Integrated energy system planning considering peak-to-valley difference of tie line and operation benefit of power grid

被引:0
|
作者
Zhang X. [1 ]
Li J. [1 ]
Zhang L. [1 ]
Wu B. [1 ]
Wang L. [1 ]
Tang W. [1 ]
机构
[1] College of Information and Electrical Engineering, China Agriculture University, Beijing
关键词
Integrated energy system; Optimal planning; Peak-to-valley difference of tie line; Power grid operation; Renewable energy;
D O I
10.16081/j.epae.201908016
中图分类号
学科分类号
摘要
Aiming at the current situation that the IES(Integrated Energy System) planning does not consi-der the impact of the peak-to-valley difference of the tie line on the operation of the power grid, an IES planning method considering both the peak-to-valley difference of the tie line and the power grid operation benefit is proposed. The optimal planning model of IES is established, which takes the minimum per unit sum of the annual operating cost of the power grid and the annual cost of IES as the objective function and with the tie line transmission power as the constraint. The elite energy reserve genetic algorithm and branch and bound method are used to solve the equipment configuration and optimal scheduling results of IES, and the optimal power flow is used to calculate the power grid operation cost under the given transmission power of the tie line. The simulative results of the improved IEEE 30-bus system verify the effectiveness of the proposed model. Meanwhile, controlling the peak-to-valley difference of the tie line can reduce the safety risk and the operation cost of the power grid brought by the access of IES. © 2019, Electric Power Automation Equipment Press. All right reserved.
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页码:195 / 202
页数:7
相关论文
共 18 条
  • [1] Peng K., Zhang C., Xu B., Et al., Status and prospect of pilot projects of integrated energy system with multi-energy collaboration, Electric Power Automation Equipment, 37, 6, pp. 3-10, (2017)
  • [2] Lei X., Tang W., Li Z., Et al., Distribution network expansion planning considering optimal operation of regional integrated energy system, Power System Technology, 42, 11, pp. 3459-3468, (2018)
  • [3] 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)
  • [4] Liu C., Li H., Sun L., Et al., Day-ahead optimal sche-duling of integrated energy system considering suppression of tie line peak-valley dfference and photovoltaic accommodation, Electric Power, 51, 8, pp. 70-76, (2018)
  • [5] Guo L., Liu W., Cai J., Et al., A two-stage optimal planning and de-sign method for combined cooling, heat and power microgrid sys-tem, Energy Conversion and Management, 74, pp. 433-445, (2013)
  • [6] Hong B., Chen J., Zhang W., Et al., Integrated energy system planning at modular regional-user level based on a two-layer bus structure, CSEE Journal of Power and Energy Systems, 4, 2, pp. 188-196, (2018)
  • [7] Bai M., Tang W., Wu C., Et al., Optimal planning based on integrated thermal-electric power flow for user-side micro energy station and its integrating network, Electric Power Automation Equipment, 37, 6, pp. 84-93, (2017)
  • [8] Cui P., Shi J., Wen F., Et al., Optimal energy hub configuration considering integrated demand response, Electric Power Automation Equipment, 37, 6, pp. 101-109, (2017)
  • [9] Nunes J.B., Mahmoudi N., Saha T.K., Et al., A stochastic inte-grated planning of electricity and natural gas networks for Queensland, Australia considering high renewable penetration, Energy, 153, pp. 539-553, (2018)
  • [10] Jing W., Liu Y., Xiang Y., Et al., Energy management strategy of DCCHP based on demand response, Electric Power Construction, 38, 12, pp. 68-76, (2017)