Search Results (486)

A new energy storage unit, which is fed by a piezoelectric wind energy harvester, is explored. The outputs of a three-phase piezoelectric wind energy device have been initially recorded from the laboratory experiments. Following the records of voltage outputs, the power ranges of the device were measured at several hundred microwatts. The main issue of piezoelectric voltage generation is that voltage waveforms of piezoelectric materials have high total harmonic distortion (THD) with incredibly high subharmonics and superharmonics. Therefore, such a material reply causes a certain power loss at the output of the wind energy generator. In order to fix this problem, we propose a combination of a rectifier and a storage system, where they can operate compatibly under high THD rates (i.e., 125%). Due to high THD values, current–voltage characteristics are not linear-dependent; indeed, because of capacitive effect of the piezoelectric (i.e., lead zirconium titanite) material, harvested power from the material is reduced by nearly a factor of 20% in the output. That also negatively affects the storage on the Li-based battery. In order to compensate, the output waveform of the device, the waveforms, which are received from the energy-harvester device, are first rectified by a full-wave rectifier that has a maximum power point tracking (MPPT) unit. The SOC values prove that almost 40% of the charge is stored in 1.2 s under moderate wind speeds, such as 6.1 m/s. To conclude, a better harvesting performance has been obtained by storing the energy into the Li-ion battery under a current–voltage-controlled boost converter technique. Full article

The temperature of the thermal energy storage unit is a critical parameter for the stable operation of seasonal borehole thermal energy storage (BTES) systems. However, existing temperature prediction models predominantly focus on estimating single-point temperatures or borehole wall temperatures, while lacking effective methods for calculating the average temperature of the storage unit. This limitation hinders accurate assessment of the thermal charging and discharging states. Furthermore, some models involve complex computations and exhibit low operational efficiency, failing to meet the practical engineering demands for rapid prediction and response. To address these challenges, this study first develops a thermal response model for the average temperature of the storage unit based on the finite line source theory and further proposes a simplified engineering algorithm for predicting the storage unit temperature. Subsequently, two-dimensional discrete convolution and Fast Fourier Transform (FFT) techniques are introduced to accelerate the solution of the storage unit temperature distribution. Finally, the model’s accuracy is validated against practical engineering cases. The results indicate that the single-point temperature engineering algorithm yields a maximum relative error of only 0.3%, while the average temperature exhibits a maximum relative error of 1.2%. After employing FFT, the computation time of both single-point and average temperature engineering algorithms over a 10-year simulation period is reduced by more than 90%. When using two-dimensional discrete convolution to calculate the temperature distribution of the storage unit, expanding the input layer from 200 × 200 to 400 × 400 and the convolution kernel from 25 × 25 to 51 × 51 reduces the time required for temperature superposition calculations to approximately 0.14–0.82% of the original time. This substantial improvement in computational efficiency is achieved without compromising accuracy. Full article

The growing penetration of renewable energy sources requires resilient microgrids capable of providing stable and continuous operation. Hybrid energy storage systems (HESS), which integrate hydrogen-based storage systems (HBSS), battery storage systems (BSS), and supercapacitor banks (SCB), are essential to ensuring the flexibility and robustness of these microgrids. Accurate modelling of these microgrids is crucial for analysis, controller design, and performance optimization, but the complexity of HESS poses a significant challenge: simplified linear models fail to capture the inherent nonlinear dynamics, while nonlinear approaches often require excessive computational effort for real-time control applications. To address this challenge, this study presents a novel state space model with linear variable parameters (LPV), which effectively balances accuracy in capturing the nonlinear dynamics of the microgrid and computational efficiency. The research focuses on a high-voltage DC bus microgrid architecture, in which the BSS and SCB are connected directly in parallel to provide passive DC bus stabilization, a configuration that improves system resilience but has received limited attention in the existing literature. The proposed LPV framework employs recursive linearisation around variable operating points, generating a time-varying linear representation that accurately captures the nonlinear behaviour of the system. By relying exclusively on directly measurable state variables, the model eliminates the need for observers, facilitating its practical implementation. The developed model has been compared with a reference model validated in the literature, and the results have been excellent, with average errors, MAE, RAE and RMSE values remaining below 1.2% for all critical variables, including state-of-charge, DC bus voltage, and hydrogen level. At the same time, the model maintains remarkable computational efficiency, completing a 24-h simulation in just 1.49 s, more than twice as fast as its benchmark counterpart. This optimal combination of precision and efficiency makes the developed LPV model particularly suitable for advanced model-based control strategies, including real-time energy management systems (EMS) that use model predictive control (MPC). The developed model represents a significant advance in microgrid modelling, as it provides a general control-oriented approach that enables the design and operation of more resilient, efficient, and scalable renewable energy microgrids. Full article

This paper describes two low-cost, modular instruments developed for rapid room-temperature characterization of mainly thermoelectrics. The first instrument measures the Seebeck coefficient across diverse sample geometries and incorporates a four-point probe configuration for simultaneous electrical conductivity measurement, including disk-shaped samples. The second instrument implements the Van der Pauw method, enabling detailed investigation of charge carrier behavior within materials. Both devices prioritize accessibility, constructed primarily from 3D-printed components, basic hardware, and readily available instrumentation, ensuring ease of reproduction and modification. A unique calibration protocol using pure elemental disks and materials with well-established properties was employed for both instruments. Validation against comparable systems confirmed reliable operation. Control and data acquisition software for both devices was developed in-house and is fully documented and does not require an experienced operator. We demonstrate the utility of these instruments by characterizing the electronic properties of polycrystalline SnSe thermoelectric materials doped with Bi, Ag, and In. The results reveal highly complex charge carrier behavior significantly influenced by both dopant type and concentration. Full article

The discharge of synthetic dyes into aquatic ecosystems stands as a pointed environmental concern, with serious consequences affecting not only biodiversity and water quality but also human health. To address this challenge, this study introduces a natural Tunisian chert, a silica-rich sedimentary rock, as a promising, sustainable, and low-cost adsorbent for treating textile dye-polluted wastewater. For the first time, the adsorption capabilities of a Tunisian chert were systematically evaluated for both cationic (Methylene Blue; MB and Cationic Yellow 28; CY28) and anionic dyes (Eriochrome Black T; EBT). To assess the impacts of key operational parameters, such as pH (2–12), contact time (0–240 min), adsorbent dosage (0.02–0.25 g), and initial dye concentration (50–500 mg/L), batch mode adsorption trials were performed. The Langmuir isotherm model most accurately fits the adsorption data, yielding a maximum adsorption capacity of 138.88 mg/g for MB, 69.93 mg/g for CY28, and 119.04 mg/g for EBT, outperforming multiple conventional adsorbents. Kinetic modeling revealed that adsorption adhered to a pseudo-second-order model, with rapid equilibrium within 45–60 min, highlighting the efficiency of the Tunisian chert. Optimal dye removal was obtained at pH = 8 for cationic dyes and pH = 4 for EBT, driven by electrostatic interactions and surface charge dynamics. The current research work reveals that Tunisian chert is a low-cost and efficient adsorbent with a high potential serving for large-scale industrial applications in wastewater treatment. Using a locally abundant natural resource, this work provides a maintainable and economical approach for dye removal from polluted wastewater. Full article

Adverse climate events have recently highlighted an increasing need to deploy sustainable energetic infrastructures. The existing electric conversion circuits for solar energy provide high efficiency; however, gaps in sustainability and robustness can be identified by considering their operation during intense perturbations, potentially occurring for interplanetary energy transfer. Additionally, charging characteristics for energy storage units influence differently the operation life of battery arrays, with increased stability providing favorable operating conditions. Therefore, the present study develops an alternative controller for managing solar energy as well as a prototype for tracking the maximum power point, both constrained by robustness and renewability studies. For the presented design, stability analyses and simulations validated the management of electric energy from solar panels and the developed configuration resulted in improving current peak integral transient characteristics by using an alternative control method, demonstrating stability for an indefinite number of energy storage units. Furthermore, the estimation for VLSI (Very-Large-Scale Integration) of this constrained design has been concluded to potentially provide a solution with adequate performance, comparable to state-of-the-art computational circuits. However, certain limitations could arise when substituting the main computation parts with analyzed solutions and proceeding with integration-based manufacturing. Full article

The wireless charging of electric vehicles (EVs) has drawn much attention as it can ease the charging process under different charging situations and environmental conditions. However, power transfer rate and efficiency are the critical parameters for the wide adaptation of wireless charging systems. Different investigations are presented in the literature that have aimed to improve power transfer efficiency and to maintain constant power at the load side. This paper introduces a Maximum Efficiency Point Tracking (MEPT) system designed specifically for a reconfigurable S-LCC compensated wireless charging system. The reconfigurable nature of the S-LCC system supports the constant current (CC) and constant voltage (CV) mode of operation by operating S-LCC and S-SP mode. The proposed system enhances power transfer efficiency under load fluctuations, coil misalignments, and a wide range of operating conditions. The developed S-LCC compensated system inherently maintains the power transfer rate constantly under a majority of load variations. Meanwhile, the inclusion of the MEPT method with the S-LCC system provides stable and maximum output under different coupling and load variations. The proposed MEPT approach uses a feedback mechanism to track and maintain the maximum efficiency point by iteratively adjusting the DC-DC converter duty ratio and by monitoring load power. The proposed approach was designed and tested in a 3.3 kW laboratory scale prototype module at an operating frequency of 85 kHz. The simulation and hardware results show that the developed system provides stable maximum power under a wider range of load and coupling variations. Full article

The increasing deployment of photovoltaic-storage systems in distribution-level microgrids introduces a critical control conflict: traditional maximum power point tracking algorithms aim to maximize energy harvest, while grid-forming inverter control demands real-time power flexibility to deliver frequency and inertia support. This paper presents a novel two-layer co-optimization framework that resolves this tension by integrating adaptive traditional maximum power point tracking modulation and virtual synchronous control into a unified, grid-aware inverter strategy. The proposed approach consists of a distributionally robust predictive scheduling layer, formulated using Wasserstein ambiguity sets, and a real-time control layer that dynamically reallocates photovoltaic output and synthetic inertia response based on local frequency conditions. Unlike existing methods that treat traditional maximum power point tracking and grid-forming control in isolation, our architecture redefines traditional maximum power point tracking as a tunable component of system-level stability control, enabling intentional photovoltaic curtailment to create headroom for disturbance mitigation. The mathematical model includes multi-timescale inverter dynamics, frequency-coupled battery dispatch, state-of-charge-constrained response planning, and robust power flow feasibility. The framework is validated on a modified IEEE 33-bus low-voltage feeder with high photovoltaic penetration and battery energy storage system-equipped inverters operating under realistic solar and load variability. Results demonstrate that the proposed method reduces the frequency of lowest frequency point violations by over 30%, maintains battery state-of-charge within safe margins across all nodes, and achieves higher energy utilization than fixed-frequency-power adjustment or decoupled Model Predictive Control schemes. Additional analysis quantifies the trade-off between photovoltaic curtailment and rate of change of frequency resilience, revealing that modest dynamic curtailment yields disproportionately large stability benefits. This study provides a scalable and implementable paradigm for inverter-dominated grids, where resilience, efficiency, and uncertainty-aware decision making must be co-optimized in real time. Full article

The current global utilization rate of electric vehicle (EV) charging stations ranges from approximately 20% to 40%. Despite numerous studies focusing on enhancing this utilization through single-variable approaches—such as optimizing charging point (CP) locations, analyzing charging behaviors, and adjusting pricing—low utilization rates persist. This paper examines the business model for EVs and charging stations integrated into the 5G Real-Time System for EVs and Transportation (5gRTS-ET) platform, which was operational in China in 2021. It establishes three distinct business models for EV users: the Government Subsidy Model, the Self-Operating Model without Government Subsidies, and the 5gRTS-ET Operating Model. Utilizing an integrated service modeling approach, the study constructs a dynamic business model for charging stations. Findings indicate that incorporating variables related to EV user roles significantly enhances the utilization rates of charging stations. Furthermore, onboarding EV CPs onto the 5gRTS-ET platform emerges as an effective strategy for ensuring their sustainable operation. This research offers a sustainable business model for EV charging stations in light of the evolving roles of EV users and serves as a reference for applying integrated business modeling methods in practical operational platforms. Full article

Equivalent energy consumption minimization methods of energy management systems have been implemented as a rule-based strategy to enhance electric propulsion system efficiency. This study compares the efficiencies of different systems by applying variable- and constant-speed generators with battery hybrid systems, measuring fuel consumption. In the same scenario, the variable-speed operation showed a notable improvement of 10.36% compared to the conventional system. However, in the verification of hybrid system efficiency, onshore charged energy cannot be considered a reduction in fuel consumption. Instead, when converting onshore energy usage into equivalent fuel consumption for comparative analysis, both hybrid constant- and variable-speed operation modes achieved efficiency enhancements ranging from 5.5% to 9.79% compared to the conventional, nonequivalent constant-speed operation mode. Conversely, the nonequivalent variable-speed operation mode demonstrated an efficiency that was 5.41% higher than that of the hybrid constant-speed operation mode. In contrast, the battery-integrated variable-speed operation mode indicated a system efficiency approximately equal to that of the nonequivalent variable-speed operation mode. For vessels with load profiles characterized by prolonged periods of idling or low-load operations, a battery-integrated hybrid system could be a practical solution. This study demonstrates the necessity of analyzing load profiles, even when aiming for the optimal operational set points of the generator engine. Full article

Distribution System Operators (DSOs) increasingly need planning tools that coordinate utility-influenced assets—such as electric-vehicle charging stations (EVCS) and voltage-support resources—with customer-sited distributed generation (DG). We present a Nash-equilibrium-based Iterative Best Response Algorithm (IBRA-NE) for joint planning of DG and EVCS in radial distribution networks. The framework supports two applicability modes: (i) a DSO-plannable mode that co-optimizes EVCS siting/sizing and utility-controlled reactive support (DG operated as VAR resources or functionally equivalent devices), and (ii) a customer-sited mode that treats DG locations as fixed while optimizing DG reactive set-points/sizes and EVCS siting. The objective minimizes network losses and voltage deviation while incorporating deployment costs and EV charging service penalties, subject to standard operating limits. A backward/forward sweep (BFS) load flow with Monte Carlo simulation (MCS) captures load and generation uncertainty; a Bus Voltage Deviation Index (BVDI) helps identify weak buses. On the EEU 114-bus system, the method reduces base-case losses by up to 57.9% and improves minimum bus voltage from 0.757 p.u. to 0.931 p.u.; performance remains robust under a 20% load increase. The framework explicitly accommodates regulatory contexts where DG siting is customer-driven by treating DG locations as fixed in such cases while optimizing EVCS siting and sizing under DSO planning authority. A mixed scenario with 5 DGs and 3 EVCS demonstrates coordinated benefits and convergence properties relative to PSO, GWO, RFO, and ARFO. Additionally, the proposed algorithm is also tested on the IEEE 69-bus system and results in acceptable performance. The results indicate that game-theoretic coordination, applied in a manner consistent with regulatory roles, provides a practical pathway for DSOs to plan EV infrastructure and reactive support in networks with uncertain DER behavior. Full article

This study evaluates a solar-powered electric mobility pilot implemented at the University of Cuenca (Ecuador), combining two electric vans with daytime charging from a 35 kWp PV microgrid. Real-world monitoring with SCADA covered one year of operation, including efficiency tests across urban, highway, and mountainous routes. Over the monitored period, the fleet completed 5256 km in 1384 trips with an average occupancy of approximately 87%. Energy use averaged 0.17 kWh/km, totaling 893.52 kWh, of which about 98.2% came directly from on-site PV generation; only 2.41% of the annual PV output was required for vehicle charging. This avoided 1310.52 kg of CO₂ emissions compared to conventional vehicles. Operating costs were reduced by institutional electricity tariffs (0.065 USD/kWh) and the absence of additional PV investment, with estimated savings of around USD 2432 per vehicle annually. Practical guidance from the pilot includes aligning fleet schedules with peak solar generation, ensuring access to slow daytime charging points, maintaining high occupancy through route management, and using basic monitoring to verify performance. These results confirm the technical feasibility, economic competitiveness, and replicability of solar-electric transport in institutional settings with suitable solar resources and infrastructure. Full article

The transition to fully electric bus (EB) fleets introduces new challenges in coordinating daily operations and managing charging energy needs, while accounting for infrastructure constraints. The paper proposes a three-stage optimization framework that integrates EB scheduling with overnight charging under realistic depot layout constraints. In the first stage, a mixed-integer linear program (MILP) determines the minimum number of EBs with ample batteries and related schedules to complete all timetabled trips. With the fleet size fixed, the second stage minimizes the EB battery capacity by optimizing trip assignments. In the third stage, charging schedules are iteratively optimized for different numbers of chargers to minimize charger power capacity and charging cost, while ensuring each EB is fully recharged before its first trip on the following day. The matrix-shape depot layout imposes spatial and operational constraints that restrict the charging and movement of EBs based on their parking positions, with EBs remaining stationary overnight. The entire process is repeated by incrementing the fleet size until a saturation point is reached, beyond which no further reduction in battery capacity is observed. This results in a Pareto frontier showing trade-offs between required battery capacity, number of chargers, charger power capacity, and charging cost. The proposed method is applied to a real-world airport parking shuttle service, demonstrating its potential to reduce the battery size and charging infrastructure demands while maintaining full operational feasibility. Full article

As the installed power of wind turbines increases, new challenges for the implementation of wind energy in the national power system emerge. Several hours of high energy productivity from wind turbines, together with the periodic occurrence of relatively low energy consumption (at a national scale), sometimes result in the need to stop their operation and, much more often, result in very low revenues for electricity. One of the ways to reduce these phenomena, from a technical and economic point of view, is to use energy storage. However, managing such energy storage poses many challenges due to the unpredictably different duration of favorable and unfavorable wind conditions. Based on historical data on wind turbine energy generation and market data on electricity prices, the impact of using an energy storage with an effective capacity of 2.4 MWh (total 4 MWh) with a maximum charging and discharging power (set parameter) of 1.2 MW in cooperation with a wind turbine (capacity 3 MW) was analyzed. Using simulation methods for energy production and price data from 34,964 h (4 years), the potential additional revenue for the energy storage installed at the wind turbine was calculated. The developed model considered various values: minimum charging power, maximum charging power; and as elements of price signals: price averaging period, level of price deviation from the average electricity price. Full article

Internal conductive defects in composite insulators severely degrade their insulation performance and are considered concealed defects, posing a significant threat to the safe and stable operation of the power grid. Focusing on this issue, this study develops an electro-thermal multi-physical field simulation model and uses finite element analysis to investigate the electric field distribution and temperature rise characteristics. Composite insulator specimens with varying defect lengths were fabricated using the electrical erosion test. Charged tests were then conducted on these defective specimens, as well as on field-decommissioned specimens. The impact of internal conductive defects on the infrared, ultraviolet, and electric field distribution characteristics of composite insulators during operation was analyzed. The results indicate that the surface electric field of composite insulators with internal conductive defects becomes highly concentrated along the defect path, with a significant increase in electric field strength at the defect’s end. The maximum field strength migrates toward the grounded end as the defect length increases. Conductive defects lead to partial discharge and abnormal temperature rise at the defect’s end and the bending points of the composite insulator. The temperature rise predominantly manifests as “bar-form temperature rise,” with temperature rise regions correlating well with discharge areas. Conductive defects accelerate the decay-like degradation process of composite insulators through a positive feedback loop formed by the coupling of electric field distortion, Joule heating, material degradation, and discharge activity. This study identifies the key characteristics of electrical and temperature rise changes in insulators with conductive defects, reveals the deterioration evolution process and degradation mechanisms of insulators, and provides effective criteria for on-site diagnosis of conductive defects. Full article