Search Results (47,293)

Grid-forming inverters, which are represented by droop control and virtual synchronous generator control, have been widely studied and applied because of their excellent grid-supporting ability and smooth off-grid switching. When a grid-forming inverter is connected to a microgrid or utility grid, the control loops of active power and reactive power will be coupled because of the voltage phase difference, which will affect the power control performance. This paper first derives the small-signal linearized model of the system, based on which a frequency feedforward control and an amplitude feedforward control are proposed to decouple the active power and reactive power control loops, respectively. The proposed decoupling strategy directly modifies the reference values through feedforward with an easily implementable principle that is applicable to various control coordinate systems, control coordinate systems, and control structures. By comparing system models with and without the proposed decoupling strategy, its effectiveness can be theoretically proven. Time-domain simulations and hardware experiments are presented to further validate its effectiveness. Full article

This paper investigates the deterioration of, and the abnormal temperature rise in, the GFRP core rod material of compact V-string composite insulators subjected to prolonged alternating flexural loading under wind-induced stresses. The axial stress on the GFRP (Glass Fiber Reinforced Plastic) core rod, resulting from transverse wind loads, is a focal point of examination. By establishing a stress model and damage model, the paper simulates and computes the evolution of damage in the outer arc material of composite insulator core rods subjected to alternating flexural loads. Additionally, a multi-factor coupled aging platform is set up, integrating humidity, heat, and mechanical stress, to simulate the crazing deterioration process of composite insulators under alternating flexural loads. Experimental results reveal that during 400,000 alternating load cycles, the core rod underwent stages of surface damage, damage increasing, fatigue embrittlement, matrix hydrolysis, and fiber fracture. Simultaneously, the silicone rubber sheath on the outer side of the composite insulator’s bending arc develops cracks over aging time, creating pathways for moisture ingress into the interface and core rod. The dielectric constant and dielectric loss factor of the aging region of the core rod increase to varying degrees compared to the non-aging part. Moreover, the degree of abnormal heating of the samples intensifies with the duration of aging experiments. These findings underscore the significance of understanding the aging and decay-like fracture process of compact line V-string composite insulators. They provide crucial insights for future research aimed at enhancing the material properties of composite insulator core rods. Full article

The article presents a comprehensive study of the energy strategies of both countries, aimed at achieving their goals by 2050. A literature review presents global trends in energy policy, the current situation in Poland and Germany, and the importance of sustainable energy. For Poland and Germany, the current situation, goals, and strategies for 2050 are described, and the results of surveys carried out using a survey questionnaire are presented. A comparative analysis included a comparison of the goals and strategies of both countries and the results of surveys, presented in tabular form. This analysis drew conclusions regarding the differences and similarities in the approach of both countries to energy policy. The “Challenges and Prospects” section identifies potential challenges and presents opportunities and recommendations for the future. In conclusion, the article provides a thorough analysis, based on the methodology of a literature review, survey questionnaire, and tabular analysis, and contains important conclusions and implications for energy policy in Poland and Germany. The article also addresses the limitations of the study that may affect the interpretation of the results. Full article

In recent years, several research works have addressed and developed the phase-locked loop (PLL) in single-phase grid-connected converters with different structures and properties. Each has merits and demerits, such as a complex structure, high computational burden, and slow transient response. This paper aims to comprehensively review advanced single-phase PLLs based on transport delay operators to realize signal orthogonality. A deep insight into the PLLs’ small-signal modeling, main characteristics, stability analysis, and loop filter design are provided in this paper. The main advantages and drawbacks are explained for each type of PLL in terms of different performance indexes, such as settling time, estimation error, and ripples in the estimated grid information. This paper also aims to provide optimal tuning and design of the loop filter gains from the large-signal model point of view, including all the nonlinearities, adopting the stochastic optimization method. All simulations are implemented using the MATLAB/Simulink 2018b environment to validate all theoretical analyses of this paper. The sampling and nominal frequencies are set to be 100 kHz and 50 Hz throughout all the simulation studies. Full article

Microgrids can assist in managing power supply and demand, increase grid resilience to adverse weather, increase the deployment of zero-emission energy sources, utilise waste heat, and reduce energy wasted through transmission lines. To ensure that the full benefits of microgrid use are realised, hybrid renewable energy-based microgrids must operate at peak efficiency. To offer an optimal solution for managing microgrids with hybrid renewable energy sources (HRESs) while taking microgrid reserve margins into account, the particle swarm optimisation (PSO) method is suggested. The suggested approach demonstrated good performance in terms of charging and discharging BESS and maintaining the necessary reserve margins to supply critical loads if the grid and renewable energy sources are unavailable. On a clear day, the amount of electricity sold to the grid increased by 58%, while on a partially overcast day, it increased by 153%. Microgrids provide a good return on investment for their operators when they are run at peak efficiency. This is because the BESS is largely charged during off-peak hours or with excess renewable energy, and power is only purchased during less expensive off-peak hours. Full article

The distribution of renewable energy sources is geographically limited. In the process of long-distance transmission, the direct current flowing from a ground electrode into the ground will cause a higher step voltage, which will bring serious security risks to the surrounding industry and life. Accurate calculation of the complex soil electrical model around the grounding electrode is crucial for site selection. Existing simulation software like CDEGS results in significant errors, particularly in complex karst topography. Therefore, constructing a finite element model that accurately reflects the characteristics of geotechnical soil near the DC grounding electrode is an essential but unresolved problem. This paper establishes a soil electrical model for karst topography and explores the impact of cave-type caverns and underground rivers on the step voltage distribution of DC grounding electrodes. These research findings can guide the site selection of DC transmission projects in karst topography. Full article

In response to challenges in constructing charging and hydrogen refueling facilities during the transition from conventional fuel vehicles to electric and hydrogen fuel cell vehicles, this paper introduces an innovative method for siting and capacity determination of Electric Hydrogen Charging Integrated Stations (EHCIS). In emphasizing the calculation of vehicle charging and hydrogen refueling demands, the proposed approach employs the Voronoi diagram and the particle swarm algorithm. Initially, Origin–Destination (OD) pairs represent car starting and endpoints, portraying travel demands. Utilizing the traffic network model, Dijkstra’s algorithm determines the shortest path for new energy vehicles, with the Monte Carlo simulation obtaining electric hydrogen energy demands. Subsequently, the Voronoi diagram categorizes the service scope of EHCIS, determining the equipment capacity while considering charging and refueling capabilities. Furthermore, the Voronoi diagram is employed to delineate the EHCIS service scope, determine the equipment capacity, and consider distance constraints, enhancing the rationality of site and service scope divisions. Finally, a dynamic optimal current model framework based on second-order cone relaxation is established for distribution networks. This framework plans each element of the active distribution network, ensuring safe and stable operation upon connection to EHCIS. To minimize the total social cost of EHCIS and address the constraints related to charging equipment and hydrogen production, a siting and capacity model is developed and solved using a particle swarm algorithm. Simulation planning in Sioux Falls city and the IEEE33 network validates the effectiveness and feasibility of the proposed method, ensuring stable power grid operation while meeting automotive energy demands. Full article

Load forecasting is a research hotspot in academia; in the context of new power systems, the prediction and determination of load reserve capacity is also important. In order to adapt to new forms of power systems, a day-ahead automatic generation control (AGC) reserve capacity demand prediction method based on the Fourier transform and the attention mechanism combined with a bidirectional long and short-term memory neural network model (Attention-BiLSTM) optimized by an improved whale optimization algorithm (IWOA) is proposed. Firstly, based on the response time, Fourier transform is used to refine the distinction between various types of load reserve demand, and the power of the AGC reserve band is calculated using Parseval’s theorem to obtain the reserve capacity demand sequence. The maximum mutual information coefficient method is used to explore the relevant influencing factors of the AGC reserve sequence concerning the data characteristics of the AGC reserve sequence. Then, the historical daily AGC reserve demand sequences with relevant features are input into the Attention-BiLSTM prediction model, and the improved whale algorithm is used to automatically find the optimal hyperparameters to obtain better prediction results. Finally, the arithmetic simulation results show that the model proposed in this paper has the best prediction performance with the upper (0.8810) and lower (0.6651) bounds of the coefficient of determination ($R^2$) higher than the other models, and it has the smallest mean absolute percentage error ($MAPE$) and root mean square error ($RMSE$). Full article

The use of renewable energy sources is becoming increasingly widespread around the world due to various factors, the most relevant of which is the high environmental friendliness of these types of energy resources. However, the large-scale involvement of green energy leads to the creation of distributed energy networks that combine several different generation methods, each of which has its own specific features, and as a result, the data collection and processing necessary to optimize the operation of such energy systems become more relevant. Development of new technologies for the more optimal use of RES is one of the main tasks of modern research in the field of energy, where an important place is assigned to the use of technologies based on artificial intelligence, allowing researchers to significantly increase the efficiency of the use of all types of RES within energy systems. This paper proposes to consider the methodology of application of modern approaches to the assessment of the amount of energy obtained from renewable energy sources based on artificial intelligence technologies, approaches used for data processing and for optimization of the control processes for operating energy systems with the integration of renewable energy sources. The relevance of the work lies in the formation of a general approach applied to the evaluation of renewable energy sources such as solar and wind energy based on the use of artificial intelligence technologies. As a verification of the approach considered by the authors, a number of models for predicting the amount of solar power generation using photovoltaic panels have been implemented, for which modern machine-learning methods have been used. As a result of testing for quality and accuracy, the best results were obtained using a hybrid forecasting model, which combines the joint use of a random forest model applied at the stage of the normalization of the input data, exponential smoothing model, and LSTM model. Full article

Nowadays, increasing the penetration of renewable heat technologies is an important approach to minimise global primary energy use and reduce CO₂ emissions for a sustainable future. Thermoelectric heat pumps, which have some unique characteristics in comparison with conventional vapour compression heat pumps, can be integrated with solar thermal energy storage to form a promising renewable heat technology. However, currently, a reliable numerical model for TeHPs suitable for building energy simulation is lacking and the benefits achievable for a TeHP thanks to the integration with heat storage are unclear. To solve these issues, in this work, an experimental apparatus consisting of a water-to-air TeHP unit with a heat storage tank is modelled and tested for the first time, under the scenarios with thermal energy storage and without thermal energy storage, respectively. The results found that the developed numerical model could well predict the output performance of the TeHP unit, with deviations within 12%. Additionally, the output performance of the TeHP unit when combined with a heat storage tank is better than that of the TeHP unit without heat storage, in terms of the maximum temperature achieved in the testing box, the temperature response speed of the testing box, and the coefficient of performance (COP) of the TeHP unit. This work not only paves the way for the following building-integrated simulations of TeHP units, but also provides guidance for the design of the integrated systems that include TeHPs and thermal energy storage. Full article

The wind–sand climate prevalent in the central and western regions of Inner Mongolia results in significant damage to wind turbine blade coatings due to sand erosion. This not only leads to a decline in power generation but also poses safety risks. This study replicated the wind–sand environment of Alashan and numerically simulated the erosion and wear process of the blade coatings of a 1.5 MW horizontal axis wind turbine under rotational conditions using the DPM model. Additionally, erosion tests were conducted on the operating wind rotor in a wind tunnel. The simulation results demonstrate that sand particle trajectories in the rotating domain are influenced by vortex, incoming wind speed, and sand particle size. For small-sized sand particles, variations in wind speed do not substantially alter the number of particles in contact with the wind turbine blades. However, alterations in the momentum of these particles lead to changes in the impact force on the coating surface. Conversely, the change of wind speed will not only alter the number of large-size sand particles in contact with the wind rotor but also modify the impact force on the coating surface. Furthermore, after impacting the blade, small sand particles continue to move along an approximate helical trajectory with the airflow, while large-size sand particles swiftly rebound. Through statistical analysis of erosion pits on the blade surface after the erosion experiments, it was observed that, in comparison among the leading edge, windward side, trailing edge, and leeward side, the leading edge presents the greatest number of erosion pits, whereas the leeward side has the fewest. Along the spanwise direction, the 0.7R-blade tip segment exhibits the highest count, while the blade root-0.3R section displays the fewest number of pits. The wear morphology of the blade coating was observed from the blade root to tip. The leading edge coating exhibits a range from shallow pits to coating flaking and deeper gouge pits. On the windward side, the coating displays wear patterns varying from tiny cutting pits to cutting marks, and then to gouge pits and coating flaking. Erosion morphology of the trailing edge evolves from only minor scratches to spalling pits, further deepening and enlarging. These research findings provide a basis for the study of zoning-adapted coating materials for wind turbine blades in wind–sand environments. Full article

Large amounts of natural gas hydrates have been discovered in the Qiongdongnan Basin (QDNB), South China Sea. The chemical and stable carbon isotopic composition shows that the hydrate-bound gas was a mixture of thermogenic and microbial gases. It is estimated that microbial gas accounts for 40.96% to 60.58%, showing a trend of decrease with the increase in burial depth. A significant amount of gas hydrates is thought to be stored in the mass transport deposits (MTDs), exhibiting vertical superposition characteristics. The stable carbon isotopic values of methane (δ¹³C₁) in the MTD1, located near the seabed, are less than −55‰, while those of the methane below the bottom boundary of MTD3 are all higher than −55‰. The pure structure I (sI) and structure II (sII) gas hydrates were discovered at the depths of 8 mbsf and 145.65 mbsf, respectively, with mixed sI and sII gas hydrates occurring in the depth range 58–144 mbsf. In addition, a series of indigenous organic matters and allochthonous hydrocarbons were extracted from the hydrate-bearing sediments, which were characterized by the origin of immature terrigenous organic matter and low-moderate mature marine algal/bacterial materials, respectively. More allochthonous (migrated) hydrocarbons were also discovered in the sediments below the bottom boundary of MTD3. The gas hydrated is “wet gas” characterized by a low C₁/(C₂ + C₃) ratio, from 2.55 to 43.33, which was mainly derived from a deeply buried source kitchen at a mature stage. There is change in the heterogeneity between the compositions of gas and biomarkers at the site GMGS5-W08 along the depth and there is generally a higher proportion of thermogenic hydrocarbons at the bottom boundary of each MTDs, which indicates a varying contribution of deeply buried thermogenic hydrocarbons. Our results indicate that the MTDs played a blocking role in regulating the vertical transportation of hydrate-related gases and affect the distribution of gas hydrate accumulation in the QDNB. Full article

As the penetration rate of new energy generation in distributed distribution networks continues to increase, the integration of numerous new energy power plants and associated power electronic devices presents challenges to the power quality of traditional power systems. Therefore, conducting power quality-related research in distribution networks is of significant importance for maintaining power system stability, safeguarding electrical equipment, and enhancing electrical safety. A framework for evaluating the overall power quality of new energy-penetrated distribution network systems based on the analytic hierarchy process (AHP) is proposed. This framework aggregates and calculates the global power quality index (GPQI) through averaging, thereby completing the assessment of power quality situations. By enhancing the computation speed of evaluation metrics through an improved S-transform and considering various disturbances such as diminished illumination, wind power disconnection, and high-current grounding, the GPQI values are used to assess power quality under diverse scenarios. Simulation and experimental results confirm the framework’s close alignment with real scenarios and its effectiveness in evaluating power quality within distribution networks. This method is crucial for maintaining power system stability, protecting electrical equipment, and enhancing overall electrical safety within distribution networks. Full article

The current research on CO₂ cosolvent primarily focuses on reducing the minimum miscibility pressure and improving oil recovery. However, investigations into the impact of additive agents on the phase behavior of crude oil during the CO₂ injection process are relatively limited. In this study, we introduced tributyl citrate as a cosolvent to the CO₂ injection process. By comparing the phase parameters of crude oil and changes in component composition in the residual oil before and after the addition of tributyl citrate, we explored the influence patterns of this cosolvent during CO₂ injection. The experiments show that the optimum concentration of tributyl citrate is 0.3%. After the addition of tributyl citrate, the bubble point pressure of crude oil is reduced from 14.28 MPa to 13.36 MPa, and the density is decreased from 1.00 g/cm³ to 0.95 g/cm³. These alterations of bubble point pressure and density indicate an enhanced solubility of CO₂ and improved miscibility with the oil, coinciding with an increased volume expansion coefficient rising from 1.12 to 1.18 under 20 MPa and a decrease in viscosity from 0.73 mPa·s to 0.64 mPa·s. Tributyl citrate primarily affects the properties of crude oil by reducing interfacial tension and the content of heavy components in the dissolution system. The addition of tributyl citrate stabilizes the deposition trend of heavy components in crude oil and promotes the transformation of heavy components into light components, thereby enhancing the efficiency of CO₂ extraction. This study provides valuable insights into a novel and simple method to further increase oil recovery in the CO₂ injection process. Full article