Feng Xue

The limiter in grid-connected inverter control may cause sustained oscillation in the system. The large-signal impedance model is provided since the traditional small-signal impedance model cannot accurately describe the characteristics of the limiter. In this paper, there are three established large-signal impedance models of grid-connected inverters that take into account the limiter in the phase-locked loop (PLL), the limiter in the current control loop and the limiter in the pulse width modulation (PWM). Based on the established models, the influences of these different limiters on the output impedance characteristics of the grid-connected inverter are discussed. Furthermore, the stability of the system considering the influence of different limiters is analyzed and the oscillation frequency and amplitude of the system are predicted. The simulation verifies the accuracy of the large-signal impedance model and the predicted oscillation frequency and amplitude.

In this paper, a blockchain-enabled energy trading method is proposed to deal with the inefficiency and security issues in energy trading for electric vehicles in smart grids. It includes the design of a smart contract and the excitation mechanism of energy sharing. The credit points of each vehicle as a node are considered in the design of the smart contract, which is used to supervise the process of energy trading. A strategy to estimate the credit points of each node and describe the excitation mechanism is illustrated. The connection between the credit points and the probability that a node would be accepted for energy trading has been established. To control the energy trading access, a double auction method is used to choose the part of the nodes participating in energy trading. Only selected nodes with winning bids can supply or request energy from the blockchain-based platform. Then it reaches the conclusion that the higher the credit points they have, the more trading initiative they would have during the energy transaction and transmission. The smart contract design and the excitation mechanism proposed in this paper would reward the vehicles that perform well and punish the beguiling vehicles for regulating the trading process.

The traditional black-box Thevenin equivalent method cannot analyze the influence mechanism of wind power integration on Thevenin equivalent parameters. With the increase in wind power penetration, it will be difficult to accurately assess the voltage stability of power systems with wind power. Therefore, a Thevenin equivalent analytical method is proposed to analyze the voltage stability of a power system with wind power. This method adopts the equivalent model of wind power integration based on the current source model. It establishes the Thevenin equivalent analytical model for power systems with wind power by dividing the node types. Then, the analytical expressions of the Thevenin equivalent parameters are derived based on two equivalent modes to characterize the mechanism of wind power integration on the Thevenin equivalent parameters. In addition, the calculation flow chart of the voltage stability criterion is formulated based on the analytical value of the Thevenin equivalent impedance under different load growth ratios and wind power penetrations. Finally, a case study is conducted on the improved IEEE 39 node system with wind power. The results demonstrate the feasibility and effectiveness of the proposed Thevenin equivalent analytical method, which can more accurately judge the voltage stability of the power system with wind power.

Boosting the capacity of grid-connected wind farms will greatly contribute to increasing the share of sustainable energy in the global generation mix. It is imperative to study the way to quantitatively assess the maximum capacity of grid-connected wind farms in combination with power system stability characteristics. In this work, a method to evaluate the maximum capacity of grid-connected wind farms considering the joint constraints of frequency and voltage stability is proposed based on the global intrinsic property of frequency stability and the local characteristic of voltage stability. Firstly, the maximum capacity of grid-connected wind farms in the power grid with high wind power penetration is assessed globally based on the frequency stability constraints, and then locally considering the voltage stability constraints of each local power grid. Further on, a quantitative method to evaluate the capacity of grid-connected wind farms is proposed based on the correlation between the local static voltage stability margin and the local capacity of grid-connected wind farms, as well as the global constraint of the maximum capacity of grid-connected wind farms. Finally, the effectiveness of the proposed method is verified by the simulation results of an actual regional power grid.

The great uncertainty caused by the high penetration of renewable energy brings severe challenges to the economic dispatch of transmission systems. In this study, a day-ahead economic dispatch model is proposed. The model is based on the coordination framework of transmission and distribution, and it fully considers the response potential of the distribution network. The scenario generation method based on the Copula function is used to describe the uncertainty of the energy output of renewable energy sources such as wind power, and then, the response potential of the distribution network is analyzed. A day-ahead economic scheduling framework for transmission and distribution coordination is proposed, which is solved by a deep reinforcement learning algorithm. Finally, the effectiveness of the proposed method is verified through application to the IEEE 6-bus transmission network and the IEEE 7-bus distribution network.

Accurate prediction of power business communication bandwidth is the premise for the effectiveness of power communication planning and the fundamental guarantee for regular operation of power businesses. To solve the problem of scientifically and reasonably allocating bandwidth resources in smart parks, communication bandwidth prediction technology of intelligent power distribution service for smart parks is proposed in this paper. First, the characteristics of mixed service data arrival rate of power distribution and communication mixed services in smart parks were analyzed. Poisson process and interrupted Poisson process were used to simulate periodic and sudden business of smart parks to realize accurate simulation of the business arrival process. Then, a service arrival rate model based on the Markov modulation Poisson process was constructed. An active buffer management mechanism was used to dynamically discard data packets according to the set threshold and achieve accurate simulation of the packet loss rate during the arrival of smart park business. At the same time, considering the communication service quality index and bandwidth resource utilization, a business communication bandwidth prediction model of smart parks was established to improve the accuracy of business bandwidth prediction. Finally, a smart power distribution room in a smart park was used as an application scenario to quantitatively analyze the relationship between the communication service quality and bandwidth configuration. According to the predicted bandwidth, the reliability and effectiveness of the proposed method were verified by comparison with the elastic coefficient method.

Subsequent commutation failures (CFs) in HVDC systems will cause large-scale power flow transfer in AC/DC transmission systems and lead to overload risk in HVAC systems. In order to cope with these effects, a power coordination control strategy for the AC/DC transmission system with high-proportion wind power is proposed. Firstly, a model of the AC/DC transmission system considering the large-scale wind farms access is established by analyzing the power transmission characteristics of the AC/DC transmission system with high-proportion wind power, and the power transmission characteristics are analyzed after subsequent CFs. Secondly, the HVDC subsequent CFs can be mitigated by adjusting DC power transmission, while the active power output of the sending-end AC system is reduced by active control of wind turbine generators (WTGs) to reduce the overload risk of the HVAC system. Finally, the proposed power coordination control strategy is simulated and verified based on the established simulation model and actual power grid, and the results show that this strategy can effectively mitigate HVDC’s subsequent CFs and reduce the overload risk in HVAC systems.

Cyber-physical systems (CPSs) are becoming increasingly important in safety-critical systems. Particular risk analysis (PRA) is an essential step in the sa