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.

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.

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

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.

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.