Low Voltage Distribution Grids Research Articles

An Enhanced Edge Computing Technique for Detection of Voltage Fluctuation in Grid-tied Renewable Energy

Renewable energy sources (RES) such as solar photovoltaic and wind are becoming the most attractive power generation options in many nations. Even while high penetration seems likely, power quality anomalies such as voltage fluctuation, harmonics, and frequency fluctuation associated with RES hinder seamless integration. The variability and unpredictability of these sources create the most oddities. In grid-tied renewable energy, monitoring power quality efficiently is crucial. Power grid monitoring solutions in related literature use sensor-based cloud and edge computing techniques. The existing systems struggle with excessive latency when delivering large amounts of generated data to the cloud. To fill this gap, a new approach for the detection and localization of voltage fluctuation is proposed in this study. The approach integrated three techniques namely; feed-forward neural network (FFNN), Stockwell transform, and anomaly-aware edge computing to detect and locate voltage fluctuation in a GtRE. Using MATLAB/Simulink, virtual emulation of a modified IEEE 33 Bus and a GtRE representing a section of Ado Ekiti (in Nigeria) low-voltage distribution grid are carried out for data generation and system evaluation. Feature extraction was carried out in a Python IDE using Stockwell transform. The voltage fluctuation events are detected and localized based on the extracted features using the trained FFNN model deployed and evaluated within three microcontroller-based computing devices. The proposed approach integrated anomaly-aware with edge computing to send only voltage data that are considered abnormal to a dedicated data center for visualization and storage. Performance evaluation of the proposed technique on the simulated GtRE demonstrates a significant decrease of 98% and 90% in latency when compared to cloud computing and conventional edge computing respectively. Comparison of the proposed approach to two closely related solutions in literature also demonstrates a 50% and 92.5 % reduction in latency. The contribution of the study is the reduced latency and minimal bandwidth utilization achieved by the implementation of the developed technique.

A bi-level inter-phase coordinated control method for voltage regulation in unbalanced LV distribution networks using PV-battery energy storage systems

Photovoltaic systems coupled with battery energy storage (PV-BES) can help to minimize the effects of variability in PV generation including voltage problems in low voltage distribution grids (LVDNs). Therefore, a joint centralized-decentralized method consisting of two control levels based on sensitivity analysis is proposed in this paper, which employs the BES charging and discharging control in the first level and reactive power capability of inverters in the second control level. When the BES charging and discharging control is insufficient for voltage regulation, the second level of the proposed method is triggered. For full utilization of the BES capacity and to ensure adequate capacity for the following day's voltage regulation needs, an enhancement algorithm is applied to the voltage to active power sensitivity coefficients. All of the voltage sensitivity coefficients are calculated by a central controller using an offline procedure and sent to the PV-BES inverters to determine the amount of active and reactive power in real-time according to the measured local voltage. Taking into account the inter-phase voltage effects, a request for Var compensation signal flow with inter-phase coordination constraints is utilized to properly coordinate the inverters in reactive power control. The proposed method can efficiently regulate voltage by preventing over and under-voltage problems, improving the average total voltage deviation (TVD), reducing the total reactive power absorption and injection by the inverters, and avoiding reduction in PV generation. To evaluate the performance of the proposed control method, it is compared with the commercially available inverter voltage control techniques in an unbalanced residential test feeder. Moreover, a comparison is conducted between the proposed method and an adaptive decentralized control approach presented in the literature. Furthermore, a three-phase Volt-Var strategy, with and without the inter-phase coordination constraints, is simulated that indicates the necessity of the constraints for proper coordination.

The Use of Data Transmission Technique Via Power Line Communication

The smart grid requires the use of communication methods. One of these communication methods is power line communication (PLC). In this study, TMDSPLCKITV4 evaluation boards are programmed with the G3-PLC standard and operated as transmitter and receiver in low voltage distribution grid. Then, the distances between the transceiver points, the load characteristics were changed and the received signal strength indication, signal noise ratio, bit error rate and package error rate values for each modulation type of the G3-PLC standard were measured in real time. According to these measured values, the success of the PLC has been demonstrated. In general, it is observed that the number of erroneous data bits increases in each modulation type under pulsed variable load. Robust mod and binary phase shift keying modulation types appear to be the most successful modulation types with the least number of erroneous data bits when all experimental conditions are considered.

Optimal allocation of distributed energy resources to cater the stochastic E-vehicle loading and natural disruption in low voltage distribution grid

The everyday extreme uncertainties become the new normal for our world. Critical infrastructures like electrical power grid and transportation systems are in dire need of adaptability to dynamic changes. Moreover, stringent policies and strategies towards zero carbon emission require the heavy influx of renewable energy sources (RES) and adoption of electric transportation systems. In addition, the world has seen an increased frequency of extreme natural disasters. These events adversely impact the electrical grid, specifically the less hardened distribution grid. Hence, a resilient electrical network is the demand of the future to fulfill critical loads and charging of emergency electrical vehicles (EV). Therefore, this paper proposes a two-dimensional methodology in planning and operational phase for a resilient electric distribution grid. Initially stochastic modelling of EV load has been performed duly considering the geographical feature and commute pattern to form probability distribution functions. Thenceforth, the impact assessment of extreme natural events like earthquakes using damage state classification has been done to model the impact on distribution grid. The efficacy of the proposed methodology has been tested by simulating an urban Indian distribution grid with mapped EV on DigSILENT PowerFactory integrated with supervised learning tools on Python. Subsequently 24-h load profile before event and after event have been compared to analyze the impact.

Invariance-based control for cyber-physical electrical distribution grids

Voltage control in low-voltage distribution grids gain importance due to integration of renewable energies and introduction of smart grids. However, the presence of disturbances and communication non-idealities make the problem hard to solve. In addition, lack of integration of converter-based devices caused non-controllability of the grid. In this paper, an updated invariance-based control approach is presented to address these shortcomings. The updated version of the invariance method addresses the non-controllability of the system. In addition, the control approach is discussed in a hybrid formalism in which the long update intervals of the communications are considered. Finally, results show the effectiveness of the approach.

Empirical Characterization of Non-Intentional Emissions generated by PV Installations

Non-Intentional Emissions (NIEs) generated by solar photovoltaic (PV) systems have significantly increased concerns about disturbances in the 9-150 kHz band of the lowvoltage distribution grid, which can lead to failures or cause thermal stress in the devices connected to the grid. Moreover, these emissions can cause interference in narrowband power line communications (NB-PLCs). This paper presents a characterization of emissions generated by different real PV systems. Specifically, measurement campaigns were carried out in isolated PV systems, which employed different panel configurations, as well as in a grid-connected system. The analysis of the NIEs allows the identification of the frequencies and amplitudes of the emissions, as well as the evaluation of the NIEs variation over time. In addition, the impedances of the PV systems were also measured to correlate impedance variations with emissions.

A robust and optimal voltage control strategy for low-voltage grids utilizing group coordination of photovoltaic and energy storage systems via consensus algorithm

This study presents a novel voltage control strategy for low voltage (LV) distribution grids, addressing the lack of coordination between photovoltaic (PV) reactive control and energy storage system (ESS) active control. The proposed strategy concentrates on group coordination of PV and ESS to improve LV grid performance. Initially, it suggests employing PV reactive power for voltage regulation before utilizing ESS active power, relying on the voltage cost sensitivity factor (VCSF) of different regulating devices, to reach efficient PV resource utilization. Devices are categorized by their VCSF, prioritizing groups with larger VCSF for voltage regulation, enhancing overall coordination. In the PV reactive voltage regulation stage, the reactive power utilization rate is the consensus variable, while in the ESS active control stage, the change in state of charge (SOC) is the consensus variable, collectively working towards desired voltage regulation and SOC change. Coordinated control is utilized to converge key node voltages to set values and obtain effective LV grid voltage regulation. An IEEE 14-node LV grid simulation incorporating PV and ESS validates the proposed strategy, demonstrating its effectiveness and correctness in improving voltage control performance. The strategy achieves 70.56% of the capacity and 81.45% of the setup cost compared to similar research, with associated costs limited to 15.80% and 35.0% of accumulated costs.

Impact analysis of photovoltaic systems and energy storage systems on a low-voltage distribution grid

Impact analysis of photovoltaic systems and energy storage systems on a low-voltage distribution grid

Mitigation of voltage sag and voltage swell by using dynamic voltage restorer

Recent power quality (PQ) research shows that the most common types of power quality disturbances are voltage sags and swells in medium and low-voltage distribution grids. This paper shows how to improve two significant power quality disturbances: sags and swells voltage. To find out what effect these two PQ issues have in real life, a study case based on real nonlinear loads data from large induction motors at Beshai Company in Sadat City in Egypt is investigated. The dynamic voltage restorer (DVR) has been suggested as a solution to the voltage swell and voltage sag issues. The point of common coupling (PCC) is linked with the dynamic voltage restorer to mitigate the PQ problems that have been found. The power network, loads, and DVR may all be modeled using the MATLAB/Simulink platform. The jellyfish search optimizer (JFS) is used to get the gain settings of the proportional and integral (PI) controller for the proposed DVR. MATLAB/Simulink's results show that the proposed device is effective, reliable, and has low latency.

A transfer-learning-based robust technique for multi-type fault detection and classification using Hilbert–Huang transform in low-voltage power distribution grids

A transfer-learning-based robust technique for multi-type fault detection and classification using Hilbert–Huang transform in low-voltage power distribution grids

Flexible Energy Storage for Sustainable Load Leveling in Low-Voltage Electricity Distribution Grids with Prosumers

The sustainability of the energy sector is linked today with the diminishing of the reliance on fossil fuels and on the large-scale adoption of renewable generation. Medium- and low-voltage electricity distribution grids see the proliferation of microgrids that supply consumers able to generate electricity with local installations of PV panels. These consuming and generating entities, called prosumers, use the local generation for their own consumption needs and are exporting the surplus in the grid, modifying the typical steady state operation conditions. For mitigating this inconvenience, local storage equipment can be used, which also helps the prosumers to reduce their costs and preserve the sustainable operation of the distribution infrastructure. The literature shows that by optimally using storage in microgrids, the deterioration in quality and security of supply can be minimized in the presence of prosumers. This paper presents a study regarding local storage management in prosumer-enabled microgrids, seeking to find the optimal configuration of community (shared) storage systems that charge batteries overnight, during low consumption hours, providing load leveling opportunities and energy loss minimization. A study case performed on a real low-voltage electricity distribution network (LVEDN) shows the performance of the proposed optimization.

Grid Quality Services from Smart Boilers: Experimental Verification on Realistic Scenarios for Micro-Grids with Demand-Side Management Oriented to Self-Consumption

The deeper penetration of renewables in the energy mix is an intense requirement in order to reduce global carbon dioxide emissions. In addition, new technologies are being developed, such as electric mobility and Distributed Generation (DG) in urban areas. However, the unpredictable fluctuations in energy generation from roof-installed PVs and the switching operation of their inverters greatly aggravate the already-present grid quality problems. In this paper, the Smart Boiler (SB) concept for grid quality improvement is presented. Furthermore, its experimental verification is implemented on a flexible testbed that accurately emulates several realistic scenarios for the low voltage distribution grid, under complex operating conditions. The proposed low-cost electronic kit, which contains a converter of fairly simple topology and requires connection to the internet, is used to upgrade conventional domestic boilers to smart devices. The SB automatically regulate the local reactive power flow, helping to stabilize the voltage level and suppress the grid current harmonic content, with both services provided in a matter of seconds. The higher the active power consumed and the denser the SB cluster, the wider the beneficial impact on the affected network area. While this service is provided, excess energy generated by PVs is temporarily stored as heat in the boiler tanks, given the users’ hot water consumption habits. The whole application, as a powerful demand-side management tool, proves beneficial for both the network operator and the end-user, especially when self-consumption is desirable in order to achieve a Nearly Zero Energy Building.

Two-stage collaborative information interaction reliability improvement for the distribution grid

The impulse noise generated by a large volume of power electronics devices imposes a hazardous impact on information interaction reliability in low-voltage distribution grids. In this paper, we propose a two-stage collaborative information interaction reliability improvement algorithm to minimize the bit error rate (BER) of the information interaction under impulse noise. In the first stage, the transmission-side peak-to-average power ratio (PAPR) is reduced based on the adaptive particle swarm optimization (PSO)-enabled partial transmit sequence (PTS). In the second stage, the reception-side dual-signal blanking is proposed based on the transmission-side PAPR and reception-side useful signal power estimation and peak median ratio. The transmission–reception collaborative information interaction reliability improvement is realized through two aspects. First, transmission-side PAPR reduction improves the performance of reception-side signal blanking by making it easier to distinguish useful signals from impulse noise. Second, the transmission-side PAPR is utilized to improve the estimation accuracy of both coarse and precise thresholds in dual-signal blanking. Simulation results show that the proposed algorithm outperforms existing algorithms in both PAPR reduction and BER performances to achieve information interaction reliability improvement effectively.

A Method for Assessing the Degradation of PVC-Insulated Low-Voltage Distribution Cables Exposed to Short-Term Cyclic Aging

The distribution grid comprises cables with diverse constructions. The insulating material used in low-voltage (LV) distribution cables is predominantly PVC. Furthermore, the presence of cables with different structures in the grid poses challenges in detecting the aging of the cable network. Finding a universal and dependable condition-monitoring technique that can be applied to various types of cables is indeed a challenge. The diverse construction and materials used in different cables make it difficult to identify a single monitoring approach that can effectively assess the condition of all cables. To address this issue, this study aims to compare the thermal aging behavior of different LV distribution cables with various structures, i.e., one cable contains a PVC belting layer, while the other contains filler material. The growing adoption of distributed generation sources, electric vehicles, and new consumer appliances in low-voltage distribution grids can lead to short, repetitive overloads on the low-voltage cable network. Hence, these cable samples were exposed to short-term cyclic accelerated aging in the climate chamber at 110 °C. The cable’s overall behavior under thermal stress was evaluated through frequency and time domain electrical measurements (including tan δ and extended voltage response) and a mechanical measurement (Shore D). The tan δ was measured in the frequency range of 20 Hz–500 kHz by using the Wayne-Kerr impedance analyzer. The extended voltage response measurement was conducted using a C# application developed in-house specifically for laboratory measurements in the .NET environment. The study observed a strong correlation between the different measurement methods used, indicating that electrical methods have the potential to be adopted as a non-destructive condition-monitoring technique.

Disaggregation Model: A Novel Methodology to Estimate Customers’ Profiles in a Low-Voltage Distribution Grid Equipped with Smart Meters

In the context of increasingly necessary energy transition, the precise modeling of profiles for low-voltage (LV) network consumers is crucial to enhance hosting capacity. Typically, load curves for these consumers are estimated through measurement campaigns conducted by Distribution System Operators (DSOs) for a representative subset of customers or through the aggregation of load curves from household appliances within a residence. With the instrumentation of smart meters becoming more common, a new approach to modeling profiles for residential customers is proposed to make the most of the measurements from these meters. The disaggregation model estimates the load profile of customers on a low-voltage network by disaggregating the load curve measured at the secondary substation level. By utilizing only the maximum power measured by Linky smart meters, along with the load curve of the secondary substation, this model can estimate the daily profile of customers. For 48 secondary substations in our dataset, the model obtained an average symmetric mean average percentage error (SMAPE) error of 4.91% in reconstructing the load curve of the secondary substation from the curves disaggregated by the model. This methodology can allow for an estimation of the daily consumption behaviors of the low-voltage customers. In this way, we can safely envision solutions that enhance the grid hosting capacity.

Power Quality improvement in LV smart grid by using the Open UPQC device

This paper presents the application of the Open Unified Power Quality Conditioner as a tool to improve the power quality in low voltage distribution grids. This system consists of a single or three-phase AC/DC power converter installed at customer’s premises and a main three-phase AC/DC power converter in the MV/LV substation. O-UPQC will be installed and tested in the city of Brescia (north of Italy) within Smart Domo Grid, a project co-funded by the Italian Ministry of Economic Development. A preliminary analysis of the power quality and the load distribution of the test area will be used as input for the design of the system.

Power Quality in Wind Power Systems

Wind power generation systems influence power quality in a specific way making important the need for detailed and accurate evaluation of disturbances caused by wind generators. Wind power system can cause sub- and interharmonic components to appear in the spectrum of voltages and currents. The paper shows different aspects of spectrum estimation in power systems, including the doubly fed induction generator (DFIG) connected to low voltage distribution grid. Harmonic distortions caused by wind generator under various operational conditions regarding wind speed, active and reactive power are shown and discussed. Advanced spectral methods (like ESPRIT) are applied to overcome the drawbacks of Fourier-based techniques.

Shunt Active Power Filter with Selective Harmonics Compensation for LV distribution grid

A Shunt Active Power Filter (SAPF) employable in a Low Voltage distribution grid four-wires model is presented. The use of this device helps to improve Power Quality compensating harmonic currents, reactive power and current unbalances of a disturbing loads. Each compensating function can be activated or disabled according to the specific requirements of the application. A selective harmonic compensation is also possible, in order to avoid possible resonances at specific frequencies. A current hysteresis modulation with predictive calculation of threshold bands achieving fixed switching frequency is adopted for a fast dynamic response. The compensation performance of the proposed active power filter and the associate control scheme under steady state and transient conditions is demonstrated through digital simulations.

Load Recognition in Hardware-Based Low Voltage Distribution Grids Using Convolutional Neural Networks

Due to climate targets of the German government, the share of renewable energy in the power grid will be increased and the number of grid participants connected to the low voltage level of the power grid will rise. This leads to new requirements in voltage control, especially in low voltage distribution grids. In order to achieve a stable power grid in future, further development of control strategies is necessary. In this paper, a load recognition concept, which was tested on simulative data in previous work, is further developed to reduce simulation effort. Additionally, the concept is adapted for real hardware influences and active grid participants complicating the recognition task. Thus, the main contribution of this study is the successful application of the methodology within a hardware-based test grid containing a charging electric vehicle. Using a convolutional neural network in a time series classification setting, the recognition rates in this use-case exceeded 99 % while benefiting from an asymmetric charging behavior. Due to these promising results, future voltage control strategies could be supported based on gained information through integration of the presented concept.

Mitigation of Harmonic Distortions in Low Voltage Distribution Grids With Fair Utilization of Resources

Mitigation of Harmonic Distortions in Low Voltage Distribution Grids With Fair Utilization of Resources