Probabilistic analysis of solar photovoltaic self-consumption using Bayesian network models

Probabilistic analysis of solar photovoltaic self-consumption using Bayesian network models
复制标题

利用贝叶斯网络模型进行太阳能光伏自耗概率分析

DOI:
10.1049/iet-rpg.2015.0360
复制
发表时间:
2016
影响因子:
2.6
通讯作者:
Leicester P
Leicester P
中科院分区:
工程技术4区
文献类型:
--
作者:
Leicester P

文献摘要

参考文献

被引文献

相似文献

为了评估城市地区多个光伏系统的系统价值和影响,需要以相对较高的时间分辨率详细分析现场用电量和太阳能光伏发电量,并了解用电量和光伏发电量随机变化的影响。在这项研究中,测量和模拟的时间序列数据的消费和光伏发电在5分钟和1分钟的分辨率为大量的国内光伏系统进行了分析,并进行了统计评估的自我消费(SC)。结果显示,样本人群的年PV SC存在显著变异性,典型的年SC中位数为31%,四分位数间范围为22- 44%。大约10%的住宅超过SC的60%,10%达到14%或更少。结果已被用来构建贝叶斯网络模型,能够概率分析SC给定的消费和光伏发电。该模型为快速详细分析光伏在一系列建筑环境背景下的技术经济特征和社会经济影响提供了基础,从单个建筑到区域规模。
To assess the systemic value and impacts of multiple photovoltaic (PV) systems in urban areas, detailed analysis of on‐site electricity consumption and of solar PV yield at relatively high temporal resolution is required, together with an understanding of the impacts of stochastic variations in consumption and PV generation. In this study, measured and simulated time‐series data for consumption and PV generation at 5 and 1 min resolution for a large number of domestic PV systems are analysed, and a statistical evaluation of self‐consumption (SC) carried out. The results show a significant variability of annual PV SC across the sample population, with typical median annual SC of 31% and inter‐quartile range of 22–44%. About 10% of the dwellings exceed an SC of 60% with 10% achieving 14% or less. The results have been used to construct a Bayesian network model capable of probabilistically analysing SC given consumption and PV generation. This model provides a basis for rapid detailed analysis of the techno‐economic characteristics and socio‐economic impacts of PV in a range of built environment contexts, from single building to district scales.
DOI: --
发表时间: 1995
影响因子: 3.9
作者:
Someswar Kesh
通讯作者: Someswar Kesh
通过集成空间和概率建模对光伏影响进行多领域分析
DOI: 10.1049/iet-rpg.2014.0374
发表时间: 2015
影响因子: 2.6
作者:
P. Rowley;P. Leicester;D. Palmer;P. Westacott;C. Candelise;T. Betts;R. Gottschalg
通讯作者: R. Gottschalg
去中心化系统和燃料匮乏:有什么联系或风险吗☆
DOI: --
发表时间: 2008
期刊:
影响因子: --
作者:
G. Walker
通讯作者: G. Walker
DOI: 10.1016/j.ecolmodel.2012.01.013
发表时间: 2012-04-10
影响因子: 3.1
作者:
Marcot, Bruce G.
通讯作者: Marcot, Bruce G.
DOI: --
发表时间: 2012
期刊:
影响因子: --
作者:
M. Patsalides;A. Stavrou;V. Efthymiou;G. Georghiou
通讯作者: G. Georghiou