexity and minimize the demand for heavy communication. The proposed control strategy is validated on the 33-bus distribution network and modified IEEE 123-bus distributed network, under high PV penetration and EV charging stations. It is seen that the proposed reduced model framework with very limited measuring devices and control equipment can effectively regulate the voltages with a standard deviation of 0.0059 p.u. and 0.0035 p.u. as compared to the full order system model, for 33-bus network and IEEE 123-bus network, respectively. Furthermore, there is a net 23.24% reduction in energy losses when power loss minimization is considered along with the minimization of voltage deviations in the 33-bus network.

An Active Distribution Network Voltage Optimization Method Based on Source-Network-Load-Storage Coordination and Interaction

In response to global energy, environment, and climate concerns, distributed photovoltaic (PV) power generation has seen rapid growth. However, the intermittent and uncertain nature of PVs can cause voltage fluctuations in distribution systems, threatening their stability. To address this challenge, this paper proposes an active distribution network voltage optimization method, of which the main contribution is the development of a comprehensive voltage optimization strategy that integrates day-ahead prediction and real-time adjustment, significantly enhancing the stability and efficiency of distribution networks with high PV penetration. In the day-ahead prediction stage, the forecast scenarios of load and PV output guide network reconfiguration for improved voltage distribution. In the real-time operation stage, flexible regulation of PV and energy storage systems is used to adjust power outputs, further optimizing voltage quality. Simulations on the IEEE 33-bus system show that the method effectively improves voltage distribution, enhances renewable energy consumption, and ensures the safe, economic operation of the distribution system.

Optimal Sizing and Siting of Fresh and Second-Life Battery Energy Storage Systems Based on Linearized Optimal Power Flow for High Photovoltaic Penetration: A Comparative Study

Optimal Sizing and Siting of Fresh and Second-Life Battery Energy Storage Systems Based on Linearized Optimal Power Flow for High Photovoltaic Penetration: A Comparative Study

Low‐frequency oscillations in MMC‐MVDC systems with high PV penetration: Modelling, mechanism, and assessment

AbstractThis study investigates the low‐frequency oscillations (LFOs) in MMC‐MVDC systems with high photovoltaic (PV) penetration, considering the whole operating conditions of the grid‐connected MMC, including both the inverter and rectifier modes. First, the multi‐port impedance models of converters and networks are developed, upon which a stability criterion is defined. The mechanism of LFOs is then identified using bus participation analysis and parameter sensitivity analysis. In addition, the stable zones of the dominant parameters are identified, taking into account the whole operating conditions of the grid‐connected MMC. Interestingly, a phase‐locked loop may induce LFOs in two low‐frequency ranges. Finally, the experimental results confirm the correctness of the theoretical analysis.

Voltage Hierarchical Control Strategy for Distribution Networks Based on Regional Autonomy and Photovoltaic-Storage Coordination

High-penetration photovoltaic (PV) integration into a distribution network can cause serious voltage overruns. This study proposes a voltage hierarchical control method based on active and reactive power coordination to enhance the regional voltage autonomy of an active distribution network and improve the sustainability of new energy consumption. First, considering the reactive power margin and spatiotemporal characteristics of distributed photovoltaics, a reactive voltage modularity function is proposed to divide a distribution grid into voltage regions. Voltage region types and their weak points are then defined, and the voltage characteristics and governance needs of different regions are obtained through photovoltaic voltage regulation. Subsequently, a dual-layer optimal configuration model of energy storage that accounts for regional voltage regulation is established. The upper-layer model focuses on planned configurations to minimize the annual comprehensive operating cost of the energy storage system (ESS), while the lower-layer model focuses on optimal dispatch to achieve the best regional voltage quality. KKT conditions and the Big-M method are employed to convert the dual-layer model into a single-layer linear model for optimization and solution. Finally, an IEEE 33-node system with high-penetration photovoltaics is modeled using MATLAB (2022a). A comparative analysis of four scenarios shows that the comprehensive cost of an ESS decreased by 8.49%, total revenue increased by 19.36%, and the overall voltage deviation in the distribution network was reduced to 0.217%.

Multi-Timescale Voltage Regulation for Distribution Network with High Photovoltaic Penetration via Coordinated Control of Multiple Devices

The high penetration of distributed photovoltaics (PV) in distribution networks (DNs) results in voltage violations, imbalances, and flickers, leading to significant disruptions in DN stability. To address this issue, this paper proposes a multi-timescale voltage regulation approach that involves the coordinated control of a step voltage regulator (SVR), switched capacitor (SC), battery energy storage system (BESS), and electric vehicle (EV) across different timescales. During the day-ahead stage, the proposed method utilizes artificial hummingbird algorithm optimization-based least squares support vector machine (AHA-LSSVM) forecasting to predict the PV output, enabling the formulation of a day-ahead schedule for SVR and SC adjustments to maintain the voltage and voltage unbalance factor (VUF) within the limits. In the intra-day stage, a novel floating voltage threshold band (FVTB) control strategy is introduced to refine the day-ahead schedule, enhancing the voltage quality while reducing the erratic operation of SVR and SC under dead band control. For real-time operation, the African vulture optimization algorithm (AVOA) is employed to optimize the BESS output for precise voltage regulation. Additionally, a novel smoothing fluctuation threshold band (SFTB) control strategy and an initiate charging and discharging strategy (ICD) for the BESS are proposed to effectively smooth voltage fluctuations and expand the BESS capacity. To enhance user-side participation and optimize the BESS capacity curtailment, some BESSs are replaced by EVs for voltage regulation. Finally, a simulation conducted on a modified IEEE 33 system validates the efficacy of the proposed voltage regulation strategy.

Study of rooftop PV hosting capacity in 20 kV systems in facing distributed generation penetration

---With the increasing request for integrating rooftop photovoltaic (PV) systems into the distribution grid, it is crucial to prevent the potential negative impacts of high PV penetration. Considering the uncertainty and variability characteristics of high rooftop PV penetration, a stochastic approach for determining PV hosting capacity (HC)—the maximum capacity of a PV system to receive electricity from the power distribution network before the network reaches an operating limit violation—is necessary. Therefore, this study proposes calculating PV hosting capacity using the Monte Carlo simulation. Unlike previous works, this paper uses real feeders as case studies, representing both urban and rural areas. The feeder representing an urban area with many industrial and business customers has a higher hosting capacity, 31 % of full load, compared to the feeder representing rural areas, which has 18 % of full load. By using actual feeders that represent urban and rural areas, more representative results for specific problems can be achieved without assuming urban and rural feeders have the same specific problems.

Comprehensive Analysis of the Integration and Advanced Control of Photovoltaic Systems for Grid-Connected Applications

In-depth examination of photovoltaic (PV) system integration and enhanced control for grid-connected applications is presented in this study. It examines the difficulties, methods of control, and cutting-edge technologies needed to raise the dependability and effectiveness of PV systems in contemporary power networks. The study explores innovative Maximum Power Point Tracking (MPPT) algorithms, dynamic modeling methodologies, and different adaptive control strategies, emphasizing their importance in PV system performance optimization. It also looks at how high solar PV penetration affects grid stability and talks about creative ways to deal with these issues so that we can have robust and sustainable energy sources in the future. Key Words: photovoltaic Systems, pv integration, pv control strategies, energy storage systems, smart grid technologies, MPPT.

Studying the Optimal Frequency Control Condition for Electric Vehicle Fast Charging Stations as a Dynamic Load Using Reinforcement Learning Algorithms in Different Photovoltaic Penetration Levels

This study investigates the impact of renewable energy penetration on system stability and validates the performance of the (Proportional-Integral-Derivative) PID-(reinforcement learning) RL control technique. Three scenarios were examined: no photovoltaic (PV), 25% PV, and 50% PV, to evaluate the impact of PV penetration on system stability. The results demonstrate that while the absence of renewable energy yields a more stable frequency response, a higher PV penetration (50%) enhances stability in tie-line active power flow between interconnected systems. This shows that an increased PV penetration improves frequency balance and active power flow stability. Additionally, the study evaluates three control scenarios: no control input, PID-(Particle Swarm Optimization) PSO, and PID-RL, to validate the performance of the PID-RL control technique. The findings show that the EV system with PID-RL outperforms the other scenarios in terms of frequency response, tie-line active power response, and frequency difference response. The PID-RL controller significantly enhances the damping of the dominant oscillation mode and restores the stability within the first 4 s—after the disturbance in first second. This leads to an improved stability compared to the EV system with PID-PSO (within 21 s) and without any control input (oscillating more than 30 s). Overall, this research provides the improvement in terms of frequency response, tie-line active power response, and frequency difference response with high renewable energy penetration levels and the research validates the effectiveness of the PID-RL control technique in stabilizing the EV system. These findings can contribute to the development of strategies for integrating renewable energy sources and optimizing control systems, ensuring a more stable and sustainable power grid.

Study of distribution network loss allocation with high photovoltaic penetration ratio

With the rapid development of renewable energy, the penetration ratio of photovoltaic (PV) in the distribution network is getting higher and higher. The fair and reasonable allocation of high loss caused by high PV penetration in the distribution network is of great significance to the healthy development of distribution systems. In order to study the loss allocation in distribution networks with high PV penetration, based on the cooperative game theory, combined with the power flow algorithm, the power flow and loss of the 72-node active distribution network in agricultural and pastoral areas were analyzed. Three scenarios were included: no PV, low PV penetration, and high PV penetration. The allocated loss of the distribution network with high PV penetration and multiple distributed generators was computed. The results show that the loss allocation method, which takes into account the power as well as the network topology, is applicable to distribution networks with multiple distributed generators. In distribution networks with high PV penetration, distributed generators are the main cause of high loss. If the network contains the extreme reverse power flow concerned in this paper, the loss allocated to DGs accounts for more than 95% of the total network power loss.

Research on Grid-connected Voltage Improvement Technologies for High-penetration Photovoltaic Power Generation

The degradation in power quality due to the high penetration of grid-connected photovoltaic (PV) systems is a critical issue that urgently needs to be addressed in the field of renewable energy generation. Solar PV systems typically lack mechanical inertia, which means that they are unable to provide additional mechanical inertia to maintain voltage and frequency stability when the power system is subjected to external disturbances. Therefore, to ensure stable operation of the power system, alternative measures need to be relied on to maintain voltage stability. This article first analyzes the mechanism of voltage fluctuations when photovoltaic power generation is connected to the grid. It then delves into the challenges of power quality brought about by the grid integration of renewable distributed generation systems, as well as the current research status of mainstream voltage improvement technologies, customized power devices, and energy storage systems. Finally, the paper presents recommendations for improving grid voltage quality, enhancing the stability and reliability of the power system, and promoting the widespread application of renewable energy in power systems.

Malta's low carbon transition towards sustainability

AbstractThe transition to low‐carbon energy and energy independence of a country play an important role in the sustainable development of its energy sector. Another important issue of sustainable energy development is the cost competitiveness in the generation process; with new renewable energy technologies, a sustainable energy transition to carbon‐neutral society is possible. In this article, we present a view of sustainable energy transformation based on a case study of Malta. We have created a simulation of a Maltese electricity system with projected growth and dominance of photovoltaic energy in the electricity market. The study results suggest that a system with a high penetration of photovoltaics has significant advantage over a conventional system using fossil fuels. In particular, in the simulated Maltese system, the total annual cost of energy was reduced threefold, the CO2 emissions were reduced by 40%, and the energy independence of Malta increased by 60%. In the end, the article gives a recommendation for further research into the Maltese energy system.

Advanced Control Strategies for Resilient Voltage and Frequency Regulation in Smart Grids

This study discusses advanced control strategies for voltage and frequency regulation in smart grids, particularly in the integration of renewable energy sources and electrification. These strategies, including Model Predictive Control (MPC), adaptive control, optimal control, robust control, and distributed control, aim to optimize control actions while adhering to system constraints. Case studies show their effectiveness in high photovoltaic penetration, wind power integration, and microgrid operation. However, challenges persist, such as managing uncertainties and coordinating multiple controllers in decentralized power systems. The study acknowledges ongoing research and development in this field, emphasizing the potential for enhancing voltage and frequency regulation in smart grids.

Impact of High PV Penetration on Transient Stability — a Case Study on the U.S. ERCOT System

This study was performed to assess the impact of high photovoltaic (PV) penetration on transient stability using a series of hypothetical models of the ERCOT system. This was done by calculating the critical clearing time (CCT) when faulting various busses. Varying levels of PV penetration were used to study the system transient stability. For each case 15% wind penetration was also included. It was found that under the PV volt/Var control with plant-level GE SolarControl settings, PV penetration at lower level can slightly improve the transient stability in the ERCOT system model. However, at approximately 54% penetration of renewables (39% PV and 15% wind), transient stability starts to show declining trend. This value has slight variance depending on PV distribution.

Coordinated Q‐V/P‐f Control Strategy Using Virtual Power Factor for Autonomous AC Microgrid with PV Smart Inverters

Given the increasing interests in carbon neutrality due to climate change, photovoltaic (PV)‐based microgrid has become an important research topic worldwide. Typically, high PV penetration without proper control schemes causes power quality issues such as voltage or frequency violation, resulting in the limited PV hosting capacity. Reactive and active power support from the PV is effective to solve the issues, however, it is a critical challenge to efficiently contribute to the stabilizing controls under the inverter capacity constraint. Recent studies have applied smart inverters, equipped with fixed active and reactive power control reserves, for dynamic voltage and frequency support. In this paper, we proposed a control strategy in which the control reserves for voltage and frequency support are flexibly adjusted using virtual power factor (VPF) to improve the power quality with reducing active power curtailment. The effectiveness of the proposed Q‐V/P‐f control is verified through numerical simulations using a microgrid model developed in MATLAB/Simulink platform. It was observed through the simulation that the proposed method contributed to mitigating voltage and frequency fluctuation with satisfying the inverter capacity constraint. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Robust microgrids for distribution systems with high solar photovoltaic penetration

Robust microgrids for distribution systems with high solar photovoltaic penetration

Analysis of Financial Penalties for Low Power Factor in Distribution Systems with High Penetration of Photovoltaics

Analysis of Financial Penalties for Low Power Factor in Distribution Systems with High Penetration of Photovoltaics