In order to explore the potential of fruit peel waste conversion to produce highvalue platform chemicals, the hydrothermal conversion of citrus peel to furfural (FF) and 5hydroxymethylfurfural (5HMF) was conducted in the choline chloride (ChCl)/ carboxylic acid based deep eutectic solvents (DES) system. Conclusions can be drawn from experiments in xylose and glucose: The carboxylic acid performance was ranked lactic acid > acetic acid > glycolic acid. The optimal molar ratio of choline chloride to carboxylic was 1:2. The optimal water content of solvent system was 20%. The effects of temperature and time on citrus peel conversion were studied based on the optimized operating conditions. Since the pectin component in the citrus peel was mainly converted to 5HMF in DES, the yield of the peel converted to 5HMF was significantly higher than that of FF. The maximum mass yield of 5HMF from citrus peel was 8.6% (molar yield was 43.1%). The maximum mass yield of furfural reached 2.4% (molar yield was 19.1%).

It is a promising technology to store CO2 by hydrate formation in seafloor sediments. In this paper, the evolution process of CO2 hydrate formation promoted by amino acids in natural sand system was studied by hydrate formation test in a visible reactor. The experimental results showed that the formation rate and amount of CO2 hydrates in 8 mmol/L Lmethionine solution were significantly higher than those in deionized water system; The natural sand with medium particle size had the best promotion effect on the formation of CO2 hydrate, and a large amount of CO2 hydrates were generated in it, which effectively filled the gap between natural sands; Secondly, a lot of CO2 hydrates were also generated in small size natural sand; The effect of large particle size natural sand on promoting the formation of CO2 hydrate was not obvious, and no obvious CO2 hydrate formation was found inside, only a small amount of CO2 hydrates was observed on the inner wall of the reactor.

This paper studied the simulation of methanol synthesis from CO2 and green hydrogen, and proposed an indicator of the energy storage density of CO2. Then influences of multiple variables on the performance indicators were analyzed. The results show that the systematic energy efficiency and energetic yield of methanol increase with the increase in the electrolysis efficiency, per pass CO2 conversion rate, electrolysis pressure, and initial CO2 pressure. However, these indicators decrease with the increase in the methanol synthesis pressure. The variations of the energy storage density of CO2 with these variables are opposite to the systematic energy efficiency and energetic yield. The electrolysis efficiency and per pass CO2 conversion rate are the sensitive and key variables of this process. Under the optimal conditions, the systematic energy efficiencies based on the higher and lower heating values are 68.0% and 59.6%, respectively, the energy storage density of CO2 is 6.07 kWh/kg, and the energetic yield of methanol is 0.108 kg/(kW·h), indicating the powertomethanol system using CO2 as feedstock is unsatisfactory in term of systematic energy efficiency, but has significant advantage in the energy storage density.

Aiming at the longterm operation of the mediumdeep coaxial borehole heating system which has issues of cold accumulation in rocksoil and decrease in the heat extraction capacity of the system, in this research, a numerical heat transfer model for MDGSHPs was established, the governing equations were discretized based on the finite difference method, and the accuracy of the model was verified with experimental data. This research separately studied the effects of heat storage temperature (Tin) and flow rate of hot water injection (G) on BHE heat extraction rate (Q), system energy consumption(W) and the coefficient of system performance (CSP) in the next heating period. The results show that the first step to realize heat storage is to determine the threshold value for the temperature of heat storage water. Below the threshold, heat storage will not be achieved, and the threshold temperature for this study is 50 °C. After operating for 500 hours, when the inlet water temperature increases from 50 °C to 80 °C, Q, W and CSP increase by 54.41 kW, 8.96 kW and 0.17. Furthermore, when the flow rate of hot water injection increases from 1 kg/s to 7 kg/s, the growth rate of Q, W and CSP are 7.71%, 6.34% and 1.19%. Therefore, a small flow rate with high temperature of heat storage water is recommended during the heat storage period which will improve heat storage effect and reduce energy consumption. This study provides a theoretical basis for heat storage in MDGSHPs.

In view of the problem that data center evaporative cooling technology limited by the ambient wet bulb temperature, a solar energy and heat pump complementary drive the desiccant wheel evaporative cooling air conditioning system in data center was proposed. The system uses the waste heat of photovoltaic modules to provide thermal energy complementary heat pump system to drive the dehumidification regeneration. According to the outdoor meteorological conditions, the system can realize three operation modes: fresh air, evaporative cooling and dehumidification & evaporative cooling. The TRNSYS software is used to simulate the thermal, power and energy consumption characteristics of the three typical regional data centers in Shanghai, Guangzhou and Kunming. The results show that in the typical daily dehumidification +evaporative cooling mode in Shanghai, Guangzhou and Kunming area, the desiccant wheel pretreatment reduced the air wet bulb temperature by 10.9 °C, 11.6 °C and 10.3 °C on average compared with the outdoor wet bulb temperature. The average typical monthly system COP values in Shanghai, Guangzhou and Kunming were 4.9, 5.1 and 3.6, respectively, and the maximum instantaneous COP value was 12.1, 11.4 and 8.1.

The abandoned mines contains abundant geothermal resources.This article takes the mine water of gob area as the research object; in order to ensure the stability of pumping temperature during the heating season, the layout and parameter sensitivity of pumpingrecharging wells of water source heat pump of abandoned mine are studied. Firstly, based on the Darcy's law and the theory of heat transfer in porous media, the twodimensional numerical calculation models of the coupled multiphysical fields of the pumpingrecharged well are established.Secondly, the pumping water's temperature variation of 14 arrangement forms of pumpingrecharging wells are analyzed while the theoretical models are employed. The most reasonable arrangement form can be selected according to the degree of the heat transfixion. Finally, when the selected pumping recharging wells'arrangement form is taken into consideration, the effects of different factors including the recharge temperature, the pumpingrecharging water's flow rate, the wells' spacing, the hydraulic slope, the aquifer thickness and the porosity on the pumping temperature are discussed. The results of the analysis show that the well placement method of triangle 4 only decreases the pumping temperature by 0.148 K at the end of the system operation, and the occurrence of "thermal penetration" is the least and the well placement method is the most reasonable. The occurrence of "heat transfixion" in the aquifer is more sensitive to parameters such as pumping flow rate, well spacing, hydraulic gradient, and aquifer thickness, while it is less sensitive to recharge temperature and porosity.

The downstream wind turbines suffered by the deflected wake are subjected to unbalanced aerodynamic loads and resulting in a significant increase in fatigue loads. Two NREL 5 MW wind turbines have been adopted to study the influence of the yaw control of upstream wind turbine on the aerodynamic characteristics of downstream wind turbine under staggered arrangement, based on open source software FAST.Farm. The results show that the downstream wind turbine is gradually in the core area of wind velocity deficit with the increase of yaw angle of the upstream wind turbine, the reduction of rotor power of the downstream wind turbine is significantly increased, and the rotor thrust suffered by the downstream wind turbine is gradually reduced. The yaw control of the upstream wind turbine will significantly affect the fluctuation characteristics of the aerodynamic load of the downstream wind turbine. When the yaw angle of the upstream wind turbine is 40°, the standard deviation of the flapwise moment at the blade root of the downstream wind turbine increases by 50.5% compared with the case that the upstream wind turbine is not yawed. This study can provide a reference for the whole wind farm control collaborative optimization and aerodynamic characteristics analysis under yaw inflow.

Aiming at the problem of lack of a large number of actual fault image training samples during the fault diagnosis and modeling of offshore wind turbine blades, an image recognition method for offshore wind turbine blade faults based on small data sets is proposed. In this method, the Kmeans clustering algorithm is improved to identify blade segmentation according to the color and shape characteristics of blades and their faults in wind turbine blade images, an adaptive algorithm is designed to adjust the Canny operator parameters to identify the segmentation of early fault areas on the blade surface, and the Kmeans clustering algorithm is used to extract the color and shape features of faults and design corresponding classifiers to achieve fault classification. Simulation examples show that this method is effective for the identification of early faults on the blade surface, and can provide an accurate diagnostic model for the blade fault identification of offshore wind turbines on the basis of a small number of fault samples, which can improve the operation and maintenance efficiency of offshore wind farms.

The wide shallow bucket foundation with concrete arc transition section is subjected to significantly larger wave loads which will easily affect the vibration response of the entire structural system. For an offshore wind turbine (OWT) supported by bucket foundation, a finite element model of the whole wind turbine was established based on the measured vibration data, and then the influence of wave loads on the vibration response of the tower top of the OWT supported by bucket foundation was simultaneously analyzed through the established finite element model. It is shown in the analysis results that the vibration response of the tower top caused by wind load is greater than that caused by wave load during the operation period. Subsequently, the influence of the wave load can be ignored compared to the wind load when the wave height is small. In addition, the impact of wave loads on the vibration response of the tower top increases with the increase of external wind speed and wave height and the corresponding impact on the vibration displacement response of the tower top is greater than the vibration acceleration.

With the largescale integration of wind power, power system subsynchronous oscillation (SSO)events occur frequently, which seriously threatens the safe and stable operation of the power grid. The accurate detection of SSO in wind power gridconnected system is of great significance to ensure the stable operation of the power systems. Most of the existing SSO detection methods are singlechannel methods, which are difficult to take into account the global SSO characteristics of the systems. Therefore, this paper proposes a SSO detection method for wind power gridconnected system based on multivariate empirical mode decomposition (MEMD). Firstly, the multivariate empirical mode decomposition is performed on the measurements of wind power gridconnected points, and then the IMF components with SSO mode are screened out via TeagerKaiser energy operator (TKEO). Then, the HilbertHuang transform (HHT) is used to identify the SSO frequency and damping ratio. Finally, the proposed detection method is analyzed by the improved 4machine 2area system simulation data, and the results verify the effectiveness of the proposed method.

As the interface of microgrid photovoltaic power generation system, inverter control strategy directly affects the stability of gridconnected system. The stability of gridconnected inverter is easily affected by the internal and external parameters of the system, especially when the gridconnected inverter adopts LCL filter, the design and operation conditions of the system become more and more complex. In this paper, an active disturbance rejection control strategy based on weighted average current is proposed to solve the disturbance problem of highorder gridconnected inverter system. Firstly, based on the WACC control principle, the system is reduced from third order to first order. At the same time, the internal and external disturbances of the inverter system are regarded as generalized disturbances of a single structure, and the control law is used to adjust the parameters of the closedloop system. Finally, the effectiveness of the control strategy is verified by simulation and experiment.

Integrated energy system is an important means to improve the permeability of distributed new energy and enhance the flexibility of terminal energy consumption. In view of the shortcomings of existing technologies in the modeling of external energy characteristics of multienergy systems and the research of multisystem interaction strategies, this paper proposes a coordinated control method of integrated energy system based on virtual energy storage, and constructs threelayer energy architecture in terms of building layer, agent layer and distribution network layer based on multiagent technology.Based on the interactive architecture, the virtual energy storage model describing the external characteristics of the system is used as the interactive interface to quantitatively analyze and control the virtual energy storage of agents which regulates multi energy distributed resources, such as multi buildings, grid connected energy storage, micro gas turbine, etc. Furthermore, according to the system spatial scope, the hierarchical expansion and progressive analysis are carried out to build a multiagent based integrated energy system coordinated control strategy. The decisionmaking goal is to maximize the resource endowment of the building, park and other comprehensive energy systems so as to meet the energy demand as much as possible and realize autonomous operation.

The fluctuation of renewable energy unit output and the unreasonable grid connection position lead to voltage fluctuations, power deviation, and increased investment costs in the coupled system. A discrete particle swarm optimization method for multi photovoltaic power supply access site selection is proposed to meet the optimization and regulation requirements of wind solar thermal coupling system. Analyzed the reactive power compensation characteristics of photovoltaic power sources and the impact of their connection positions on system voltage deviation and grid losses, established a power generation system model that couples renewable energy and thermal power, and used photovoltaic power sources as reactive power regulation devices for the coupled system. Taking the comprehensive optimization of voltage deviation and line loss as the objective function, the discrete particle swarm optimization algorithm is used to solve the photovoltaic power supply access point. The analysis results of the example show that the multi photovoltaic power station access point optimization method ensures the voltage deviation of each node, reduces line loss, and improves the safety and stability of the wind solar thermal coupling system.

In order to calculate the time history response of wind turbine structure more accurately, the influence of wind shear, tower shadow and mountain environment was considered. Based on Kaimal selfpower spectrum and crosspower spectrum, the harmonic superposition method was used to simulate fluctuating wind speed. The spatial three dimensional non stationary wind field simulation method with wind direction correlation was established by using turbulence coherence model. Taking 2 MW wind turbine of a wind farm as an example, the correctness of the simulation method is verified and compared with the simulation results without considering the correlation of wind direction. The results from statistical analysis of simulated data and comparison with target spectrum demonstrated the accuracy and accuracy of the presented method, the simulation of threedimensional nonstationary fluctuating wind field can be realized. The results from statistical analysis of simulated data and comparison with target spectrum demonstrated accuracy of the presented method, and considering the correlation of wind direction can improve the simulation coincidence, which proves the necessity of simulation method.

Since the output voltage level of a range of green renewable energy sources is low, it is necessary to use Boost converter to increase the voltage level in the process of grid connection. A high gain Boost converter is proposed which not only achieves high voltage gain but also extends the circuit structure to meet higher boost requirements. Firstly, the operating principle and switching device stress of the proposed converter are theoretically analyzed, and the design method of the device parameters is given; then the boosting capability of the converter is comparatively studied, and the influence of nonideal devices on the voltage gain is analyzed; finally, the correctness and feasibility of the theoretical analysis are fully verified through the combination of simulation model building and experimental prototype.

In order to suppress the false information existing in the interactive information between microgrid (MG) and microgrid cluster operator (MGCO), a trading mechanism with the Stackelberg game is proposed, and a dynamic integrity factor is used to consider the honesty behavior of the MG. Firstly, a reward and punishment mechanism based on the reported electricity quantity and the actual trading quantity is established. Transaction price can be adjusted by credit factor. Secondly, a Stackelberg game model with MGCO as leader and MGs as followers is developed. The upper level minimizes fluctuation of power for microgrid cluster, where a contract mechanism of transaction is established to adjust basic transaction prices within the cluster. In the lower level, the cost of MG operation is minimized. Each MG acts as the follower responding to the dayahead trading price and decides the electricity of exchange power with MGCO. Finally, the study prove that the presented transaction mechanism effectively suppresses the false information.

The unique heatdetermined power working mode of coalfired cogeneration units and the antipeaking characteristics of wind power lead to the problems of insufficient peaking capacity and high carbon emissions in virtual power plants. In this paper, we propose an optimal scheduling technology of virtual power plant based on antlion optimization algorithm. The carbon capture technology is supplemented by a reasonable demand response mechanism to realize the flexible and lowcarbon operation of the virtual power plant. Firstly, an optimal scheduling model was established with the objective of the highest economic efficiency in one scheduling cycle. Secondly, a hybrid strategy based on chaotic mapping and tournament selection is designed. The boundary checking mechanism on the search space is utilized to effectively avoid the situation that too many potential solutions are at the same boundary. Finally, the simulation results show that the planned virtual power plant has a reasonable structure, and the proposed scheduling strategy can improve the system's new energy consumption capacity and total revenue while reducing carbon emissions by coordinating the resources on both the source and load sides.

With the advancement of the "dual carbon" goal, the scale and capacity of randomly fluctuating new energy connected to the power grid are increasingly increasing, seriously affecting the safe and stable operation of the power grid. This paper proposes a power grid voltage security and stability control strategy based on time series convolutional residual network and Pelican optimization algorithm for the problem of voltage stability control in large disturbance faults. Firstly, taking advantage of the advantages of low loss of temporal convolutional information, wide receptive field, and strong deep feature extraction ability of residual networks, a voltage stability prediction model based on temporal convolutional residual networks is constructed, mapping the relationship between sensitive node voltage temporal features and voltage stability; Secondly, a voltage stability control model is constructed to output control strategies, and the Pelican optimization algorithm is utilized to solve the control model with its fast convergence speed and strong search ability, resulting in the optimal measures for machine and load shedding actions. Finally, after simulation and verification, the experimental results show that the proposed method improves the accuracy of voltage safety and stability prediction in the power grid, and improves the safe and stable operation level of the power grid after faults through the optimal voltage stability control strategy.