Voltage Issues Research Articles

Effective interception of redox mediator shuttle behavior for Li[sbnd]O2 battery by separator modification based on g-C3N4 doped with Co elements

The utilization of redox mediators (RMs) offers a promising solution to address the issue of excessive charging voltage resulting from the generation of lithium peroxide (Li2O2) at the cathode in lithium‑oxygen (LiO2) batteries. However, the effectiveness of RMs is significantly impeded by a crucial drawback commonly referred to as the “shuttle phenomenon.” This phenomenon involves the RMs not only participating in the decomposition of Li2O2 but also migrating to the anode, where it reacts with the Li metal. Consequently, the RMs experience inevitable degradation, resulting in a severely limited cycling life. To tackle this challenge, we propose a strategy on limiting the 2,2,6,6-tetramethylpiperidin-1-yloxy (TEMPO) worked as RM to the cathodic side by modifying the separator with the g-C3N4 doping with Co (Co-C3N4). Through the adsorption of TEMPO onto the Co-C3N4, the modified separator efficiently captures the TEMPO thus suppresses the shuttle effect. As a result, the Li metal anode is effectively safeguarded, facilitating uninterrupted and prolonged operation of the rechargeable battery. A remarkable cycle life of up to 160 cycles for LiO2 batteries can be realized, thus demonstrating the successful implementation of our strategy.

Auction-based peer-to-peer energy trading considering echelon utilization of retired electric vehicle second-life batteries

Lately, the growing emergence of electric vehicles (EVs) brings problems of retired batteries proliferation. Seeking effective application scenarios targeting echelon utilization of retired EV second-life batteries (EVSLBs) becomes important. This paper proposes an auction-based P2P energy trading approach in a residential community market that incorporates retired EVSLBs utilization. A unified P2P energy trading model is proposed to coordinate the economic layer and the physical layer. In the economic layer, the household energy management system (HEMS) of each agent is in charge of operating and market bidding through optimization models to maximize their net profit. Comprehensive operation models of fresh batteries and retired EVSLBs have been proposed and embedded into HEMS models. The battery life degradation issue is also considered by calculating the cycling cost. The P2P energy trading is conducted by a double-sided auction method with an average pricing market (APM) mechanism, in which the re-bidding process is allowed. In the physical layer, voltage issues and line congestion management are considered. There is a community manager in the P2P market to ensure the economic layer decisions do not violate the constraints in the physical layer. The proposed models are tested on the modified IEEE 33-bus distribution system and the comparison between new batteries and retired EVSLBs in the community market is discussed based on the simulation results. The echelon utilization effectiveness of EVSLBs in residential P2P trading has been verified as well.

Carbon-Aware Operation of Resilient Vertical Farms in Active Distribution Networks

Emerging utilization of Electric Vehicles (EVs) in Distribution Networks (DNs) decreases the power quality in the DN. The main quest of this research is to find out Can EVs and Photovoltaic (PV) systems support the DN and mitigate the voltage magnitude violations due to utilizing high penetration level EV? This article proposes a novel volt/VAR optimization (VVO) model by leveraging the reactive power support of EVs and PVs as Distributed Energy Resources (DERs) for the DN. The proposed VVO model contains the second-order conic relaxed form of the AC power flow equations. Thus, the presented VVO problem is a Mixed-Integer Second-Order Cone Programming (MISOCP) problem. To obtain the ability to support the DN, Smart Inverters (SIs) are utilized to connect EVs and PV systems to the DN. Thus, to add the PV and EV systems to the convexified form of the VVO problem, the P-Q characteristics and the model of SIs working at different operating points are presented based on experimental results. The proposed model of SIs allows the participation of DERs in the reactive power compensation to mitigate voltage issues of DN due to utilizing high penetration level EVs. Besides, the proposed model of SIs enables DERs to increase their dispatchability. The performance of the proposed model is examined in the case studies using the IEEE 33-bus system and the 123-bus system. It is illustrated in the case studies that the solar dispatchability increases by 12% when the proposed volt/VAR model is utilized for IEEE 33-bus system. Besides, it is illustrated in the case studies that the voltage profile of buses remains in the desired operating range when the proposed model is leveraged, even if the penetration level of EVs increased to 40%.

Improving the Control Strategy of the DVR Compensator Based on an Adaptive Notch Filter with an Optimized PD Controller Using the IGWO Algorithm

One of the objectives of electrical distribution networks is to provide customers with access to high‐quality electricity. Because any disruptions in these systems result in voltage disorders, different devices are employed to offset these disruptions on consumers who are more susceptible. One of the most important and contemporary pieces of equipment that is connected in series with the network is dynamic voltage restoration (DVR), which shields delicate loads from network voltage issues by injecting the proper voltage. This article presents a DVR control scheme optimized with improved grey wolf optimization (IGWO) that uses a proportional derivative (PD) controller and adaptive notch filter (ANF). The output LC filter’s resistance has been removed, and the control system has actively engaged in oscillation damping in order to accelerate dynamic responsiveness and lower system losses. The major component of the voltage, which comprises its frequency, amplitude, and phase, is extracted using ANF. The capacitor current of the output filter in this structure is fed back to the control system and from the current mode control in the inner loop to boost stability. Owing to the occasionally complex dynamic behavior in distribution networks, particularly during a fault, the system’s frequency response has been altered and response speed has been accelerated using the PD controller. This kind of controller is distinguished by its accurate functioning in the presence of frequency deviations and its swifter dynamic reaction in the face of voltage swell and sag. In order to improve the THD and voltage sag indicators of the sensitive load, the PD coefficients were adjusted using the IGWO algorithm. As a consequence, the simulation results demonstrated that the suggested controller performed better than traditional controllers.

Synthesis and characterization of biodegradable seaweed-based paper battery for sustainable energy storage

This article deals with the design and development of a seaweed-based paper battery, synthesized using different material coatings. Batteries have a high potential to power up the next generation of medical devices, electronics and hybrid vehicles but it require high working capacity. With the presence of several deficiencies like a regular, fluctuating voltage, spill out and damage issues, itching and irritation during human direct contact with wet and non-paper batteries, a need for dry and paper-based batteries has arisen. The design and fabrication of paper-based batteries with enhanced electrochemical and structural stability play a pivotal role to fix the above-mentioned problems. A battery made up of seaweed paper offers remarkable capacity with better performance and also helps to avoid the use of wood-based paper. The battery has been prepared with different materials of cathode and electrolyte, which are further tested for identifying an optimum match in terms of generated voltage. A biodegradability test and toxicity test were performed which ensured the eco-friendly nature of the proposed battery. The proposed battery is made of nanocomposites, which can pack more power into smaller spaces. Moreover, it is found that there is a reduction of weight by 58%, an enhancement of 16.7% in voltage capacity and eco-friendly compared to conventional AA 1.5–3.5 V Li-on battery.

Revaluation Method of Sensor Power Supply

This study proposes an approach for wireless sensor power supply voltage early warning using statistical models. Experimental and statistical analysis of electrical parameters and battery discharge characteristics were conducted to establish a reliable evaluation process. A linear regression model was employed to analyze and fit known temperature and voltage data, establishing a relationship model between voltage and temperature and using it to predict unknown voltage threshold data. This solves the problem of the inability to real-time predict the warning voltage threshold of wireless sensors as the actual working temperature changes and ensures their reliability. The results of experiments and statistical analysis demonstrate the effectiveness and accuracy of this method. Compared to the traditional method of using fixed voltage thresholds for warning, the proposed method offers a practical solution that can timely address the issue of low power supply voltage in wireless sensor networks.

Day-Ahead Operational Planning for DisCos Based on Demand Response Flexibility and Volt/Var Control

Considering the integration of distributed energy resources (DER) such as distributed generation, demand response, and electric vehicles, day-ahead scheduling plays a significant role in the operation of active distribution systems. Therefore, this article proposes a comprehensive methodology for the short-term operational planning of a distribution company (DisCo), aiming to minimize the total daily operational cost. The proposed methodology integrates on-load tap changers, capacitor banks, and flexible loads participating in demand response (DR) to reduce losses and manage congestion and voltage violations, while considering the costs associated with the operation and use of controllable resources. Furthermore, to forecast PV output and load demand behind the meter at the MV/LV distribution transformer level, a short-term net load forecasting model using deep learning techniques has been incorporated. The proposed scheme is solved through an efficient two-stage strategy based on genetic algorithms and dynamic programming. Numerical results based on the modified IEEE 13-node distribution system and a typical 37-node Latin American system validate the effectiveness of the proposed methodology. The obtained results verify that, through the proposed methodology, the DisCo can effectively schedule its installations and DR to minimize the total operational cost while reducing losses and robustly managing voltage and congestion issues.

Modelling SiC MOSFET module threshold voltage (VTH) and impact of parallel device ΔVTH on short circuit robustness

In SiC modules, where several power MOSFETs are connected in parallel for high current conduction capability, the issue of threshold voltage (VTH) variation between individual devices can become problematic. In instances where the standard deviation of device VTH is minimized by appropriate VTH pre-screening, non-uniform VTH shift under bias-temperature-instability can lead to increased VTH dispersion and potentially poor current sharing. Although non-destructive for normal operation, VTH dispersion in surge events like short circuits can cause premature module failure. In this paper, experimental investigations backed by theoretical models have been developed to explain the relationship between device VTH dispersion and module VTH shift. This is done for Si and SiC MOSFETs. Five Si/SiC MOSFETs are paralleled in a custom printed-circuit-board allowing individual VTH and module VTH measurements. It is shown that the module VTH is typically between the smallest VTH and the mean VTH, depending on the VTH standard deviation. Using empirical models for MOSFETs in weak inversion derived from the measured subthreshold gate transfer characteristics, the model can estimate module VTH from a dispersion of individual MOSFET VTH. It can also predict the impact of non-uniform VTH shift between constituent devices on the overall module VTH. Finally, the impact of VTH mismatch on current sharing during short circuits in parallel connected SiC MOSFETs is presented. The results show that VTH mismatch in parallel connected SiC MOSFETs reduces the short circuit withstand time from 5 μs to 4.5 μs compared to VTH matched SiC MOSFETs.

Power quality improvement in distributed generation system using intelligent control methods

Hybrid <span>electric power generation and its integration with the grid to supply consumer demand is main focus of this paper. The use of nonlinear load and advanced power electronic equipment-based devices at the consumer end introduces power quality issues in the power system network in terms of voltage and current. This paper explains the design of a control algorithm for a unified power quality conditioner used for mitigating both voltage and current-based power quality issues. The dynamic voltage restorer of unified power quality controller (UPQC) is designed with a unit vector control algorithm and the distribution static synchronous compensator (DSTATCOM) is designed with fuzzy logic and adaptive network-based fuzzy inference system based instantaneous reactive power theory control algorithm. The simulation model built using the MATLAB platform includes a three-phase voltage source along with hybrid electric power generation connected to linear and non-linear loads operating under different conditions. The result is analyzed in terms of voltage and current total harmonic distortion compared with IEEE 512 power quality standards and power factor improvement. The paper shows the adaptive neuro-fuzzy inference systems (ANFIS)-based control algorithm gives better results in terms of total harmonic distortion (THD) compared to the fuzzy-based control algorithm. The power factor is improved using ANFIS-based controller proving the efficiency of the controller</span>.

A Low Voltage Prediction Based on LSTM-BP Combined Model for Distribution Station Areas

The timely management of low voltage issues in the distribution network relies heavily on accurate predictions of voltage in the station areas. Many current methods for voltage prediction require complex data collection involving power grid topology parameters and electricity information. However, these methods suffer from drawbacks such as the need for extensive data, limited real-time performance, and significant prediction errors. Hence, this study proposes an approach to voltage prediction utilizing a combined LSTM-BP model. Initially, an analysis of the mechanism of low voltage formation in the station areas reveals that the primary factor influencing node points voltage is the power consumption of users. Subsequently, the LSTM neural network is employed to forecast short-term load curves in the distribution station areas, while the self-learning capability of the BP neural network is utilized to establish the correlation between users’ power and their corresponding voltage levels. By effectively combining the above two neural network models, the historical load’s data can be used to accurately and quickly predict the future low voltage situation in the station areas. Finally, taking station areas as the research object and comparing the actual voltage data with the voltage data predicted in this paper, the results show that within the 1V error range, the prediction accuracy is 99.8%. In contrast to the conventional voltage prediction approach, the method put forward in this research paper enables instantaneous and precise anticipation of low voltage levels without relying on details such as station configuration, line characteristics, or user voltage information.

Coordinated optimization model for solar PV systems integrated into DC distribution networks

AbstractSolar photovoltaic (PV) systems will drive deep electrification of energy systems leading to clean energy 2050. However, connecting large amounts of solar PV systems on direct current (DC) networks, like solar farms and potential future DC distribution systems, would lead to over voltages and loss of solar PV power output due to voltage issues. Further, current PV integration within distribution networks operate exclusively to maximize output using maximum power point tracking algorithms, without network coordination, which may lead to reduced solar output due to voltage issues. Here, a coordinated optimization model for solar PV systems and distribution network voltage regulators is presented. The proposed model optimally controls the settings of voltage controllers (DC‐DC converters), placed at the outputs of solar PV units and selected distribution lines, while maximizing solar power output and minimizing substation power (i.e. system losses). The solar PV systems are modelled using a trained neural network. Testing various systems against uncoordinated situations revealed that the proposed model yielded an increase in solar power of up to 60.06%, in the 28‐bus case. The proposed method will be an excellent tool enabling deep electrification using solar PV system and it overcomes limitations of uncoordinated systems used in practice today.

Simulation of Threshold Voltage Instability of 4H-SiC MOSFET

The reliability issue of threshold voltage (Vgs(th)) still exists in Silicon carbide (SiC) based metal-oxide-semiconductor-field-effect-transistors (MOSFETs). In this paper, the threshold voltage instability of 4H-SiC MOSFET is deeply studied through Silvaco TCAD simulation. This work mainly investigates the instability (shift) of the Vgs(th) affected by interface states (interface traps), near interface traps, and mobile ions. The results display that the effect of near interface traps on the Vgs(th) shift is greater than that of interface traps. The electron capture ability is related to the energy level of the traps. With the energy level increasing, the Vgs(th) shift increases firstly and then decreases. The peak energy level is related to the trap position and trap density. Furthermore, the effect of the mobile ions in the oxide layer on the Vgs(th) shift is limited. However, when moving to the SiC/SiO2 interface, they will greatly impact the Vgs(th) and affect the device performance seriously.

P2P market coordination methodologies with distribution grid management

As prosumers and energy communities gain prominence in power systems, energy trading between prosumers in local P2P markets is paramount. Within this novel market design, peers can directly exchange energy with each other, leading to economic advantages while supporting the decarbonization of the sector. To ensure that voltage and congestion issues are properly addressed, a thorough coordination between the P2P market and the Distribution System Operator is required. This paper presents and compares three mutual-benefit coordination methods. The first method entails applying product differentiation on an iterative basis to avoid exceeding the lines thermal limits, which is performed through penalties on P2P exchanges that may be overloading the network. The second method uses the P2P market with an AC-OPF, ensuring network operation through a flexibility market via upward and downward flexibility. The last one proposes an integrated operation of the P2P market with AC-OPF. All methods are assessed in a typical distribution network with high prosumers integration. The results show that the second method is the one that, fulfilling the network constraints, presents greater social welfare.

Expert System Integrating Rule-Based Reasoning to Voltage Control in Photovoltaic-Systems-Rich Low Voltage Electric Distribution Networks: A Review and Results of a Case Study

Nowadays, in low voltage electric distribution networks, the distribution network operators are encountering a high number of connected small-scale distributed generation units, mainly photovoltaic prosumers. The intermittent nature of the prosumers, together with the degree of uncertainty of the requested and injected powers associated with all end-users from low voltage electric distribution networks, can cause voltage variations that violate the allowable limits. In this context, this paper developed an efficient and resilient expert system integrating rule-based reasoning applied to the on-load tap changer-fitted transformer to improve the efficiency of the voltage control in the PV-rich LV EDNs. An in-depth analysis based on 75 scenarios, resulting from the combinations of three indicators—the penetration degree of the photovoltaic prosumers, the consumption evolution associated with the consumers, and the energy production of the photovoltaic systems—was performed to demonstrate the efficiency of the proposed expert system in a low voltage electric distribution network from a rural area belonging to a Romanian distribution network operator. The success rate of the expert system was 86.7% (65 out of 75 scenarios did not have voltage issues). All voltages were between the allowable limits in 100% of the time slots associated with the analysed period. For the other scenarios (representing 13.3%), voltages were inside the range [−10%, +10%] in at least 95% of the time slots.

Research on Optimal Voltage Control of Distribution Network with the Participation of EVs and PVs

With the accelerating penetration of photovoltaics (PVs) and electric vehicles (EVs), distribution networks face the risks of voltage violations and fluctuations. On the one hand, conventional voltage regulation resources like OLTC transformers and capacitor banks feature slow response and limited lifetime duration, making them incapable of quickly responding to the temporary voltage issues created by PVs and EVs. On the other hand, EVs and PVs interact with the power grid via fully controllable power electronic converters capable of real-time adjusting their operating settings, making them ideal voltage support resources. To exploit the voltage support capability of PVs and EVs, this paper proposes a two-stage control scheme for the voltage regulation of distribution networks, consisting of the day-ahead and intraday control stages. The day-ahead control mitigates potential voltage violations via day-ahead scheduling of the operation settings for OLTC transformers and capacitor banks. The intraday control further alleviates voltage deviations and voltage fluctuations based on the reactive power support of PV systems and the rational EV charging/discharging scheduling. A rolling optimization-based control technique is proposed in the intraday control stage to achieve real-time control of EVs and PVs with the stochastic nature of EV charging behaviors inherently considered. The proposed two-stage voltage regulation scheme is validated via case studies performed on the IEEE 123-node test feeder integrated with PVs and EVs.

An improvement of stability and dynamic response in hybrid AC-DC microgrids using optimal power control management

Microgrid topologies enable more effective use of renewable resources as well as the autonomous process. Microgrids are effective frameworks for managing dispersed assets such as renewable structures with small-scale distributed generator supplies. Smart grids are adaptable electricity networks that have arisen as a result of the introduction of new technologies and features. It is suggested that a three-terminal AC/DC hybrid microgrid with DC two and AC one terminal be used. A two dual active bridge (DAB) with cascaded H-bridge (CHB) converter with AC grid link-based interactions that connect isolated two DC buses are included in the suggested structure. To minimise the energy generation stages and power devices, the DAB converters are intrinsically linked to the CHB of DC rails based on the structure-specific requirements. To present the unnecessary grid currents and DC rail voltage issues exist by this revised structure topology by simply two power alteration stages, a better solution is suggested that employs zero-sequence voltage (ZSV) injection in the CHB converters. The impacts of managed settings on structure stability and dynamic responsiveness are investigated in order to reduce conflicts among ZSV injection by structure voltage/current regulation. This paper compares the performance of a PI and a PR for DC voltage regulation. A comparison of simulation results for both control approaches is provided. The major difficulty is to normalise the system model in order to identify the appropriate controller settings for robust control. The findings are confirmed and compared to the conventional regulator PI. The suggested 3-Φ AC current and DC rail voltage regulating approach's universal efficacy is proved by MATLAB/Simulink analytical model from the three and five-terminal hybrid AC/DC power structures.

A new concept of highways infrastructure integrating energy storage devices for e-mobility transition

European Commission aims to reach net zero carbon emissions by 2050. Since transport produces 23 % of the global emissions, a massive electrification is necessary. A proper infrastructure for battery and fuel cell electric vehicles (BEVs/FCEVs) charging/refueling should be developed, especially along the highways. This research study illustrates three different alternatives of energy storage integration into fast charging stations (FCSs) aiming to support BEVs/FCEVs fast charging/refueling by exploiting the surplus of renewable energy assessed in Italy at 2040. Specifically, the integration of Lithium-Ion Battery (LIB), Vanadium Redox Flow Battery (VRFB) and LIB/Proton Exchange Membrane Electrolyzer (PEM-E) into FCS is analyzed assessing the overgeneration exploitation and volumetric encumbrance of storage section. Dynamic FCS models are developed for each scenario and simulations are performed to proper sizing the storage components. The paper outcomes highlight that the number of charged/refueled EVs at parity of occupied volume is for the PEM-E case of one order magnitude lower than LIB case. If the comparison is made over the charged/refueled kWh per cube meter, the difference between PEM-E and LIB is significantly reduced (i.e., 11.7 vs. 28 kWh m−3). It is highlighted as BEVs fast charging (once LIB is considered) allows more than halve volume occupation with respect to FCEVs refueling with H2 on-site production, since territory occupation is a constraint at systemic level. Moreover, the LIB integration allows a reduction up to 53 % of the power requested from the grid with respect to the storage absence, reducing under voltage and power stability issues as well.

Sequentially Coordinated and Cooperative Volt/Var Control of PV Inverters in Distribution Networks

Electric distribution grids are seeing an increased penetration of photovoltaic (PV) generation. High PV generation exceeding the grid load demand results in a reverse active power flow in the grid, which raises the voltage level. This paper presents a reactive power controller to overcome the overvoltage problem in the distribution system. A sequentially coordinated and cooperative volt/var control technique is presented. The proposed controller aims to use as low reactive power as possible while mitigating the voltage issues. Accordingly, it reduces the active power loss associated with reactive power flow and reduces the probability for active power curtailment of the PV system. The controller is developed for each lateral and is replicated for all laterals. The lateral controller coordinates the operation of the smart PV inverters in a sequential manner. Cooperative control is proposed between the laterals’ controllers as well and is engaged when the individual laterals’ controllers are unable to solve their overvoltage issues. The performance of the proposed controller is evaluated by comparing it to two other volt/var controllers, and it demonstrates better performance in terms of reactive power requirement. To conduct the simulation study, a modified version of the unbalanced IEEE 13-bus system is utilized, which includes an additional 44 low-voltage bus. The study involves simulating 720 operating points across daily time series. The results indicate that the proposed controller effectively addresses overvoltage problems that occur during periods of high PV generation.

A Hybrid Discontinuous PWM Strategy for Current Ripple and Neutral-Point Fluctuation Reduction of Parallel Vienna Rectifier

Generally, discontinuous pulsewidth modulation (DPWM) strategy used in single Vienna rectifier will result in large current ripple and neutral-point fluctuation. When applied in interleaved rectifier, the issue of neutral-point voltage still exists. Besides, the input current around zero-crossing point is distorted due to the characteristics of unidirectional topology. Hence, a novel hybrid DPWM (H-DPWM) strategy for parallel Vienna rectifier is proposed in this article to reduce the distortion, current ripple, and neutral-point fluctuation. In this article, the characteristics of current ripple and neutral-point fluctuation with traditional DPWM (T-DPWM) are clarified at first. Then, the quantitative analyses on current ripple and neutral-point fluctuation with T-DPWM, classical space vector modulation, and optimized DPWM (O-DPWM) are presented in detail. To solve the issue of current distortion, the H-DPWM is proposed based on O-DPWM. Furthermore, the switching losses of these modulations are evaluated. At last, the analyses and performance of the proposed H-DPWM are verified by the experiments.

Data-Driven Coordinated Voltage Control Method of Distribution Networks With High DG Penetration

The highly penetrated distributed generators (DGs) aggravate the voltage violations in active distribution networks (ADNs). The coordination of various regulation devices such as on-load tap changers (OLTCs) and DG inverters can effectively address the voltage issues. Considering the problems of inaccurate network parameters and rapid DG fluctuation in practical operation, multi-source data can be utilized to establish the data-driven control model. In this paper, a data-driven voltage control method with the coordination of OLTC and DG inverters on multiple time-scales is proposed without relying on the accurate physical model. First, based on the multi-source data, a data-driven voltage control model is established. Multiple regulation devices such as OLTC and DG are coordinated on multiple time-scales to maintain voltages within the desired range. Then, a critical measurement selection method is proposed to guarantee the voltage control performance under the partial measurements in practical ADNs. Finally, the proposed method is validated on the modified IEEE 33-node and IEEE 123-node test cases. Case studies illustrate the effectiveness of the proposed method, as well as the adaptability to DG uncertainties.