Search Results (499)

Understanding how urban park landscape features are associated with service population and service radius can inform park planning and management. In Changsha, China, this study measured both indicators for 29 parks on one weekday and one weekend day in spring 2025 using mobile signaling data, quantified landscape features from multisource data, and examined their associations. Service population and service radius were not highly correlated. The adjusted R² values for the two indicators were 71.8% and 84.5%, respectively. Park area and the number of parking lots within the park were significantly associated with both indicators in the same direction. Percent vegetation cover and the number of stores within the park were significantly associated with the two indicators in opposite directions. Elevation, presence of large-scale flower landscapes, distance to the nearest subway station, number of surrounding bus stops, distance to the city center, slope, percent water body, edge density of vegetation patches, number of public restrooms, and number of surrounding residential quarters were significantly associated with only one indicator. These findings reveal synergistic, trade-off, and indicator-specific association patterns between landscape features and urban park recreational services, and may inform differentiated urban park planning and management. Full article

Renewable energy and energy storage stations require frequent updates of monitoring and control logic across heterogeneous devices and changing operating strategies. This paper proposes a rule graph-based reference architecture that combines low-code logic configuration, graph–model semantic binding, and microservice-oriented functional decomposition. A component status matrix separates the target architecture from the implemented subset. The runnable subset comprises a minimal FastAPI backend, REST/WebSocket telemetry interfaces, an in-process queue, and stateful rule evaluators; gateway, authentication, external message bus, time-series database, visual editor, and industrial protocol services remain design-level elements. Beyond the original single-rule example, a priority-ordered multi-device rule is implemented for cooperative BESS dispatch, communication/topology blocking, low-SOC protection, frequency-based load shedding, backup request, and five-sample recovery release. Existing local network benchmarks are complemented by a 600-step software-in-the-loop trace with scripted telemetry fluctuations and communication quality faults and by 500 in-process ASGI timing samples at each of the four point levels. The trace produced no safety dispatch or protected device violations. P99 application path latency ranged from 1.1962 to 5.5287 ms, but one 75.3065 ms outlier exceeded a 50 ms reference deadline, demonstrating that the Windows/FastAPI path is not deterministic. No industrial controller, hardware-in-the-loop facility, field data, or engineer usability study was used. Accordingly, the paper makes no claim of industrial real-time readiness or measured development effort reduction. Full article

Currently, insulation faults in the DC system of photovoltaic (PV) power stations are handled by a full shutdown strategy of inverters, and fault branch localization relies on manual inspection, resulting in low efficiency and poor accuracy, leading to prolonged unplanned outages and substantial power generation losses. This paper proposes an integrated solution combining high-precision insulation monitoring and intelligent fault line selection, which ensures the reliability of line selection criteria through improved measurement accuracy and achieves automatic fault isolation via optimized line selection strategies. The paper analyzes the mathematical essence of the ill-conditioned measurement equations of the traditional bridge method under severe single-pole grounding faults, establishes a dual-channel heteroscedastic noise model, and utilizes the inherent physical constraint that the sum of the positive and negative pole-to-ground voltages always equals the bus voltage to transform the ill-posed inverse problem into an equality-constrained optimal estimation problem, deriving an analytical solution in the sense of constrained least squares. A collaborative monitoring strategy of “balanced bridge monitoring first, unbalanced bridge precision measurement afterward” is proposed. An automatic fault line selection and isolation algorithm based on sequential branch switching is designed, which leverages the operational characteristic that PV systems allow short-term branch interruption, enabling automatic identification and isolation of faulty branches and automatic restoration of non-faulty branches without installing any leakage current sensors. Experimental results show that under severe fault conditions with a single-pole insulation resistance as low as 22 kΩ, the proposed method limits the error to within 5%; the proposed line selection strategy can complete identification and isolation of all faulty branches within at most two rounds of switching. Full article

The increasing penetration of renewable energy has made the transient stability of new power systems a critical concern. Grid-forming (GFM) energy storage can provide voltage and frequency support for renewable energy stations. However, existing studies on the transient stability of GFM converters predominantly consider only the synchronization of a GFM converter with an infinite bus and do not fully account for the effects of renewable-energy injection and LVRT control in remote-grid-connected renewable energy stations. To fill this gap, this paper establishes a transient power-angle stability analysis model for a GFM energy storage system in renewable energy stations connected to a remote grid. Based on the equivalent swing equation and the equal-area criterion, the transient instability mechanisms under different renewable energy source LVRT depths are investigated. The results demonstrate that increasing renewable energy output reduces the transient stability margin of the GFM converter. Furthermore, the system exhibits two distinct transient response modes depending on the renewable energy source LVRT depth: under shallow LVRT depth, the GFM converter accelerates first and then decelerates, whereas under deep LVRT depth, it decelerates first and then exhibits a swing-back oscillation. These findings, validated through time-domain simulations, provide a theoretical basis for understanding the effects of renewable energy output, LVRT control, virtual inertia, and virtual damping on the transient stability of GFM-integrated renewable energy systems. Full article

Urban low-altitude bus operations require coordinated eVTOL route decisions under station time windows, dynamic passenger boarding and alighting, load-dependent energy consumption, opportunity charging, and battery safety requirements. We formulate a mixed-integer programming model for reservation-based shared services that lexicographically minimizes the number of deployed aircraft first and total flight distance second while enforcing passenger-capacity, time-window, charging, and battery-safety constraints. To solve large instances efficiently, an Elite-Pool guided Load-Coupled Energy-aware Adaptive Large Neighborhood Search algorithm (EP-LCE-ALNS) is developed by combining forward load-energy-coupled decoding, multi-start construction, elite-route guidance, and adaptive neighborhood search. Benchmark comparisons show that EP-LCE-ALNS consistently achieves strong solution quality across instances of different scales and outperforms the comparison algorithms on large-scale problems. Sensitivity analyses further show that increasing passenger capacity reduces fleet requirements and flight distance, whereas a larger battery safety margin increases both, providing decision support for fleet configuration, route organization, and safety settings. Full article

Energy-storage-integrated renewable energy stations contain both grid-following and grid-forming converters, which makes their wideband impedance behaviour difficult to predict. This paper studies a field-oriented harmonic impedance measurement method for such stations. A three-phase cascaded H-bridge converter is used to develop a harmonic impedance measurement device connected to the 35 kV bus. For the measured system, a generalized Norton equivalent model is established for the grid-following part, while a generalized Thevenin equivalent model is derived for the grid-forming energy-storage part. A frequency-domain multi-objective target-oriented decoupled control strategy is then designed for the measurement device. The strategy assigns fundamental power synchronisation, harmonic disturbance injection, and submodule capacitor voltage balancing to different frequency components. This design prevents the fundamental current loop from suppressing the injected harmonic current. Simulation studies are carried out under four conditions, including no harmonic injection and 5th-, 25th-, and 99th-order harmonic injections. The baseline case shows no clear commanded-frequency current component. Under harmonic commands, the device injects the corresponding current components while maintaining stable multilevel bridge-port voltage. The device also demonstrates robust impedance-identification performance under grid background harmonics, measurement noise, and equivalent-impedance variations. The results indicate that the proposed device has application capability for wideband impedance measurement and stability analysis in energy-storage-integrated grid-connected systems. Full article

Fuel cell electric vehicles represent a promising option for reducing greenhouse gas emissions from heavy-duty transport. In this context, integrating Hydrogen Refueling Stations (HRSs) into renewable-based microgrids represents a key strategy for ensuring sustainable hydrogen production. This study investigates the integration of an HRS into a photovoltaic-based microgrid supplying a fleet of 21 urban buses. A detailed hourly model of the photovoltaic system, battery storage, hydrogen generator, hydrogen storage, compression and refueling processes was developed. A multi-objective optimization was performed to minimize the Levelized Cost of Hydrogen (LCOH) while maximizing the Self-Sufficiency Rate (SSR). Three Energy Management Strategies (EMSs) were compared: hydrogen production using only renewable electricity, mixed renewable and grid electricity and grid-only electricity. Results reveal a marked economic penalty associated with achieving full self-sufficiency. Under the renewable-only EMS, the LCOH increases from 16.8 €/kg at an SSR of about 80% for the minimum-LCOH solution to 24.3 €/kg at an SSR of 100%. Under the MIXED-EMS, it increases from 12.3 €/kg at an SSR of about 47% to 22.7 €/kg at an SSR of 100%. When revenues from surplus electricity export are included, the corresponding LCOH values at 100% SSR decrease to approximately 15 €/kg, regardless of the EMS adopted. Compared with the emissions from the diesel-bus fleet, hydrogen buses could reduce emissions by about 12% with grid-based production and up to 99% with renewable hydrogen. Full article

To address the dynamic communication topology switching, asynchronous perception information, and uncertainty caused by vehicle mobility in the cooperative control of a vehicle-charger pile-grid under industrial Internet environments, this paper proposes a cooperative optimal control method based on decentralized holistic sensing graph-based estimation. First of all, this method constructs a time-varying weighted directed graph by using decentralized holistic sensing data obtained from the industrial Internet to characterize the dynamic evolution of communication topologies in real time. Secondly, a distributed graph estimator relying solely on local perception information is designed, enabling each agent to predict online its neighbor set and link reliability over a short future horizon based on its own position, the motion trends of nearby objects, and historical link states. On this basis, the graph-based estimation results are embedded as a feedforward compensation term into the consensus control law, forming a predictive graph consensus control algorithm that enables the system to proactively adjust control inputs before topology switching occurs, achieving a paradigm shift from “passive response” to “active pre-compensation.” Meanwhile, an Age of Information (AoI)-aware event-triggered mechanism is introduced, where broadcasting is triggered when the state error exceeds a threshold or the AoI approaches its upper bound, significantly reducing communication load while ensuring control accuracy. Finally, simulations are conducted on a modified IEEE 33-bus distribution system comprising 61 agents (20 electric vehicles, eight charging stations, and 33 grid nodes). The results show that, compared to the event-triggered consensus method without prediction, the proposed method reduces the steady-state error by 40.1%, shortens the convergence time by 40.5%, and decreases the number of broadcasts by 36.5%. In a large-scale system with 169 agents, the proposed method still maintains the highest accuracy, the fastest convergence speed, and the lowest communication overhead, while meeting real-time computational requirements. This method can fully exploit the spatiotemporal redundancy of decentralized holistic sensing, offering a new solution for efficient, robust, and low-cost cooperative control of “vehicle–charger–grid” under industrial Internet environments. Full article

The increasing penetration of electric vehicles (EVs) introduces significant uncertainties into fast-charging station (FCS) planning due to the stochastic nature of EV charging behavior. Accurately representing these uncertainties is essential for making reliable planning decisions in coupled transportation–power networks. This paper proposes a copula-based stochastic planning framework for the optimal allocation of FCSs while accounting for the correlated uncertainties associated with EV charging behavior. A multivariate copula model is employed to capture the dependency structure among key charging variables and generate realistic stochastic charging scenarios, which are subsequently incorporated into the EV charging load forecasting process over the planning horizon. Based on the resulting stochastic charging demand, a multi-objective optimization model is developed to simultaneously minimize investment costs and EV users’ travel distances, improve distribution network performance, and maximize environmental benefits through decarbonization. In addition, distributed generation (DG) units are optimally integrated to improve voltage profiles and reduce power losses. The proposed framework is implemented using MATLAB R2013a and R.4.0.2 and evaluated using both the IEEE 33-bus test system and a realistic 37-bus coupled transportation–power network in Meshgin-Shahr, Iran. The results demonstrate the effectiveness of the proposed stochastic planning framework in addressing uncertainties in EV charging behavior and identifying robust FCS deployment strategies. Full article

Smart mobility strategies often emphasize digital information, applications, and data-driven transport management, while giving less attention to the stop-level conditions that shape passengers’ everyday experience. This study develops and applies a Smart Bus Stop Readiness Index (SBSRI) to assess seven interchange bus stops in Jeddah, Saudi Arabia. The index integrates five weighted dimensions: Passenger Information and Digital Readiness; Physical and Thermal Comfort Provision; Pedestrian Accessibility and Universal Design; Safety and Security; and Land-Use and Activity Integration. Data were collected through field audits, spatial mapping, passenger observations, and a short survey of 71 users. The results indicate that the selected stops have operational interchange importance but generally limited readiness. The mean SBSRI score was 39.07/100; under the adopted planning-oriented classification scheme, only Al-Balad Main Station A achieved moderate readiness, while the remaining stops were classified as showing low or very low readiness. Physical and Thermal Comfort Provision was the weakest dimension, particularly in relation to shade, seating, shelter, and shaded waiting areas. Passenger information and pedestrian accessibility also showed substantial deficiencies. Sensitivity analysis indicated that the principal stop rankings remained stable under alternative weighting scenarios, although category labels were more responsive to threshold selection. This study concludes that smart bus stop readiness should be assessed as a socio-technical condition integrating digital systems with climate-responsive waiting provision, pedestrian accessibility, safety, and the surrounding urban context. Full article

As a crucial flexible regulation resource in distribution networks, electric vehicle fast-charging stations exhibit high-power, stochastic fluctuation characteristics. This randomness makes false data injection attack (FDIA) particularly challenging to detect with conventional methods, thereby posing a significant threat to the secure operation of vehicle-to-grid cyber–physical systems. To address this issue, this paper proposes an FDIA detection method based on ResNet-iTransformer. Firstly, a residual network (ResNet) is employed to capture abnormal patterns in the measurement data layer by layer. Secondly, the dimension reversal technique of iTransformer is utilized to model the interrelationships among channels, enabling information exchange among feature variables through multi-head self-attention. Then, attention pooling is introduced to filter multi-channel features and focus on key channels, thereby achieving accurate attack detection. Finally, simulation tests are conducted on the IEEE 33-bus system. The results show that, compared with existing common detection methods, the proposed method achieves significant improvements in detection precision, recall, and F1 score, enabling more accurate detection of FDIA in the vehicle-to-grid cyber–physical system. Full article

Due to the continuously rising demand for electric vehicle use in distribution networks and power system disruptions caused by natural events and cyber threats, difficulties arise in managing, designing, and recovering the active distribution network. This paper proposes a whole process restoration model considering an electric vehicle battery swapping station with black-start service and islanding partition with loop-elimination radiality. Firstly, the framework for electric vehicle demand and the charging and discharging processes of battery swapping facilities is created, reflecting driving patterns and the order of charging and discharging. Next, the possible main bus and the removal of circular networks are considered in the context of multi-timeframe islanding partitions. Then, the models of units’ start-up sequence and grid reconstruction are established to ensure the system’s successful restoration. The objective function is to minimize the outage loss, restoration time, switch operations and scale of distribution islands. Finally, the practicality and efficiency of the suggested approach are confirmed through the PG&E69-bus system and the 185-node distribution network, which achieves considerable enhancement in system strength and dependability. Full article

The transition from conventional to fully digital substations represents a major transformation in power system communication, protection, and automation. This paper presents a Systematic Literature Review (SLR) of migration strategies, IEC 61850-based standards, implementation challenges, and emerging technologies for digital substations. Following the PRISMA framework, peer-reviewed studies published between 2005 and 2025 were selected from IEEE Xplore and ScienceDirect. The review provides an explicit digitalization perspective through architectural diagrams and comparative analyses describing the evolution from conventional to fully digital substations. The results identify IEC 61850, particularly the integration of a station bus and process bus, as the technological foundation of digital substations, improving interoperability, operational flexibility, monitoring, and protection while reducing copper wiring. Despite these benefits, challenges related to interoperability, synchronization, cybersecurity, and engineering complexity remain. The review also highlights digital twins, artificial intelligence, virtualization, and software-defined protection as key technologies for future digital substations. Full article

With the growing demand for electricity, the penetration of Renewable Distributed Generators (RDGs), alongside the transition from Internal Combustion Engine Vehicles (ICEVs) to Electric Vehicles (EVs), has become a pressing challenge for the stable and efficient operation of distribution networks. This research focuses on a critical task of determining the optimal integration of RDGs, including solar photovoltaic systems, wind turbines, biomass units, and EV charging stations, into an Unbalanced Radial Distribution System (URDS). This work proposes an optimization approach aiming to minimise the total costs (TCs), active power losses (APLs), voltage unbalance factor (VUF), and voltage deviation (VD) of the network under consideration simultaneously. The integration of RDGs is carried out using a metaheuristic technique, which accounts for the intermittent nature of renewable energy sources, the stochastic behaviour of EVs, and the variability of load demands over 24 h a day. Fuzzy decision-making is applied to select an optimal trade-off solution from the Pareto front. The effectiveness of the developed approach is assessed comprehensively on a Pakistani 60-bus URDS as a primary study, while the IEEE-123 bus system is employed as a validation case to demonstrate the applicability and scalability of the proposed methodology. Among the five analysed case studies, the simulation results indicate that coordinated integration of RDGs and EVCSs into the system yields significant benefits, including a decreased reliance on conventional centralised generation, with a reduction of 56.29% in costs, 46.61% in losses, 7.17% in voltage unbalance, and 27.13% in voltage deviation as compared to the base case. Full article

Enclosed transport environments are becoming an integral part of compact urban structures; however, their air quality is monitored less systematically than that of the outdoor urban environment. This study evaluates particulate matter concentrations (PM₁, PM_2.5, PM₁₀) in two urban microenvironments in Banská Bystrica (Slovakia): an underground parking garage (representing private urban mobility) and an underground bus station (representing public transport). Continuous measurements using an enviDUST monitoring device were analysed in relation to occupancy rates and transport intensity. The results showed a dominance of the PM₁₀ fraction in both environments, suggesting the importance of non-exhaust sources and dust resuspension in enclosed urban transport spaces. In the parking facility, the immediate relationship between occupancy and PM concentrations was weak; however, a time lag effect was observed, indicating particle accumulation. The bus station exhibited higher average concentrations (PM₁: 8.67; PM_2.5: 14.12; PM₁₀: 34.12 µg/m³), while peak levels during nighttime highlighted the critical role of air stagnation and ventilation regimes. The study emphasizes the need to perceive such transport nodes as semi-public urban spaces requiring the integration of intelligent air quality management within sustainable urban development. Full article