Power Generation Characteristics Research Articles

Kesan Rekabentuk Parametrik dalam Pengoptimuman Prestasi Turbin Angin Berpaksi Menegak: Satu Ulasan

Wind energy is one of the renewable energy resources that is gaining attention from industry players and researchers. In the last few years, there is an increasing interest in small-scale wind turbines as a power generator in built environments as the urgency to reduce carbon footprint in urban areas increases as well as reducing adverse effects of fossil fuels on human health and the environment. Generally, wind turbines can be categorized into two categories which are horizontal axis wind turbines (HAWTs) and vertical axis wind turbines (VAWTs). VAWTs have good potentials to be developed considering their suitability to be used in complex wind conditions associated with built environments. However, the number of research, publications, as well as basic understanding of flow phenomena associated to the performance of VAWTs such as dynamic stall, flow separation, flow curvature effect and blade-wake interaction are scarce. These flow phenomena are attributed by operational and geometrical parameters that significantly affect the overall performance of VAWTs that includes turbine power generation and aerodynamic characteristics. This paper provides a review and discussion of the effects of various design parameters such as blade profile, blade pitch angle and turbine solidity on the performance of VAWTs and serves as a basic guideline to the designer in designing an ideal VAWT

Complementarity and development potential assessment of offshore wind and solar resources in China seas

The intensification of global energy crisis has attracted worldwide attention on the development of offshore renewable resources. An accurate assessment of spatiotemporal distribution and resources feature of offshore wind and solar (OWS) energy helps to facilitate the proper development and utilization of China’s offshore renewable resources. The published ERA5 reanalysis database from 2012 to 2021 is employed to comprehensively evaluate the richness and variability of OWS resources in China seas. Subsequently, the complementarity between these two resources is estimated using Kendall’s correlation coefficient, and results indicate the complementarity show seasonal changes in most of the China seas. However, in South China Sea, these two offshore renewable resources are complementary throughout the year. Furthermore, by considering various restrictions such as bathymetry and offshore distance, four typical regions in China seas are selected and their power generation characteristics are calculated. Among these regions, the typical region located in South China Sea exhibits the highest annual energy output, with a 100 km2 combined offshore wind-solar system generating 15.29 TWh. In addition, the advantage of joint system in suppressing output fluctuations is confirmed, which encouraging the confidence in combined development of OWS energy.

Generating characteristics and experimentation of counter rotating dual rotor wound field flux switching wind generator

AbstractIn this paper, counter rotating dual rotor wound field flux switching wind power generator is revisited to study the generating characteristics of the AC output power curves based on finite element analysis (FEA) and experimental study. Analysis are performed under dynamic conditions, such as variable resistance, field excitation and speed. Also, electromagnetic performance is studied under variation of the field and armature currents. Analysis reveals that outer port machines with higher power capability and better electromagnetic performance compared to the inner port counterparts, although with higher fluctuations exhibited on the torque profiles of the former due to higher slotting effects. From the power generation characteristics curves, it is clear that the developed wind generator is able to produce reliable performance over a wide operating range. The accuracy of the FEA predicted results are validated, experimentally.The cover image is based on the Research Article Generating characteristics and experimentation of counter rotating dual rotor wound field flux switching wind generator by Wasiq Ullah et al., https://doi.org/10.1049/elp2.12374.

Design and Power Generation Characteristics Analysis of a Self-adaptive Thermoelectric Power Generation System Based on LTspice

Design and Power Generation Characteristics Analysis of a Self-adaptive Thermoelectric Power Generation System Based on LTspice

Design of Market Load Control Mechanism for New Power System

Under the background of energy transformation, China vigorously promotes the construction of a new power system with new energy as the main body. However, the random and volatile power generation characteristics of new energy increase the demand for flexible regulation resources of the system operation. It is difficult to take into account the economy and security of the system operation only by power side regulation resources, so it is necessary to fully tap the potential of flexible adjustment on the demand side and promote the gradual transformation of the source-load mode to the operation mode of source-load interaction. Based on the mature experience of domestic and foreign demand-side response mechanisms, this paper studies the load-side regulation mechanism to provide references for domestic load-side regulation. Aiming at the regulation requirements of the power system, a flexible and efficient load-side regulation mechanism involving large-scale load-side regulation resource aggregation is proposed. This mechanism is designed from four aspects: load regulation of market players, multi-time scale regulation of transactions, regulation form and regulation of capital sources. It is of great significance for breaking the interaction barriers of source and load and forming a market system with an efficient economy, orderly competition and perfect governance.

Effect of Water Vapor and Hydrogen Concentration on Power Generation Characteristics of Protonic Ceramic Fuel Cell

The proton and hole conductivities of BaZrO3-based perovskites depend on partial pressures of oxygen and water vapor. These conductivities affect the power generation characteristics of Proton Ceramic Fuel Cells (PCFCs) using the perovskite as an electrolyte. In this study, the effect of humidification conditions on the power generation characteristics of an anode-supported PCFCs was investigated.The configuration of the anode-supported PCFC was La0.6Sr0.4Co0.2Fe0.8O3-δ (LSCF) cathode/BaZr0.8Yb0.2O3-δ(BZYb) electrolyte/Ni-BZYb anode. The diameter of the effective cathode area was approx. 10 mm. The cathode gas composition was fixed at 97% concentration of air and 3% concentration of water vapor. The concentration of water vapor in the anode gas was controlled to be 3-69%. The current density-voltage characteristics and AC impedance were measured by Bio-Logic SP-150.In all water vapor concentration conditions, the cell showed the highest OCV (approximately 1 V) at 3% concentration of water vapor. However, the maximum power density was highest at 30% concentration of water vapor (346 mW/cm2). The highest maximum power density at 30% concentration of water vapor can be explained by the following reason. The OCV values decrease with increasing the concentration of water vapor because of decreasing the concentration of hydrogen. On the other hand, from the results of impedance measurements, the ohmic resistance of the cell decrease with increasing the concentration of water vapor because of increase of proton conductivity of the cell. Thus, the increase of cell voltage by increase of proton conductivity should be higher than the decrease of OCV values.【Acknowledgements】This presentation is the result of the research and development of ultra-efficient proton-conducting ceramic fuel cell devices, JPNP20003, funded by the New Energy and Industrial Technology Development Organization (NEDO), Japan. We would like to express our gratitude to all parties involved.

Short‐term prediction of behind‐the‐meter PV power based on attention‐LSTM and transfer learning

AbstractDistributed photovoltaic (PV) systems often lack adequate measurements due to cost considerations, which makes it very difficult to predict them accurately. Here, an approach is proposed for behind‐the‐meter (BTM) PV power prediction using attention‐LSTM neural network and transfer learning. First, the weather is classified into four types based on the deviation ratio β. Second, the correlation analysis algorithm identifies the weather factors that contribute the most to PV power generation as GHI, DNI, humidity, and temperature. Then, attention‐LSTM pre‐trained model is constructed, in which the LSTM network fully extracts the temporal characteristics of PV power generation, while the attention mechanism enhances the attention to the important information in the input. Finally, a novel BTM PV short‐term power prediction method using transfer learning that the upper layer parameters of the pre‐trained model were frozen, and a small amount of DP‐NB data was used to fine‐tune the model. The proposed methodology has higher prediction accuracy compared with other benchmark methods under four weather types, and the time cost is saved by freezing the parameters of the first layer of the network by 37.2%.

Research on key technologies of large-scale wind-solar hybrid grid energy storage capacity big data configuration optimization

Due to the uncertainty and randomness of large-scale wind and light, the output power of the power grid has great fluctuations. If it is directly connected to the grid, it will affect the main grid. In addition, when the grid switches between on-grid/off-grid operation modes, there will be power shortages, shocks and oscillations. The scientific and reasonable configuration of energy storage system capacity big data can reduce the load power shortage rate, improve the utilization rate of renewable energy, and ensure the reliable operation of the power grid. For this reason, the key technology of large-scale wind-solar hybrid grid energy storage capacity big data configuration optimization is studied. A large-scale wind-solar hybrid grid energy storage structure is proposed, and the working characteristics of photovoltaic power generation and wind power generation are analyzed, and the probability model of photovoltaic power generation, wind power generation and load, as well as the charging and discharging model of battery and super capacitor are established accordingly. On this basis, the optimization objective function is set, the constraints are determined, and the large-scale wind-solar hybrid grid energy storage capacity big data configuration optimization model is constructed. And the PSO algorithm is used to solve the model to realize the big data configuration optimization of large-scale wind-solar hybrid grid energy storage capacity. The research results show that the proposed method of large-scale wind-solar hybrid grid energy storage system has good power supply reliability and economy, and can effectively improve the utilization rate of renewable energy.

Experimental and theoretical analyses on power generation characteristics of co‐axial MHD energy conversion device

AbstractExperiments on power generation were conducted under the open‐circuit condition to validate theoretical analyses on the power generation characteristics of a co‐axial MHD energy conversion device. Considering distribution of externally applied magnetic field and the electromotive force induced by the rotation of the conductive inner cylinder, the results show that the experimental open‐circuit voltage was lower than the theoretical one for the wide channel width, whereas the experimental open‐circuit voltage was higher than the theoretical one for the narrow channel width. The inclination of the inner cylinder might cause the decrease in effective radial ratio.

Study on characteristics of photovoltaic and photothermal coupling compressed air energy storage system

This paper studies the energy storage and generation characteristics of the photovoltaic power generation coupling compressed air energy storage system for the 5 kW base station, and analyzes the photovoltaic power generation characteristics within 24 h and its influence on the flow characteristics of the compressed air energy storage system. The results show that, affected by precipitation and sunlight, the compressed air energy storage power reaches highest value in May and August, and the compressed air flow and cooling water flow in a single day increase with the increase of light intensity. The power generation time reaches longest value in June, shortest in December, the energy storage time reaches longest in June and shortest in January. Considering the combined demand of cold energy, thermal energy and electric energy in actual production and life, the setting scheme of the compressed air energy storage system for combined cold heat power supply is obtained, and the parameter values such as compression/expansion stage, compression/expansion pressure ratio, temperature and pressure at the inlet and outlet of the compressor/expander/heat exchanger are defined. Adding solar thermal energy storage to the photovoltaic power generation compressed air energy storage system, it is found that it can effectively increase the air temperature and thus reduce the expansion stages required at a specific time.

Short-term PV Power Prediction Based on SAGA-FCM and XGBoost

The stable and economic operation of the power grid cannot be achieved without accurate prediction of PV plant power. To address the problem of unstable clustering quality of the fuzzy c-mean clustering algorithm, this paper proposes to combine the genetic algorithm and simulated annealing algorithm to optimize the FCM clustering algorithm, and then combine it with XGBoost to construct a short-term PV power generation prediction model. Firstly, the robustness of the clustering algorithm is improved. Secondly, the differences in power generation characteristics under different weather types are considered, and the prediction models under three typical weather types are separately trained. Finally, to verify the improvement of the model on prediction accuracy, different clustering methods are used to compare the prediction results, and the results show that the algorithm proposed in this paper has higher accuracy compared with the other three methods.

Experimental and Theoretical Analyses on Power Generation Characteristics of Co-axial MHD Energy Conversion Device

Experimental and Theoretical Analyses on Power Generation Characteristics of Co-axial MHD Energy Conversion Device

Huanghua Port enters carbon neutrality ahead of schedule through technological innovation

Abstract To improve the energy utilization rate and reduce the pollution of the port, the Huanghua Port uses technological innovation to enter carbon neutrality is proposed. According to the study of the working characteristics of a three-phase asynchronous motor, the copper loss and iron consumption of the motor are reduced, permanent magnets are embedded in the rotor to generate a magnetic field directly, and the kinetic energy and potential energy of mechanical operation are converted to power generation and recycled, and the braking power generation characteristics of the motor are used to complete power recovery. The tension of the upper and lower sides of the belt before it starts to rotate is equal, and the tensioning force should meet the starting requirements, and the working section of the belt carrying goods horizontally is divided and calculated according to the evenly distributed rollers until it runs at a uniform speed. According to its power consumption, calculate the cost of using an auxiliary generator to generate and connect electricity, use the power supply to supply the power demand, let the motor run in the rated load area as much as possible, reduce the voltage, and reduce the motor subway consumption, to improve the efficiency of the motor and realize the green energy saving of the port. The analysis of the results shows that: through this paper technical innovation of the whole process of all equipment comprehensive optimization, the port process line efficiency increased by 17.5% on average, equivalent energy saving of nearly 17%, the amount of work using time more reasonable, to ensure that the quality of work does not decline while reducing the waste of power resources, thus affecting the port efficiency improvement.

Development of capacitive‐coupled hall‐type MHD generator

AbstractWe have demonstrated a capacitively coupled Hall‐type MHD generator using ECR plasma. To clarify the characteristics of the fabricated MHD generator, we measured the power generation characteristics as a function of magnetic field strength using a DC Hall‐type MHD power generation experiment. The results showed that the output power decreased due to magnetic pressure at the higher magnetic field. However, the output power corresponded to the theoretical value at the lower magnetic field. An AC Hall‐type MHD power generation experiment was conducted using an AC magnetic field. As a result, full‐wave rectification voltage was observed as per theory. Finally, capacitively coupled Hall‐type MHD power generation experiments were conducted, and full‐wave rectified waveforms were observed as in AC Hall‐type MHD power generation. These waveforms were similar to the output waveforms predicted from theory. These results show that the capacitively coupled Hall‐type MHD generator is feasible.

Coupled dynamic and power generation characteristics of a hybrid system consisting of a semi-submersible wind turbine and an array of heaving wave energy converters

A wind-wave hybrid system consisting of a semi-submersible floating wind turbine and an array of heaving wave energy converters (HWECs) provides a solution for co-located marine renewable energy extraction. The knowledge of the coupled dynamic and power features of the hybrid system is important to the design and operation but is poorly understood. This study proposes a comprehensive numerical model that can tackle the full couplings by bridging the aerodynamic module of OpenFAST and the hydrodynamic simulator WAFDUT through an in-house code based on multi-body dynamics. The coupled dynamic and power generation characteristics of the hybrid system are investigated, with an emphasis on the influence of the HWECs on the wind-induced motion, mooring tension, and wind power generation of the turbine. Results show that the HWECs do not produce negative effects on the wind-induced surge, heave, and pitch motions. The HWECs can slightly reduce the mooring tension and slightly improve wind power generation. The array of HWECs can generate over 500 kW wave power in the waves with periods of 6 s–10 s, which can be a qualified supplement to wind power. The findings offer useful knowledge about the key properties of the hybrid system for practical use.

Numerical Study of Plasma Behavior and Power Generation Characteristics in a Disk MHD Generator With Xenon-Seeded Neon Gas

Plasma behavior and power generation characteristics in a disk-shaped magnetohydrodynamic (MHD) power generator with xenon (Xe)-seeded neon (Ne) working gas have been examined by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$r$</tex-math> </inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\theta $</tex-math> </inline-formula> 2-D numerical simulation under the assumptions of isentropic gas flow and a non-MHD interaction. The seed fraction (mole% of Xe in the mixture) is varied from 0.0% (pure Ne) to 100.0% (pure Xe) to assess the effect that Xe seeding has on plasma behavior and power generation characteristics. Adding a small amount of Xe to Ne improves the power performance due to the resulting enhancement of electrical conductivity, whereas adding an excessive amount (over 5.0%) deteriorates the performance. At an appropriate load resistance, uniform plasma structure occurs for low seed fractions. However, the plasma structure becomes nonuniform for excessively high seed fractions (over 5.0%). This result suggests that adding an excessive amount of Xe can reduce the uniformity of the plasma structure in the generator. On the other hand, at low load resistance ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&lt;$</tex-math> </inline-formula> the appropriate load resistance) and high load resistance ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&gt;$</tex-math> </inline-formula> the appropriate load resistance), a nonuniform plasma structure occurs for any seed fraction and results in the deterioration of generator performance. The electron temperature ranges for maintaining uniform plasma structure become narrower as the seed fraction increases which can be attributed to the low ionization potential of Xe and its large atomic weight.

Grey Wolf Optimizer for RES Capacity Factor Maximization at the Placement Planning Stage

At the current stage of the integration of renewable energy sources into the power systems of many countries, requirements for compliance with established technical characteristics are being applied to power generation. One such requirement is the installed capacity utilization factor, which is extremely important for optimally placing power facilities based on renewable energy sources and for the successful development of renewable energy. Efficient placement maximizes the installed capacity utilization factor of a power facility, increasing energy efficiency and the payback period. The installed capacity utilization factor depends on the assumed meteorological factors relating to geographical location and the technical characteristics of power generation. However, the installed capacity utilization factor cannot be accurately predicted, since it is necessary to know the volume of electricity produced by the power facility. A novel approach to the optimization of placement of renewable energy source power plants and their capacity factor forecasting was proposed in this article. This approach combines a machine learning forecasting algorithm (random forest regressor) with a metaheuristic optimization algorithm (grey wolf optimizer). Although the proposed approach assumes the use of only open-source data, the simulations show better results than commonly used algorithms, such as random search, particle swarm optimizer, and firefly algorithm.

A hybrid model for online short-term tidal energy forecasting

A hybrid model is proposed for the short-term online prediction of tidal currents. The harmonic residual analysis (HRA) model is designed to augment the numerical schemes employed by tidal energy installations by forecasting the residual error of existing methods. Using a combination of techniques from Information and Fractal Theory, a novel component selection criterion for singular spectrum analysis (SSA) is used to remove true noise from the residual time series and to decompose the signal into components that are appropriate for linear-recurrent forecasting (LRF) and high order fuzzy time series (HOFTS) respectively. The performance of the HRA method is evaluated using a combination of simulated and real data from sites in the United Kingdom and the United States. Results demonstrate the model’s viability for 6-minute and 1-hour forecast horizons across sites exhibiting variable degrees of non-linearity. Empirical analysis of the resultant tidal energy forecast verifies the superior accuracy and reliability of the HRA method when compared with existing numerical schemes. Simulated data from three sites at the Pentland Firth, UK is also provided to facilitate further study of the site’s power generation characteristics and to allow for direct model performance comparisons.

Modeling and simulation of power quality detection for tidal current power generation based on HHT

On the basis of summarizing the characteristics of tidal current power generation and power quality analysis methods at home and abroad, this paper comprehensively analyzes the power quality problems existing in tidal current power generation, and Hilbert–Huang transform (HHT) is finally applied to detect and analyze the issues. Using MATLAB to establish the simulation model, and the analysis algorithm of power quality in frequency domain and time domain is focused. The simulation results of single disturbances and some mixed disturbances show that this method has good adaptability to the non-stationary and multi-disturbance characteristics of tidal power generation.

Effect of Water Vapor and Hydrogen Concentration on Power Generation Characteristics of Protonic Ceramic Fuel Cell

To investigate the effect of water vapor in the feed gas on the power generation characteristics of PCFCs, the water vapor concentration was changed to 3%, 15%, 30%, and 50%, while the hydrogen concentration in the gas fed to the anode was fixed at 50%. The impedance measurements showed that the ohmic resistance decreased with increasing water vapor concentration, which was attributed to the increase in the proton conductivity of the electrolyte. The measured current density-voltage characteristics showed that the power output increased with increasing water vapor concentration, which was attributed to the decrease in ohmic overvoltage caused by the increase in proton conductivity. In addition, as a more practical condition, the power generation characteristics were measured when the water vapor concentration was varied while the hydrogen concentration was varied in an anode gas consisting only of hydrogen and water vapor.