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Robust Scheduling of Integrated Electricity and Heating System Hedging Heating Network Uncertainties
IEEE Transactions on Smart Grid ( IF 8.6 ) Pub Date : 2019-09-09 , DOI: 10.1109/tsg.2019.2940031
Huansheng Zhou , Zhigang Li , J. H. Zheng , Q. H. Wu , Haibo Zhang

The coordinated operation of an integrated electricity and heating system (IEHS) can improve overall energy efficiency and provide additional flexibility. However, the inherent uncertainties pertaining to pipeline parameters and ambient temperature in a district heating network (DHN) have not been addressed in the literature, although such uncertainties could affect the quality or even security of IEHS operation. To address this issue, we propose a two-stage robust IEHS scheduling model that considers the uncertainties of the heat load, ambient temperature and heat dissipation coefficients of heating pipelines. The proposed model embedded with bilinear terms is equivalently transformed via the big-M method into an adaptive linear robust optimization problem that can be solved by the column-and-constraint generation (C&CG) algorithm. Case studies are conducted for two test systems. The simulation results show that the proposed method can effectively handle the uncertainties in DHN and improve the robustness of the IEHS.

中文翻译:

集成电热系统的鲁棒调度对冲热网不确定性

集成的电力和供热系统(IEHS)的协调运行可以提高整体能源效率,并提供更多的灵活性。但是,文献中并未涉及与管道参数和区域供热网络(DHN)中的环境温度有关的内在不确定性,尽管这些不确定性可能会影响IEHS操作的质量甚至安全性。为了解决这个问题,我们提出了一个两阶段鲁棒的IEHS调度模型,该模型考虑了加热管道的热负荷,环境温度和散热系数的不确定性。通过big-M方法将提出的嵌入双线性项的模型等效地转换为可以通过列约束生成(C&CG)算法解决的自适应线性鲁棒优化问题。案例研究针对两个测试系统。仿真结果表明,该方法能够有效处理DHN中的不确定性,提高IEHS的鲁棒性。
更新日期:2020-04-22
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