Photovoltaic Penetration Levels Research Articles

The Impact of Solar Distributed Generation on Distribution Networks: Case Study of Chipata Distribution Network

The installation of solar PV systems in distribution networks is slowly increasing. The study focused on identifying the challenges and benefits of installing Distributed Solar Generation in the Chipata 33kV and 11kV distribution Networks. Chipata Town is in the Eastern Part of Zambia, and it has a peak demand of about 23.3MW. The 2023 version Power Factory Dig Silent Software was used to model the Chipata 33kV and 11kV distribution network and different Solar penetration levels were used to understand the impact of Distributed Solar. Chipata Distribution Network has four major stations operating at 33kV and 11kV voltages and four main distribution lines. The main objective of the study was to determine the impact of distributed solar PV in the Chipata Distribution Network. One of the specific objectives was to determine the hosting capacity of the Chipata Distribution Network. The hosting capacity gives the maximum amount of PV power integrated in a power system network without violating the set operation limits. The study analysed the impact of solar Distributed Generation on network losses, fault levels, voltage stability and line loading. The study revealed that an increase in penetration level resulted in a general increase in the Bus Bar voltages on both 11kV and 33kV voltage levels. Different Penetration levels of solar ranging from 6.66MW to 132MW were studied. Simulations revealed that the hosting capacity for Chipata Distribution Network is 96MW (412% of Solar PV Penetration Level). The voltages in the distribution network at hosting capacity were ranged from 0.93p.u to 1.02p.u. Short Circuit analysis simulations showed negligible impact on the fault level after integration of solar in the distribution network. Some circuits showed both increased and reduced power losses with increased solar penetration. The obtained results indicated that increased installation of distributed Solar PV systems in the Distribution Network impacts voltage stability, line losses and line loading.

Analysis of Grid-Forming Inverter Controls for Grid-Connected and Islanded Microgrid Integration

Autonomous grid-forming (GFM) inverter testbeds with scalable platforms have attracted interest recently. In this study, a self-synchronized universal droop controller (SUDC) was adopted, tested, and scaled in a small network and a test feeder using a real-time simulation tool to operate microgrids without synchronous generators. We presented a novel GFM inverter control adoption to better understand the dynamic behavior of the inverters and their scalability, which can impact the distribution system (DS). This paper provides a steady-state and transient analysis of the GFM power inverter controller via simulation to better understand voltage and frequency stabilization and ensure that the critical electric loads are not affected during a prolonged power outage. The controllers of the GFM inverter are simulated in HYPERSIM to examine voltage and frequency fluctuations. This analysis includes assessing the black start capability for photovoltaic microgrids, both grid-connected and islanded, during transient fault conditions. The high photovoltaic PV penetration levels open exciting opportunities and challenges for the DS. The GFM inverter control demonstrated appropriate response times for synchronization, connection, and disconnection to the grid. The DS has become more resilient and independent of fossil fuels by increasing the penetration of inverter-based distributed energy resources (DERs).

Effect of photovoltaic penetration level and location on power system transient stability during symmetrical and unsymmetrical faults

Due to the constant growth in the power demand and the raised risks from unsustainable energy resources, it is essential to continue investigating the operations of renewable energy sources (RESs), such as photovoltaic (PV) systems. Integrating conventional power system with PV plants creates challenges that affect the overall stability of the power system. In this work, the effects of PV penetration levels, PV location, type of faults, and inertia reduction of the conventional synchronous generators on the transient stability of the power system are examined. This is done on 9-bus system based on the critical clearing time values required for the operation of protective devices. It is found that higher PV penetration levels increase the critical clearing times resulting in an improved stability response. Further, the stability of the system under distributed- or concentrated-PV generation depend highly on the location of the PV. Moreover, extensive analysis on the impact of a variety of faults on systems stability are provided (symmetrical vs. unsymmetrical, permanent vs. temporary). The findings of this study indicate that systems experiencing symmetrical faults had lower critical clearing times and tend to be less stable than systems under unsymmetrical faults. Also, the system stability is notably more impacted by permanent faults as opposed to temporary ones with a case of an increase of 80 ms (29.62%). Finally, the negative effect of conventional system inertia reduction on the systems stability is demonstrated with differences reaching 250 ms (28% reduction).

Control strategy of battery inverter for voltage profile improvement in low voltage networks with high PV penetration level

Control strategy of battery inverter for voltage profile improvement in low voltage networks with high PV penetration level

Analysis of fast frequency control using battery energy storage systems in mitigating impact of photovoltaic penetration in Ethiopia–Kenya HVDC link

The high penetration of photovoltaic (PV) in power grids typically leads to the displacement of traditional synchronous generators (SGs). However, with a high penetration of PV, fewer SGs are running, and the sharing of responsibility to control the system frequency is reduced and easily exacerbates the problem of reduced inertia response in the power system. This can increase frequency deviation when there is a load-generation imbalance or unexpected disturbances. The limited amount of inertial response from the PV generation means that it cannot provide the same frequency support as SGs. Therefore, this paper suggests a fast frequency control (FFC) technique for the battery energy storage system (BESS) to reduce the instantaneous frequency deviation (IFD) in the Ethiopian grid. The authors specifically provide knowledge of the modeling of droop-type controlled BESS, which can provide additional damping, enhance the inertial ability of the system, and reduce IFD. The simulation results indicate the effectiveness of BESS in mitigating the adverse inertial impact of PV and meeting the necessary grid requirement. The proposed method was tested on the Ethiopian power system model through simulations by using DIgSILENT simulation software. To validate the model, transient frequency simulation studies are performed for various fault conditions, and comparisons are made with and without BESS for different levels of PV penetration.

Three-Stage Stochastic Unit Commitment for Microgrids Toward Frequency Security via Renewable Energy Deloading

Renewable energy is boosting the deployment of microgrids (MGs) with stochastic and low inertia nature. To improve the operational efficiency of MGs while guaranteeing frequency security, a three-stage stochastic unit commitment problem is proposed, where renewable energy can be deloaded. In the first stage, the diesel generators (DGs) are scheduled, responding to uncertainties of loads and photovoltaic generator output. In the second stage, the outputs of DGs are optimized to reduce the operational cost under uncertain disturbances. In the third stage, a novel PV deloading strategy is proposed to test the frequency security of MGs. The three-stage optimization problem is formulated as a multi-stage stochastic optimization problem with recourse. This problem is then solved using a novel nested Benders decomposition algorithm with both dual cuts and partial primal cuts. Simulations are performed on an AC MG under different PV penetration levels and disturbances. The results verify the effectiveness of the proposed model in balancing operational efficiency, renewable energy utilization, and frequency security.

Development of control strategy for community battery energy storage system in grid-connected microgrid of high photovoltaic penetration level

The focus of this paper is to develop a control strategy for a community battery bank in a grid-connected microgrid in which a significant level of photovoltaic generation is embedded. In order to minimize the capacity of the community battery, the power transfer capacity of the interconnection link between the microgrid and the external grid system is utilized to safe maximum levels. Through Empirical Mode Decomposition analysis of the net power flows of the microgrid, the daily and seasonal modes of the net power oscillations are identified as the two dominant low-frequency components. Whence a rule-based operational strategy is developed to control the power flows of the community battery via a novel dynamic referencing scheme for the state-of-charge of the battery bank. The battery control scheme counteracts the dominant daily and seasonal modes of oscillations of the net power. The numerical calculations performed for a case study shows that the proposed scheme leads to an approximately 16% decrease in the required battery capacity for particular growth rate of solid-electrolyte interphase film in the battery bank. The scheme does not require the forecasting of the net power, and thus, it has an increased degree of robustness when the community battery undertakes the power buffering task.

Performance Analysis of Bus Voltage in Distribution Network with High Penetration of PV Controlled via Data-Driven Approach

Integration of large-scale distributed photovoltaic (PV) generation resources can lead to technical challenges, particularly voltage rise caused by PVs power injection at the time of high solar radiation profile and low load demand. Reactive power control of PV inverters can help mitigate the voltage rise, which arises just for a short duration due to high incident solar radiation. There is a possibility to control functions on these PV inverters based on the rating of the PV inverter. For one-second resolution, local data-driven voltage sensitivity estimation is applied to update the control functions such as volt-var and volt-watt on the PV inverters so as to regulate the bus voltage. Different forms of solar radiation profiles, transient varying, smooth varying, and worst operating scenario corresponding to the minimum load at the time of high PV generation, are included. The study is demonstrated for different PV penetration levels. The voltage analysis on buses is performed using power hardware (PV emulator) in the loop simulation, at one of the buses in the network, while the remaining PVs are being controlled using volt-var control (VVC)/volt-watt control (VWC) methods. The applied approach confirms to maintaining bus voltage within limits even against a very short transient time instant of solar radiation profile.

Smart electric vehicles charging with centralised vehicle-to-grid capability for net-load variance minimisation under increasing EV and PV penetration levels

Smart electric vehicles charging with centralised vehicle-to-grid capability for net-load variance minimisation under increasing EV and PV penetration levels

PV Hosting Capacity in LV Networks by Combining Customer Voltage Sensitivity and Reliability Analysis

This paper investigates voltage regulation in low voltage (LV) networks under different loading conditions of a supply network, with increased levels of distributed generation, and in particular with a diverse range of locational solar photovoltaic (PV) penetration. This topic has been researched extensively, with beneficial impacts expected up to a certain point when reverse power flows begin to negatively impact customers connected to the distribution system. In this paper, a voltage-based approach that utilizes novel voltage-based reliability indices is proposed to analyse the risk and reliability of the LV supply feeder, as well as its PV hosting capacity. The proposed indices are directly comparable to results from a probabilistic reliability assessment. The operation of the network is simulated for different PV scenarios to investigate the impacts of increased PV penetration, the location of PV on the feeder, and loading conditions of the MV supply network on the reliability results. It can be seen that all reliability indices improve with increased PV penetration levels when the supply network is heavily loaded and conversely deteriorate when the supply network is lightly loaded. Moreover, bus voltages improve when an on-load tap changer is fitted at the secondary trans-former which leads to better reliability performance as the occurrence and duration of low voltage violations are reduced in all PV scenarios. The approach in this paper is opposed to the conventional reliability assessment, which considers sustained interruptions to customers caused by failure of network components, and thus contributes to a comprehensive analysis of quality of service by considering transient events (i.e., voltage related) in the LV distribution network.

Evaluating the impact of wildfire smoke on solar photovoltaic production

There are growing needs to understand how extreme weather events impact the electrical grid. Renewable energy sources such as solar photovoltaics are expanding in use to help sustainably meet electricity demands. Wildfires and, notably, the widespread smoke resulting from them, are one such extreme event that can impair the performance of solar photovoltaics. However, isolating the impact that smoke has on photovoltaic energy production, separate from ambient conditions, can be difficult. In this work, we seek to understand and quantify the impacts of wildfire smoke on solar photovoltaic production within the Western United States. Our analysis focuses on the construction of a random forest regression model to predict overall solar photovoltaic production. The model is used to separate and quantify the impacts of wildfire smoke in particular. To do so, we fuse historical weather, solar photovoltaic energy production, and PM2.5 particulate matter (primary smoke pollutant) data to train and test our model. The additional weather data allows us to capture interactions between wildfire smoke and other ambient conditions, as well as to create a more powerful predictive model capable of better quantifying the impacts of wildfire smoke on its own. We find that solar PV energy production decreases 8.3% on average during high smoke days at PV sites as compared to similar conditions without smoke present. This work allows us to improve our understanding of the potential impact on photovoltaic-based energy production estimates due to wildfire events and can help inform grid and operational planning as solar photovoltaic penetration levels continue to grow.

Identifying small decentralized solar systems in aerial images using deep learning

Statistics on installed solar energy systems (SES) play a crucial role in the solar energy industry, providing valuable information for a wide range of stakeholders, such as policy makers, authorities, and financial evaluators. For example, grid operators rely on accurate data on photovoltaic penetration levels to ensure the quality and stability of the power supply. In this research, we present an automatic approach helping generate these statistics using deep learning and image processing techniques. Our proposed model is a machine learning approach that utilizes a specific architecture of convolutional neural networks (CNN) called the “U-net” to detect SES from aerial images. We experimented different network settings to enhance the SES identification performance.In this study, the model was evaluated using two datasets from different locations, one from Sweden and one from Germany. Additionally, the model was trained and tested on a combination of both datasets. The impact of image resolution was also examined. The experimental results show that this architecture performs better than many recent CNN models that have been proposed in the literature for the task of SES identification from aerial images. To make it easy for others to replicate our findings, We have shared all the scripts, software, and dependencies required for running the model in this paper, along with instructions on how to use it in Appendix A.

Stochastic restoration of distribution networks with high penetration of solar PV systems through a generic switching order mechanism

The process of fault isolation and service restoration (FISR) is an essential component of the implementation of distribution automation. By using FISR to determine the switching order, whether manually or remotely, the network's reliability is significantly enhanced in comparison to that of conventional switching. On the other hand, it is impossible to refute the exponential development of distributed energy resources such as photovoltaic (PV) generators. This paper introduces a general FISR for distribution networks with high penetration of solar PV systems. The proposed FISR strategy is an optimum switching sequence with the goal of reaching the best restoration hour before any likely fault occurrence. The proposed framework takes into account the inherent uncertainty in network demand and renewable generation in addition to the innovative mathematical programming model for the switching order. In addition, this stochastic programming handles the radiality constraint in the restoration process by creating a fictional layer as a means of reducing the complexity of the modeling. Moreover, the impact of PV penetration level on the optimal switching order for heavy-loaded distribution feeders is addressed and investigated.

Battery energy storage systems reinforcement control strategy to enhanced the maximum integration of PV to generation systems

Java Bali area has high potential of renewable energy resources (RES) especially for photovoltaic (PV) energy which can supply the power system electricity. However, the PV generation has intermittent characteristic, which in may disturb the power system operation. The disturbance is related to the system technical minimum load (TML) and system ramping capability. For that purpose, the maximum size of PV generation should be determined and regulated since it depends on generating unit size and type. The regulation can be realized using the reinforcement of battery energy storage system (BESS) which can provide the system flexibility, frequency regulation and energy management. The method to determine maximum penetration level of PV penetration is proposed in this research, which is based on the unit commitment (UC) procedure. The BESS facilities are also included as the technology option which can provide more flexibility. The proposed method will determine penetration level, periodically committed generating unit, dispatched generating unit, BESS charging and discharging status. The method is simulated in simplified Java Bali System under three different period that are weekdays, weekend and lowestday scenario having different demand and peakload combining to BESS facilities as the options. The result shows that under BESS reinforcement the PV integration are 49%, 35% and 23% during weekdays, weekend and lowestday, respectively. On contrary, without BESS reinforcement the PV integration are only 45%, 31% and 17%.

A Study of Grid-Connected Residential PV-Battery Systems in Mongolia

For national energy capacity improvement and CO2 emission reductions, Mongolia has focused its attention on grid-connected residential PV systems. Due to the feed-in tariff (FIT), the aggregated residential PV systems are expected to increase with the PV penetration level. Currently, there is no power injection limitation in Mongolia. A new policy for the PV penetration level of residential PV systems needs to be developed. This study analyzed the techno-economic performances of distributed PV-battery systems, considering PV generation, the historical load demand, and the tariff structure. We studied the performances of 40 combinations of PV sizes (2 kW–9 kW) and battery capacities (4.4 kWh, 6.6 kWh, 10 kWh, 12 kWh, and 15 kWh) to find feasible system sizes. The aggregated PV-battery systems in a low-voltage (LV) distribution system located in Ulaanbaatar, Mongolia, are also discussed. The results show that six combinations satisfied the technical and economic requirements. The maximum profit was determined to be an NPV of 1650 USD with a 9-year payback period using combination 3 (6 kW PV and 6.6 kWh battery capacity). Combination 6 (8 kW PV and 15 kWh battery capacity) shows that the energy management strategy for residential houses with battery storage has the potential to increase the installed capacity of PV systems without voltage violence in the LV network. For the distributed PV-battery storage system (BSS), the environmental analysis indicates that CO2 and SO2 emissions were reduced by 3929 t/year and 49 t/year, respectively. The findings obtained from this analysis will be used for power system planning.

IMPACT AND EVALUATION OF OPTIMIZED PV GENERATION IN THE DISTRIBUTION SYSTEM WITH VARYING LOAD DEMANDS

Most distributed renewable energy generation (DREG) planning studies are performed using a constant load model and a dispatchable generation unit. However, the renewable generation unit and load demand vary in real life, and the generation size at the peak demand varies accordingly with loading levels. Such considerations may lead to the erroneous conclusion: the power loss reduction and bus voltage improvement may not be optimal. Consequently, the generation unit must be adequately integrated to offer optimal capacity in the distribution system while considering non-constant load demand as a part of DREG planning. Therefore, the impact of integrating photovoltaic (PV) considering historical solar weather data and varying load demand for five different voltage-dependent load models is proposed in this study. Particle swarm optimization (PSO) is employed to find the optimal location and size of PV with the objective to minimize power losses in the distribution system using IEEE 33-bus and IEEE 69-bus test systems. The findings are evaluated based on the comparative analysis of power losses reduction, PV penetration level, power loss index, and voltage deviation index. Findings revealed that the proposed model is effective in determining the optimal location and size of PV with a significant reduction of power losses that varies between 13.84% to 32.71% in 33-bus, and between 18.56% to 43.80% in 69-bus. In addition, the improvement in minimum bus voltage and other performance indices are also significant.

A Static and Dynamic Analysis of Photovoltaic Penetration into MV Distribution Network

Photovoltaic (PV) systems are becoming increasingly prevalent worldwide, particularly in power distribution networks. However, their intermittency and integration into distribution networks can have adverse effects. This study investigates the impact of large-scale solar integration into a typical Malaysian power grid network, focusing on voltage stability, short circuits, and power loss under peak and no-load conditions. Using Digsilent Power Factory software, static and dynamic power flow analyses were performed on a network consisting of two 132/11 kV transformers, an 11 kV busbar, and 112 loads served through eight feeders. Solar PV of 100 kW was integrated into each node, and the maximum allowable solar grid connection level was determined. The static results show that there were no violations in no-load conditions at 100 kW PV penetration. However, during peak load, there were violations at 0% PV penetration, but by increasing the level of solar grid connection to 60% (60 kW), the voltage level moves up to the acceptable range. Under contingency conditions, the results show that the minimum level of solar penetration is 80% (80 kW). The highest power loss occurs during peak time and is observed at 0% PV penetration. Feeder 8, the lounge feeder with the highest number of loads, is identified as the main cause of power loss. According to the short circuit analysis in peak and no-load conditions, the system experiences the highest shorts during peak loads. On the other hand, we conducted a dynamic simulation with load characteristics and compared the results for different levels of PV penetration. The results from the dynamic simulations show that lower limit violations occur even at 100% PV penetration for a brief period in all case studies. This study identifies the maximum permissible PV penetration as 125 kW.

Stochastic Optimal Selection and Analysis of Allowable Photovoltaic Penetration Level for Grid-Connected Systems Using a Hybrid NSGAII-MOPSO and Monte Carlo Method

Generally, the main focus of the grid-linked photovoltaic systems is to scale up the photovoltaic penetration level to ensure full electricity consumption coverage. However, due to the stochasticity and nondispatchable nature of its generation, significant adverse impacts such as power overloading, voltage, harmonics, current, and frequency instabilities on the utility grid arise. These impacts vary in severity as a function of the degree of penetration level of the photovoltaic system. Thus, the design problem involves optimizing the two conflicting objectives in the presence of uncertainty without violating the grid’s operational limitations. Nevertheless, existing studies avoid the technical impact and scalarize the conflicting stochastic objectives into a single stochastic objective to lessen the degree of complexity of the problem. This study proposes a stochastic multiobjective methodology to decide on the optimum allowable photovoltaic penetration level for an electricity grid system at an optimum cost without violating the system’s operational constraints. Five cutting-edge multiobjective optimization algorithms were implemented and compared using hypervolume metric, execution time, and nonparametric statistical analysis to obtain a quality solution. The results indicated that a Hybrid NSGAII-MOPSO had better convergence, diversity, and execution time capacity to handle the complex problem. The analysis of the obtained optimal solution shows that a practical design methodology could accurately decide the maximum allowable photovoltaic penetration level to match up the energy demand of any grid-linked system at a minimum cost without collapsing the grid’s operational limitations even under fluctuating weather conditions. Comparatively, the stochastic approach enables the development of a more sustainable and affordable grid-connected system.

Impact of Photovoltaic Penetration on Medium Voltage Distribution Network

Nowadays, large-scale solar penetration into the grid and the intermittent nature of PV systems are affecting the operation of distribution networks. This paper aims to investigate the effect of PV penetration on a typical medium-voltage distribution network in Malaysia. The main objectives of this study are to investigate voltage stability, power loss, and short circuit under two conditions: peak load and no load. The network is evaluated using two methods: static and dynamic analysis, utilizing the Digsilent Power Factory software. The network comprises two 33/11 kV parallel transformers connected to the 11 kV busbar and consists of 13 feeders and 38 loads. PV penetration of 500 kW per node is added, and the maximum potential PV penetration that is acceptable to connect to the grid is evaluated. The findings indicate that during peak load conditions, some nodes experience violations, but by increasing the PV penetration, the lower violations move up to the acceptable range. The highest power loss is 191 kW, occurring during peak load conditions at 0% PV penetration level. On the other hand, dynamic simulations were carried out with specific load time characteristics, and the results were compared under different PV penetration levels. The dynamic simulation results show that during contingency conditions, there are violations in peak load, and the maximum PV penetration for this study was determined to be 2MW. It is observed that the nodes 27, 28, and 29 violate lower voltage limits even at 100% PV penetrations.

Assessment of energy losses in power distribution systems with individual prosumers and energy communities

AbstractAchieving the energy transition target will require the extensive engagement of consumers and the private sector in investment and operation of renewable‐based power systems. Support of individual prosumers and proliferation of energy communities are efficient ways to implement this engagement. To facilitate smooth integration of prosumers with photovoltaic (PV) installations, while satisfying effective operation of the power distribution system (PDS), it is important to fundamentally assess energy losses for different grid development scenarios. In this paper, the energy losses are compared for two alternatives: (a) when prosumers with PV installations act as individual grid users, and (b) when prosumers become participants of a solar energy community. To achieve this goal, modeling of loads, prosumers’ behavior and PV generation was performed. Furthermore, it has been analyzed how the physical topology of the distribution network can be harmonized with the underlying bidirectional power flows for each alternative, while complying with system constraints. The IEEE 123 Node Test Feeder was employed to capture the performance of the PDS and to estimate the energy loss with various penetration levels of prosumers. The results indicate that reduction of energy losses is only possible until a certain PV penetration level, after which additional PV capacities cause increase in energy losses and complicate the PDS's operation. Lower energy losses were supervised for the cases with dispersed PV generation, compared to the cases focused on energy communities. This means that the PDS demonstrates better tolerance to evenly distributed prosumers, rather than to single sources of a larger scale installed in one node. The outputs of this study will help the energy planners and utilities in improving performance of the PDS in terms of loss minimization and loadability maximization.