Floating offshore wind turbines are faced with the problem that the unconstrained platform pitch motion will stimulate the resonant motion of itself and then reduce the power output, resulting in damage to the whole system. Collective blade pitch control is able to tune both generator speed and platform pitch motion. However, it is difficult for state -based feedback controllers aimed to satisfy multiple objectives to avoid the contradiction between control performance and computational cost. In this paper, a model reference adaptive control scheme with inner robust control law for multi-objective is proposed to generalized a linear control law designed for a particular operating point to the whole region, making the actual responses tracking the ideal ones to guarantee the performances of power generation and platform stabilization beyond rated wind speed. According to the co-simulation based on OpenFAST and Simulink under a series of wind and wave conditions, compared with baseline controller, the proposed controller obtained promotions in both generator speed tracking and platform motion rejection.

High -efficiency direct -drive heating devices are the key part to improve the performance of direct-drive wind heating systems. In this paper, the optimal structural parameters of a typical straight-blade disc turbine agitator heating device were investigated. The effect of input torque and power for the agitator heating device were also investigated via single-factor experiments and orthogonal experiments, and a multiple linear regression model for input power and the various factors of the agitator heating device were established. The results showed that the increasing in the number of blades, liquid level height, and rotational speed can enhance the performance of the agitator heating device, while the increasing in the height of the agitator blade decreasing its performance. And the increasing in the number of baffles initially can improve the performance of the heating device, but the performance improvement will no longer increase as the number of blades reaches a certain value. The degree of influence of the aforementioned factors on the performance of the agitator heating device is as follows: rotational speed > height of agitator blades > number of baffles > liquid level height > number of blades. The agitator blade height and rotational speed have a positive impact on the performance of the heating device, while the number of baffles and liquid level height have a significant influence. The performance of the direct-drive agitator heating system can be predicted with the established multiple linear regression model based on the various optimal structural parameters. The investigation of this paper can founded a basis for designing and optimizing of the direct-drive agitator heating devices.

As the penetration rate of distributed photovoltaic (PV) power generation in distribution networks continues to rise, the problem of loss of selectivity and sensitivity of distribution line protection is becoming more and more prominent. Distance protection has the advantages of fast response speed, independent of system operation mode, and independent of communication, which is an effective way to solve the protection problems of distribution networks containing distributed PV. However, the additional impedance generated by the controlled phase characteristics of PV short-circuit currents makes it difficult for distance protection to meet the requirements of sensitivity and selectivity in power grids containing distributed PV. To this end, the fault characteristics of PV-containing distribution networks are analyzed, and the coupling relationship between the measured impedance and the actual fault location and the additional impedance is analyzed; the expression for the additional impedance during interphase faults in distribution networks containing distributed PV is derived, and the principle of interphase fault location in distribution networks with multi -PV access is proposed, and then new distance protection criteria are constructed, and adaptive distance protection for interphase faults in distribution networks containing distributed PV is proposed. The method is proposed. Examples show that the method can accurately identify and locate interphase short -circuit faults in distribution lines under different fault locations, fault severities and PV outputs, and it has the advantages of simple and reliable principle, convenient realization, and wide range of application.

Accurate modeling of photovoltaic-energy storage systems (PV-ESS) is critical to analyzing the stability and reliability of grid-connected microgrid systems. Firstly, the system reliability assessment model is established, the fault repair time model and the component failure rate model of the optical storage system are refined, and the battery aging-aware charging/discharging model accounting for energy storage lifespan degradation is established. Secondly, the reliability indicators are defined and the load-shedding and islanding strategies are developed, and the reliability evaluation method of grid-connected microgrids considering the correction of the fault repair time model of the photovoltaic storage system is proposed based on the sequential Monte Carlo simulation method. Finally, the improved IEEE RBTS BUS6 F4 feeder is used as a validation system to compare and analyze the influence of the fault repair time correction model of the PV-ESS on the reliability of grid-connected microgrids. The results more accurately evaluate the microgrid reliability by accounting for practical repair processes within PV-ESS.

Under the dual carbon goal, wind energy as a green energy source has received much attention, but the issue of wind abandonment still restricts the development of wind power generation. The configuration of hydrogen storage in a comprehensive energy system can effectively solve the problem of wind abandonment and achieve the effective utilization of wind energy in multiple ways and times. This article proposes a comprehensive energy system scheduling method that includes wind power hydrogen production and multiple types of energy storage, taking into account the impact of wind power output uncertainty on the system, considering the joint optimization scheduling and load demand response strategy of electricity, heat, cold, and hydrogen, and analyzing the carbon emissions of the system. The research results indicate that the established comprehensive energy system scheduling model can achieve scientific collaboration of multiple types of energy and improve the operational economy of the comprehensive system.

The reactive power output of new energy and the recovery rate of grid voltage will affect the voltage characteristics of other nodes in the system. Traditional parameter determination methods for a single station are difficult to ensure the minimum overall voltage deviation of important nodes in the system. To solve the issue, an optimization method for new energy low voltage ride through (LVRT) control parameters considering the reactive power and voltage interaction is proposed in this paper. Firstly, the impact of LVRT control parameters and reactive power interaction on the overall voltage support capability is analyzed. Then, an index for the coupling degree of reactive power and voltage between nodes is proposed, based on this index as well as the degree of voltage drop at the new energy grid connection point, the value range of the reactive power current proportion coefficients of LVRT in different stations are determined. Finally, within the value ranges, with the goal of minimizing the overall voltage deviation of important nodes in the system, a deep reinforcement learning algorithm is used to coordinate and optimize the above parameters. The results of case studies show that the proposed method can improve the overall voltage recovery characteristics of the system compared to traditional methods, and the pre determination of the control parameter value range can enhance the convergence speed of the algorithm reward function.

With the integration of dispatchable resources such as distributed photovoltaics and energy storage into the distribution network, the demand for dynamic frequency regulation capability in the system has significantly increased, posing comprehensive challenges to load frequency stability control. To better mitigate frequency fluctuations in the new energy distribution network system, a new energy distribution network load frequency control strategy considering source load storage dispatchable resources is proposed. Firstly, based on the frequency response characteristics of distributed photovoltaic, energy storage equipment, and demand side interruptible loads, a load frequency control model for the new energy distribution network was established; Then, based on model predictive control, frequency adjustment was achieved without difference, and the control parameters were adaptively adjusted using deep learning algorithms. A multidimensional index system was constructed to comprehensively evaluate the control performance of the proposed control strategy; Finally, the effectiveness of the proposed method was verified through Matlab/Simulink simulation.

Compared to traditional energy, new energy exhibits obvious randomness, volatility, and regional characteristics, and its large-scale integration into the power grid will undoubtedly have a profound impact on the operation of the power system. Therefore, this article takes wind power as the research object, first analyzes its output characteristics and common distribution line loss calculation methods, and proposes an optimized power loss calculation method for the power grid. Considering the fluctuation of wind power output, the equivalent output curve of typical days in the month is corrected by combining the average electricity quantity and shape factor to calculate the power flow. Furthermore, the power loss data of typical days is used to estimate the power loss situation of the entire month. Finally, the proposed improved power loss calculation method was validated through numerical examples, and the results fully demonstrated the engineering feasibility of the proposed improved algorithm, effectively improving work efficiency and providing important guidance for engineering applications.

With the rapid development of power electronics technology, flexible direct current (DC) transmission technology has also made significant progress. However, the oscillation issues that arise in practical applications of this technology have gradually attracted widespread attention. This paper aims to explore the impact on system impedance stability by modeling and analyzing each link of impedance measurement. First, the paper introduces the method of impedance stability analysis, emphasizing the importance of assessing system stability through impedance characteristics. On this basis, an in-depth analysis of the types of disturbance signal sources is conducted, and a model of the impedance measuring device is established to analyze its impedance characteristics in detail. Finally, through Matlab simulation, a comprehensive analysis of the impact of disturbance signal source types and impedance measuring devices on system impedance stability is carried out.

The effects of reaction temperature and alkaline catalyst on the yield of pyrolysis products and the selectivity of methoxy-aromatic compounds were studied during microwave-assisted pyrolysis of eucalyptus sawdust in a fixed-bed reactor. The results showed that 400 °C was the optimum temperature for methoxy-aromatic compounds production, where the yield of bio-oil was 28.4%, and the concentration of methoxy-aromatic compounds in the bio-oil reached to 70.4%. The dominant methoxy-aromatic compounds were identified as guaiacyl and syringyl derivatives. Weakly alkaline catalysts (K₂CO₃ and Na₂CO₃) enhanced both bio-oil yield and the methoxy-aromatic compounds selectivity. However, the strong base NaOH reduces methoxy-aromatic compounds content. The catalytic efficiency for methoxy-aromatic compounds selectivity followed the order: Na₂CO₃ >K₂CO₃ >NaHCO₃ >NaOH. Furthermore, the reaction mechanisms underlying the formation of MACs from woody biomass and their subsequent conversion into benzoquinone, phenol, and catechol were elucidated, with guaiacol serving as a key structural model.