Driven by the goals of "Carbon Peak" and "Carbon Neutrality", the rural energy transition is faced with the problems of irrational energy structure, low proportion of renewable energy supply and low utilisation efficiency. For rural areas endowed with renewable energy sources such as biomass and solar energy, a rural integrated energy system (RIES) planning method considering photo-thermal assisted biogas production is proposed based on the effect of temperature on the efficiency of biogas production. Firstly, a RIES architecture is designed based on the coupled use of biomass and solar energy resources, and secondly, an economically optimal integrated rural energy planning optimisation model is constructed, which contains constraints such as energy balance and equipment operation. Finally, the example compares two planning scenarios with and without photothermal-assisted biogas production using a rural area in Shanxi as a scenario, and the results show that the biogas production rate is improved, the pressure on energy storage is alleviated, and the system planning cost and carbon emission are sig-nificantly reduced, which verifies the validity and economy of the proposed planning model.

To address the issue of low wave energy capture efficiency caused by the nonlinear effects in the actual operating conditions of wave energy conversion devices, a model-based improved power optimization strategy is proposed. Considering the resultant force acting on the free state of the float, an equivalent approximation is carried out using series expansion, and an independent iterative algorithm is introduced. Based on the Kalman filter with statistical similarity measurement, the polynomial coefficients are determined, and then the Euler-Lagrange equations are established to obtain the optimal control law. By tracking the control current, the maximum power can be captured. Simulation results show that the improved Kalman filter can reduce the influence of noise and the parameter identification error. The proposed strategy can effectively enhance the output power of the system under actual operating conditions.

Activated carbon was used as catalyst for the catalytic reforming of straw biomass (soybean straw, corn stalk) pyrolysis volatiles to phenolic compounds. The effect of catalysts on the yield, composition, and phenolic compound content of liquid products was investigated, and the catalytic mechanism of the catalysts was analyzed. The results showed that, after the catalytic reforming of volatiles by activated carbon, the liquid decreased in the products while the gas increased. The liquid yields of soybean straw and corn stalk were the highest at the pyrolysis temperature of 500 ℃, reaching 43.9% and 42.9%, respectively. After their volatiles were catalytically reformed by activated carbon, the liquid product yields were decreased to 30.1% and 37.9%, respectively. However, after catalytic reforming of volatiles, the aliphatics in the liquid products decreased while the aromatics increased. When the pyrolysis temperature was 500 ℃, the aromatic compounds in the soybean straw and corn stalk pyrolysis liquid products were increased by 10.0% and 9.7%, respectively. The content of phenolic compounds in the liquid products increased significantly, and the relative content of phenolic compounds reached 42.9% and 55.1%, respectively.

Based on the constant volume combustion bomb combined with the high -speed schlieren system, the effects of initial temperature of 450 K, initial pressures and equivalence ratios on the flame instability of hydrogen-added ethanol premixed fuel were studied. The results show that the increase of Ф or P₀ enhances crack and cellularity on the flame surface, and the flame instability is enhanced, and the effect of P₀ on the flame instability is more significant. The flame instability was comprehensively evaluated from the aspects of hydrodynamic instability (HDI) and thermal diffusion instability (TDI), and it was found that the increase of P₀ increased the hydrodynamic instability, but the thermal diffusion instability was not greatly affected by P₀. In addition, under the experimental conditions, the effective Lewis number is greater than 1, and the thermal diffusion effect always suppresses the instability of the flame, so flame instability is primarily driven by the hydrodynamic effect, which can be further verified by evaluating the global growth rate of each instability parameter. Finally, the linear stability theory model was used to determine the critical condition for the instability of the premixed flame, and it was found that the critical radius of flame instability decreases and the flame instability is promoted with the increase of Ф or P₀.

In electrocatalytic anaerobic digestion, the methane content in biogas can be enhanced. With acetic acid as the substrate, this study investigated the kinetics of biogas production and substrate degradation in an electrocatalytic anaerobic digestion system. Experimental results showed that with the addition of different initial acetic acid concentrations (8.3, 10.0, 11.7 g/L), the methane content in biogas increased with increasing acetic acid concentration. When the acetic acid concentration was 11.7 g/L, the average methane content reached 80.6% in batch experiments. Based on the carbon balance relationship in the electrocatalytic anaerobic digestion process, kinetic studies were conducted using both the first-order kinetic model and the Gompertz model. The study revealed that acetic acid conversion efficiencies at the three concentrations were 85.6%, 97.2%, and 97.4%, with biomass growth accounting for 22.1%, 29.9%, and 28.5% of the carbon distribution, respectively. The correlation coefficients (R²) for both models in fitting the biogas production process were greater than 0.99, and those for the acetic acid degradation process were above 0.90, with the first-order kinetic model demonstrating a better fit for acetic acid degradation.

The output performance of PEMFC stack is mainly related to operating conditions, control strategies, and structural design, while the voltage consistency of the stack is an important indicator of the stability and reliability of the stack performance. This study conducted experimental research on an 8.5 kW proton exchange membrane fuel cell stack by constructing a water-cooled hydrogen fuel cell stack test bench. The polarization curve and output power curve were used as performance reference indicators, and the voltage fluctuation rate C_v was used as a consistency evaluation indicator to investigate the effect of different dew point temperatures of reactive gases on the output performance and voltage consistency of the stack. The results indicate that the dew point temperature has a significant impact on the performance and voltage consistency of the stack. As the dew point temperature increases, the output performance of the fuel is improved, and the performance decreases when the dew point temperature exceeds 57 ℃. Both high and low dew point temperatures can cause uneven distribution of water and heat inside the fuel cell stack, leading to an increase in voltage fluctuation rate and a decrease in PEMFC consistency.

In practical applications, photovoltaic (PV) modules often experience partial shading due to obstructions such as chimneys, trees, or bird droppings, leading to power mismatch losses in the system. To minimize the impact of shading and further enhance the power generation capacity of PV systems, this paper first derives the output characteristics of PV power stations under shaded conditions and establishes a model for improving string performance based on power optimizers. Subsequently, based on the known proportion of shading on the module surface, an experimental platform was built to analyze the deviation between measured and simulated results using three experimental schemes and to compare the power generation of the strings before and after incorporating power optimizers. Data show that the deviation in daily power generation between measured and simulated results is within 4%, and power optimizers can increase power generation by up to 16.14%. The research findings provide important guidance for enhancing the power generation capacity of PV systems under shading conditions in practical scenarios.

With the gradual increase of photovoltaic installed capacity, the stable and safe operation of power system is facing challenges. By improving the prediction accuracy of photovoltaic power generation, the operation stability and safety of power system can be improved. Therefore, this paper proposes a DBO -CNN -BiLSTM -AM short -term photovoltaic power generation prediction method based on feature optimization. Firstly, Variance Inflation Factor (VIF) and Extremely Randomized Trees (ERT) are used to calculate and select the features with low VIF value and high importance score as input. Secondly, a CNN -BiLSTM -AM prediction model is established by using Convolutional Neural Network (CNN), Bi-directional Long Short Term Memory (BiLSTM) and Attention Mechanism (AM) with dynamic adjustment ability of feature weights. Finally, the Dung Beetle Optimization algorithm (DBO) is used to perform global optimization of hyperparameters to maximize the prediction accuracy. The experimental results show that the prediction accuracy of the short-term photovoltaic power prediction method proposed in this paper is significantly higher than that of the traditional method, which provides a good basis for optimizing power dis-patching and stable operation of power system.

Addressing the current issues of insufficient precision in the economic evaluation of geothermal power generation projects and the imperfection of the assessment system, an evaluation index system tailored for the technical and economic aspects of such projects has been established. It proposes a comprehensive life-cycle economic evaluation model for geothermal power generation projects that incorporates carbon trading considerations. Taking the Xizang binary fluid geothermal power generation project as an example, the model is applied to conduct a detailed calculation and analysis of the project's economic performance after completion. The results show that the project's levelized kW•h cost is 0.588 5 yuan /(kW•h), the internal rate of return is 10.94%, and the payback period is 16.12 years, which verifies the practicability and accuracy of the evaluation system in practical application. At the same time, the influence of multi -dimensional sensitivity factors such as cost, income and financing on the profitability of geothermal power generation projects is systematically analyzed to provide reference for the cost control of geothermal power generation projects.

To investigate the combined effect of different turbulence intensity wind fields and yaw faults on the dynamic response of IEA 15 MW wind turbines, the empirical mode decomposition (EMD) method was used to decompose the wind speed at the hub, analyze the differences between traditional stationary and non-stationary models, and study the non-stationary dynamic response of wind turbine blade root flapping moment, platform pitch and pitch under different operating conditions. Research has shown that the time-varying average term obtained through EMD decomposition can better describe the pulsating trend of wind power response. The non-stationary model used in the article improves the accuracy of wind power response calculation under different operating conditions; The mean flapping moment of the blade root gradually decreases with the yaw angle, and due to the stability of steady-state wind, the mean flapping moment of the blade root decreases with the increase of turbulence intensity. And its extreme value decreases first and then increases under the combined effect of turbulent wind field and yaw fault, indicating that the combined effect of the two causes the wind turbine structure to exhibit more severe non-stationary dynamic response. The pitch and heave of the platform gradually decrease with the increase of yaw angle under steady-state wind conditions. Compared with the normal turbulent conditions under steady-state wind conditions, the proportion of pitch and heave decrease decreases. However, under extreme turbulent conditions, the mean pitch increases at a 15° yaw angle, and the extreme and mean pitch increase at a 15° yaw angle. This indicates that in the event of a unit yaw failure, turbulent wind can increase the platform's motion response.