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考虑用户热适应性的含跨季储热综合能源系统两阶段容量配置

TWO-STAGE CAPACITY CONFIGURATION OF INTEGRATED ENERGY SYSTEM WITH SEASONAL THERMAL ENERGY STORAGE TAKING INTO ACCOUNT THERMAL ADAPTABILITY OF USERS

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【作者】 闫宇声高建伟吴浩宇孟琪琛王紫莹

【Author】 Yan Yusheng;Gao Jianwei;Wu Haoyu;Meng Qichen;Wang Ziying;School of Economics and Management, North China Electric Power University;Beijing Key Laboratory of New Energy Electricity and Low-carbon Development(North China Electric Power University);

【通讯作者】 高建伟;

【机构】 华北电力大学经济与管理学院新能源电力与低碳发展研究北京市重点实验室(华北电力大学)

【摘要】 针对月度发电量分布不均以及用户用能差异带来的季节性供需匹配问题,构建一种考虑用户热适应性的含跨季储热综合能源系统两阶段容量配置模型。首先,对不同供暖时期用户舒适度特征进行刻画,提出一种用户热经历影响下的供暖温度动态设置及用户舒适度差异化评估策略。其次,考虑经济与环境成本,构建含跨季储热综合能源系统的一阶段容量配置模型,在时间序列重构下采用多目标粒子群算法求解,并生成跨季储热全年参考容量状态序列。然后,建立第二阶段多时间尺度运行优化模型,研究不同配置条件下考虑长短时电热综合需求响应的系统运行情况,最终确定使得用户满意度最高的设备最优配置容量。通过算例仿真验证所提出模型及其求解方法的可行性。

【Abstract】 In response to the seasonal supply-demand mismatch caused by uneven distribution of monthly power generation and differences in user energy consumption, a two-stage capacity allocation model for an integrated energy system with seasonal thermal energy storage is constructed by considering the thermal adaptability of users. Firstly, the comfort characteristics of users in different heating periods are portrayed, and a strategy for dynamic setting of heating temperatures and differentiated assessment of user comfort is proposed, taking into account the influence of user thermal experience. Secondly, considering the economic and environmental costs, a one-stage capacity allocation model is constructed for an integrated energy system with seasonal thermal energy storage, which is solved by a multi-objective particle swarm algorithm under time series reconstruction and generates an annual reference capacity state sequence for seasonal thermal energy storage. Then, a two-stage multi-timescale operation optimization model is developed to study the system operation under different configuration conditions considering the integrated demand response of long and short-term electricity and heat, and ultimately determine the optimal configuration capacity of the system that makes the highest user satisfaction. The model is simulated with examples to verify the feasibility of the proposed model and its solution method.

【基金】 国家自然科学基金(72071076)
  • 【文献出处】 太阳能学报 ,Acta Energiae Solaris Sinica , 编辑部邮箱 ,2025年12期
  • 【分类号】TM73;TK01
  • 【下载频次】151
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