华电技术

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工业园区蒸汽热网智慧调度技术研究及应用

叶青1,孙海龙1,孔凡淇2,王叶飞3,赵琼2,钟崴2,李丰均1,居国腾1   

  1. 1. 浙能绍兴滨海热电有限责任公司
    2. 浙江大学
    3. 常州英集动力科技有限公司
  • 收稿日期:2020-06-11 修回日期:2020-07-27 发布日期:2020-09-29
  • 通讯作者: 赵琼
  • 基金资助:
    国家重点研发计划;山东省重大科技创新工程项目

Study and application of intelligent dispatch technology of steam heating network in industrial park

Qing Ye1, 1, 1, 1,Qiong Zhao 1, 1, 1   

  • Received:2020-06-11 Revised:2020-07-27 Published:2020-09-29
  • Contact: Qiong Zhao

摘要: 随着“退城入园”政策的持续推进和工业园区蒸汽热网的快速发展,园区热网调度的复杂性已超出人工经验可以快速反应和判断的能力范围。针对这一问题,本文首先以工业园区蒸汽热网智慧供热系统为基础,提出了一种运行优化调度技术架构;其次,建立了与实际热网相映射的数字孪生拓扑网络模型,并提出了一种蒸汽热网仿真计算方法,作为优化调度的预测和分析基础;最后,以浙江某印染园区的大型蒸汽热网作为研究对象,对比了在热源停机的情况下,分别依靠经验调度方法和智慧调度方法的热网调度运行结果。结果表明,智慧供热技术精准实现了园区蒸汽热网优化调度,其方案预期温度与实际调度后热网温度的最高偏差为2.27%,而压力的最高偏差为8.57%。同时,经验调度方法导致整网用户蒸汽压力平均下降0.14 MPa,而经过优化调度后,整网用户蒸汽压力平均下降0.07 MPa,有效降低了调度方案对用户用汽质量的不良影响,表明智慧供热技术在工业园区有优秀的发展潜力和应用价值。

关键词: 蒸汽热网, 优化调度, 信息物理融合, 智慧供热

Abstract: With the continuous promotion of “retreat from city into park” policy and the rapid development of the steam heating network in industrial park, the complexity of dispatching heating network has exceeded the capability of quick response and judgment by human experience. To solve this problem, this paper firstly proposes an overall technical scheme of optimal scheduling based on intelligent heating system of steam heating network in industrial park. Secondly, a digital twin topology network model corresponding to the actual heating network is established, and a simulation calculation method of steam heating network is proposed as the prediction and analysis basis of optimal dispatch. Finally, this paper takes a large-scale steam heating network in a printing and dyeing park in Zhejiang Province as research object. In the case of shutting down a heat source, the operation results based on empirical dispatching method and intelligent dispatching method are compared. The results show that the intelligent heating technology accurately realizes the optimal dispatch of the steam heating network in the park. After the optimal dispatch, the maximum deviation between the expected temperature of the dispatch scheme and the actual temperature of the heating network is 2.27%, while the maximum deviation of the pressure is 8.57%. Meanwhile, the empirical dispatching method results in the average pressure drop of user-end steam in the whole network is 0.14 MPa, while that is 0.07MPa under optimal dispatch, which effectively reduce the adverse impact of dispatching scheme on the quality of user-end steam consumption. The results indicate that intelligent heating technology has excellent development potential and application value in the industrial park.

Key words: steam heating network, optimal dispatch, cyber physical integration, intelligent heating