智能建筑能量优化策略的改进法向-边界求交算法
Improved normal-boundary intersection algorithm: a method for energy optimization strategy in smart buildings
摘要：
随着分布式能源的广泛应用，智能建筑相对于传统建筑的优势日益明显。随之而来，其能量优化调度和多目标优化问题也变得越来越复杂，亟待解决。本文提出了一种新的方法来优化智能建筑中的能源利用。首先，在分布式可再生能源的评价中加入了多个传输保留比（TRR）参数。其次，通过自适应权值求和、调整均匀轴法和马氏距离对法线-边界求交（NBI）算法进行改进，形成改进的法线-边界求交（INBI）算法。针对智能建筑中的多目标优化问题，采用参数TRR和INBI算法进行求解，以提高调节效率。针对决策者对评价指标的需求，平均偏差较前一案例降低60%。数值算例表明，该方法在三个优化目标方面均优于现有技术。目标包括设备成本降低8.2%，供电成本降低7.6%，居住者舒适度提高1.6%。
英文摘要：
With the widespread use of distributed energy sources, the advantages of smart buildings over traditional buildings are becoming increasingly obvious. Subsequently, its energy optimal scheduling and multi-objective optimization have become more and more complex and need to be solved urgently. This paper presents a novel method to optimize energy utilization in smart buildings. Firstly, multiple transfer-retention ratio (TRR) parameters are added to the evaluation of distributed renewable energy. Secondly, the normal-boundary intersection (NBI) algorithm is improved by the adaptive weight sum, the adjust uniform axes method, and Mahalanobis distance to form the improved normal-boundary intersection (INBI) algorithm. The multi-objective optimization problem in smart buildings is solved by the parameter TRR and INBI algorithm to improve the regulation efficiency. In response to the needs of decision-makers with evaluation indicators, the average deviation is reduced by 60% compared with the previous case. Numerical examples show that the proposed method is superior to the existing technologies in terms of three optimization objectives. The objectives include 8.2% reduction in equipment costs, 7.6% reduction in power supply costs, and 1.6% improvement in occupants' comfort.
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