Highlights

    Please wait a minute...
    For Selected: Toggle Thumbnails
    Application and Prospect of Two-Part Tariff Mechanism in Context of Transmission and Distribution Price Reform
    REN Xijun, SONG Zhumeng, WANG Bao, YE Yutong, PAN Sijia, WANG Mengyuan, XU Xiaoyuan
    Journal of Shanghai Jiao Tong University    2024, 58 (10): 1479-1488.   DOI: 10.16183/j.cnki.jsjtu.2023.102
    Abstract752)   HTML51)    PDF(pc) (1057KB)(633)       Save

    In the context of the reform of transmission and distribution tariff mechanism, the drawbacks of the existing two-part tariff system which cannot reasonably reflect the real cost of electricity consumption by power users have gradually emerged. The two-part tariff mechanism is responsible for allocating the space for electricity generation, transmission, distribution and sale tariffs, and regulating the resources of the power system. Therefore, it is urgent to improve the existing two-part tariff mechanism. This paper, focusing on the two-part tariff mechanism, first, introduces the basic theory and billing ratio of the two-part tariff, and studies the method of apportioning transmission and distribution costs based on different load rates and voltage levels. Then, it summarizes the electricity tariff mechanisms such as load rate packages and time-of-use tariffs and the basic tariff mechanisms such as tariff, load adjustments, and improved billing ratios respectively for the collection methods of two-part tariffs. Afterwards, it analyzes the implementation mode of two-part tariff mechanism theory by combining the practical experience of two-part system in the United States, France, Japan, and other foreign countries. Finally, it proposes the future development direction and suggestions of China’s two-part tariff mechanism.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    A Prediction Method of New Power System Frequency Characteristics Based on Convolutional Neural Network
    LU Wen’an, ZHU Qingxiao, LI Zhaowei, LIU Hui, YU Yiping
    Journal of Shanghai Jiao Tong University    2024, 58 (10): 1500-1512.   DOI: 10.16183/j.cnki.jsjtu.2023.071
    Abstract676)   HTML18)    PDF(pc) (2722KB)(782)       Save

    In order to solve the problems existing in the traditional frequency analysis method for the frequency analysis of grids with a high proportion of new energy, such as the large amount of calculation, the difficulty of modeling, and the prominent contradiction between the calculation speed and the calculation accuracy, this paper proposes a new frequency characteristic prediction method for the new power system based on convolutional neural network (CNN). First, the main frequency indexes of the power system with a high proportion of new energy under power disturbances are predicted using one-dimensional CNN, including the initial frequency change rate, frequency extremum, and frequency steady-state value. The prediction accuracy is improved by setting reasonable input characteristics and optimizing the parameters of the neural network. Then, the impact of disturbance location and disturbance type is further considered, and the power system characteristic data set containing disturbance information is established by the method of data dimensionality reduction. The input characteristics are constructed by using the principle of three primary channels for reference, and the extended two-dimensional CNN is used to predict the frequency security index, which improves the adaptability of CNN in the frequency analysis of grids with a high proportion of new energy. Finally, the method is verified by an example in the improved BPA 10-machine 39-node model, and the results are compared with the prediction results of the recurrent neural network, which proves that the proposed method has a high accuracy and adaptability.

    Table and Figures | Reference | Related Articles | Metrics | Comments0
    Multi-Energy Flow Modeling and Optimization of Electric-Gas-Thermal Integrated Energy System
    LI Bingjie, YUAN Xiaoyun, SHI Jing, XU Huachi, LUO Zixuan
    Journal of Shanghai Jiao Tong University    2024, 58 (9): 1297-1308.   DOI: 10.16183/j.cnki.jsjtu.2022.494
    Abstract3705)   HTML41)    PDF(pc) (8902KB)(778)       Save

    In view of the fact that the conversion of various energy forms such as electricity, gas, and heat in the regional integrated energy system (RIES) seriously affects the economy of the system operation, a mathematical model and an optimization model of RIES energy flow are established to improve the economy of the system and the absorption of renewable energy. First, the mathematical models of all kinds of energy conversion equipment in the system are established to determine the constraints of three kinds of energy transmission networks, namely electricity, natural gas, and heat. Then, taking economic operation as the primary objective, and taking into account the objective function of low carbon emissions and increasing the uptake rate of renewable energy, the RIES multi-energy flow optimization model is constructed. Finally, based on the large-scale integrated energy system, the load side demand response is introduced and the simulation model is established. The simulation results show that the introduction of demand response improves the flexibility of system scheduling, reduces the dependence of the system on energy storage equipment, and effectively reduces the energy consumption cost of users.

    Table and Figures | Reference | Related Articles | Metrics | Comments0