文章摘要
高 晋,王雪文,陈凯鹏,刘丁豪,何迎春,吴英俊.考虑光储柔的楼宇综合能源系统优化调度[J].电力需求侧管理,2025,27(1):33-39
考虑光储柔的楼宇综合能源系统优化调度
Optimal dispatch of building integrated energy systems in buildings considering optical storage flexibility
投稿时间:2024-10-21  修订日期:2024-11-26
DOI:10. 3969 / j. issn. 1009-1831. 2025. 01. 006
中文关键词: 楼宇综合能源系统  光伏  储能  柔性负荷  环境舒适度  优化调度
英文关键词: BIES  photovoltaic  energy storage  flexible loads  environmental comfort  optimal scheduling
基金项目:国网重庆市电力公司科技项目(52202323001C)
作者单位
高 晋 国网重庆市电力公司 电力科学研究院,重庆 401123 
王雪文 国网重庆市电力公司 电力科学研究院,重庆 401123 
陈凯鹏 河海大学 电气与动力工程学院,南京 211100 
刘丁豪 国网重庆市电力公司 电力科学研究院,重庆 401123 
何迎春 国网重庆市电力公司,重庆400015 
吴英俊 河海大学 电气与动力工程学院,南京 211100 
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中文摘要:
      楼宇综合能源系统(integrated energy system of buildings,BIES)负荷容量大、能源种类多样。如何协调不同类型能源与负荷的运行,实现电网的削峰填谷,是一个研究热点。通过兼顾光储柔和环境舒适度等因素进行楼宇综合能源系统优化调度。首先,采用Beta分布法,构建了考虑太阳辐射强度分布不确定性的光伏出力模型;其次,构建了考虑移动特性的电动汽车(electric vehicle,EV)储能模型,以及计及温度对柔性负荷影响的楼宇环境舒适度量化模型;最后,基于混合整数线性规划方法,提出了求解楼宇综合能源系统最优调度模型的方法。通过对某地区楼宇在不同场景下负荷优化效果、成本以及相关影响因素分析,验证了所提模型的正确性和有效性。
英文摘要:
      The integrated energy system of buildings(BIES)has a large load capacity and various types of energy. How to coordinate the operation of different types of energy sources and loads to realize the peak shaving and valley filling of the power grid is a research hotspot.Considering the factors such as light storage and soft environment comfort, BIES is optimized. First, a photovoltaic(PV)output model based on the uncertainty of solar radiation intensity distribution is constructed by using the Beta distribution method; second, considering the mobility characteristics, an electric vehicle(EV)storage model is proposed and a quantitative model of building environmental comfort that takes into account the influence of temperature on flexible loads are constructed; finally, based on the mixed-integer linear programming method to solve the optimal scheduling model of the integrated energy system in buildings is proposed. The correctness and validity of the proposed model are verified by analyzing the load optimization effect, cost, and related influencing factors of buildings in a certain region under different scenarios.
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