As the proportion of renewable energy and variable loads in the distribution system gradually increases, the uncertainty of power flow in the distribution network will affect the optimal network topology. Since distributed generation and demand response are affected by the time factor, the topology obtained by modeling at a single time period is difficult to be optimized at different times of the day. To address this uncertainty, this paper proposes a secondorder cone optimizationbased distribution network reconfiguration model for multitemporal tidal flow analysis for billing and demand response. By considering the "sourcestorageload" structure of the actual distribution system, an optimization problem with the objectives of network operation cost and switching operation cost is established, and the secondorder cone relaxation is used to transform the nonconvex search space into a convex feasible domain for fast solution. Experimental results on an improved IEEE 33 node distribution network show the superiority of the proposed method over traditional methods in terms of accuracy and solution speed.

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.

In order to reduce the influences of renewable energy power fluctuations on power systems, an energy storage configuration optimization method considering renewable energy power probability distribution is proposed in this paper. Firstly, calculate and count the renewable energy power fluctuations at different time scales, and determine the probability distribution characteristics of renewable energy power. Secondly, according to the probability distribution characteristics and the gridconnected index of renewable energy, the configuration optimization model of energy storage considering the renewable energy timescale and power fluctuation is set up. Thirdly, based on the given constraints and time scale, calculate the minimum energy storage charging and discharging power where the fluctuations meet any set probability levels, thereby determining the rated power, capacity and initial state of the energy storage. At last, through calculation and analysis using the data measured from a 50 MW photovoltaic power station, the method is proved to be correct and effective. This method only compensates the fluctuated power that does not meet the fluctuation index, and has no impact on the power that has already satisfied.

Biomass is a rich and renewable carbon source. The efficient production of fuel ethanol with sugar, starch, straw cellulose or other biomass feedstocks can reduce the demand for fossil energy, among which the second generation fuel ethanol with lignocellulose as feedstock has broad prospects for development. Compared with fossil energy, fuel ethanol has the advantages of environmental protection, economy and renewable energy, but its production technology, economic benefits and environmental impact still need to be further studied. In recent years, through the optimization of fuel ethanol refining system and the study of the whole life cycle analysis, the progress of fuel ethanol technology has been effectively promoted, and the related research on carbon emission reduction of fuel ethanol has been promoted. This paper mainly discussed the development of fuel ethanol production technology in recent years, focused on the research progress of simulation optimization and carbon emission reduction of fuel ethanol system, and looked forward to the development trend of fuel ethanol, in order to provide reference for the sustainable development of fuel ethanol.

In order to achieve high efficiency and clean combustion of crop straw in Bashang area, typical naked oats straw was selected as the research object to analyze the pyrolysis characteristics. The pyrolysis atmosphere environment in the combustion process was created by simulating flue gas with mixed gases. The thermogravimetric analyzer was used to study the thermogravimetric characteristics and the influence of temperature rise rate on the mixed gas atmosphere composed of air and N2, CO2, and O2 in different proportions. The AKTS software was used for kinetic analysis. The results showed that: the pyrolysis process of naked oats straw was divided into three stages, which were drying stages (30~140 °C), volatilization stages (140~370 °C), carbonization stages (370~900℃). Gas atmosphere mainly affected the pyrolysis of carbonization stage, drying and volatilization stage had little effect, heating rate affects volatilization and carbonization stage, the faster the heating rate, the greater the reaction rate. When the pyrolysis atmosphere was 15%O25% CO280% N2 mixed gas (gas 2), the activation energy required for pyrolysis process was the least, and the average activation energy was 139.86 kJ/mol. The results provided a certain theoretical basis for the energy utilization of biomass straw in the alpine Bashang area.

Reverse electrodialysis (RED) technology relies on the permeation selectivity of ion exchange membranes (IEMs) and the conversion of salinity gradient energy of working solutions into membrane potential, which can be used for power generation or driving electrochemical reactions. The progress in domestic patents in RED field was introduced. First, the tradeoff assessment mechanism of suitable IEMs for a RED system was discussed from the perspectivesof membrane resistance, membrane thickness, ionic selectivity, ionic exchange capacity, fouling resistance, antibacterial ability and stability. Accordingly, the IEMs modification methods and optimization development directions were analyzed. Then, the development and patent layout of RED technology in the fields of power generation, hydrogen production, wastewater treatment, seawater desalination, were reviewed emphatically. Besides, several energy conversion technical routes were ascertained, including (thermal energy→)salinity gradient energy→(electricity→) hydrogen, etc. The regeneration methods and development process of the cycling working solutions were elucidated. The RED technology is suggested to be coupled with the electrodialysis, renewable energy generation, and lowgrade heat recovery technologies, which is an effective strategy to achieve complementary advantages of various technologies and beneficial to improve the output capacity and energy efficiency.

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.

A solar thermochemical reactor was designed based on a 5 kW non coaxial concentrator simulator, and a mathematical model of the thermal performance of the reactor under concentrated irradiation was established. The model was used to calculate the influence of solar simulator power, material emissivity of reactor inner wall, working pressure and inlet velocity on the temperature distribution in the reactor. The results show that increasing the power of the solar simulator and the emissivity of the inner wall of the reactor will increase the temperature distribution of the reactor centerline. At the same inlet velocity, the temperature distribution of reactor centerline increases with the increase of working pressure. Under the same working pressure, the temperature distribution of reactor centerline increases with the increase of inlet velocity. The research results have certain reference significance for reactor parameter optimization and thermal stress analysis.

The photovoltaic (PV) array fault detection method based on Spread Spectral Time Domain Reflectometry (SSTDR) has detection blind spots and attenuation characteristics. It is necessary to study the property of the detection signal to improve the fault detection performance. Firstly, the transmission behavior of the detection signal in the PV array is studied to explore the influence of different signal parameters on the detection range and accuracy. Secondly, based on the dynamic model and layout pattern of the PV cells, a simulation platform for PV array fault detection is established. The simulation results are validated through a simulated experiment of an opencircuit fault. The results show that improving the signal can effectively enhance the ability to identify correlation peaks, increasing the number of PV components detected by four units. Finally, the influence of blind area and attenuation characteristics is comprehensively analyzed. A signal selection strategy of PV array based on SSTDR is proposed to determine the fault detection distance and the optimal parameters of test signal.

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.