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Review on State Estimation and Remaining Useful Life Prediction Methods for Lithium-ion Battery AI Introduction
Abstract：Accurate estimation of state of charge (SOC), battery state of health (SOH) and prediction of battery remaining useful life (RUL) of lithium-ion battery are important contents of battery management. It is of great significance to prolong battery life and ensure the reliability of battery system. Researchers all over the world have done a lot of research on battery state evaluation and RUL prediction methods, and proposed a variety of methods. This paper first introduced the definition of SOC and SOH and the existing estimation methods and compared them. Then, the definition of RUL was introduced and the main methods were classified and compared. Finally, the challenges of lithium-ion battery state estimation and RUL prediction were summarized, and the future development direction was proposed.Keywords：lithium-ion battery;state of charge (SOC) estimation;state of health (SOH) estimation;remaining useful life (RUL) prediction150|294|13<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06Analytical Method for Power Grid Dispatching Centralized Thermal Storage to Reduce Wind Abandoned Rate AI Introduction
Abstract：In order to achieve clean heating and reduce the rate of abandoned wind, the northern region has invested in various heat storage devices, especially the large-capacity heat storage devices invested by thermal power plants to improve adjustment flexibility. The power consumption calculation method of large-capacity heat storage device invested by thermal power plants and the calculation method of abandoned wind power in power grid were proposed. Moreover, the relationship between the input timing of the heat storage device and the timing of abandoning wind was researched, and the delay of deep peak shaving of the unit after the input of the heat storage device was discussed. The actual data show that the input timing of the heat storage device and the timing of abandoning wind have a demonstration effect on the consumption of wind power through thermal storage in the northern region.Keywords：thermal storage;abandoned wind power;deep peak shaving;time series39|48|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06
Energy Storage
Research on Two-stage Optimization Approach of Community Integrated Energy System Considering Load Supply Reliability AI Introduction
Abstract：The community integrated energy system (CIES) can significantly improve energy utilization and promote the consumption of renewable energy through multi-energy coupling complementary and collaborative optimization scheduling. It has become a new energy utilization realization approach for users to meet multi-energy supply and demand. Taking a community in Xiong’an New District, Hebei province as the research object, this paper designed a two-stage optimization approach for the CIES that takes into account the reliability of load supply. The first stage is based on the non-dominated sorting genetic algorithm II(NSGA-II) with elite preservation strategy to optimize the equipment type and capacity of the community energy station. It is a multi-objective planning optimization problem, and its purpose is to achieve the coordinated optimization of economic costs and environmental costs. The second stage is an operation optimization problem. As for the multiple Pareto frontier solutions obtained in the previous planning stage, the mixed integer linear programming (MILP) was used to separately optimize the operation cost and load supply reliability indicators of each planning scheme, and the result is used as an important reference for determining the best planning scheme. Case studies show that the designed planning approach can effectively reduce the system operating cost and guarantee the reliability of load supply, and it is more practical for instructing the CIES planning.Keywords：community integrated energy system;planning optimization;load supply reliability;non-dominated sorting genetic algorithm II (NSGA-II);mixed integer linear programming95|83|21<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06- Abstract：This paper reviewed the current development research of China’s offshore wind power industry in the field of integrated design of wind turbine, tower and foundation. This paper explored the feasibility of integrated design from the aspects of load reduction optimization technology, structural optimization technology and engineering exploration and application, and discussed the key technologies and implementation methods of integrated design that can be adopted under the optimization goal of lightweight offshore wind turbine support structure. The research shows that China’s offshore wind power industry needs to be gradually implemented from three levels: providing the prerequisites for integrated design, using the technologies that can be adopted at the current stage,and exploring the next research directions. In the context of offshore wind power moving towards grid parity, owner-engineers and third-party certification bodies need to play a greater role in promoting the integrated design method.Keywords：offshore wind power;integrated design;global design optimization;structure lightweight design98|687|3<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06
Two-Way Fluid-Structure Interaction Numerical Simulation Method for Offshore Wind Power Based on Immersed Boundary Method AI Introduction
Abstract：In order to study the flow field characteristics and dynamic fluid-structure interaction response of offshore wind turbine during operation process, the concept of integrated analysis of offshore wind power project was introduced and the simulation method for the integrated fluid-structure interaction operation process of offshore wind power was established based on the immersed boundary method. The stator-rotor interaction caused by the rotation of the fan was simulated by the immersed boundary method. With the alternating iteration method, a two-way fluid-structure interaction numerical method for the integrated research of offshore wind turbines “fan-tower-foundation” was presented. With the proposed method, the fluid-solid interaction effect of offshore wind turbine can be truly reflected and its dynamic response can be accurately solved. The immersed boundary method can effectively solve the stator-rotor interaction caused by fan rotation without updating the grid motion. Finally, the integrated fluid-structure interaction operation process of an offshore wind power project was simulated.Keywords：offshore wind power;two-way fluid-structure interaction;immersed boundary method;numerical simulation81|192|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06Performance Analysis of Photovoltaic/Thermal Hybrid System Integrated With Phase Change Heat Storage Materials AI Introduction
Abstract：Incorporating phase change material (PCM) with photovoltaic/thermal (PV/T) modules can improve the power generation efficiency of photovoltaic panels by increasing the cooling capacity, and the stored heat can also be used rationally. Based on the design of two PV/T modules integrated with phase change heat storage materials, the performances were analyzed numerically and compared with the traditional PV/T panel. The overall performance of integrated system was analyzed from the energy and exergy aspect. The influence of cooling fluid flow was also examined. The results show that the integration of PCM with PV/T module can significantly improve the overall performance of the system. The PV/T system with two phase change heat storage materials have the highest daily total energy efficiency and overall exergic efficiency, reaching 67.65% and 12.86%, respectively. Moreover, the maximum energy per day could reach 3603.2 W·h/m2. With the increase of the volume rate of cooling fluid, the overall energy efficiency increases slightly, but the overall exergic efficiency decreases significantly.Keywords：phase change heat storage;photovoltaics/thermal (PV/T);exergy efficiency;solar energy93|261|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06Research of Key Technologies for n-i-p Perovskite Solar Cells With SnO2 Electron Transport Layer AI Introduction
Abstract：Perovskite solar cells (PSCs) have attracted extensive attentions due to their high-efficiency, simple preparation process and low-cost. The efficiency of the PSCs has increased from 3.8% to 25.7%. So far, more and more studies focus on n-i-p structured PSCs using SnO2 as electron transport layer. However, its process reproducibility is relatively poor, and efficiency is still low. This report conducted a systematic study of planar n-i-p PSCs, mainly including the selection of transparent conductive oxide (TCO) glass, optimization of preparation parameters and the influence of storage conditions on device performance. Experimental results show that these parameters have an important impact on the device performance. At the same time, it was analyzed by scanning electron microscope, X-ray diffraction, absorption spectrum. The devices achieved an average efficiency of 21.85% and a highest efficiency of 23.47% with good reproducibility under the optimal conditions (Indium Tin oxide substrate, PbI2 annealed at 70 ℃ for 1 min, standing time after dropping amine salt solution is less than 5 s, and stored in 4.5% humidity environment). This work provides scientific support for the preparation of high-efficiency and repeatable PSCs.Keywords：perovskite solar cells (PSCs);n-i-p;SnO2;high-efficiency;reproducibility80|40|1<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06
New Energy
Research and Application of Numerical Simulation for Selective Catalytic Reduction Denitration of 9F Gas Turbine AI Introduction
Abstract：Taking a 9F gas turbine waste heat boiler as the research object, the numerical simulation of gas flow field from gas turbine outlet flue to catalyst layer was carried out, the flue gas flow field of single layer catalyst, two-layer catalyst and two-layer catalyst+uniform plate was obtained. The results show that the expansion flue in front of the first-layer heat exchanger of the original structure has a short distance and a large expansion angle. When the high-speed swirling flue gas at the outlet of the gas turbine enters the large-area static basin within a short distance, it is too late to evenly scour the entire large cross-section and dissipate the inertial swirling flow, resulting in the poor uniformity of flue gas flow field at the inlet section of the first layer of heat exchanger. The flow field distribution after adding one layer of catalyst is basically the same as that of single layer catalyst, and the uniformity of flow field distribution at the inlet of the first layer catalyst is slightly better than that of single layer catalyst when adding two layers of catalyst. This is because adding one layer of catalyst is equivalent to adding one layer of flow blocking element, which has a blocking effect on the flue gas. The flow field uniformity at the inlet of the first layer heat exchanger can be improved by adding a deflector in the inlet flue, and the cross-sectional velocity Cv decreases to 21.3%, which indicates that the deflector can improve the flow field distribution in the subsequent flue.Keywords：9F gas turbine;selective catalytic reduction(SCR);flow field;numerical simulation;catalyst44|203|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06Energy Saving Optimization of Extraction Steam Distribution for Cogeneration Units Under Carbon Neutral Background AI Introduction
Abstract：In order to study the change rule of coal consumption of cogeneration units under different heating load distributions in the whole working condition, and realize the goal of deep energy saving and carbon emission reduction in power plants, two 630 MW cogeneration units were taken as the research objects. The EBSILON software was used for modeling, and the different heating load distribution schemes of single and double units were studied and analyzed based on the Freuger formula and the principle of caloric method. It is found that there is a critical heating extraction steam flow point in the influence of thermoelectric load change on coal consumption of a single unit. When the heating flow is less than the critical point, the greater the electric load, the higher the thermal efficiency of the units. When the heating flow is greater than the critical point, the smaller the electrical load, the higher the thermal efficiency of the units. For two operating units, when the heating load is distributed centrally to one unit, the coal consumption of the whole plant under different working conditions is the least, and the energy saving effect is better. It is of great significance to find the best way of heat supply distribution to reduce the coal consumption of power plants, save energy and reduce emission and respond to the national “carbon neutral” policy.Keywords：carbon neutral;cogeneration units;extraction steam optimization;thermodynamic modeling;energy conservation and emission reduction;thermodynamic analysis61|142|3<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06Study on WESP Multi-pollutant Emission Reduction and Energy Efficiency Test of Ultra-low Emission Unit AI Introduction
Abstract：Wet electrostatic precipitator (WESP) is a fine treatment equipment for the treatment of coal flue gas. Taking a 660 MW ultra-low emission unit as the research object, the multi-pollutant removal performance and energy efficiency parameters of WESP were tested and analyzed systematically. The removal efficiencies of particulate matter, fog drop, SO3 and Hg of WESP were 81.12%, 75.60%, 76.13% and 53.08%, respectively, and the power consumption was 402.6 (kW·h)/h, which met the design requirements. The emission mass concentration of each pollutant were 4.20, 17.25, 9.80, 4.08×10-4 mg/m3, respectively, the emission factors were 13.76, 56.49, 32.10, 1.34×10-3 g/(kW·h),respectively, the specific power consumption was 1.48×10-4 (kW·h)/m3.The energy consumption for particle removal per unit mass was 22.87 (kW·h)/kg, which was in the industry average level. This study can provide reference for the subsequent pollutant reduction and energy efficiency control of coal-fired power plants.Keywords：wet electrostatic precipitator (WESP);coal-fired power plant;pollutant emission reduction;removal efficiency;indicators of energy efficiency34|107|1<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06Research on Performance Prediction of Coal-fired Power Plant Denitrification Device Based on Online Monitoring Data AI Introduction
Abstract：The precise control of pollutant removal in thermal power plants has always received wide attention. By applying big data analysis technology to the denitration system of a 600 MW generator set, the in-depth mining research on environmental protection online monitoring data under complex conditions was carried out, and the impact of pollution can be obtained efficiently and accurately. By analyzing the key factors of the performance of waste removal equipment, combined with the principle of pollutant removal, the input and output elements of the environmental pollution index predict ion model was determined, the resource consumption indicators in the denitration system were characterized, and the big data of the unit environmental pollution index forecast model was built. The results show that after rationally cleaning the associated parameters in the process, the results of the key factor analysis are consistent with the results of the qualitative analysis of the removal mechanism of environmental pollutants. The trained model can not only reproduce the current environmental performance with high precision, but also has the ability to predict environmental performance. The specific analysis of the selective catalytic reduction (SCR) system can provide a certain theoretical basis and data support for the implementation of further precise control of other environmental protection equipment in thermal power plants.Keywords：thermal power plant;big data;ultra-low emission;denitration system56|141|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06Study on Parameter Optimization of Desulfurized Wet Flue Gas in Spray Condensation Process AI Introduction
Abstract：The wide application of wet desulfurization technology makes the desulfurization efficiency reach more than 90%, but the high moisture content of flue gas after desulfurization increases the possibility of smog formation. The spray tower was the main body of research, and the three-dimensional steady-state numerical simulation of gas-liquid two-phase flow field in the tower was carried out based on Fluent software. The results show that the spray droplet diameter plays a key role in flue gas condensation and dehumidification. The smaller the droplet diameter, the larger the gas-liquid two-phase contact area, the more obvious the heat transfer effect. If the droplet diameter is less than 700 μm, the flue gas temperature drop above 6 K can be achieved. When the inlet flue gas temperature is in the range of 319-335 K, the ratio of condensed water caused by this temperature is basically unchanged. The spray droplet velocity has an integration effect on the flue gas flow field. Choosing the appropriate droplet velocity can reduce the flue gas reflux area, and improve the space utilization rate in the tower. When the droplet velocity increases to 40 m/s, the temperature drop of outlet flue gas can increase by about 1.9 K.Keywords：wet flue gas desulfurization;spray tower;gas-liquid two-phase flow;dehumidification;three-dimensional steady state numerical simulation33|259|4<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06
Power Generation and Environmental Protection
Study on Participation of Electricity-driven Thermal Load in Real-time Scheduling of New Power System AI Introduction
Abstract：The power balance of the new power system mainly based on new energy is facing an important technical challenge, and the participation of flexible load in power system regulation is an important way to enhance the active balance capability of the new power system. In view of the obvious seasonal and temporal characteristics of the electric and thermal loads, the new energy sources are “extremely cold and hot without wind” and “late peak without light”, and the thermoelectric loads in the new power system show the trend of anti-peak regulation. To address this problem, this paper analyzed the spatial and temporal characteristics and energy-use characteristics of electric and thermal loads, explored their regulation potential, focused on the control scenarios of electric and thermal controllable loads, and systematically gave a flexible scheduling strategy for electric and thermal loads to complete the flexible control and regulation of electric and thermal loads. The results realize the network-load cooperative optimization and flexible scheduling on the whole time scale, and thus verify the feasibility of the real-time participation of telectric and thermal loads in the scheduling of the grid.Keywords：new energy;new power system;source network load storage;electric and thermal loads;adjustable load resources;flexible control56|110|15<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06Power Grid Topology Identification Based on Immune Algorithm AI Introduction
Abstract：Power grid topology identification for large power grid trajectories is of great significance for information-driven large power grid operation situation awareness and intelligent control. Firstly, based on the principle of power balance and power flow constraints, the identification of power grid topology was reduced to the problem of seeking the global optimal combination of box and ball. The idea of power grid topology identification was given from a new perspective, which simplified the complex process of traditional power grid topology identification. Secondly, according to the power flow balance characteristics of bus nodes, a mathematical model of power grid topology identification was established, which improved the efficiency of power grid topology identification from the perspective of global optimization. At the same time, the voltage loss was introduced to overcome the non-uniqueness problem of power grid topology identification. Thirdly, the immune intelligent algorithm was used to solve the model. The algorithm effectively maintained the diversity of antibodies and avoided the premature convergence problem. Finally, the proposed method was tested on IEEE 39 and IEEE118 bus systems to verify the effectiveness.Keywords：new power system;power grid;topology identification;immune algorithm;information-driven44|81|6<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06Power Quality Disturbance Classification Method Based on Particle Swarm Optimization and Convolutional Neural Network AI Introduction
Abstract：Aiming at the problems of difficult manual selection of features, cumbersome classification steps and low accuracy in traditional power quality disturbance classification methods, a disturbance classification method based on particle swarm optimization (PSO) and convolutional neural network (CNN) was proposed. Firstly, the one-dimensional time series of power quality disturbance signals were converted into two-dimensional matrices with equal rows and columns by using the reshaping function, and these two-dimensional matrices were properly divided into training data set and test data set. Secondly, the classification model of power quality disturbance was built based on CNN. Thirdly, the PSO algorithm was used to optimize the parameters of the classification model, and the trained data set was used to train the optimized power quality disturbance classification model. Finally, the trained power quality disturbance classification model was tested by using the test data set, and the class results of various power quality disturbances were obtained according to the output labels. Simulation results show that the classification model can extract the characteristics of power quality disturbance data by itself. Compared with other power quality disturbance classification models, this method has higher classification accuracy for power quality disturbance signals.Keywords：new energy;power quality;disturbance classification;feature extraction;particle swarm optimization (PSO);deep learning;convolution neural network (CNN)41|106|17<HTML><L-PDF> <WORD> <Meta-XML>Updated：2025-06-06
Smart Grid
