Modeling and simulation of integrated solar PV - hydrogen systems

To achieve “carbon neutrality”, clean energy such as wind and solar energy is being developed, but due to the random and intermittent characteristics of wind energy and photovoltaics, the instability of grid connections and the abandoning wind and photovoltaics need to be addressed urgently. This paper proposes a method to solve the problems of grid connection and abandonment in wind and photovoltaic generation systems, that is, to establish a combined pumped storage/wind/photovoltaic/hydrogen production system through the pumped storage and hydrogen production system. The system consists of a pumped storage/wind/photovoltaic complementary subsystem and a hydrogen production subsystem. First, different models in the system are modelled using Simulink and the characteristics of the models are analysed. Subsequently, the wind turbine model and the PV model are simulated to derive the wind-PV complementary characteristic curves, and it is found that the load demand cannot be met by relying on wind-PV complementary power generation alone. To achieve system stability and economy, pumped storage is configured to smooth the output of wind power and PV. After comprehensive consideration, the optimal pumped storage capacity is determined to be 1000 MW. Then, through the simulation of the pumped storage/wind/photovoltaic system, it is found that even though pumped storage can absorb the wind and photovoltaic outputs, there is still a surplus when the wind and photovoltaic outputs are in excess. Therefore, this surplus energy is used for hydrogen production and the configuration of the hydrogen production system is optimized using a particle swarm algorithm to minimize the cost per unit of hydrogen production. After particle swarm optimization, it was determined that the unit cost of hydrogen production was minimized to 3.54 CNY/Nm3 for the configuration of 55 electrolysis tanks of 4 MW and 219 lead-acid tanks of 1 MW/2 MWh. Meanwhile, the electrolysis tank simulation model and the lead-acid battery simulation model were used to obtain maps of their operating conditions, hydrogen production and hydrogen storage tank pressure. In view of the addition of an energy storage system to the wind and photovoltaic generation system, this paper comprehensively considers the two energy storage modes of pumped storage and hydrogen production, and proposes a corresponding capacity optimization configuration scheme, which has reference value for improving the consumption and stability of wind and photovoltaics and realizing the sustainable utilization of clean energy. 

Modelling and capacity allocation optimization of a combined pumped storage/wind/photovoltaic/hydrogen production system based on the consumption of surplus wind and photovoltaics and reduction of hydrogen production cost

The photovoltaic (PV) water electrolysis method currently stands as the most promising approach for green hydrogen production. The rapid iteration of photovoltaic technologies has significantly affected on the technical and economic evaluation for photovoltaic hydrogen production. In this work, the photovoltaic hydrogen production of three most advanced silicon photovoltaic technologies is systematically compared for the first time under the climatic conditions of the Kucha region. All-weather stable hydrogen production control system with optimal charging and discharging strategies is constructed to realize stable and efficient hydrogen energy production. Seven machine learning (ML) algorithms are used to forecast the performance in power generation and hydrogen production of a 100 ​MW photovoltaic hydrogen production and energy storage (PH-S) system throughout its operational life. The long short-term memory (LSTM) algorithm exhibits the best performance, achieving mean absolute error (MAE) of 0.0415, root mean square error (RMSE) of 0.0891, and coefficient of determination (R2) of 0.8402. In terms of cost-effectiveness, heterojunction with intrinsic thin layer (HJT) PV technology achieves the lowest levelized cost of electricity (LCOE) and hydrogen (LCOH) at 0.025 $/kWh and 6.95 $/kg, respectively. According to the sensitivity analysis, when the cost of proton exchange membrane electrolysis (PEMEC) reduced 50%, the LCOH for PH-S system decreased 21.40%. This study provides valuable insights for the practical implementation of large-scale photovoltaic hydrogen production and cost reduction in PH-S systems. 

Machine learning assisted prediction for hydrogen production of advanced photovoltaic technologies

High Efficiency Bi2S3/Bi2MoO6/TiO2 Photoanode for Photoelectrochemical Hydrogen Generation

Under the background of “peak carbon dioxide emissions by 2030 and carbon neutrality by 2060 strategies” and grid-connected large-scale renewables, the grid usually adopts a method of optimal scheduling to improve its ability to cope with the stochastic and volatile nature of renewable energy and to increase economic efficiency. This article proposes a short-term optimal scheduling model for wind–solar storage combined-power generation systems in high-penetration renewable energy areas. After the comprehensive consideration of battery life, energy storage units, and load characteristics, a hybrid energy storage operation strategy was developed. The model uses the remaining energy in the system after deducting wind PV and energy storage output as the “generalized load”. An improved particle swarm optimization (PSO) is used to solve the scheduling schemes of different running strategies under different objectives. The optimization strategy optimizes the battery life-loss coefficient from 0.073% to 0.055% under the target of minimizing the mean squared deviation of “generalized load”, which was optimized from 0.088% to 0.053% under the minimized fluctuation of combined system output and optimized from 0.092% to 0.081% under the minimized generation costs of the combined system. The results show that the model can ensure a stable operation of the combined system, and the operation strategy proposed in this article effectively reduces battery life loss while reducing the total power generation cost of the system. Finally, the superiority of the improved PSO algorithm was verified.

/pdf/optimal-scheduling-of-the-wind-photovoltaic-energy-storage-3cnc9zwp.pdf

Optimal Scheduling of the Wind-Photovoltaic-Energy Storage Multi-Energy Complementary System Considering Battery Service Life

Hydrogen production using solar energy is an important way to obtain hydrogen energy. However, the inherent intermittent and random characteristics of solar energy reduce the efficiency of hydrogen production. Therefore, it is necessary to add an energy storage system to the photovoltaic power hydrogen production system. This paper establishes a model of a photovoltaic power generation hydrogen system and optimizes the capacity configuration. Firstly, the mathematical model is modeled and analyzed, and the system is modeled using Matlab/Simulink; secondly, the principle of optimal configuration of energy storage capacity is analyzed to determine the optimization strategy, we propose the storage capacity configuration algorithm based on the low-pass filtering principle, and optimal time constant selection; finally, a case study is conducted, whose photovoltaic installed capacity of 30 MW, verifying the effectiveness of the proposed algorithm, analyzing the relationship between energy storage capacity and smoothing effect. The results show that as the cut-off frequency decreases, the energy storage capacity increases and the smoothing effect is more obvious. The proposed algorithm can effectively reduce the 1 h maximum power variation of PV power generation. In which the maximum power variation of PV generation 1 h before smoothing is 4.31 MW. We set four different sets of time constants, the maximum power variation of PV generation 1 h after smoothing is reduced to 0.751, 0.389, 0.078, and 0.04 MW, respectively.

/pdf/modeling-of-hydrogen-production-system-for-photovoltaic-2klvgi6k.pdf

Modeling of hydrogen production system for photovoltaic power generation and capacity optimization of energy storage system

In the present study, buckling and vibrational analysis of a double-curved piezoelectric panel structure under low-velocity impact force is presented. In this regard, the first-order deformation theory of shell structures is utilized to approximate the displacement of the shell, and the linear strain-displacement relations are presented in a constitutive equation in small deformation elastic region. Finally, the principle of virtual work is exploited to obtain equations of motion under electrical and mechanical loads. The complexity of the equations of double-curved shell structure under electrical and impact loads necessitates using semi-analytical methods in obtaining the effects of different factors on the frequency, contact force, and indentation of the impactor. The results are presented in a detailed parametric study. Effects of moduli of elasticity of both panel and impactor on the contact force and indenter velocity are investigated. As a desirable result, it is determined that in a certain range of applied external voltage, the vibration of the panel is suppressed completely. 

Low-velocity impact, buckling, and vibrations of the piezoelectric doubly curved system via coupled Galerkin and Newmark method

Wind and photovoltaic (PV) power generation and other distributed energy sources are developing rapidly. But due to the influence of the environment and climate, the output is very unstable, which affects the power quality and power system stability. Pumped hydroelectric energy storage (PHES) systems are suitable as peaking power sources for wind and photovoltaic (Wind–PV) complementary systems because of their fast start–stop and long life. The mathematical models and operational characteristics of the three subsystems in the wind–PV–PHES complementary system are analyzed to improve the generation efficiency and access capacity of wind and PV power. The peaking characteristics of the PHES system are used to balance the maximum benefit and minimum output fluctuation of the wind–PV complementary system. The stable operation of the pump turbine is an important guarantee for the smooth output of the wind–PV complementary system. Three operating points are selected from the net load curve and converted to the pump turbine model parameters. The internal flow characteristics and laws of the pump turbine under different guide vane opening conditions are summarized through the analysis of the computational fluid dynamics (CFD) numerical simulation post-processing results. The study shows that the output of wind and PV power generation varies with the changes in wind speed and solar radiation, respectively. The output of the wind–PV complementary system still has large fluctuations, and the PHES system can effectively suppress the power fluctuation of the wind–PV complementary system and reduce the abandoned wind and light rate. CFD technology can accurately and efficiently characterize the internal flow characteristics of the pump turbine, which provides a basis for the design, optimization, and transformation of the pump turbine.

/pdf/research-on-the-internal-flow-characteristics-of-pump-16c2f7sa.pdf

Research on the Internal Flow Characteristics of Pump Turbines for Smoothing the Output Fluctuation of the Wind–Photovoltaic Complementary System

Fault diagnosis is an effective tool to ensure safe operation of machinery and avoid serious accidents. As most currently used fault diagnosis methods usually employ mapping relationship established by training samples and their labels to achieve classification of testing samples, it is difficult for them to achieve fault diagnosis under the condition of incomplete training sample types. In addition, previous studies usually focus on feature extraction of single-channel vibration signal, which cannot get complete fault feature information. To solve the above problems, a progressive fault diagnosis method is investigated in this paper. First, the preliminary fault detection for the rotor is performed by studying reconstruction error of a sparse auto-encoder. Second, if a fault exists in the rotor, the outlier detection is implemented by the support vector data description method. Finally, if there are no outlier samples, the well -trained support vector machine is used to confirm the type of fault samples and complete the diagnosis. The performance of the proposed method was verified using the data obtained from a rotor laboratory bench. The types of rotor states investigated include normal, contact-rubbing, unbalance and misalignment. The experimental results verify the effectiveness and superiority of the proposed method in reducing the incidents of fault omission and fault misunderstanding.

Fault diagnosis for rotor based on multi-sensor information and progressive strategies

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Papers

Modeling of hydrogen production system for photovoltaic power generation and capacity optimization of energy storage system

Low-velocity impact, buckling, and vibrations of the piezoelectric doubly curved system via coupled Galerkin and Newmark method

Research on the Internal Flow Characteristics of Pump Turbines for Smoothing the Output Fluctuation of the Wind–Photovoltaic Complementary System

Fault diagnosis for rotor based on multi-sensor information and progressive strategies