The photovoltaic array will produce multi-peak P-U characteristics under partial shading conditions. Aiming at the problem of how to quickly and accurately realize maximum power point tracking (MPPT) to avoid a large amount of energy loss, this paper proposes an improved aquila optimization (AO) algorithm, which uses Circle chaotic mapping and reverse learning strategy to reasonably allocate the initial population position, so as to shorten the optimization time of the algorithm. At the same time, spiral optimization is carried out for the short gliding attack in aquila optimization algorithm. The whale optimization algorithm is combined to improve local optimal stagnation and convergence speed. Simulations and experiments demonstrate that, in comparison to particle swarm optimization (PSO), whale optimization algorithm (WAO) and aquila optimization algorithm, the algorithm can search the global maximum power point with greater speed, accuracy and suppleness under both static and dynamic partial shading conditions.

For the purpose of absorbing renewable energy, the coal-fired power units are required to operate flexibly, and the resulting variable operating environment will lead to large nonlinearity and uncertainties of the wet desulphurization process. Particularly, the time delay will make the control even harder. Therefore, in order to achieve a more flexible control structure, a new desulphurization control strategy based on frequency retrofit is proposed. Based on the strategy, a dynamic model is obtained through field experiments. Meanwhile, in order to deal with uncertainty well and achieve safe compensation of uncertainty in the control process, an updated Gaussian process model predictive control method for time-delayed objects is proposed, and the performance of the method is demonstrated by parameter analysis and simulation experiments. Finally, the effectiveness of the proposed control strategy and control method is verified by field application.

The dynamic characteristics of the bottoming cycle of a gas turbine combined cycle have a significant influence on the load variation characteristics of the unit. Partially recuperation is a new method which can be used to improve the performance of combined cycle at partial load, it is an important part of system feasibility evaluation to study the effect of partially recuperation on the dynamic characteristics of the bottoming cycle. In this paper, a dynamic simulation model of the bottoming cycle system of a partially recuperative combined cycle unit is established by using modular modeling method, and the dynamic characteristics of inlet parameter disturbance and load shedding process are studied. The results show that, the dynamic model can accurately reflect the dynamic characteristics of the bottoming cycle, and the simulation results show that the dynamic response of partially recuperative units facing the disturbance of exhaust parameters is consistent with that of conventional units. The disturbance of exhaust temperature T₄ mainly affects the high-pressure superheated steam and reheated steam, and the influence range is larger. The disturbance of T₄ with 5% can reduce the bottoming cycle power by 16.32%. The response speed of the unit is slower, and the time constant of the steam turbine power is about 400. The disturbance of exhaust flow affects the steam of each stage, and the influence range is relatively small, the disturbance of 10% reduces the bottoming cycle power by 9.49%, the response speed of the unit is faster, the time constant of the steam turbine power is about 60. When the recuperative ratio is disturbed, the dynamic response of the unit is similar to that of the T₄ disturbance, and the operation strategy of recuperative regulation results in the load variation of the combined cycle being borne entirely by the bottoming cycle, the time needed for partially recuperative units to reach steady state is 1 100 s later than that of conventional units, and the recuperative regulation mode is suitable for use in the load interval below 51.4%.

In response to the instability problem of distributed new energy as an independent power source supplying energy to household energy systems, a capacity configuration method for distributed home energy systems based on hydrogen energy is proposed. This method is based on the characteristics of hydrogen energy that can suppress wind and solar fluctuations and flexibly convert load demands, and constructs a hydrogen coupled distributed energy family terminal energy system structure. Combining with the characteristics of renewable resources in the region, a hydrogen based distributed household energy system capacity allocation model is established with the goal of minimizing the net total cost. Taking the wind and solar resources and typical household energy data in Xinjiang region as an example, the impact of the configuration capacity of distributed energy and hydrogen energy systems on the system is simulated and analyzed, and the optimal capacity configuration of hydrogen energy systems under the optimal wind and solar ratio conditions is obtained. From the simulation results, it can be seen that the proposed model can effectively reduce the total cost of the household energy system while achieving reliable energy supply off the grid, and promote the consumption of new energy, which provides suggestions for the design of distributed household energy based on hydrogen energy.

As the global climate continues to warm, capturing carbon dioxide in the air has become one of the most effective measures to reduce greenhouse gas pollution. Carbon dioxide storage systems not only store carbon dioxide in the air, but also consume excess electricity to fill the shortage of electricity supply during peak periods. As the core equipment of CO₂ storage system, the performance of the compressor directly affects the overall performance of the system. This paper summarizes the application scope and performance characteristics of seven different forms of carbon dioxide compressors and the current status of research at home and abroad. The potential problems that may exist in the application of piston, centrifugal and axial flow compressors in CO₂ energy storage systems are discussed, and corresponding suggestions and improvement ideas are given. The results of the study can provide a reference for the design and optimization of CO₂ compressors in the future.

To solve the problem of excessive air leakage from the four-compartment air preheater, a four-compartment rotary air preheater of a 1 000 MW power plant is used as the study object to investigate the thermal characteristics, rotor thermal deformation and air leakage of the air preheater, by combining theoretical analysis with numerical simulation. The numerical simulation results show that, for every 1% increase in air leakage rate of the 1 000 MW unit, the heat transfer efficiency of air preheater will be reduced by 1.13%, and the power plant will consume 3 604 tons of standard coal more on average per year. There are large temperature gradients in the axial and circumferential directions inside the air preheater, and most of the corrosion and deposition areas are distributed in the low temperature section. There are large differences in rotor thermal deformation during different operating conditions of the air preheater, and the maximum thermal deformation occurs on the secondary air side. It is necessary to make corresponding adjustments according to the thermal deformation characteristics of different positions of the rotor when setting the sealing system.

Creep rupture is one of the most common failure modes of pipelines used in thermal power plants. Residual life prediction is an effective guarantee to ensure the safety, utilization and benefit maximization of equipment. Based on the creep rupture test data of 2.25Cr-lMo heat-resistant steel in actual service for over 200 000 hours, the selection principle of TTP parameters and its influence on the accuracy of life prediction are analyzed by comprehensively considering the working stress and TTP parameters. The relationship curve family of Z-parameter method is used to characterize the vertical dispersion of pipeline durability data in different power plants. The stress-TTP-reliability curve for evaluating the reliability of life prediction is established, and the relationship between the predicted life of different power plant pipelines and the working state of the unit is obtained. The creep residual life of different power plant samples at 540 ℃/45.26 MPa is 1.725 6×10⁵ h and 3.378 8×10⁵ h respectively, and the predicted reliability reaches 99%, which provide maintenance suggestions for the operation reliability of power plant equipment.

A Python model was established for thermal performance of the heavy-duty gas-steam combined cycle triple-pressure heat recovery steam generator. The model calculates the detailed heat recovery steam generator parameters under the condition of changing unit load, including main steam pressure and flow rate, heat and heat transfer coefficient of each heat exchanger, as well as power output and efficiency. As the effect of exhaust gas temperature and flow rate on the heat recovery steam generator is analyzed, how the ambient temperature, humidity and fuel heating affect the heat recovery steam generator output is also discussed when the unit is in part-load. It is verified that the model has good simulation accuracy and calculation efficiency. Simulations for one certain frame gas turbine combined cycle show that: When the unit load is reduced from full load 650 MW to partial load 250 MW, the triple main steam pressure and feed water flow rate of heat recovery steam generator decrease, the steam turbine power output decreases from 219.1 MW to 130.4 MW, and the efficiency of heat recovery steam generator increases from 89.3% to 92.1%; main-steam flow increases as the flue gas flow rate and temperature increase at the inlet of heat recovery steam generator; As the load of the random group decreases, the heat transfer coefficient and heat transfer amount of each heat exchange surface of the waste heat boiler decreases, but the proportion of heat exchanger between the flue gas and the high-temperature section heat exchanger in the total heat increases, and the heat transfer between the flue gas and the low-temperature section increases. The proportion of heat exchanger heat transfer in the total heat is reduced; when the unit load is reduced from 650 MW to 300 MW, the proportion of steam turbine shaft power increases by 1.67 percentage points, the proportion of heat loss in the chimney flue gas decreases by 2.63 percentage points.

The long-term vibration of ZGM133G-I type medium speed coal pulverizers in a power plant causes weld fatigue fracture of the powder delivery pipeline, which results in coal powder leakage, polluting the environment and seriously affecting the operation of the unit. Based on the mechanical vibration analysis and field test of medium-speed coal pulverizers, this paper studies the influence of operating parameters such as loading force, speed of separator and output of coal pulverizers on the vibration of coal pulverizers. The results show that, the vibration of medium-speed coal pulverizers is mainly caused by the mechanical equipment itself and the setting of operating parameters. The size and separator type of coal pulverizers are not the inevitable factors that cause the vibration of coal pulverizers, but the wear and damage of mechanical structure will cause the vibration of coal pulverizers. In order to reduce the vibration of medium-speed coal pulverizers, it is necessary to comprehensively consider the output of coal pulverizers and the fineness of coal powder according to the test results, and reasonably control the loading force, separator speed and output.

The fault early warning of the coal mill is of great significance to the safe operation of thermal power unit, but the operation of the coal mill has many interference noises and a high degree of coupling, which makes the fault early warning more difficult. Based on this, this paper proposes a fault warning method based on wavelet packet transform (WPT) and Transformer. Firstly, the signal is denoised by the wavelet packet analysis method with adaptive threshold value. Then, the characteristic parameters related to the fault measurement point are selected as input to establish a Transformer coal pulverized prediction model based on the self-attention mechanism. Finally, the kernel density estimation method is used to analyze the prediction deviation and determine the warning threshold. Taking a 660 MW medium-speed coal mill as the research object and using actual data for verification, the experimental results show that the prediction accuracy of the proposed method is higher than that of CNN, LSTM, and CNN+LSTM models, and it can provide early warning of coal mill failures.