Multi-time Scale Dispatching for Integrated Energy Park Considering Energy Transfer Behavior

被引:0
|
作者
Li T. [1 ]
Han X. [1 ]
Du X. [1 ]
机构
[1] College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Energy transfer behavior; Integrated energy park; Multi-time scale dispatching; Power deviation; User evaluation;
D O I
10.7500/AEPS20190516003
中图分类号
学科分类号
摘要
The operation control of the integrated energy park (IEP) should take into account the interests of multiple market subjects. According to the demand of energy supply of different types of parks, this paper proposes a multi-time scale optimal scheduling strategy for IEP that combines day-ahead dispatching and real-time dispatching considering user demands. Firstly, the basic framework of IEP is established including intelligent power management unit, power-gas coupling combined supply unit, electric vehicle (EV) charging unit and user power-cold energy dispatching unit, and the operation methods of the park in the market environment are analyzed. Secondly, this paper establishes a non-cooperative game model with the goals of operator profit and user evaluation in the day-ahead dispatching to determine energy prices and energy usage arrangements of IEP. Thirdly, aiming at the problem of forecasting error in day-ahead dispatching, the real-time energy deviation coping model which includes energy transfer behavior and meets different types of energy demands of users is constructed in real-time dispatching. Finally, the micro energy network with a 14-node distribution network and a 7-node natural gas pipeline network is simulated as a scene to verify the effectiveness of the proposed model. The result shows that the multi-time scale optimal scheduling strategy can improve the economic benefits of multi-market participants in the park, as well as the feasibility of considering the diversified energy demands of users. © 2019 Automation of Electric Power Systems Press.
引用
收藏
页码:164 / 172
页数:8
相关论文
共 21 条
  • [1] Jia H., Wang D., Xu X., Et al., Research on some key problems related to integrated energy systems, Automation of Electric Power Systems, 39, 7, pp. 198-207, (2015)
  • [2] Zhou X., Chen S., Lu Z., Et al., Technology features of the new generation power system in China, Proceedings of the CSEE, 38, 7, pp. 1893-1904, (2018)
  • [3] Liu D., Xu E., Xu X., Source-network-load-storage" integrated operation model for microgrid in park, Power System Technology, 42, 3, pp. 681-689, (2018)
  • [4] Shi J., Xu J., Zeng B., Et al., A bi-level optimal operation for energy hub based on regulating heat-to-electric ratio mode, Power System Technology, 40, 10, pp. 2959-2966, (2016)
  • [5] Li Z., Wu W., Wang J., Et al., Transmission-constrained unit commitment considering combined electricity and district heating networks, IEEE Transactions on Sustainable Energy, 7, 2, pp. 480-492, (2016)
  • [6] Pan Z., Wang K., Qu K., Et al., Coordinated optimal dispatch of electricity-gas-heat multi-energy system considering high penetration of electric vehicles, Automation of Electric Power Systems, 42, 4, pp. 104-112, (2018)
  • [7] Jin X., Mu Y., Jia H., Et al., Optimal scheduling method for a combined cooling, heating and power building microgrid considering virtual storage system at demand side, Proceedings of the CSEE, 37, 2, pp. 581-590, (2017)
  • [8] Solanki B.V., Raghurajan A., Bhattacharya K., Et al., Including smart loads for optimal demand response in integrated energy management systems for isolated microgrids, IEEE Transactions on Smart Grid, 8, 4, pp. 1739-1748, (2017)
  • [9] Tang W., Gao F., Optimal operation of household microgrid day-ahead energy considering user satisfaction, High Voltage Engineering, 43, 1, pp. 140-148, (2017)
  • [10] Tran N., Pham C., Nguyen M., Et al., Incentivizing energy reduction for emergency demand response in multi-tenant mixed-use buildings, IEEE Transactions on Smart Grid, 9, 4, pp. 3701-3715, (2018)