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1.智能电网教育部重点实验室(天津大学),天津市 300072
2.天津市智慧能源与信息技术重点实验室(天津大学),天津市 300072
3.国网天津市电力公司,天津市 300010
4.国网天津市电力公司武清供电分公司,天津市 301700
张嘉睿(1995—),男,硕士研究生,主要研究方向:综合能源需求侧响应。E-mail:jerry_zhang@tju.edu.cn
穆云飞(1984—),男,通信作者,博士,副教授,博士生导师,主要研究方向:电力系统稳定性分析、综合能源系统能量管理。E-mail:yunfeimu@tju.edu.cn
贾宏杰(1973—),男,博士,教授,博士生导师,主要研究方向:综合能源系统及智能电网领域的建模、优化、分析及控制。E-mail:hjjia@tju.edu.cn
收稿日期:2020-03-31,
修回日期:2020-05-06,
网络出版日期:2020-07-15,
纸质出版日期:2020-11-10
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张嘉睿,穆云飞,贾宏杰等.考虑停电时段用户热需求的蓄热式电采暖日前优化调度方法[J].电力系统自动化,2020,44(21):15-22.
ZHANG Jiarui,MU Yunfei,JIA Hongjie,et al.Day-ahead Optimal Scheduling Method for Regenerative Electric Heating Considering Thermal Demand of Users During Power Outage[J].Automation of Electric Power Systems,2020,44(21):15-22.
张嘉睿,穆云飞,贾宏杰等.考虑停电时段用户热需求的蓄热式电采暖日前优化调度方法[J].电力系统自动化,2020,44(21):15-22. DOI: 10.7500/AEPS20200331002.
ZHANG Jiarui,MU Yunfei,JIA Hongjie,et al.Day-ahead Optimal Scheduling Method for Regenerative Electric Heating Considering Thermal Demand of Users During Power Outage[J].Automation of Electric Power Systems,2020,44(21):15-22. DOI: 10.7500/AEPS20200331002.
文中提出一种考虑停电时段用户最小热需求的蓄热式电采暖日前优化调度方法。首先,建立含蓄热水箱的空气源热泵供暖系统模型和房屋热负荷模型。然后,提出一种电网故障场景下,综合考虑可维持供暖时长及用户舒适度的最小用热量计算方法。最后,以经济性为目标,以故障场景下的最小用热量为约束,构建一种考虑停电时段用户最小热需求的蓄热式电采暖日前优化调度模型。算例结果表明,所提方法可基于蓄热式电采暖的蓄热量,实现“停电不停暖”的同时,降低供暖费用,同时配合蓄热水箱容量提升或房屋围护结构改造,可有效提升用户供暖可靠性。
Day-ahead optimal scheduling method for regenerative electric heating is proposed considering the minimum thermal demand of users during power outage period. Firstly
an air-source heat pump heating system model with hot water storage tank and a house heat load model are established. Then
a calculation method of minimum heat consumption that comprehensively considers the maintained heating duration and comfort of users is proposed in a failure scenario of power grid. Finally
a day-ahead optimal scheduling model of regenerative electric heating considering the minimum of heat demand for users during outage period is constructed
which takes economy as the goal and the minimum heat consumption in the fault scenario as the constraint. The case results show that the proposed method can achieve the goal of “heating supply guarantee during power outage” based on heat storage capacity of regenerative electric heating and reduce heating costs. At the same time
it can effectively improve the heating reliability of users together with the capacity improvement of heat storage tank or the reconstruction of building envelope.
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