Abstract： With the increase of electric vehicle penetration, the coupling of power network and transportation network in time and space is closer. In order to reduce the challenges brought by the disorderly integration of electric vehicles to the safe and stable operation of power system, this paper fully considers the influence of power load demand and traffic condition uncertainty, and establishes a multi-agent interest hierarchical game model of EV users-charging station aggregators-grid operators. On the premise of satisfying the constraints, the multi-agent interest hierarchical optimization problem is solved based on improved bat algorithm. The simulation example shows that the grid operators can obtain higher operating benefits by actively adjusting the pricing strategy for different electric vehicle penetration rates. The proposed method can effectively improve the voltage quality of power grid to ensure the safe and stable operation of the system, and provide theoretical support for improving the value chain system of power industry.

Abstract：Electricity safety inspection is an important way to ensure the normal operation of the power grid. Traditional electricity safety inspection mainly relies on manual inspection of places and equipment with safety hazards one by one. With the development of artificial intelligence technology, intelligent analysis based on image data can assist in timely identification of relevant safety hazards, reduce the experience requirements for inspectors, and improve efficiency while ensuring the accuracy of safety inspections. In order to better improve the accuracy of electricity safety inspection, the article proposes an electricity hazard identification algorithm based on YOLO neural network, which can dynamically identify the indicator lights of electrical equipment and compare them with normal states, and promptly issue alarm messages when abnormal states are found. Based on this algorithm, the article also designed and implemented an electricity safety inspection subsystem based on image recognition. Through actual data validation, the system can achieve a high level of inconsistent detection of equipment indicator status, meeting the demand for electricity safety inspection.

Abstract： Effective power maintenance schedule will significantly increase the reliability of power grid operation as a crucial component of assuring the normal operation of the power system. In order to achieve the optimization of the maintenance plan, a probabilistic maintenance model is created in this work using equipment condition categorization, equipment operation life, equipment operation cost, and other indicators. The Markov Chain Monte Carlo approach is utilized in the maintenance model to increase model accuracy, and the probabilistic maintenance plan optimization strategy is employed to improve the reliability and economic indicators of the power grid. Finally, simulation is used to assess and compare the probabilistic maintenance model and the conventional maintenance model. The superiority of the probabilistic maintenance model, which offers a theoretical foundation for the enhancement of the power maintenance link in the power industry value chain system, is highlighted while determining the best maintenance probability.

Abstract： The current industrial electricity prices in China have peak and trough periods in a day, and cement production is characterized by high electricity consumption. The optimization of cement production arrangements can improve the utilization rate of production equipment and use the optimization results to study the production regulation capacity, so that the production can be adjusted according to the peak and trough electricity prices to achieve cost savings and reduce the load on the power grid. The study uses state task network to model the cement production process with and without storage process, taking into account electrical safety constraints, and obtains the optimal production arrangement by solving the corresponding mixed integer linear programming model, from which it is concluded that the cement production process with storage process can provide more production regulation capability.

Abstract： In the operation process of the value chain of group-type manufacturing enterprises, there is a problem of insufficient power supply during peak periods, and the demand for production electricity cannot be effectively guaranteed. The group company urgently needs to comprehensively consider the synergistic relationship between the production demand of the production base and the safety of electricity consumption, complete the fine-grained upstream and downstream power distribution of the value chain, and ensure the safe and reliable operation of the value chain. This paper designs a blockchain-based upstream and downstream electricity security collaboration system in the value chain, adopts a method based on smart contracts to ensure the compliance of value chain data use, and effectively solves the risk of value chain data sharing of group-type manufacturing enterprises and conflict of values in each production base. The system provides a good reference and decision-making basis for the safety guarantee of electricity consumption in the upstream and downstream of the value chain by completely recording the order coordination data of the production base and the electricity load data of the production base, which is of great significance for maintaining the company's safe and stable operation and improving the company's economic benefits.