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With the frequent occurrence of electromechanical oscillation in the power systems, the fast response characteristics of the photovoltaic (PV) power generation system are used to actively damp the electromechanical oscillation in the power system. The proportion and position of PV generations in the system are usually different, therefore, the dynamic process of PV damping the grid electromechanical oscillation will also be changed. This paper divides the conventional system into two parts: the power system and the infinite power grid, the steady-state output of the PV generation system is equivalent to the active output current Id0 and the reactive output current Iq0. The analysis conclusions of these two parts shows that: the inertia level, synchronization and damping effect of the conventional system will increase with the increase of Id0, and first decrease with the increase of Iq0, then increase rapidly, and then decrease. Moreover, the closer the PV module to the electromechanical oscillation source, the better the oscillation damping effect. Finally, this paper verifies the conclusion correctness through MATLAB/Simulink.

This paper studies the cooperative absorption mechanism of wind-photovoltaic power generation and electric vehicle interconnection. Markov decision process is used to model the two random events of wind-photovoltaic generation and electric vehicle charging and discharging. Based on this, a multi-objective bilevel optimal charging and discharging scheduling model is proposed for the interconnection of wind-photovoltaic generation and electric vehicle based on cluster. The upper dispatching agency considers the consumption of wind-photovoltaic power generation and the economy of grid side operation, and EV group institution takes charge-discharge fees with battery internal losses into account. When solving the problem, making full use of the correlation between the structural features and variables between the upper and lower layers, the basic strategy of information exchange between the upper and lower layers is constructed, and based on the hierarchical features and future situation simulation, the double-layer optimal scheduling strategy is obtained. Finally, the effectiveness of the proposed optimization strategy is simulated and analyzed in IEEE 30 nodes system.

To quantify the oxygen content in molten salts, we examined the performance of an yttria-stabilized zirconia solid electrolyte oxygen sensor with a Bi/Bi2O3 reference electrode, focusing on its output accuracy. When the above sensor was tested in a flow of gas with known oxygen partial pressure, $$p_{O_2}$$ , a linear relationship between $$lgp_{O_2}$$ and the electromotive force (EMF) was observed, and the correlation slope exhibited a positive deviation from Nernstian behavior. EMF measurements performed in molten NaCl–KCl indicated that the oxygen content of this salt mixture increased with increasing oxygen partial pressure in the covering gas, in agreement with Henry’s law. Moreover, the EMF exhibited a linear decrease with increasing melt temperature of molten NaCl–KCl, in agreement with the theoretical model. Finally, a relationship between the structure of molten NaCl–KCl and its oxygen diffusion behavior was established. As a result, the developed sensor was demonstrated to be well suited for determining the oxygen content of molten salts.

Thioglycolic acid (TGA)-coated colloidal Ag2S quantum dots (QDs) emitting in the near-infrared (NIR) region upon excitation by an 808 nm diode laser were synthesized. The observed photoluminescence (PL) was attributed to the presence of ligand-modified Ag2S on the QD surfaces and could be easily controlled by a simple dilution process due to the concentration-dependent surface structure of the colloidal QDs. Upon dilution of the solution, the PL intensity initially increased before later decreasing, with a blueshift being observed in the PL spectra. These phenomena can be accounted for by the aggregation of QDs due to a decrease in the content of ligand-modified Ag2S on the QD surfaces upon dilution, which in turn affected the fluorescence resonance energy transfer (FRET), and re-emission of the surface energy level.

Several Ir/IrO2 pH electrodes were prepared by a cyclic thermal oxidation process via dip-coating in a concentrated solution of NaOH. A hydrothermal hydration treatment at 220 °C for 24 h was used to address the problematic potential drift that is common in Ir/IrO2 pH electrodes. The electrodes that were treated by the hydrothermal method exhibited good stability and high sensitivity compared to those that were hydrated at room temperature. The reasons for this improvement were investigated by Raman spectroscopy, X-ray photoelectron spectroscopy, and field emission scanning electron microscopy. The results suggested that the hydrothermally treated electrode had a more orderly crystal arrangement and a higher content of OH− groups, which drove improvements in the performance of electrode by modification of the Ir/IrO2 structure. The relationship between the electrode structure and performance was investigated and discussed in detail herein.

Ag2S quantum dots (QDs) coated with thioglycolic acid (Ag2S QDs-TGA) have been synthesized in an organic solvent via a stepwise addition of reagents. When excited by a 980 nm laser, the near-infrared-emitting colloidal Ag2S QDs-TGA exhibit upconversion luminescence (UCL). The observed photoluminescence (PL) was attributed to the presence of ligand-modified Ag2S on the QD surfaces. Hence, upon dilution of the solution, the PL intensity initially increased before subsequently decreasing, accompanied by a blue shift in the PL spectra. The PL phenomena can be attributed to the increase in the amount of ligand-modified Ag2S on the QD surfaces upon dilution, which in turn affected the fluorescence resonance energy transfer (FRET) and re-emission of the surface energy level. The relations between the emission intensity of Ag2S QDs-TGA and the excitation power are investigated, and the results confirm that the UCL in Ag2S QDs-TGA can be ascribed to a two-photon-assisted absorption process via a real energy state.

It is an important part for the power system operation risk control to identify the critical lines. Fluctuation of wind power and fluctuation of load will have a great influence on power transmission and distribution, which will lead to the change of critical lines. Based on probabilistic load flow (PLF) analysis, the risk theory is introduced to put forward, and probabilistic flow betweenness considering uncertainty of wind power and load is presented for critical line identification, which reflects the influence of power grid structure characteristics, change of system running state and uncertain factors on power transmission. It can identify critical lines more accurately. Simulation calculation on CEPRI-36 bus system integrated with wind farms and IEEE-39 bus system with wind farms verify effectiveness of this method. It is able to search for the critical lines according to system running state in actual application, so as to adopt security control measures for the system.

The optimal charge and discharge schedule of EVs is studied under distribution network considerring wind power. Markov decision process is adopted to model the randomness of supply and demand. Two-level scheduling model of electric vehicles with electric vehicle agents are adopted. The electric vehicle agents are responsible for collecting the real-time charging-discharging demand of electric vehicles in the region and reported to the upper dispatching center. The goal of the upper dispatching center considers the power losses in the distribution network, load variance and the matching degree between EV charging-discharging and wind energy. The goal of the lower agent considers the EV charging-discharging fees and EV charging battery losss costs. When deciding the optimal charging strategy, two-level Rollout methodis adopted considering the the effects on future decisions by the current decisions. Finally, the optimal results under four different strategies are simulated on the IEEE 30 nodes distribution network system.

Voltage is one of the measurement standard of power quality. The issue of low voltage in distribution network seriously affect the social economic development and people's life. Consequently, it would optimize low voltage investment program, clear direction of low voltage investment and provide decision support for the management of low voltage. Canopy- Kmeans is one of the widely used classical partition clustering algorithm. Support vector machine is a kind of sorting algorithms that could take full advantage of limited learning sample to acquire generalization. Both Canopy-Kmeans and Support Vector Machine have better behavior and precision rate. However, the runtime and RAM would be the bottleneck in the case of large amount of data. The application of data mining algorithm based on big data is particularly important. This paper take advantage of distributed Kmeans and SVM algorithm to realize diagnosis model of cause of low voltage based on big data platform of Hadoop. Experiments have shown that this method has a higher accuracy and reliability compared to traditional Kmeans and SVM algorithm.

With the increasing voltage class of power equipment, the turn number of winding equipment becomes more great and the coupling between the turns becomes stronger. As a result, it is difficult to solve circuit equation by analytical algorithm. This paper provides a method using waveform relaxation (WR) to solve the circuit equation. This method could be applied in calculation of complex computation, such as turn- to-turn voltage calculation of winding equipment and flow calculation of big power grid. Before calculation, this paper provide a method to calculate electromagnetic parameters of an air-core reactor. At last the paper presents a calculating example and experiment. From the experiment, the method provided in this paper proves its veracity and superiority.

Accurately mastering the capability of wind power accommodation is conducive to construction planning of wind plant and provide auxiliary to dispatching decision in actual operation. Based on deep analysis of key factors influencing accommodation capability of wind power basic idea and method were proposed to manoeuvre wide and flexible adequacy resources involved in system regulation. Comprehensively considering technical characteristics of various power generations and such constrains as the balance of power and thermal loads and transfer capacity and taking the maximum accommodation capability of new energy as objective function, a model is built to analyze new energy accommodation capacity of power grid. Taking shanxi province in China, which is rich in new energy resources, as calculation example, the changes of new energy accommodation capability were simulated and analyzed under different scenes of introducing in different flexible resources.

A large number of wind farms access power system, which will bring new challenges to the security and stability of the power grid, because the stability of the power system is greatly influenced by the dynamic performance of the wind turbine. This paper describes a performance appreciation method of wind farm, which is proved practical and effective by the measured data of the wind farm.

The low excitation limit curve of generator which is tuned correctly can helps to ensure the normal operation of generator, because the generator and power system will be separated if the voltage of auxiliary power is too low, loss of field protection is in operation or static stability of generator is not enough. This paper describes a tuning method of low excitation limit curve of Generator. Experiment proved that the method is practical and effective.

The voltage of power grid will drop when the units pump water in the pumped storage power station.This paper uses the method of simulation and field test to study effect of reactive power regulation on the power grid in the pumped storage power station,which will provide reference for voltage regulation of pumped storage units and meet the peak load regulation of power grid and acceptance of wind power requirements.

This paper introduced several types of distributed wind turbines, discussed the impact on grid-connected and put forward the measures. Combined with the wind data in Shanghai area, economy of the currently used widely distributed wind power generator was calculation. The results show that, the distributed wind power generator had better stability and economy, suitable for application in the surrounding areas of the city.