Search Results (171)

The article explores the current challenges and prospects for the electrification of the bus fleet in urban passenger transport, with a particular focus on the municipal operator Municipal Transport Ruse EAD. The study is motivated by the growing importance of sustainable mobility and the European Union’s policy framework aimed at decarbonization of urban transport systems. A mixed-integer linear programming (MILP) model is developed to optimize the investment and operational strategies for the gradual replacement of diesel buses with electric ones, taking into account capital expenditures, operational costs, charging infrastructure, and environmental benefits. Scenario analysis is employed to compare six different pathways of fleet electrification, ranging from partial to full transition within a defined planning horizon. The results highlight significant trade-offs between financial feasibility and ecological impact, illustrating that an accelerated electrification strategy yields the largest emission reductions but requires substantial upfront investment. Conversely, gradual transition scenarios demonstrate better budget alignment but achieve lower environmental benefits. The discussion emphasizes the practical applicability of the model for municipal decision-makers, offering a tool for strategic planning under economic and ecological constraints. The paper concludes that sustainable electrification of municipal bus fleets requires a balanced approach that aligns environmental objectives with financial and operational capacities. Full article

This study presents the electrification plan of a school bus (SB) fleet and examines its potential in vehicle-to-grid (V2G) applications. The data collected includes the efficiency of a 120 kW EV charger, energy consumption of a 40-foot electric school bus (ESB), and a diesel bus operating on the same route. The energy consumption data of the ESB and diesel school bus (DSB) were processed to derive the yearly average distance-specific energy consumption of 0.37 mile/kWh (0.60 km/kWh) grid electricity and 5.55 MPG (2.36 km/L), respectively. The energy consumption ratio of the ESB over the DSB is 14.92 kWh/gallon (3.94 kWh/L) diesel. Based on the CO₂ intensity, 1.956 lb/kWh (0.887 kg/kWh) of electricity produced in WV and that of diesel fuel, the distance-specific CO₂ emissions of the ESB were 5.38 lb/mile (1.52 kg/km), which are higher than the 4.08 lb/mile (1.15 kg/km) from the diesel bus operating on the same route. This study also presents the V2G potential of the proposed electrical school bus fleet. Based on the estimated grid-to-vehicle battery (G2VB) efficiency of 92% and vehicle battery-to-grid (VB2G) efficiency of 92%, the grid–vehicle battery–grid (G2VB2G) efficiency is 84.64%. The application of V2G technology is associated with a loss of electricity. Based on the 20% to 80% battery charge, and the estimated 92% VB2G efficiency, the proposed ESB fleet has the potential to provide 14,929 kWh electricity, 55.2% of the ESB fleet battery capacity. The increased cost associated with the implementation of the proposed V2G is about USD 7.5 million, a 400% increase compared to the charger satisfying the operation of ESBs when V2G is not used. The V2G application also is expected to increase the charging cycles, which raises concerns about battery degradation and its replacement during SB service lifetime. Accordingly, more research work is needed to address the increased cost and grid capacity demand, and battery degradation associated with V2G applications. Full article

Amid the increasing demand to reduce carbon emissions, replacing diesel buses with electric buses has become a key development direction in public transportation. However, a significant challenge in this transition lies in developing efficient charging strategies and accurately determining the required fleet size, as existing research often fails to adequately account for the impact of real-time traffic congestion on energy consumption. To address this gap, in this study, an optimized charging strategy is proposed, and the necessary fleet size is calculated using a deep reinforcement learning (DRL) approach, which integrates actual route characteristics and dynamic traffic congestion patterns into an electric bus operation model. Modeling is conducted based on Beijing Bus Route 400 to ensure the practical applicability of the proposed method. The results demonstrate that the proposed DRL method ensures operational completion while minimizing charging time, with the algorithm showing rapid and stable convergence. In the multi-route scenarios investigated in this study, the DRL-based charging strategy requires 40% more electric buses, with this figure decreasing to 24% when fast-charging technology is adopted. This study provides bus companies with valuable electric bus procurement and route operation references. Full article

Permanent magnet synchronous machines (PMSMs) are the preferred choice for electric vehicles (EVs), hybrid EVs, and wind turbines because of their high torque density, efficiency, and wide constant-power speed range. Conventional PMSMs rely heavily on rare-earth (RE) permanent magnets like Nd-Fe-B, which offers high remanence and coercivity but comes with high costs, supply chain issues, and environmental concerns. To address these challenges, this paper explores the potential of tetragonal Fe₂Ni₂N, a newly developed RE-free permanent magnet, as a replacement for commercial Nd-Fe-B (N35) in high-performance PMSMs. Fe₂Ni₂N shows a remanent flux density of 1.2 T and coercivity of 0.957 MA/m, closely matching those of commercial N35 magnets. Finite element analysis (FEA) in Ansys Maxwell was performed on both surface-mounted (SPM) and interior-mounted (IPM) PMSMs under EV-representative operating conditions. Results demonstrate that Fe₂Ni₂N-based machines have similar demagnetization resistance, torque, and efficiency to those with N35 magnets, with slight performance advantages at low speeds and nearly identical performance at high speeds. Furthermore, system-level parameters such as DC bus voltage and stator current were analyzed, showing that increased voltage extends the constant torque region while higher current enhances torque output but can slightly reduce efficiency at elevated speeds. These findings confirm that Fe₂Ni₂N is a promising RE-free alternative to Nd-Fe-B for sustainable, high-performance PMSMs. Results show that Fe₂Ni₂N-based machines have similar demagnetization resistance, torque, and efficiency to those with N35 magnets, with slight performance benefits at low speeds and nearly identical results at high speeds. Furthermore, system-level parameters, such as DC bus voltage and stator current, were analyzed. The results show that increased voltage extends the constant-torque region, while higher current enhances torque output but can slightly reduce efficiency at elevated speeds. These findings confirm that Fe₂Ni₂N is a promising RE-free alternative to Nd-Fe-B for sustainable, high-performance PMSMs. Full article

Distribution network data may encounter random missing data caused by abnormal conditions and continuous missing data caused by natural disasters during gathering, transmission, and conversion. To address these problems, this paper proposes a missing data imputation method based on the Temporal Generative Adversarial Network with Gradient Penalty (TGAN-GP), which takes the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) as its basic framework, replaces traditional fully connected layers with a Temporal Convolutional Network (TCN) in the generator’s core, leverages causal dilated convolution to efficiently capture the long-range temporal dependencies and periodicity of measurement data, and integrates residual connections to mitigate gradient vanishing and network degradation during deep training. For the discriminator, the method adopts a Long Short-Term Memory (LSTM) network, which enhances the evaluation of the temporal rationality of generated data and thereby further improves imputation accuracy. Finally, simulations were conducted on the IEEE 33-bus distribution network test system. Results show that under the random missing scenario (10% missing rate), the Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) of node voltage magnitude imputation are as low as 0.00062 and 0.00051, those of node injected active power imputation are 0.00081 and 0.00065, and those of node injected reactive power imputation are 0.00082 and 0.00076. Under the continuous missing scenario, the RMSE and MAE of node voltage magnitude imputation are 0.00147 and 0.00122, those of node injected active power imputation are 0.00373 and 0.00268, and those of node injected reactive power imputation are 0.00314 and 0.00226. The imputation errors of all three data types are significantly lower than the comparison methods’. Full article

Public transport still uses vehicles powered by fossil fuels. Replacing the fleet with zero-emission vehicles will take many years. During this period, it is still necessary to carry out work aimed at reducing energy consumption and thus the emission of toxic substances into the atmosphere. An important part of this work is the study of the relationship between energy demand of buses with different power plants and urban traffic conditions. These conditions include traffic intensity, average and maximum speeds, and number of stops. The VSP (Vehicle-Specific Power) model is useful in research on this relationship. In this article, such research was carried out using data from public bus monitoring and data provided by the city authorities of Rzeszów. In the first stage, a VSP model was created and tuned for three buses with different power plants operating on selected routes. Then, as a result of a large number of simulation processes, the impact of the average speed on the energy demand was determined. The results of the conducted research can be used in the modernization or planning of public transport networks and the modification of road infrastructure. All these activities should contribute to reducing energy consumption and environmental pollution. Full article

A proactive power compensation strategy applicable to achieving transient ride-through of ship microgrid (SM) under pulsed load is presented in this paper. The essence of this strategy can be summarized as the generator enters a transient process when a large portion of the pulsed load is connected to the islanded microgrid. Next, the pulsed load power is calculated and predicted over a 20 ms time scale based on the changes in stator current, stator voltage, excitation current and excitation voltage during the process. As a result, the predicted power is used as the control desired value of the compensation device to ensure that the microgrid recovers the power balance and achieves transient ride-through. Finally, the proposed control strategy not only replaces the one machine infinite bus (OMIB) with the transient model of the SG but also utilizes the energy storage device to actively guide the generator to output the differential power in the microgrid. The power response time of the compensation system is in the range of 6–20 ms, which is able to realize the transient ride-through of the SG within one cycle. Full article

The displacement of synchronous machines by inverter-based resources raises critical concerns regarding the stability of future low-inertia power systems. Grid-forming (GFM) inverters offer a pathway to address these challenges by autonomously establishing voltage and frequency while emulating inertia and damping. This paper investigates the feasibility of operating a transmission-scale network with 100% GFM penetration by fully replacing all synchronous generators in the IEEE 39-bus system with a heterogeneous mix of droop, virtual synchronous machine (VSM), and synchronverter controls. System stability is assessed under a severe fault-initiated separation, focusing on frequency and voltage metrics defined through center-of-inertia formulations and standard acceptance envelopes. A systematic parameter sweep of virtual inertia (H) and damping ($D_p$) reveals their distinct and complementary roles: inertia primarily shapes the Rate of Change in Frequency and excursion depth, while damping governs convergence speed and steady-state accuracy. All tested parameter combinations remain within established stability limitations, confirming the robust operability of a fully inverter-dominated grid. These findings demonstrate that properly tuned GFM inverters can enable secure and reliable operation of future power systems without reliance on synchronous machines. Full article

The transportation sector is undergoing a rapid energy transition. Electric Vehicles (EVs) are gradually replacing conventional ones in many different sectors, but battery management still represents a critical limitation of this process. Consequently, research in this area is expanding, aiming to develop solutions that enhance performance while minimizing environmental impact. This study addresses the application of Machine Learning (ML) techniques to estimate the battery State of Charge (SoC) for a full-electric bus fleet operating public service. The methodology is built based on the available driving data disclosed from the fleet monitoring system. The ML methods are assessed starting from model-based (MB) observers assumed as reference and performances are compared upon this basis. The datasets are retrieved from a public repository or derived from real cases, particularly referring to an electric bus fleet operating for an urban public service. The most critical limitation is the absence of the electrical input data coming from the battery, typically required by model-based approaches. Despite this, the proposed ML model achieved sufficient accuracy levels (RMSE < 0.3%) comparable to those of traditional observers. These outcomes demonstrate the potential of data-driven approaches to provide scalable and more straightforward tools for battery monitoring. Full article

Smart grids (SGs) are becoming increasingly complex with the integration of communication, protection, and automation technologies. However, this digital transformation has introduced new vulnerabilities, especially false data injection attacks (FDIAs) and Denial of Service (DoS) attacks. FDIAs can subtly corrupt measurement data, misleading operators without triggering traditional bad data detection (BDD) methods in state estimation (SE), while DoS attacks disrupt the availability of sensor data, affecting grid observability. This paper presents a deep learning-based framework for detecting and localizing FDIAs, including under DoS conditions. A hybrid CNN, Transformer, and BiLSTM model captures spatial, global, and temporal correlations to forecast measurements and detect anomalies using a threshold-based approach. For further detection and localization, a Multi-layer Perceptron (MLP) model maps forecast errors to the compromised sensor locations, effectively complementing or replacing BDD methods. Unlike conventional SE, the approach is fully data-driven and does not require knowledge of grid topology. Experimental evaluation on IEEE 14–bus and 118–bus systems demonstrates strong performance for the FDIA condition, including precision of 0.9985, recall of 0.9980, and row-wise accuracy (RACC) of 0.9670 under simultaneous FDIA and DoS conditions. Furthermore, the proposed method outperforms existing machine learning models, showcasing its potential for real-time cybersecurity and situational awareness in modern SGs. Full article

This paper presents a new power delivery architecture to bring AC distribution voltages to core levels for computing loads using only two conversion stages with new converter topologies to potentially replace the traditional four-stage structure in the development of new data centers. This paper also includes new converters as solutions to the proposed two stages. A new switched capacitor (SC)-based AC-DC converter is proposed for the first stage and demonstrated for an intermediate bus with 90 V–110 VAC to 48–60 VDC conversion and power factor correction. The second stage also includes an SC-based hybrid converter with multi-phase operation suitable for power delivery for core voltages of up to ~1 V with a high current density. This work also reports a new phase sequence for the second stage for an extended output voltage range. Individually, the first stage was measured at 96.1% peak efficiency for output currents ranging from 0 to 4.5 A, while the second stage achieved 90.7% peak efficiency with a load range of 0–220 A at 1V. The measured peak power densities were 73 W/in³ for the first stage and 2020 W/in³ for the second stage. In combination, the direct conversion from ~110 VAC to 1 VDC led to a peak efficiency of 84.1% at 50 A, and this setup has been tested with output currents of up to 160 A, where the efficiency was 73.5%. Full article

Large-scale wind power grid-connected systems can trigger the risk of power system instability. In order to enhance the stability margin of grid-connected systems, this paper accurately characterizes the topology of the global boundary of stability domain (BSD) of the grid-connected system based on BSD theory, using the method of combining the manifold topologies and singularities at infinity. On this basis, the effect of large-scale doubly fed induction generators (DFIGs) replacing synchronous units on the BSD of the system is analyzed. Simulation results based on the IEEE 39-bus system indicate that the negative impedance characteristics and low inertia of DFIGs lead to a contraction of the stability domain. The principle of singularity invariance (PSI) proposed in this paper can effectively expand the BSD by adjusting the inertia and damping, thereby increasing the critical clearing time by about 5.16% and decreasing the dynamic response time by about 6.22% (inertia increases by about 5.56%). PSI is superior and applicable compared to traditional energy functions, and can be used to study the power angle stability of power systems with a high proportion of renewable energy. Full article

Air pollution caused by CO₂ emissions has become a global issue of vital importance, posing irreversible risks to health and life when concentration of CO₂ becomes too high. This study aims to estimate the CO₂ emissions and carbon footprint of the public transport bus fleet in Bucharest, with a comparative analysis of greenhouse gas (GHG) emissions generated by diesel and electric buses of the Bucharest Public Transport Company (STB S.A.) in the period 2021–2024, after the modernization of the fleet through the introduction of 130 hybrid buses and 58 electric buses. In 2024, the introduction of electric buses and the reduction in diesel bus mileage reduced GHG emissions by almost 13% compared to 2023, saving over 11 kilotons of CO_2e. There was also a 2.68% reduction in the specific carbon footprint compared to the previous year, which is clear evidence of the potential of electric vehicles in achieving decarbonization targets. We have also developed two strategies, one for 2025 and one for the period 2025–2030, replacing the aging fleet with electric vehicles. This demonstrates the relevance of electric transport integrated into the sustainable development strategy for urban mobility systems and alignment with European standards, including improving air quality and living standards. Full article

Active power decoupling (APD) technology demonstrates significant advantages in addressing the mismatched second-order ripple power issue in single-phase rectifiers. However, conventional methods typically require additional voltage or current sensors to achieve precise decoupling control, thereby increasing the cost of the decoupling circuit. To reduce costs and simplify the control system, a sensor-reduced decoupling control method is proposed, with its key advantages highlighted in three aspects: First, the proposed method operates by replacing actual sampled variables with designed reference values, reducing the number of sensors—only the DC bus voltage information is required for operation. Second, the sensor-reduced control scheme is designed based on Lyapunov stability conditions and ensures system stability. Third, virtual impedance produces the reference current of the decoupling circuit, which eliminates grid signal interaction and simplifies control. Simulation and experimental results validate the effectiveness and feasibility of the proposed method. Full article

The behavior of the cast-in-place continuously reinforced concrete (CRC) bus pad applied to bus stop pavement in a central bus-only lane was experimentally analyzed under environmental and moving vehicle loads, and the early-age performance of the CRC bus pad was evaluated using experimental data and finite element analysis results. Using various measurement sensors, the concrete slab strain, longitudinal steel bar strains, horizontal and vertical displacements, and crack behavior of the CRC bus pad due to environmental loads were measured, and the dynamic responses of the concrete slab and steel bars due to moving vehicle loads were also measured. Additionally, a method for converting strain gauge measurements of a cracked concrete slab to the strain of an uncracked concrete slab was also proposed. Under environmental loads, the range of stresses acting on the steel bars and the bond between concrete and steel bars were analyzed to be appropriate for ensuring excellent performance of the CRC bus pad. The crack widths and vertical and longitudinal displacements of the CRC bus pad were found to have no effect on the pavement performance. Within the vehicle velocity range used in this experiment, the strains of the slab and steel bars as the vehicle passed through the CRC bus pad were virtually independent of the vehicle velocity and were within a range that did not cause any reduction in pavement performance. This study confirmed that the CRC bus pad has excellent performance and can replace asphalt concrete bus stop pavement or jointed concrete bus pad. Full article