The growing integration of power electronic converters into power systems presents challenges to conventional stability analysis approaches. This article proposes a stability indicator based on disk margin (DM) theory to evaluate the degree of system stability. It inherently avoids the stability assessment limitations of classical methods, such as the generalized Nyquist criterion (GNC), particularly when coexisting grid-forming (GFM) and grid-following (GFL) converters result in open-loop right-half-plane (RHP) poles. Additionally, the proposed indicator offers a simple computation procedure that directly yields the apparatus impedance margin to reflect the system strength without complex mathematical transformations, while simultaneously accounting for both gain and phase conditions to provide a comprehensive assessment. Furthermore, by evaluating the individual margin of each apparatus, the method facilitates the identification of instability sources and facilitates targeted improvements in overall system robustness.

Rapid integration of electric vehicles (EVs) into low-voltage networks (LVNs) has intensified phase unbalance, particularly where single-phase charging is unevenly distributed. To address this, this paper proposes a device-agnostic framework for the optimal placement of phase-balancing support in EV-induced unbalanced LVNs. The method identifies locations where balancing actions are expected to have the greatest effect, without assuming a specific device technology at the optimisation stage. The framework was validated on modified IEEE-13 and IEEE-37 LVNs and further examined on a real UK Electricity North West Limited (ENWL) LVN. Results show that balancing support can be positioned at effective network locations to reduce both voltage unbalance and feeder power loss. Among the simulated scenarios, one moderate-skew case in the IEEE-37 LVN and the most skewed case in both test networks required phase-balancing intervention. Using a candidate pre-filter based on bus/phase sensitivity and graph-topological distance from the slack bus, the optimiser determined locations and compensation levels that reduced the voltage unbalance factor (VUF) and power loss. In the ENWL unbalanced-base and PhAM cases, power loss reductions of 1.192 kW (9.47%) and 1.072 kW (9.26%) were obtained, while restoring VUF below the 2% threshold. Further validation with practical devices, including a VAR device, autotransformer, and static transfer switch (STS), showed that all were effective. For the IEEE-13 LVN, the VAR device reduced VUF to 1.856% with a 0.06 kW loss reduction. For the IEEE-37 LVN, the VAR device also produced the lowest post-compensation VUF of 1.886%.

The growing deployment of power-electronics converters in modern power systems calls for quantitative tools to evaluate their grid-tied performance. The conventional grid-following/grid-forming classification neither explicitly captures device functions nor provides quantitative guidance for assessing their power-source characteristics. To address this gap, this article proposes a frequency-domain framework for characterizing and comparing the dynamic grid-interactive behavior of converters. Within this framework, two sensitivity-based indices and four decomposed metrics are developed to quantify small-signal source attributes over a wide frequency range. To interpret the resulting observations, dynamic admittance modeling is further employed, revealing fundamental differences in the current-forming behavior of grid-following and grid-forming resources. Case studies demonstrate that the proposed approach offers a systematic and control-agnostic tool for evaluating converter-grid interoperability and the impacts of diverse control strategies.

The rapid growth in inverter-based resource penetration is leading to the widespread integration of grid-following and grid-forming inverters within ac grids. Despite their distinct operational characteristics, these two inverter modes share fundamental similarities, motivating joint investigations into their attributes. Building on the identified symmetry between these devices, this paper proposes a novel phase-locked loop-free grid-following control strategy inspired by the grid-forming control architecture. The proposed approach simplifies the grid-following inverter control structure while retaining its inherent capabilities and enabling the intuitive configuration of synchronous inertia and damping. Analytical, experimental, and simulation results validate the effectiveness of the proposed strategy.

The anticipated widespread adoption of Electric Vehicles (EVs) presents significant challenges for electricity infrastructure integration. In parallel, the rapid expansion of Photovoltaic (PV) systems in urban areas introduces additional operational challenges. In this context, this work presents a PV-EV penetration assessment framework with a scheduled charging scheme to reduce peak electricity demand from the grid through temporal load shifting. A stochastic agent-based modelling framework is adopted to represent user behaviour and EV charging demand. Then, a scheduled charging scheme is presented based on the simulated charging profiles, while different combinations of PV and EV penetration are assessed through a parametric scenario analysis. The performance of different combinations is evaluated by the grid electricity saving ratio, self-consumption ratio, self-sufficiency ratio, and self-consumption-sufficiency ratio. A case study of a mixed-use district in Milan, Italy, with a gross floor area of 0.73 km2 is analysed at hourly resolution over a one-year period. The proposed scheduled charging scheme reduces peak electricity demand by 10.26% and 40.06%. Within the simulated scenario set, the best-performing PV-EV penetration scenarios are found at high PV penetration levels (80% to 100%) combined with moderate EV penetration levels (30% to 50%). The results identify best-performing PV-EV penetration combinations for the selected case study and show that the proposed framework can provide practical planning guidance for mixed-use urban districts. Subject to the availability of comparable input data, the proposed district-scale framework can also be adapted to other geographical contexts.

PurposeIn the emerging power system dominated by photovoltaic and wind power generation, the virtual synchronous generator (VSG) has become an effective control approach because it can emulate synchronous inertia and damping. However, unbalanced loads and power grid faults often lead to voltage and current asymmetry. Under such unbalanced conditions, traditional VSG control fails to maintain satisfactory performance. To address this issue, this paper aims to propose a multi-objective integrated VSG control strategy.Design/methodology/approachThis paper first analyzes the principles of the traditional VSG control and illustrates its limitations under unbalanced conditions using MATLAB/Simulink simulations. Next, a mathematical analysis of the VSG output power under unbalanced conditions is performed, leading to the derivation of oscillation expressions for both active and reactive power. Finally, considering the control objectives in both islanded and grid-connected modes, a negative-sequence voltage calculation module is developed. A closed-loop negative-sequence voltage control is further introduced to ensure accurate tracking of the voltage reference. In addition, a sequence component extraction module is incorporated and coordinated with the proposed multi-objective integrated VSG control.FindingsUnder unbalanced conditions, achieving simultaneously balanced voltage, balanced current, constant active power and constant reactive power is inherently conflicting. The proposed integrated VSG control addresses this issue by deriving the reference values for the negative-sequence voltage under different control objectives. Compared to the traditional VSG control, it can reduce voltage unbalance factor below 2% in islanded mode. In grid-connected mode, it can suppress reactive power fluctuations by up to 91%, active power fluctuations by up to 75% and current unbalance factor (IUF) below 2%. The proposed control strategy is validated through both simulation and hardware experiments, demonstrating its effectiveness and feasibility.Originality/valueCompared to the existing VSG control, the proposed VSG control strategy is applicable to both unbalanced load and unbalanced grid voltage conditions. It significantly reduces voltage and current unbalance and substantially mitigates active and reactive power fluctuations under unbalanced conditions, demonstrating strong disturbance rejection performance.

The number of electric vehicles (EVs) connected to the distribution system is growing significantly worldwide. Since the majority of EVs are single-phase connected, there is a concern that voltage unbalance levels may increase in areas with high penetration of EVs. This paper uses a realistic UK network model and electric vehicle charging profiles to perform a probabilistic assessment of the impact of electric vehicles on voltage unbalance in distribution systems. To reduce the simulation time, a current-source based model is used, in combination with real charging data. The results show that for EV penetration levels equal to 60 %, voltage unbalance limits are exceeded at some busbars. For higher penetration levels, voltage unbalance does not change significantly. A mitigation strategy is then deployed, employing three single-phase batteries to equalize current flow in the three phases. This solution is most effective in reducing voltage unbalance at the busbar where the batteries are connected, with reduced impact when the electrical distance increases.

This paper proposes an integrated energy system that couples electricity, hydrogen, and carbon within a coordinated multi-energy operational framework. To achieve optimal coordination among these subsystems, a mixed-integer programming model is developed with the objective of minimizing renewable energy curtailment and is validated using real-world data from a region in Yorkshire, United Kingdom. Case studies demonstrate curtailment reductions of 97.58% on a typical day and 56.94% over a 2,208-hour test period. These improvements are attributed to the effectiveness of the multi-energy coupling strategy in enhancing internal energy utilization and system self-sufficiency. Furthermore, the integration of a hydrogen carbon methanation pathway increases the flexibility of the system and the overall economic viability. These results confirm the potential of the proposed approach for integrated energy systems that aim to achieve carbon neutrality.

The growth of renewable energy generation drives an increase in power inverter integration. Grid-following inverters remain the mainstream solution for renewable energy connection due to their operational efficiency and superior compatibility with the existing grid infrastructure. However, their reliance on phase-locked loops leads to implicit synchronous inertia and damping, challenging parameter design and system stability. This article proposes a phase-locked loop-free control strategy that enables explicit and tunable synchronous characteristics for grid-following inverters. The method achieves grid synchronization via ac capacitor dynamics without relying on active power, thereby preserving the energy conversion advantages of the grid-following mode. Further analysis reveals that inverters synchronized via reactive power inherently exhibit grid-following rather than grid-forming behavior. Last, an intuitive analytical model is developed to assess the stability, with experiments and simulations validating the proposed method.

Power electronics-interfaced devices, including photovoltaic (PV) panels, wind generators, and energy storage, are being installed at a fast pace across the electrical grid. Their control system can be programmed to perform a variety of ancillary services. Assessment of these features and their impact on power system operation requires detailed simulations and experimental validation. This article aims at presenting and verifying a control strategy where PV inverters are used as AFs. The innovative aspects of the proposed approach are: the use of detailed network data to represent the behavior of the inverter under real operating conditions, the design of control features to ensure that inverter and transformer ratings are not exceeded, and the assessment of using different measurement points to detect harmonic currents. The article presents the structure of the proposed algorithm, simulation results, and the steps undertaken to carry out the experimental validation.

The use of low-frequency ac (LFAC) technology emerges as a competitive and viable solution for the integration of offshore wind farms. This paper provides a comparison of the typologies and control strategies employed in two LFAC transmission schemes. The first scheme involves grid-following controlled offshore inverter with onshore grid-forming controlled rectifier, while the second scheme employs grid-forming controlled offshore inverter based on reactive power synchronization with onshore uncontrolled diode rectifier and ac filters. In this paper, the steady-state operational performance of two low-frequency ac transmission schemes with back-to-back structures is comparatively analyzed in terms of power flow and power quality aspects by simulations.

This paper addresses the challenge of modeling the frequency-dependent network impedance of downstream high voltage (HV) networks for accurate harmonic studies in extra high voltage (EHV) transmission systems. With the increasing integration of renewable energy sources, HVDC stations, and Flexible AC Transmission Systems (FACTS), the accurate assessment of harmonic levels within transmission systems has become crucial. The paper proposes a two-step modeling process, beginning with the determination of frequency-dependent impedance characteristics by field measurements or detailed network simulations. These characteristics are then used to fit generic equivalent circuit (EC) models, allowing for the representation of a wide range of typical impedance characteristics. Challenges encountered in the application of this framework, such as the selection of circuit topologies and parameter estimation methods, are discussed. The paper concludes with a demonstration of the suitability of various circuit models and outlines future research directions.

This work provides a high-level assessment of the harmonic performance of the future U.K. power system with high penetration of Renewable Energy Sources (RESs). A few variations to the standard harmonic analysis are proposed to allow for a more accurate representation of Inverter-Based Resources (IBRs) in frequency-domain studies. In the first part of the paper, two reduced network models (for 2020 and 2050, respectively) are developed, including both transmission and distribution system representation. A frequency-dependent impedance model for individual and aggregated IBRs is adopted, and a novel distribution load model with harmonic injection is proposed. Additionally, the variability of harmonic phase angles is modelled taking into account the physical behavior of the IBRs. Probabilistic Harmonic Load Flows (PHLFs) are carried out on the reduced networks by varying the harmonic injection magnitudes and phase angles of each harmonic source. This work shows that, while overall harmonic levels are dependent on the changes in demand, the inverter impedance has significant impact on local resonances, and accurate models for IBRs are required.

Predicting the duration of electric vehicle (EV) charging is relevant for the swift integration of EVs into the grid. It informs EV charging park operators on when to expect peak demand, and the time it takes to charge EVs. This paper describes an approach, based on three machine learning models, to predict the EV charging duration at three public charging sites in the city of Leeds (United Kingdom). The prediction is based on the use of a dataset comprising a total of 7271 charging sessions for the year 2019. In the first part of the paper, the characteristics of the considered dataset are described. The second part of the paper shows that accurate prediction performance can be achieved using features included in the charging transactions exclusively.

A recent collaboration between the TUD Dresden University of Technology and King’s College London explored the challenges associated with modeling the harmonic impedance of distribution systems and assessing its effects at higher voltage levels. Two network models, incorporating both transmission and distribution system representations, were utilized. For each model, different parameters were considered for sensitivity studies, and the harmonic impedance at the transmission level was computed for each scenario. The findings indicate that some of the parameters result in notable effects only locally, while others impact impedance at the transmission system buses. Common parameters that affect both networks are identified, and future work is outlined.

The Nigerian transmission network is prone to outages and low reliability, and both issues are currently impacting the population's quality of life and hindering economic development. This situation is expected to worsen in the future, due to the increase in forecasted demand. This paper assesses the stability of the Nigerian transmission network under existing grid conditions, and determines the impact of High Voltage Direct Current (HVDC) on voltage stability. The PV and QV analysis methods were carried out using the DIgSILENT PowerFactory software package. Two weak buses were identified, and an HVDC model was built and integrated into the existing network at these locations. The results demonstrated that the HVDC interconnector positively impacts system stability by improving the voltage profile and the reactive power margin (RPM).

Deep learning in computer vision is becoming increasingly popular and useful for tracking object movement in many application areas, due to data collection burgeoning from the rise of the Internet of Things (IoT) and Big Data. So far, computer vision has been used in industry predominantly for quality inspection purposes such as surface defect detection; however, an emergent research area is the application for process monitoring involving tracking moving machinery in real time. In steelmaking, the deployment of computer vision for process monitoring is hindered by harsh environments, poor lighting conditions and fume presence. Therefore, application of computer vision remains unplumbed. This paper proposes a novel method for tracking hot metal ladles during pouring in poor lighting. The proposed method uses contrast-limited adaptive histogram equalisation (CLAHE) for contrast enhancement, Mask R-CNN for segmentation prediction and Kalman filters for improving predictions. Pixel-level tracking enables pouring height and rotation angle estimation which are controllable parameters. Flame severity is also estimated to indicate process quality. The method has been validated with real data collected from ladle pours. Currently, no publications presenting a method for tracking ladle pours exist. The model achieved a mean average precision (mAP) of 0.61 by the Microsoft Common Objects in Context (MSCOCO) standard. It measures key process parameters and process quality in processes with high variability, which significantly contributes to process enhancement through root-cause analysis, process optimisation and predictive maintenance. With real-time tracking, predictions could automate ladle controls for closed-loop control to minimise emissions and eliminate variability from human error.

Renewable energy sources have been deployed in large amounts in the last decade, and this trend is expected to continue, and more likely to accelerate. These devices are interfaced to the power system by means of a power electronics interface, while other generating sources are directly connected to the grid. As a result, the development of dedicated models to study the integration of renewable energy sources is required. Once the models are developed, various types of system integration studies need to be performed to assess both steady-state and transient system operation. This paper focuses on a category of steady-state studies, referred to as harmonic analysis, that aims at assessing the impact of renewable energy sources on voltage and current distortion. Harmonic studies are gaining attention because under certain circumstances, the power electronics interface devices may generate undesirable harmonics, that may be further amplified under grid resonance conditions. This paper compares various cases studies where two different models, ideal and frequency-dependent impedance representation and various solvers are implemented. A nine-bus network model, including two wind plants and two photovoltaic installations, is used to demonstrate various case studies. Recommendations are proposed to appropriately model renewable energy sources depending on the specific application considered. The commercial software DIgSILENT PowerFactory is used to carry out the analysis, but the results can be generalized to other tools.

The small area of the United Kingdom relative to weather systems makes renewable energy sources variable on short time scales. Short term variability is therefore a growing concern with increasing amounts of renewable energy integration. In this work, we address how tidal energy can contribute to reducing medium-term variability in the future UK energy mix. Two tidal integration scenarios are defined for 2050: for each scenario, a 5-min interval generation profile is calculated using an oceanographic model of UK tides, and the medium-term variability is assessed. Here we show that tidal power shows a lower level of variability compared to other resources. During spring tides, a national network of tidal power stations can produce continuous, although variable, electricity. It is then shown that tidal energy and storage can provide year-round continuous and constant power output, i.e. baseload generation. Therefore, we conclude that tidal energy can provide positive contributions and complement other renewable energy sources.