To address the issues of low thermal efficiency and poor economy in the ocean temperature differencedriven ocean thermal energy conversion (OTEC) system, OTEC combined with air conditioning (OTECAC) test system was designed and built.The system utilizes the cold energy of deep seawater in a graded manner by generating electricity and then cooling the air, thus significantly improving the conversion efficiency of ocean temperature difference energy. Performance evaluation metrics such as expansion output power,refrigeration capacity, and overall thermal efficiency were defined based on thermodynamic principles.Experimental tests were conducted to analyze the performance variations of the OTECAC system under different operating conditions. A comparison between OTECAC and standalone OTEC systems was also conducted. The results show that: the optimal expansion pressure ratio exists in the power generation system when the isentropic efficiency of the corresponding expander reaches a peak of 21.83% ; lowering the deep sea water temperature and increasing the chilled water flow rate can significantly improve the performance of the OTECAC system, and when the deep sea water temperature is lowered from 9 °C to 4 °C, the integrated exergy efficiency of the system increases from 47.25% to 51.60%; Under the same operating conditions, the OTECAC system has a power generation capacity of 97 W and a cooling capacity of 5 386 W.The thermal efficiency of the system increases from 1.21% to 17.60% after conversion compared to the standalone OTEC system.

Due to a large area of heat absorbing surfaces and effects of uncertain windy condition, both the convective heat loss and solarthermal conversion efficiency of cavity receivers were unsteady. In order to reduce effects of wind on the cavity receiver performance, a novel cavity receiver design which had a windshield on its opening was investigated in the present study. The windshield could reduce the fluid flow disturbance inside the cavity, so that the convective heat transfer between the heat absorbing surfaces and ambient air were weakened, and the convective heat loss of the cavity receiver would be reduced. A solarthermal coupling numerical model was established firstly, and then effects of windshield material and wind were studied. The results showed that the material of windshield had a big influence on the receiver convective heat loss, and the convective heat loss would increase with a solid wall windshield, while with a porous material windshield, the convective heat loss would decrease. The pressurejump coefficient and thickness of the porous material windshield were key factors affecting its performance. As the pressurejump coefficient increased, the optimal thickness decreased. For the optimal pressurejump coefficient and thickness, the convective heat loss could be reduced by about 53.0%. The results in the present study could provide theoretical and technical guidance for design of cavity receivers.

Through establishing the torsional dynamic model of wind turbine gear transmission system, a method of dynamic parameter identification and fatigue damage prediction of wind turbine gear transmission system based on mechanism model and operating state is proposed, and the dynamic response and fatigue damage prediction effect of wind turbine gear transmission system under different gear wear states are analyzed. The research results indicate that the identified gear rotational inertia and meshing stiffness are in good agreement with the target values; The contact fatigue damage of the same gear is generally greater than that of bending fatigue damage, and gear wear can exacerbate the fluctuation of dynamic meshing force and increase fatigue damage. Under different gear wear states, the estimated values of system dynamic response and gear fatigue damage are in good agreement with the target values.

As China's new energy capacity grows and offshore wind power advances, controlling wind farms becomes more crucial. The study focuses on wake effect modeling and active control strategies within wind farm clusters. It optimizes wake estimation using the Gaussian FLORIDyn model, with search area pruning to speed up calculations without sacrificing precision or efficiency. A novel multiagent reinforcement learning method, guided by a GCNbased proxy wake model, is introduced. This model, grounded in wind farm wake dynamics, captures complex turbine interactions affecting output. Enhanced by wake aware reward sharing, the system improves optimization. Simulations test pruning's benefits and validate control strategies, confirming that advanced wake modeling and control tactics significantly contribute to solving wind farm control problems.

In order to reveal the influence of structural design parameters on design boundaries and improve the efficiency of wind turbine blade structure design, a structural optimization design method was proposed by combining the improved genetic algorithm NSGAII with the wind turbine blade structure design software FOUCS, and constructing an optimization design simulation system suitable for complex wind turbine blade structures. The 15 MW wind turbine benchmark model IEA15240RWT developed by NREL was chosen as the research object. The lamination, positioning, and width of the spar were treated as variables, while the blade weight and flapping stiffness were set as the optimization objectives. The selfdeveloped structural optimization design system was used to obtain the optimal solution set under different design conditions, and the influence of spar design parameters on the Pareto front was investigated. The calculation results demonstrate that for this particular blade of IEA15240RWT, a spar width of 1 000 mm, with the spar centerline positioned at 50% of the chord length, exhibits higher structural efficiency. The feasibility and effectiveness of the optimization design system for blade structure design were verified, and the system possesses strong scalability, providing new insights for more complex blade design tasks.

This paper studies the vulnerability assessment of distribution lines with multitype distributed power access. Firstly, in view of the uncertainty of distributed generation, the Latin hypercube sampling and synchronous back substitution method are used to generate the classic output scenarios of wind and light. Based on the complex network theory and power flow analysis, the vulnerability assessment indexes such as improved line betweenness, improved line degree, line voltage stability and fault loss are proposed from three aspects of power grid structure, operation state and fault influence. Secondly, a comprehensive evaluation model of game theoryVIKOR based on the correction weight of time series fluctuation characteristics is proposed to evaluate the vulnerability of the line. Then, the simulation verification is carried out based on the example of IEEE33 node system. The results show that the constructed index and evaluation model can accurately reflect the realtime fragile state of the line and conform to the time series fluctuation characteristics of source and load. Finally, based on the comprehensive vulnerability of lines in each period, combined with the distribution characteristics of line vulnerability in each period, the real vulnerability of the whole system line in different periods is further analyzed, which provides a theoretical basis for risk aversion of distribution network with distributed generation.

Rural lowvoltage distribution networks was simple grid structure and weak communication infrastructure. Largescale integration of distributed photovoltaic power system will lead to voltage violations in the rural lowvoltage distribution networks. To address this issue, this paper proposes a distributedlocal voltage control strategy for rural lowvoltage distribution networks considering complex scenarios. Firstly, considering the economic cost of voltage control for users, a control framework that takes into account the interests and responsibilities of both the grid and users is proposed. Secondly, a distributed insitu collaborative control strategy is proposed, which is suitable for the grid connection of a variety of distributed energy resources, and considers complex communication scenarios, and adapts to rural scenarios with or without communication or unstable communication. Finally, verified by simulation that the proposed control strategy can balance the interests of the grid and users and effectively solve the voltage violations in rural lowvoltage distribution networks.

In response to the issue that the randomness and volatility of wind power can affect the vulnerability assessment of the power grid and the identification of critical nodes, this paper proposes an intervalbased Electrical DebtRank algorithm to identify vulnerable nodes within the power grid. The method first incorporates the node's offset status and characteristics to improve the traditional Electrical DebtRank algorithm. Then, interval numbers are used to represent the randomness and volatility of wind power generation, leading to the development of the interval – based Electrical DebtRank algorithm to identify vulnerable nodes in a windintegrated power system. Finally, simulation results on the IEEE118 bus system demonstrate that when the vulnerable nodes identified by the proposed method are attacked, the system's power supply capability drops to 33% of its normal state, with a significant reduction in the system's power transmission capacity.

The technology for diagnosing singlephase grounding faults in mediumvoltage distribution networks is of significant importance for enhancing the operational safety and economic efficiency of the system. In light of the current scenario where a large number of distributed generation sources are connected to the distribution network, this study analyzes the impact of distributed generation on singlephase grounding fault currents. It proposes a method for identifying the types of singlephase grounding faults and introduces a fault section location technique utilizing harmonic injection from adjustable arc suppression coils. Upon the occurrence of a singlephase grounding fault in the distribution network, the type of fault is first analyzed based on the characteristics of the zerosequence voltage and phase voltage. Subsequently, the filtering device of the adjustable arc suppression coil is temporarily blocked, allowing the harmonic current from the coil to be briefly injected into the grid. The system's FTU and DTU components analyze the third harmonic content in the zerosequence current. The presence of the third harmonic is used as a criterion to accurately determine whether the detection point is on the fault path, thereby achieving fault section location. A 10 kV distribution network simulation model under various grounding conditions was constructed and analyzed using EMTP/ATP software. The simulation results demonstrate that the aforementioned method effectively reduces the grounding current and achieves a section location accuracy of over 95%. This validates that the proposed method is suitable for both metallic grounding and grounding through transition resistance, meeting practical application requirements.

In order to ensure the safe gridconnected operation of all DC wind power system, the system voltage stability control is crucial. At present, when the DC voltage stability control of all DC wind power system adopts the proportionalintegral (PI) control, the dynamic response speed is relatively slow under the nonnormal operation condition, the control accuracy is not high enough, and the PI parameter is more and more cumbersome and complicated to be calibrated. To address the above problems, this paper proposes a system DC voltage stabilization control strategy based on the principle of Finite Control SetModel Predictive Control (FCSMPC) to control the switching state of transistors of bridge arms of the system converter. The strategy combines the current prediction models of machineside rectifiers and gridconnected inverters, constructs a cost function with the output current of the converter as the control variable, takes the cost function as the optimization objective, introduces the delay compensation to improve the control accuracy in order to avoid the control delay caused by the computational delay, and introduces the weight coefficients to realize the multiobjective optimization, and generates the optimal switching combinations of the signals to trigger the converter through the traversal calculation. In this paper, the simulation model of all DC wind power system is established in Matlab/Simulink, and the proposed strategy is compared with the traditional PI control in different working conditions, and the simulation results effectively verify the static and dynamic performance of the proposed control strategy.