建筑光伏一体化系统优化调控  

Optimal Regulation of Building‑integrated Photovoltaics System

作　　者：刘溦 曾烨 张磊 闫秀英[2] 何许馨 LIU Wei;ZENG Ye;ZHANG Lei;YAN Xiuying;HE Xuxin(China Northwest Architectural Design and Research Institute Co.,Ltd.,Xi’an 710000,China;School of Building Services Science and Engineering,Xi’an University of Architecture and Technology,Xi’an 710055,China)

机构地区：[1]中国建筑西北设计研究院有限公司,西安市710000 [2]西安建筑科技大学建筑设备科学与工程学院,西安市710055

出　　处：《建筑电气》2024年第12期44-50,共7页Building Electricity

摘　　要：针对建筑分布式光伏电站在无储能情况下的经济运行问题展开研究。首先搭建光伏一体化系统,并建立相关部分的数学模型;通过QPSO-BIGRU对光伏发电量进行预测,达到了MAE、RMSE和R^(2)分别为0.202、0.109和0.939的精度;基于预测结果,分析4种方案下的调度情况。研究结果显示,在方案4的执行下,通过多目标粒子群智能优化算法使得用电成本显著降低了62.26%,负荷峰均比也下降了2.65%,并达到49.06%的光伏自发自用率。实验成果为无储能光伏一体化建筑的经济运行提供了参考依据。This study aims to investigate the economic operation of building‑distributed PV power stations without energy storage.It firstly builds an integrated PV system and establishes mathematical models for related parts;predicts PV power generation with QPSO-BIGRU,achieving an accuracy of 0.202,0.109 and 0.939 for MAE,RMSE and R^(2),respectively;and analyzes the dispatching under the 4 schemes based on the prediction results.The study results show that in the implementation of Scheme 4,the intelligent multiple objective particle swarm optimization algorithm significantly reduces the electricity cost by 62.26%,and the peak‑to‑average ratio also decreases by 2.65%,achieving a PV self‑consumption rate of 49.06%.The experimental results provide reference for the economic operation of PV integrated buildings without energy storage.

关 键 词：光伏系统 无储能 数学模型 发电预测 自发自用率 优化调度 经济运行 多目标粒子群优化算法 

分 类 号：TM615[电气工程—电力系统及自动化]