Modelling and analysis of energy demand variation and uncertainty in small-scale domestic energy systems
Modelling and analysis of energy demand variation and uncertainty in small-scale domestic energy systems
复制标题
小型国内能源系统中能源需求变化和不确定性的建模与分析
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
G. Flett
中科院分区：
文献类型：
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作者：
G. Flett
对英国未来能源供应的一系列不同情景进行了预测。虽然存在很大的不确定性，但所有人都预计，在有限或独立的网络中集成的小规模分布式发电将有所增加，并且主要是国内消费者。然而，这种系统规模的减小并没有推动设计实践的重大变化，确定性模型和经验法则占主导地位。很少考虑到具体的家庭特征和系统的大小如何影响需求水平和时间，任何需求预测的不确定性程度，以及设计实践应如何改变以反映这一点。所提出的工作的主要贡献是解决这个问题。为了量化变化和不确定性;针对电力和热水使用开发了一个高度差异化、概率性、自下而上的需求模型。1分钟的分辨率模型采用了增强的马尔可夫链占用模型，是基于一个新开发的离散事件的方法占用发起的需求。利用现实的因素家电所有权，收入，占用，和随机的能源使用行为，该模型已被证明捕捉潜在的家庭需求的范围。评估认为，开发的模型，以及任何现有的模型校准使用组数据，往往迅速收敛到组的平均基础上，促使进一步的方法开发，以提高模型的性能，在捕捉个人家庭的需求行为。对现有数据和需求模型输出的分析表明，能源系统的需求可能因社会经济特点和所供应家庭的类型而有很大差异。它还强调，即使家庭特征已知，单个家庭的需求不确定性也可能超过一个数量级。随着系统规模的增加，总体需求不确定性的水平对至少200个家庭系统仍然很重要。因此，开发了一种方法，该方法允许将概率模型的多次运行减少到一个代表性子集，该子集可以用于使用现有的优化工具概率地分析潜在的能源系统性能场景。
A range of different scenarios have been predicted for future UK energy supply. While there is significant uncertainty, all expect an increase in small-scale distributed generation integrated in constrained or independent networks and with predominantly domestic consumers. This reduction in system scale has not, however, driven a significant change in design practices, with deterministic models and rules-of-thumb prevalent. Little consideration has been given to how the specific household characteristics and the size of system impact on demand level and timing, the degree of uncertainty in any demand prediction, and how design practices should change to reflect this. The main contribution of the presented work has been to address this. To allow the variation and uncertainty to be quantified; a highly differentiated, probabilistic, bottom-up demand model has been developed for electrical and hot water use. The 1-minute resolution model incorporates an enhanced Markov chain occupancy model and is based on a newly developed discrete-event approach for occupant-initiated demands. Utilising realistic factoring for appliance ownership, income, occupancy, and random energy-use behaviours, the model has been shown to capture the range of potential household demands. Assessment that the developed model, and any existing model calibrated using group data, tended to rapidly converge to the group average basis, prompted further method development to improve the model’s performance in capturing individual household demand behaviours. Analysis of both existing data and the demand model output has shown that energy system demand can vary significantly based on socio-economic characteristics and the types of households supplied. It also highlights that demand uncertainty for individual households can exceed an order of magnitude, even if household characteristics are known. As the system scale is increased, the level of overall demand uncertainty remains significant to at least 200 household systems. A method has therefore been developed that allows multiple runs of the probabilistic model to be reduced to a representative subset, which can be used to analyse potential energy system performance scenarios probabilistically using existing optimisation tools.
影响因子：
11.2
作者：
M. Muratori;M. C. Roberts;R. Sioshansi;V. Marano;G. Rizzoni
通讯作者：
M. Muratori;M. C. Roberts;R. Sioshansi;V. Marano;G. Rizzoni