In the smart grid and big data environment, accurate and large amount of power load data for users can be obtained with the wide application of non-intrusive load monitoring technology. In the research process of customers’ information, information security protection of users’ electricity data has become a research hotspot urgently. This article proposes a new type of load decomposition method for electric vehicle load information and compares it with hidden Markov model algorithm to verify its accuracy. On this basis, the elliptic curve encryption algorithm is used to encrypt the users’ electricity data, and the function and effectiveness of the encryption algorithm are verified by comparing the load decomposition of the electric vehicle with the unencrypted data.

As an emerging and active entity in China's electricity market, electricity selling companies call for a more reliable operational mechanism and new consumption mode to broaden their profit margins. Aiming at distributed power generation-based sales companies and by considering the participation of virtual power plants (VPPs), this paper presents the relevant operating systems in the Chinese power market. Then the paper proposes a new platform for power transactions and optimal dispatch based on a master-slave game optimization model. The model is built so that the main gamer, power sales company, can achieve maximum profit while at the same time the secondary gamer, represented by the VPP attains the lowest internal dispatching cost. The energy of both parties is linked together, and the two parties continuously exchange their own strategies and optimize the operational decisions and scheduling plans iteratively. The results of the investigated case study reveal the benefits to retail electricity companies from adopting the proposed model to aggregate and manage decentralized resources, and optimize decision-making. The platform facilitates the use of controllable loads and distributed energy sources to participate in market transactions on a large scale, and optimize the operational strategies of electric utilities.INDEX TERMS Energy transaction, virtual power plant, master-slave game, optimal scheduling.

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Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value. However, the randomness of wind power generation puts forward higher requirements for electricity market transactions. Therefore, the carbon trading market is introduced into the wind power market, and a new form of low-carbon economic dispatch model is developed. First, the economic dispatch goal of wind power is be considered. It is projected to save money and reduce the cost of power generation for the system. The model includes risk operating costs to account for the impact of wind power output variability on the system, as well as wind farm negative efficiency operating costs to account for the loss caused by wind abandonment. The model also employs carbon trading market metrics to achieve the goal of lowering system carbon emissions, and analyze the impact of different carbon trading prices on the system. A low-carbon economic dispatch model for the wind power market is implemented based on the following two goals. Finally, the solution is optimised using the Ant-lion optimisation method, which combines Levi's flight mechanism and golden sine. The proposed model and algorithm's rationality is proven through the use of cases. K E Y W O R D Sant-lion optimisation algorithm, carbon trading, Levi flight, low-carbon economic dispatch, wind power marketThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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