In order to improve the grid connected efficiency of largescale renewable energy and reduce the impact on traditional power grid, this paper studies the method of aggregating distributed renewable energy and energy storage stations into virtual power plants. By describing the feasible operation domain after aggregation, peak shaving and load filling can be realized, and fossil energy consumption and environmental pollution can be reduced. A virtual power plant flexible polymerization method based on Minkowski sum and convex cell edge detection is proposed. Based on Multiple Objective Particle Swarm Optimization (MOPSO) algorithm, A set of objective functions was established considering both conventional unit operation constraints and energy conservation and capacity constraints of energy storage power station. The multiobjective optimization problem of optimal output of multitype units and charge and discharge sequence of the distributed energy storage was solved, and the unit commitment optimization with virtual power plant was realized. Furthermore, wind power plant and distributed energy storage are added into the standard case of IEEE11 units for simulation verification. The calculation results show that the virtual power plant scheme based on MOPSO optimization has significant effects on renewable energy accommodation, operation cost reduction and fossil energy saving.

In this paper, considering the soil stratification and groundwater seepage, combined with the measured data, the fluid temperature inside the buried pipe and the thermophysical parameters of different layered soils are obtained through the calculation of the outer wall temperature of the buried pipe, so as to establish the heat transfer model of the buried pipe stratified according to the equivalent physical properties of the soil. The experimental results show that the strati–fied heat transfer model is closer to the measured value than the conventional homogeneous model, and the error is smaller; The average absolute error between the simulated outlet water temperature and the measured value is 0.21 °C, and the average absolute error between the simulated inlet and outlet heat transfer temperature difference and the measured value is 0.14 °C based on the equivalent physical properties of soil stratification, which has a high accuracy and can provide a basis for engineering design and serve as the basis for the subsequent optimization study of the buried pipe heat transfer.

Based on a highpressure common rail diesel engine, a methanol injection system is installed at the intake manifold. A twostage direct injection (preinjection + main injection) of coaltoFischerTropsch (FT) diesel is installed in the cylinder. A twostage injection FT diesel/methanol (F/M) dualfuel engine test stand is built to explore the effect of different methanol substitution rates on engine emission performance at 2 000 r/min and loads of 25%, 50%, 75% and 100%. Simultaneously, the theoretical basis for realizing the FT diesel/methanol reactivity controlled compression ignition (RCCI) mode is explored. The results indicates that the fuel economy of the F/M dualfuel engine is better at medium and high loads. The emissions of HC, CO, Soot, methanol and formaldehyde increase in the F/M dualfuel combustion mode compared with the singlefuel compressionignition mode. These emissions increase with the augmentationmethanol substitution rate and decrease with an increase in load. In contrast, the emissions of CO2, NOx and NO decrease with an increase in methanol substitution rate but increase with an increase in load. The emissions of NO2 increase with both the rise in methanol substitution rate and load. The test results show that simply adding a methanol injection system to the intake manifold cannot achieve an efficient and lowemission RCCI combustion mode, and its fuel injection strategy needs to be calibrated.

The carbon dioxide emissions of various parks account for about 30% of China's total carbon emissions. The lowcarbon and efficient park integrated energy system is an important way to achieve China's "carbon peak, carbon neutrality" goal. Firstly, this paper establishes the electricitycarbon market trading architecture of the park integrated energy system, and analyses the carbon emission responsibility of the park integrated energy system. Then, considering the energy purchase cost and carbon emission transaction cost, the economic operation evaluation model of the electricitycarbon benefit of the park integrated energy system is proposed with the goal of minimizing the overall operation cost of the system. The example analysis shows that the economic operation evaluation model proposed in this paper can fully reflect the carbon emission cost of the integrated energy system, and proves that the introduction of indirect carbon emission cost will increase the overall operation cost. Higher carbon price and higher emission reduction targets can drive the parks to reduce the total carbon emission and help achieve the "double carbon" goal.

In this study, the Capricpalmitic acid (CAPA) binary eutectic PCM was vacuum impregnated into the expanded vermiculite (EVM) to prepare CAPA/EVM composite phase change thermal storage material. FTIR, DSC, TG, and thermal cycling were used to assess the chemical compatibility, heat storage performance, thermal stability, and thermal reliability of CAPA/EVM. The results showed that CAPA was stably loaded in the layered pores of EVM through physical interaction, and CAPA/EVM had excellent chemical compatibility. The Melting and solidification phase transition temperatures of CAPA/EVM were 23.61 and 20.41 °C, respectively. The latent heat of melting and solidification phase transition were 67.22 and 64.87 J/g, respectively. The amount of CAPA encapsulated in EVM could reach 52.22%, and it had favorable thermal stability at working temperature. In addition, the CAPA/EVM maintained great thermal reliability after 100 thermal cycles, indicating its potential application in the building energy conservation field.

Renewablerich remote areas are facing problems such as high cost of external energy supply, low reliability of internal green micropower, high fuel transportation cost and environmental pollution caused by diesel generators as backup power sources, which is not meeting the needs of low carbonization. To solve those problems, this paper propses a design of microenergy network based on hydrogen energy storage in an offgrid hydrogen storage energy supply scenario. The framework for a hydrogenbased zerocarbon microenergy network on account of the spatial and temporal distribution characteristics of renewable energy in remote areas is presented. Furthermore, the paper proposes the resource endowment and operation constraints of the hydrogen based micro energy network, formulates operation strategies for energy surplus and shortage periods and carries out the case simulation. Simulation results of a village in Yunnan Province prove the feasibility of the proposed microenergy network and its operation strategies, which effectively eliminates the influence of unstable regional green micropower output and seasonal shortage on the reliability of the power supply system and reduces regional thermal load burden. Furthermore, it helps decarbonize the regional energy system. Research results provide a reference for energy consumption improvement and carbon reduction in renewablerich areas such as remote areas and islands.

With the promotion of the "dual carbon" goal, the capacity of distributed new energy connected to the power grid has significantly increased. The use of distribution network source network load storage coordination optimization strategy is an important method to achieve distributed new energy consumption, among which reactive power optimization can ensure the safe and stable operation of the power grid. This article proposes an adaptive learning rate convolutional neural network based optimization technique for load storage and reactive power coordination in distribution networks. Firstly, a reactive power optimization model is constructed with the goal of minimizing network loss and voltage offset. Secondly, utilizing the powerful nonlinear fitting ability of convolutional neural networks, the mapping relationship between power grid operation scenarios, reactive power regulation equipment, and energy storage charging and discharging strategies is excavated. Adaptive learning rate is introduced to update network parameters and improve network training efficiency. Finally, by controlling the charging and discharging conditions of reactive power regulation equipment and energy storage devices to coordinate the output of distributed power sources, active optimization control of reactive power and voltage in new distribution network is achieved. After simulation verification of the IEEE33 node power grid model, the results show that the proposed optimization method for load storage and reactive power coordination in the distribution network source network improves the voltage regulation ability of the power system, laying a good foundation for the safe and reliable operation of the distribution network.

Wind turbine blade stall will reduce wind turbine output power. In this paper, the aerodynamic analysis model of NREL Phase VI wind turbine was established based on Fluent software, and the pressure coefficient and power characteristics of the wind turbine blade section were calculated at 13 m/s wind speed, and the accuracy of the aerodynamic analysis method of the wind turbine was verified by comparing with the wind tunnel experimental data. Then, the active jet and vortex generator (VGs) were coupled to the blade of the wind turbine. It was found that the power of the wind turbine increased first and then decreased with the increase of the width of the jet hole and the height of the vortex generator. A wind turbine aerodynamic analysis model with mixed flow control was established to study the influence of the chord distance between jet and vortex generator and the height of VGs at the trailing edge on the aerodynamic characteristics of the wind turbine. The results show that the wind turbine output power reaches the highest when the distance is 0.3C(C is the chord length of airfoil), and the increase is 6.61% compared with the single jet control. When the trailing edge VGs height is 15 mm, the hybrid flow control has the best effect and the highest fan power.

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.

Due to the intermittency and uncertainty of wind power on the time scale and complementarity on the spatial scale, the line capacity is underutilized and the cost of wind power is high in traditional planning. Combined with the output characteristics of largescale wind power, considering the smoothing effect, the construction cost of transmission projects, the cost of wind power curtailment, and the income, the economic evaluation model of offshore wind farm aggregation system is established, and the model is solved by using an improved genetic algorithm. The genetic algorithm is improved based on the minimum spanning tree of dynamic weight variation, and the coding, selection, crossing, and mutation links in the genetic algorithm are improved to promote the efficiency of the algorithm. Taking a wind farm cluster in Jiangsu Province as an example, the topology of wind turbines and the convergence and connection mode of wind farms are optimized, and the results show that the proposed algorithm has good optimization and convergence. And the established topology optimization model of wind farm and internal wind turbines can effectively reduce the engineering investment.