The instantaneous heat collection of the nontracing compound parabolic concentrator is greatly affected by the incident angle. Therefore, in this paper, the PV module with a mirror on its backside was arranged above the focal spot of the traditional compound parabolic concentrator to realize the reuse of the escaped light and improve the solar energy conversion efficiency of the device. The ray tracing of the novel compound parabolic concentrator based on photothermal photovoltaic coupling energy supply was carried out with optical software, and the influence of radial incident angle on the light receiving rate was compared and analyzed. In the actual environment, the variation of the inlet and outlet temperature, instantaneous heat collection and output power of the novel compound parabolic concentrator with time were tested and studied. The results indicate that the light receiving rate of the novel compound parabolic concentrator is consistent with that of the traditional compound parabolic concentrator. When the radial incident angle is 20°, the light receiving rate of the novel compound parabolic concentrator is 89.00%, which is 72.82% higher than that of the traditional compound parabolic concentrator. In sunny days, the maximum outlet temperature, the photothermal conversion efficiency and the daily output power of the novel compound parabolic concentrator. are 34.20 °C, 73.40% and 118.40 W, respectively.

This study aims to address the challenges of phosphorus recovery and solid waste treatment by preparing biochar composites(OSCS) using a copyrolysis method with cotton straw stalk and oil shale as raw materials. The physicochemical properties of the biochar were analyzed using SEMEDS, BET and FTIR tests. The influence of pyrolysis temperature, adsorbent dosage, and solution pH on phosphate adsorption was investigated, and both the adsorption kinetics and isotherm models were studied. The results indicated that the structural properties and surface morphology of the biochar were significantly enhanced through oil shale modification, leading to a notable improvement in phosphate adsorption capacity. At an injection level of 4.0 g/L and pH5.0, the maximum adsorption capacity reached 7.01 mg/g, which was 2.47 times higher than that of cotton straw biochar and 3.52 times higher than that of oil shale char. The adsorption process followed the proposed secondary kinetics and Langmuir isothermal adsorption model, and the mechanisms involved surface precipitation, ligand exchange, and electrostatic attraction. This approach of oil shale modified biochar composites provides a novel strategy for both phosphorus removal and solid waste resource utilization.

In the construction of floating wind farms, various soil conditions may be faced. Based on the needs in practice, a kind of anchor named gravity penetration column anchor is proposed for the soil with high permeability, where has high risk of installation by suction. The finite element method was used to analyze the penetration process and bearing characteristics of this kind of anchor. The analysis results show that in the coarse sand, the gravity penetration column anchor can penetrate to the design depth by its own weight. Unlike ordinary gravity anchors, which mainly provide anti sliding force through friction at the anchor bottom, the gravity penetration column anchor is shallow failure under horizontal load, and can mobilize more soil resistance during the failure improving its anti sliding ability effectively. The gravity penetration column anchor can provide a horizontal bearing capacity of more than 2 000 t, which is nearly twice that of conventional gravity anchors, and can meet the bearing requirements of floating wind turbine. This kind of anchor could provide more choices for offshore floatingturbine in China.

Offshore wind turbines installed close to earthquakeprone zones are not only affected by wind and wave loadings, but also threatened by earthquakes. In order to reduce the earthquake impacts on the structural vibration and load of largescale wind turbines, a seismic coupled analysis and structural control architecture has been developed by improving FAST based on the modal acceleration method and the Tuned Mass Damper (TMD). The control effects of TMD on tower vibration and load reduction of the IEA 15 MW monopile wind turbine due to different ground motions are investigated. The results show that the TMD can significantly reduce the towertop displacement and towerbase load for each examined ground motion. The best effect on alleviating towertop vibration is achieved when the tuning frequency ratio of the TMD is 0.9, reducing the tower top displacement by 89.8%. The fluctuation amplitude of towerbase bending moment following the earthquake event is significantly reduced by the TMD with a tuning frequency ratio of 0.8 that is capable of reducing the standard deviation by up to 99%.

This thesis constructs a coupling system inactive adjustment model for system voltage output of wind power fluctuations in renewable energy and thermal power generation coupling systems, and constructing coupling system reactive modulation models, on the basis of considering communication delays, The voltage deviation is quantified index to analyze the effect of reactive power control on voltage stability in coupling system. A coupling system bilateral reactive control optimization strategy for fusion SVG and wind turbines as reactive modulated resources is proposed. The upper layer is based on SVG as an inactive adjustment device, and the system's overall power factor optimization model is constructed by the respective node voltage deviation. The lower layer is a node having a large voltage deviation. The wind turbine near the node is used as an inactive adjustment device. The system voltage deviation is optimal, and the wind turbine reactive optimization model is constructed, and the algorithm combined with Ybus and LinWPSO is used. Solve the optimization model and derive the wind power unit reactive reference value. The case simulation results show that the twolayer reactive policies mentioned in this paper make full exertion of the powermodulated potential of the wind and motor sets, which can take care of the voltage fluctuations and web damage of the coupling system, and reduce the disturbance of the renewable energy power fluctuations on the coupling system, improve coupling the voltage stability of the system.

The solar heating system coupled with seasonal thermal storage is a promising solution to solve the seasonal mismatch between the solar energy supply and heating demand. The thermal performance of the system in the heat storage season has a significant impact on the system's annual operation performance, and has a direct impact on the discharging process of the seasonal storage in the heating season. Therefore, based on the solar heating system coupled with seasonal thermal storage in Fanshan Town, Zhangjiakou, a dynamic simulation platform is built. The influence of different operation strategies on the performance of the system is analyzed by experiment and simulation methods. Results showed that the control strategies were significant for improving the heat collection performance of solar receiver and the exergy efficiency of the UWPS. The stratification of the seasonal storage has an impact on the collection efficiency of the receiver, especially at the end of the nonheating season. In addition, at the end of the nonheating season in typical year, the monthly solar collection efficiency could be increased by 4.8% in variable flow control compared to the temperature difference control.

With the construction and promotion of greener grid, the old electricity marketing process is facing new challenges. Therefore, in order to suit the new requirements of electricity marketing, this paper proposes an electricity pricing method based on the careful consideration of regional carbon emissions. Firstly, consider the economic compensation of carbon emission reduction incentive and controllable load participating in peak regulation response, a load mobilization cost model considering carbon emission and peak regulation cost is established. Then, based on the idea of game theory, the demandside controllable load and energy storage device are used as schedulable resources to construct a 1K Stackelberg masterslave game decision model. Finally, the inverse induction method is attached to solve the model. We can see from the results that the proposed electricity pricing method of new energy power grid considering regional carbon emissions can promote the optimal operation of power system and realize the double improvement of efficiency and benefit of new distribution network.

Considering the inconvenient installation and the poor ability to capture wave energy in the traditional directdrive wave energy converter (DDWEC), a series connection floating twobody DDWEC is proposed in this paper. Two rectangular bodies of the WEC float horizontally in the waves bodies and both capture the wave energy. The primary and secondary of the Halbach array permanent magnet linear generator(HPMLG) are respectively installed on the lateral surface between the two floating bodies. Because both floating bodies capture wave energy, the ability of the WEC to capture wave energy is improved, and the structure of the WEC is simple and easy to manufacture and maintain. Then, the prototype of the twobody DDWEC is manufactured and tested in the wave tank in this paper. The experimental results show that in the case with the wave height of 16 cm and the draft of 16 cm, the average generated power of the prototype reaches the maximum value of 6.54 W at the wave period of 1.8 s, when the wave period ranges from 1.2 s to 2.4 s. Finally, the twobody DDWEC prototype is compared with the singlebody DDWEC prototype. The results show that the average power output of the twobody DDWEC prototype is always higher than that of the singlebody DDWEC prototype in a large range of wave period.

In recent years, with the rapid growth of the scale of distributed photovoltaic deployment in cities and towns, the impact of random fluctuation characteristics of its output on urban load is also increasing. The traditional method is difficult to accurately predict the complex load fluctuation after largescale deployment of distributed photovoltaic system, which is not conducive to the safe and stable operation of power grid. To solve these problems, this paper proposes a shortterm load forecasting method considering distributed PV. Since the net load including distributed PV is the difference between the actual consumption load of the user side and the PV output, this paper first adopts the big data mining technology to analyze the characteristics of PV output and the userside load as well as the correlation between the two and their respective influencing factors before constructing input data, and selects the influential factors with high correlation as the input feature set of the net load prediction model. Secondly, the LSTM neural network prediction model integrating selfattention mechanism is constructed to deeply explore the characteristics of load sequence. The grey Wolf algorithm is used to optimize the parameters of the prediction model and determine the model with the best prediction effect. Finally, an example simulation shows that the proposed method can effectively improve the prediction accuracy of net load with distributed PV.

With the increasing penetration rate of new energy in the distribution network, the bearing capacity of new energy in the distribution network is facing challenges; The electric heating load has a certain degree of adjustability and has the potential to participate in the load dispatch of the distribution network. How to improve the new energy bearing capacity of the distribution network through load dispatch has important practical significance. The article proposes a dynamic optimization scheduling strategy for electric heating loads in distribution networks that considers the bearing capacity of new energy. Firstly, a regulation model for the load of thermal storage electric heating was constructed; Then, with the goal of bearing capacity of new energy in the distribution network substation area, and with the constraints of smoothing load fluctuations, stable and safe operation of the distribution network, and user comfort of the heating load, a dynamic optimization scheduling model for the heating load of the distribution network was established, and a solution strategy based on quantum genetic algorithm was proposed. The Latin hypercube sampling method is used to generate typical application scenarios for the applicability analysis of dispatching strategies for the new energy bearing capacity of distribution networks. The calculation results show that the proposed method can fully consider the potential for regulating the electric heating load and improve the application level of new energy in the distribution network.