许继电气

In view of the high precision requirements for energy storage battery cell voltage sampling and battery cluster voltage,current,and insulation detection,this paper presented a liquid cooled battery management system based on ADBMS6830,which uses ADI's ad-vanced AFE ADBMS6830 and TI's precision ADC ADS1120 to achieve accurate measurement of battery voltage information,cluster volt-age,cluster current,and system insulation impedance detection.The test results show that the battery voltage acquisition can achieve mea-surement errors within±2 mV within the full temperature range of standard voltage 3.3 V,cluster voltage acquisition can achieve testing ac-curacy of±0.06%,cluster current acquisition can achieve testing accuracy of±0.06%,and insulation detection can achieve testing accuracy of±5%.The proposed liquid cooled battery management system has been applied in a series 5 MWh liquid cooled energy storage system,verifying the feasibility of the system.

To enhance the transient stability of power system with a high proportion of power electronic devices,an optimized control strategy for static var compensators(SVC)based on the wide area measurement system(WAMS)is proposed.The system obtains real-time generator bus voltage phasors via synchronized phasor measurement unit(PMU)and constructs a particle swarm optimization model with the objective function of minimizing the generator active power and mechanical power deviations.By dynamically calculating the optimal reactive power injection of the SVC using voltage amplitude and phase angle sensitivity coefficients,the method introduces the sensitivity coef-ficients to characterize the dependency of generator active power on SVC reactive power,which enables coordinated damping of multi-generator rotor angle oscillations.The IEEE 14-bus system is simulated on the DIgSILENT Power-Factory platform,and the simulation results show that the proposed strategy can effectively reduce rotor angle oscil-lation magnitude and slope,extending the critical clearing time by 40 ms.Compared with traditional local control methods,this approach overcomes the limitation of single-mode oscillation damping and utilizes WAMS information to achieve multi-machine coordinated control,providing a new perspective for improving the transient stability of complex power system.

Multi-terminal flexible DC transmission line protection faces various fault types and is susceptible to factors such as transition resistance and noise.To address this,a fast-action protection method for the entire flexible DC line using single-ended voltage gradient energy values is proposed,which can protect the entire length of the line based solely on single-ended measured voltage.The voltage fault characteristics inside and outside the flexible DC line are analyzed,and an improved voltage gradient algorithm is introduced to construct a protection initiation criterion.Furthermore,a full-line fault protection criterion based on energy value comparison is constructed,and fault pole selection is achieved based on the different ranges of positive and negative energy ratios under unipolar or inter-pole faults.Simulation verification shows that the proposed method can quickly identify faults inside and outside the zone,determine the fault pole,and exhibits good noise immunity and high resistance tolerance.

Aiming at the problems of poor dynamic performance of traditional VSG technology and difficulty to de-termine the optimal values of important parameters J and D,a VSG control and parameter optimization strategy based on droop control and neural network prediction was proposed to realize dynamic adjustment of key parameters J and D in VSG technology.The proposed strategy applied the active power-frequency droop control to the control algorithm of VSG.Then,simulated the rotor motion equation and the voltage and reactive power control characteris-tics of synchronous generator,the small signal analysis model of VSG was established,and the initial setting of key parameters rotational inertia and damping coefficient were completed.Finally,an artificial neural network was es-tablished for analysis learning and network training,and the weight was adjusted to change the VSG moment of in-ertia and damping coefficient.The error between the output and the input was compared by the error function,and the parameter reached the expected value after multiple learning and training.The neural network optimization algo-rithm was combined with the droop control strategy to optimize the VSG control strategy.Traditional VSG control,constant parameter droop control and adaptive parameter droop control based on neural network optimization were used to simulate a numerical example,and the results showed that,compared with traditional VSG control,the pro-posed adaptive parameter droop control based on neural network optimization reduced the maximum frequency varia-tion by 26.7%,and the frequency stabilization time by 0.25 s.The strategy was effective.

Accurate short-circuit fault current calculation is important for device selection, parameter design and protection research of flexible DC grid. To solve the problem that existing fault current calculation methods do not consider the pole-to-pole coupling of DC lines, a short-circuit fault current calculation method based on phase-mode transformation is proposed. First, the equivalent fault models of the converter station and DC line are established. Then, the phase-mode transformation is used to achieve electrical decoulping of positive and negative poles, and the node impedance matrix of the DC grid in the mode-domain is obtained. Subsequently, combining the fault boundary conditions of the DC grid, the fault current of the DC grid is calculated in the complex frequency-domain, and the fault current in the time-domain is obtained by using vector fitting. Finally, the proposed fault current calculation method is verified by PSCAD/EMTDC. The simulation results show that the proposed method can accurately calculate the DC fault currents after the DC fault occurs and before the converter station blocks.