In a weak grid, due to the existence of grid impedance, the natural resonant frequency of a new energy grid-connected LCL filter will shift, and the traditional active damping control strategy cannot guarantee the system stability. Moreover, as the proportion of new energy power generation in the power system continues to grow, how to reduce the operating costs is a hot topic for research. Therefore, a novel control strategy based on grid-connected current and common coupling voltage feedback is proposed in this paper, which not only provides active damping to suppress LCL resonance, but also reduces the use of sensors. In addition, it has a strong adaptability under wide-ranging changes in grid impedance. Simulation and experimental results show that, compared with that under the traditional control strategy, the practical range of weak grid under the improved strategy increases, the system stability is enhanced, and the capability to suppress harmonics is raised, indicating that the quality of grid-connected current is well improved.

The influence of ash deposition on the output characteristics of photovoltaic (PV) modules and the deposition rule of pollution particles on the modules' surface are studied, which are helpful for formulating an ash removal scheme and improving the efficiency of photoelectric conversion. The PV array on the roof of a fan hall in North China Electric Power University is taken as the research object, and an artificial ash distribution experiment was carried out to explore the influence of different ash deposition amounts on the output power, current and voltage of modules. To determine the influence of one single factor on the deposition of pollution particles, a numerical model of particle deposition is established using COMSOL under the same conditions as those in the natural deposition test of PV modules, and the influences of wind speed, humidity, particle size and pollution concentration on the deposition of pollution particles on the surface of PV modules are simulated and analyzed. Test results show that ash deposition has little influence on the working voltage, but a great influence on the output power and working current. When the ash deposition density is 5.07 g/m², the changing rates of output power, current and voltage are 8.71%, 6.48% and 0.40%, respectively. Simulation results show that when other conditions are the same, the deposition amount of particles decreases first and then increases with the growing wind speed and particle size, and the minimum value is reached at the wind speed of 3 m/s and particle size of 15 µm. Under the same conditions, the particle deposition amount increases with the growing humidity and pollution concentration.

As power lithium-ion batteries play a key role in the electric vehicle industry, ensuring their working reliability has become a research hotspot at present. In this paper, the materials and manufacturing processes of lithium-ion batteries are reviewed. The battery state estimation and remaining useful life prediction methods are summarized in detail, and the advantages and disadvantages of these methods are discussed. From the perspective of battery management system, the relevant knowledges of equalization management system and thermal management system are sorted out in turn. From the perspective of electric vehicle hybrid energy storage system, the performance degradation mechanism under actual working conditions and the relevant technologies are elaborated upon. Finally, the status quo of key technologies related to the reliability of power lithium-ion batteries used in electric vehicles is summarized from four aspects, and the development possibilities in the future are forecasted.

To ensure the safety of new energy vehicles during the entire period of use, it is necessary to conduct health monitoring for the full life cycle of lithium-ion batteries. Aimed at the low learning rate due to the small capacity of training data set for the remaining useful life (RUL) prediction model based on neural network and the duplicate collinearity of the extreme learning machine(ELM) method, a method for augmenting the training data set is proposed. In addition, based on the improved ELM, an RUL prediction model for the full life cycle of lithium-ion battery is built. First, the early operation data of battery is extracted to formulate health factors, and the Akima interpolation method is used to augment the amount of training data. Then, the salp swarm algorithm is used to improve the ELM network, and the RUL prediction model for the full life cycle of lithium battery is established. Finally, the NASA battery data set is used to validate the model. Experimental results show that the proposed method for augmenting the training data capacity is effective, the capacity tracking capability of the RUL prediction model in full life cycle is strong, and the prediction error is small.

To effectively reduce the inconsistency of series lithium-ion batteries in use, a novel equalization topology with the combination of a Cuk equalizer and a double-layer selector switch is proposed, which can quickly realize the energy transfer between any single cells and improve the equalization speed. According to the characteristics of the open circuit voltage (OCV)-state-of-charge (SOC) curve, piecewise equalization is adopted with voltage and SOC as equalization variables, and a fuzzy logic control (FLC) algorithm is designed to dynamically adjust the equalization current to reduce the equalization time and energy loss. Matlab/Simulink software is used to build a model and conduct simulations. Experimental results show that the energy transfer topology proposed in this paper saves of the equalization time by 22.17% compared with the traditional topology of energy transfer between adjacent cells of Cuk circuit. In addition, compared with the mean difference algorithm, the FLC algorithm improves the time efficiency by more than 30% and the energy efficiency by about 11% under static and charge-discharge conditions. Therefore, the feasibility of the proposed equalization scheme is verified.

The state-of-charge (SOC) balance control of series-connected lithium batteries is of significance to the improvement of battery life. In this paper, a hybrid SOC equalization scheme based on active-passive equalization is proposed against the SOC discreteness of a lithium battery cell, in which the topology of the active equalizer is realized by a multi-winding flyback converter, and the passive equalizer consists of a resistor and a switch connected in parallel at both ends of the cell. The operating principle for the hybrid SOC equalizer is analyzed in detail, and the effect of SOC discreteness on equalization speed is discussed in terms of control strategy. The standard deviation representing the degree of discreteness and the coefficient representing the reasons of discreteness are introduced to realize the fast equalization of SOC under different discrete conditions. The topology of the proposed hybrid equalizer and the corresponding control scheme can optimize energy consumption and balancing speed, and experimental results verify the feasibility of theoretical analysis.

The hybrid energy storage system can effectively alleviate the frequency instability caused by the strong fluctuation and randomness of wind power output. In this paper, a hybrid energy storage system composed of batteries and super capacitors is taken as the research object, and a hybrid energy storage capacity allocation method is proposed. First, adaptive wavelet transform is adopted to perform a primary distribution of the wind power output, and the grid-connected power and energy storage power satisfying the requirements are obtained. Second, HHT transform is used to decompose the energy storage power, and a series of fluctuating power components and the instantaneous frequency of each component are obtained. Third, the cutoff frequency is determined according to the instantaneous frequency, the power components with a frequency higher than the cutoff frequency are allocated to super capacitors, and the rest are allocated to batteries. Finally, the rated capacity and rated power of the energy storage system are configured according to the energy storage power of batteries and super capacitors, respectively. Simulation results show that adaptive wavelet transform and HHT transform can effectively decompose the wind power output, thus realizing the stabilization of wind power output, as well as the capacity and power allocation of hybrid energy storage system.

Aimed at the voltage distortion and current distortion of power grid with pulse load, a three-level unified power quality conditioner(UPQC) with supercapacitor energy storage is designed. A method based on artificial neural network is proposed to control the series and shunt compensation units, and a method based on double closed-loop PI control is used to control the supercapacitor energy storage unit. The series compensation unit compensates voltage to maintain the stability of load voltage and ensure the power demand of load, while the shunt compensation unit compensates current to maintain the stability of supply current and avoid the continuous and large impact on power grid. The supercapacitor energy storage unit charges and discharges on the DC side to maintain a constant voltage on the DC side and ensure the normal operation on the series and shunt sides. The proposed method eliminates the complicated coordinate transformation process and avoids the phase lag caused by multiple filters. Simulation experiment results show that the proposed topology and control strategy are helpful for improving the power quality of power grid with pulse load.

The grid-connected operation of an energy storage system is realized by a converter. Due to the low switching frequency of the conventional converter, there exists time delay in sampling and calculation, which will lead to poor transient characteristics of the energy storage system and even instability of the whole power grid. In this paper, model predictive control(MPC) is used to achieve a fast power response of energy storage system and avoid the influence of time delay. A power weight value function is introduced to calculate the optimal output voltage of energy storage converter in the MPC control of active and reactive power. To solve the problem of inaccurate MPC model caused by the parameter deviation of filter inductor, inductance error compensation control is used to improve the model accuracy. Through Matlab/Simulink simulations and experimental results, it is verified that the proposed scheme can improve the transient characteristics of energy storage system and effectively eliminate the influence of error on the MPC control performance.

The converter with constant-power control in a flexible DC distribution system has characteristics of constant-power load, which will reduce the system damping and adversely affect the system stability. To address this problem, a superconducting magnetic energy storage (SMES) device is introduced to improve the system stability. A feed-back control model of the flexible DC distribution system is derived, and the effect of constant-power load characteris-tics of the converter on system stability is investigated by frequency-domain analysis. Combined with a mathematical model and frequency-domain analysis, it is also pointed out that the SMES device can improve the system stability by introducing positive damping to grid and increasing the phase margin of the system's open-loop transfer function at the shear frequency. To prevent over-high voltage at both ends of the superconducting magnet, the DC/DC converter which connects the SMES device with the DC distribution network needs to have certain voltage regulation performance. Therefore, the SMES device with a modular multilevel DC/DC converter (DC-MMC) is studied, which can adjust the number of sub-modules flexibly to set the voltage ratio of the converter. Moreover, the DC-MMC can control the voltage at both ends of the superconducting magnet while realizing a bidirectional flow of energy in the converter, thus protect-ing storage device. The feasibility and effectiveness of the SMES device with DC-MMC in improving the stability of flex-ible DC distribution system is verified by time-domain simula-tion waveforms.