BI-LEVEL OPTIMIZATION MODEL FOR MICRO ENERGY GRID CONSIDERING CARBON TRADING AND DEMAND RESPONSE

被引:0
|
作者
Duan X. [1 ,2 ]
Huang R. [1 ]
Qi C. [1 ]
Chen B. [1 ]
机构
[1] Department of Automation, North China Electric Power University, Baoding
[2] Baoding Sinosimu Technology Company Limited, Baoding
来源
关键词
bi-level optimization; carbon trading; demand response; energy management; micro energy grid;
D O I
10.19912/j.0254-0096.tynxb.2022-1711
中图分类号
学科分类号
摘要
The global greenhouse effect is becoming more and more serious,and the construction and operation optimization of the micro energy grid plays an important role in realizing the goal of carbon reduction. This paper constructs a bi-level optimization configuration model for micro energy grids based on the basic architecture of micro energy grids,combining carbon trading and demand response with the objective function of minimizing the annual total cost. Combined with regional environmental data and annual typical day case analysis,the optimization model obtains the optimal planning configuration and the optimal daily operating output scheduling of each equipment under the configuration,which increases the installed capacity of renewable energy to obtain higher carbon emission right income compared with the basic model,and adjusts the flexible and controllable load of the customer side through demand response,which saves the total cost effectively under the premise of ensuring the capacity of renewable energy consumption. The results of the arithmetic example show that the model can enable the micro energy grid to promote the realization of carbon reduction goals while ensuring the system economy,which is important for the pre-planning and design of MEG. © 2024 Science Press. All rights reserved.
引用
收藏
页码:310 / 318
页数:8
相关论文
共 22 条
  • [1] ZHOU X Y, WEI X Y, LIN J, Et al., Supply chain management under carbon taxes:a review and bibliometric analysis[J], Omega, 98, (2021)
  • [2] ZHAO Z Y, ZENG W., Analysis of scientific and technological intelligence service issues under the goal of "carbon peak and carbon neutrality, China soft science, 1, pp. 1-6, (2022)
  • [3] SUN Y Z, ZHANG P C, KE D P, Et al., Planning,design and optimal operation of energy internet system under the condition of peak carbon dioxide emissions, Southern power system technology, 16, 1, pp. 1-13, (2022)
  • [4] ESHRAGHI A, SALEHI G, HEIBATI S, Et al., Developing operation of combined cooling, heat, and power system based on energy hub in a micro-energy grid: the application of energy storages[J], Energy & environment, 30, 8, pp. 1356-1379, (2019)
  • [5] QIU Z, WANG B B, BEN S J, Et al., Bi-level optimal configuration planning model of regional integrated energy system considering uncertainties, Electric power automation equipment, 39, 8, pp. 176-185, (2019)
  • [6] LI L, HAN S F, ZHENG H K, Et al., An interval planning method for micro energy networks considering renewable generation and demand uncertainty, Journal of power supply, pp. 1-26
  • [7] ZHAO X H, HE C G, LUO Q L, Et al., A robust planning method for micro energy grid considering spatiotemporal correlations of uncertainties, Renewable energy resources, 38, 3, pp. 388-395, (2020)
  • [8] ZHANG X H, LIANG J X, ZHAO C M, Et al., Research on low-carbon power planning with gas turbine units based on carbon transactions, Acta energiae solaris sinica, 41, 7, pp. 92-98, (2020)
  • [9] WANG Z H, XU J J, TIAN C G, Et al., Combined heat and power scheduling strategy considering carbon trading cost in wind power system[J], Acta energiae solaris sinica, 41, 12, pp. 245-253, (2020)
  • [10] FANG R C, YANG J, ZHOU K, Et al., An optimal planning method for park IES considering life cycle carbon cost [J], Electric power, 55, 12, pp. 135-146, (2022)