基于改进量子遗传算法的光伏智能楼宇负荷优化  

PV SMART BUILDING LOAD OPTIMIZATION BASED ON IMPROVED QUANTUM GENETIC ALGORITHM

作　　者：华聪聪 冯胜 李大华 田禾 李栋 Hua Congcong;Feng Sheng;Li Dahua;Tian He;Li Dong(College of Electrical and Electronic Engineering,Tianjin University of Technology,Tianjin 300384,China;CNOOC(China)Co.,Ltd.,Tianjin Branch,Tianjin 300459,China;Tianjin Key Laboratory for Control Theory&Applications in Complicated Systems,Tianjin 300384,China)

机构地区：[1]天津理工大学电气电子工程学院,天津300384 [2]中海石油(中国)有限公司天津分公司,天津300459 [3]天津市复杂系统控制理论及应用重点实验室,天津300384

出　　处：《计算机应用与软件》2024年第9期77-82,105,共7页Computer Applications and Software

基　　金：2020年天津市企业科技特派员项目(20YDTPJC01670);教育部产学合作协同育人项目(202101244031)。

摘　　要：针对楼宇用电负荷优化的问题,考虑用电成本、储能折损、用电舒适性和电网侧峰谷差波动的因素,提出一种多目标动态规划的办公楼宇负荷优化模型。结合分时电价建立楼宇净用电成本最小的目标函数,采用改进旋转门动态调整的量子遗传算法进行求解,通过动态调整量子旋转门,改变量子态的概率,提高了量子遗传算法求解的精确度;在保证得到全局最优解的同时完成负荷优化和供给侧的能量调度。实验结果表明,所提算法保证了用电舒适性,有效降低了楼宇用电成本和储能装置的折损费用,具有良好的经济收益;在降低峰谷差方面也起到了较好的效果。A multi-objective dynamic planning load optimization model for office buildings is proposed to address the problem of building load optimization,taking into account the cost of electricity consumption,energy storage discount,comfort of electricity consumption and fluctuation of peak-to-valley difference on the grid side.Combined with the time-of-use electricity price,the objective function of minimizing the net electricity cost of the building was established,and the quantum genetic algorithm with improved dynamic adjustment of the revolving gate was used to solve the problem.By dynamically adjusting the quantum revolving gate and changing the probability of the quantum state,the accuracy of the quantum genetic algorithm was improved.Load optimization and supply-side energy scheduling were accomplished while ensuring the global optimal solution was obtained.The experimental results show that the proposed algorithm has good economic benefits,which ensures the comfort of electricity consumption,and reduces the cost of electricity and the depreciation cost of energy storage devices effectively;as well as plays a good effect in reducing the peak-to-valley difference.

关 键 词：分时电价 多目标规划 优化调控 改进量子遗传 

分 类 号：TM714[电气工程—电力系统及自动化] TP3[自动化与计算机技术—计算机科学与技术]