引用本文:孙健,柯德平,徐箭,廖思阳,孙元章.基于高精度热泵模型的电热协同独立微网设备优化配置[J].电力自动化设备,2024,44(7):198-204,213
SUN Jian,KE Deping,XU Jian,LIAO Siyang,SUN Yuanzhang.Optimal configuration of electric-heat cooperative independent micro-grid equipment based on accurate heat pump model[J].Electric Power Automation Equipment,2024,44(7):198-204,213
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基于高精度热泵模型的电热协同独立微网设备优化配置
孙健, 柯德平, 徐箭, 廖思阳, 孙元章
武汉大学 电气与自动化学院,湖北 武汉 430072
摘要:
为实现含丰富工业余热、数据中心余热、生活污水余热等低品位热源的区域协同供能,以及提高区域清洁能源利用效率,针对区域独立微网供能系统的设备优化配置策略进行研究。基于多类型低品位热源的不同温度品位特征,提出用于提升热源温度品位的关键电热泵设备多参数拟合模型,并生成热泵拟合模型的误差不确定性场景;考虑微网在实际运行不确定性场景下产生的供热舒适度补偿、切负荷与切光伏风险,提出基于多条件风险价值(CVaR)理论的独立微网设备容量优化配置双层模型,上层模型基于全寿命周期成本费用年值与年CVaR值优化设备配置方案,下层模型基于场景分析法优化运行成本;采用遗传算法对双层模型进行求解。算例结果证明:考虑热泵拟合模型误差有效降低了系统运行风险,且低品位热源的回收利用具有较大经济性潜力。
关键词:  微网  低品位热源  热泵  不确定性场景  条件风险价值  设备配置  双层模型
DOI:10.16081/j.epae.202405018
分类号:TM715
基金项目:国家自然科学基金资助项目(52377121)
Optimal configuration of electric-heat cooperative independent micro-grid equipment based on accurate heat pump model
SUN Jian, KE Deping, XU Jian, LIAO Siyang, SUN Yuanzhang
School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Abstract:
In order to realize the collaborative energy supply in the region which contains rich industrial waste heat, data center waste heat, domestic sewage waste heat and other low-grade heat sources, and improve the utilization efficiency of regional clean energy, the equipment optimal configuration strategy of regional independent micro-grid energy system is studied. Based on the temperature characteristics of various low-grade heat sources, a multi-parameter fitting model for essential heat pump equipment which can improve the temperature grade of heat sources is proposed, and the error uncertainty scenario of fitting heat pump model is generated. Considering the risk of heating comfort, load cutting and photovoltaic cutting in actual operation scenario, a two-layer capacity optimization model for independent micro-grid equipment based on conditional value at risk(CVaR) theory is proposed, in which, the upper model optimizes the equipment configuration based on the annual cost of the whole life cycle and annual CVaR value, while the lower model optimizes the operating cost based on scenario analysis. The genetic algorithm is used to solve the two-layer model. The case study results show that considering the error of heat pump model can effectively reduce the system operating risk, and the recovery and utilization of low-grade heat source has great economic potential.
Key words:  micro-grid  low-grade heat  heat pump  uncertainty scenario  conditional value at risk  equipment configuration  two-layer model

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