西北村镇太阳能与沼气联合供暖系统优化配置研究

作者:陈耀文 郭萌萌 刘艳峰 王登甲 庄照犇 任鹏桥 宋聪
单位:西部绿色建筑国家重点实验室 西安建筑科技大学
摘要:针对西北村镇地区太阳能与沼气联合供暖系统设备容量设计问题,建立了以热量平准化成本最小为目标的太阳能与沼气联合供暖系统容量匹配优化模型,利用MATLAB/Simulink平台编写了联合系统模拟仿真程序,利用遗传算法对优化模型进行了求解计算,并对优化结果进行了准确性检验及分析。选取西北地区5个典型城市进行了优化模拟,分析了不同地区气候资源差异对联合系统容量配置优化结果的影响。研究结果表明:优化后的热量平准化成本相比未优化时降低了29.4%,同时太阳能子系统的能效及系统总能效得到了提升;对于太阳能资源条件较好的酒泉、西宁和银川地区,在发酵原料充足的条件下,可再生能源保证率达到了80%以上。
关键词:太阳能沼气联合供暖村镇优化设计热量平准化成本可再生能源
作者简介:陈耀文,男,1990年生,博士研究生,讲师,710055西安市碑林区雁塔路中段13号西安建筑科技大学,E-mall:yaowen@xauat.edu.cn;
基金:国家重点研发计划政府间国际科技创新合作重点专项(编号:2019YFE0104900-05);国家自然科学基金青年项目(编号:52108094);陕西省教育厅重点实验室科学研究计划项目(编号:21JS029);
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Study on optimal configuration of solar and biogas combined heating system in northwest rural areas
Chen Yaowen Guo Mengmeng Liu Yanfeng Wang Dengjia Zhuang Zhaoben Ren Pengqiao Song Cong
(State Key Laboratory of Western Green Building Xi'an University of Architecture and Technology)
Abstract: In view of the configuration design of solar and biogas combined heating system in northwest rural areas, this study establishes an optimization model for capacity configuration of solar and biogas combined heating system with the objective of minimizing the levelized cost of heat(LCOH). The simulation program of the combined heating system is compiled using MATLAB/Simulink platform. The optimization model is solved by the genetic algorithm, and the accuracy of the optimization results is tested and analysed. Five typical cities in northwest areas are selected for optimization simulation, and the influence of climate resource difference in different regions on the optimization results of the combined system capacity configuration is analysed. The results show that the LCOH after optimization is 29.4% lower than that before optimization, and the energy efficiency of the solar subsystem and the total energy efficiency of the system are also improved. For Jiuquan, Xining and Yinchuan regions with rich solar energy resources, when biogas fermentation raw materials are sufficient, the renewable energy fraction of the system reaches more than 80%.
Keywords: solar energy; biogas; combined heating; rural area; optimal design; levelized cost of heat; renewable energy;
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