The integrated energy system (IES) planning and optimization faces multiple challenges such as high volatility of new energy sources and large uncertainty of output. In view of this, this paper proposes a twostage capacitycost planning and optimization method for integrated energy systems considering scenery uncertainty. Firstly, Latin hypercube sampling is applied to generate the base wind and solar scenarios set, and the scenarios are reduced based on the improved kmeans algorithm. Secondly, a multiobjective optimization model is constructed with the lowest operating cost, optimal carbon emission reduction, and optimal pollutant emission reduction; finally, the system capacitycost twostage planning and optimization solution strategy is proposed, and a business park in the south is selected for the planning simulation. The simulation example shows that the twostage planning model of integrated energy system constructed in this paper can ensure the economy of system and environmental protection at the same time, and meet the multiple energy demands of users.

In order to further improve the efficiency and reliability of the local power grid in the process of fault recovery, this paper proposes an island partition strategy of local power grid with distributed generation based on improved GSAGWO algorithm. Firstly, the optimalworst method is used to evaluate the load to obtain the load weight value, so as to determine the priority of island division of important load restoration under local power grid fault. Secondly, combined with the load priority, the load level weight coefficient is determined, and the objective function model of island division of local power grid with distributed generation is constructed. Then, in order to obtain better objective function solution results, chaotic reverse learning and genetic annealing algorithm (GSA) are introduced to improve the grey wolf optimization algorithm (GWO) to improve the optimization performance of the algorithm. Finally, the modified IEEE 69 node is taken as an example for simulation analysis. The improved GSAGWO algorithm is used to solve the local distribution network fault model, and a better islanding result is obtained. The example analysis shows that the strategy proposed in this paper can accurately realize the optimal strategy of island division under local grid fault, ensure the restoration of power supply of important loads, and verify the effectiveness and superiority of the strategy.

With the largescale integration of renewable energy such as wind power and photovoltaics into the new power system distribution network, the traditional centralized economic dispatch method is facing difficulties due to the distributed management and control mode presented by a large number of scattered clusters of wind power and photovoltaics. Based on traditional consistency algorithms, a distributed economic dispatch model for edge clusters composed of wind and photovoltaic power is proposed. Firstly, the edge cluster models of wind and photovoltaic power and their volatility characteristics are presented; Secondly, traditional consistency algorithms and optimization models for implementing economic scheduling were derived; Thirdly, based on this, a consistent economic dispatch distributed algorithm for wind and photovoltaic edge clusters is proposed by combining the wind and photovoltaic edge cluster models; Fourthly, taking a practical system as an example, the proposed algorithm model was simulated and verified, and the results showed the effectiveness of the proposed model.

Catalytic reforming of palm kernel shell (PKS) pyrolysis volatile matter was studied using char (Char) and activated carbon (AC) as catalysts under microwaveassisted heating. The impacts of different carbonbased catalysts on the composition of products were studied. The possible reaction pathways during catalytic reforming of PKS pyrolysis volatile matter under microwaveassisted heating were also investigated. During catalytic reforming of pyrolysis volatile matter, the catalyst promoted the yield of gas product, which led to the decrease of biooil yield. Compared with the Char, AC not only has higher catalytic activity to facilitate the conversion of biooil to gas, but also exhibited better selectivity for the formation of singlering aromatic compounds (especially phenol) in biooil. Using the AC catalyst, the concentrations of the singlering aromatic compounds reached 84.25%. The catalyst mainly promoted the secondary reactions such as demethoxylation reaction and dehydrocarbylation reaction.

This paper presents an integrated energy system (IES) multiagent game cooperative optimal scheduling strategy considering carbon quota and integrated demand response. Firstly, based on Stackelberg game theory and considering the initiative of demand side and energy storage side, a multiagent game interaction framework of source – load – storage is established. Secondly, with IES operators as leaders and energy storage operators and users as followers, the decisionmaking model of each stakeholder is established. In order to guide users to use energy scientifically and reduce system carbon emissions, a dual incentive policy based on carbon quota and realtime price guidance is introduced into IES operator model, and energy selling price and internal unit output plan are formulated with the goal of maximum net profit. Finally, genetic algorithm combined with CPLEX twostage algorithm is used to solve the proposed multiagent game model. The simulation results show that the proposed dual incentive strategy and game model can effectively take into account the interests of all parties, reduce the carbon emissions of the system without harming the interests of all parties, and realize the multiagent lowcarbon collaborative operation of IES.

This paper analyzes the working mechanism of each components of the proton exchange membrane fuel cell (PEMFC) system, and the mathematical mechanism models of stack, anode, cathode, proton exchange membrane, and temperature of the PEMFC are established using MATLAB/Simulink software, furthermore, the physical model of thermal management system is built in the Simulink/Simscape environment, and the mathematical and physical models are integrated into a complete PEMFC system simulation model. Typical malfunctions, including the radiator fan failure and insufficient coolant flow failure, are injected into the PEMFC system simulation model to analyze the influence of malfunctions on the performance of PEMFC. The simulation results are basically consistent with the experimental results, which indicates that the proposed model is reasonable and accurate. Moreover, the generation mechanism of malfunctions is figured out through malfunction simulation of the thermal management system, which provides a reference for malfunction diagnosis.

The photovoltaic (PV) module slicing technology is an effective method to improve the module power, but the change of the structure brings some difficulties to the modeling of PV module output performance under complex situations. In this paper, a performance simulation method for halfcell photovoltaic module under shading conditions is proposed. To simulate the output performance of halfcell PV module under shading conditions, the method is based on the single cell and combined with the series and parallel structure of the equivalent circuit. Finally, four different shading experiments are used to verify the accuracy of the algorithm. The average deviation between the measured values and the calculated power of the PV model is 2.42%, which proves that the method has high accuracy. In addition, the output performance of halfcell and fullcell PV module under different shading conditions is compared. The results show that halfcut PV module have more obvious advantages than fullcell module under most shading conditions.

The boost capability of conventional Buck/Boost converter is weak and the power switches suffer from high voltage stress (equals the voltage at the highvoltage side (HVS)), reducing the conversion efficiency. Further, since the HVS current pulsates greatly, large capacity capacitors are required to meet the requirements of current ripple, decreasing the system reliability. Therefore, this paper proposes an improved Buck/Boost converter. By introducing one switch, one inductor and two capacitors into the conventional topology, the proposed converter has continuous input and output current, which greatly reduces the current stress of HVS filter capacitor. The voltage gain in Boost mode is increased to (2D₁)/(1D₁), and all switches have the same low voltage stress, which equals the difference between the voltages at lowvoltage side (LVS) and HVS, so it has higher conversion efficiency. The operation principle, steadystate characteristics, dynamic model and control strategy are analyzed in detail. Its feasibility is verified on a 100 W/120 kHz prototype. The experimental results demonstrate an enhanced efficiency performance over wide operating operations with a maximum efficiency of 95.6%.

With the increasing proportion of wind turbines connected to grid, the security and stability problem caused by wind farm separated from power grid are becoming more and more serious. So it is particularly important to improve DFIG fault ride through capacity and reduce the occurrence of offgrid events. In view of the problems, existing DFIG fault ride through control schemes are introduces first. Considering that frequently switched of DC chopper circuit is easy to cause voltage waveform distortion and supercapacitor control scheme has high economic cost, the DFIG fault ride through control scheme based on smart chopper circuit is further proposed. The proposed method is upgraded based on DC chopper circuit. It connects the unloading resistance with the DC bus through DC/DC converter and introduces active powerDC voltage droop control link to adjust the circuit resistance power dynamically during fault period. Besides it sets two modes of high and low voltage crossing, which can be started automatically according to grid connected voltage. Finally, the smart chopper circuit control scheme is verified in Matlab/Simulink. The simulation results show that considering the DC bus voltage suppression effect, the regulation time for voltage recovery, the distortion degree of rotor current and the economic cost of schemes, fault ridethrough control of DFIG based on smart chopper circuit has the most advantages.

In order to achieve rapid and accurate assessment of transient voltage stability in the power system following the integration of wind farms into the grid, a transient stability assessment metric is proposed based on Convolutional Neural NetworksLong ShortTerm Memory (CNNLSTM) and attention mechanisms. To better capture spatial and temporal correlations in the input data, feature dimensionality reduction is carried out using Kernel Principal Component Analysis (KPCA). Addressing challenges related to decreased shortcircuit capacity and increased shortcircuit current levels in highproportion renewable energy grids, an active support measure is introduced by installing superconducting fault current limiters to restrict shortcircuit current levels during fault processes and maintain voltage stability at grid connection points. Finally, simulations and data collection are performed on an IEEE39 node system with wind power integration using PSDBPA. The results indicate that the KPCA approach effectively screens features of significant importance in the transient stability assessment of power systems. The proposed evaluation metric demonstrates higher discriminative capability, and the suggested improvement measures are observed to play a positive role in enhancing transient voltage stability in highproportion wind power integration systems.