Generating high-resolution multi-energy load profiles for remote areas with an open-source stochastic model
Generating high-resolution multi-energy load profiles for remote areas with an open-source stochastic model
复制标题
使用开源随机模型为偏远地区生成高分辨率多能源负载曲线
DOI：
10.1016/j.energy.2019.04.097
复制
发表时间：
2019
期刊：
影响因子：
9
通讯作者：
E. Colombo
中科院分区：
文献类型：
--
作者：
F. Lombardi;S. Balderrama;S. Quoilin;E. Colombo
偏远离网地区的能源获取项目将受益于采用多能源系统的观点，通过混合能源载体解决所有能源需求-不仅是照明和电力设备，而且还有热水和烹饪。然而，在偏远地区的多能源分析受到阻碍，缺乏模型，允许多能源负载配置文件的基础上，以访问为基础的信息，其特点是高度的不确定性的生成。本研究提出了一种新的开源自下而上的随机模型，专门为位于偏远地区的系统产生多能源负载。该模型进行了测试和验证，从一个真实的系统获得的数据，显示出一个非常好的近似测量的配置文件，与百分比误差始终低于2%的所有选定的指标，并提高了准确性相比，现有的方法。特别是，一些创新的功能-如定义和调节全天电器的工作周期的可能性-似乎是决定性的，标志着与以前的方法的区别。这可能更有利于案例研究，其特点是受复杂和不可预测的占空比行为影响的电器的更大渗透。
Energy access projects in remote off-grid areas would benefit from the adoption of a multi-energy system perspective, addressing all energy needs – not only lighting and power appliances, but also water-heating and cooking – by means of a mix of energy vectors. However, multi-energy analyses in remote areas are hindered by a lack of models allowing for the generation of multi-energy load profiles based on interview-based information characterised by high uncertainty. This study proposes a novel open-source bottom-up stochastic model specifically conceived for the generation of multi-energy loads for systems located in remote areas. The model is tested and validated against data obtained from a real system, showing a very good approximation of measured profiles, with percentage errors consistently below 2% for all the selected indicators, and an improved accuracy compared to existing approaches. In particular, some innovative features – such as the possibility to define and modulate throughout the day appliances’ duty cycles – seem to be determinant in marking a difference with previous approaches. This might arguably be even more beneficial for case studies characterised by a larger penetration of appliances that are subject to complex and unpredictable duty cycle behaviour.
对英国住宅能源用户的电力负荷进行建模
DOI：
10.1109/upec.2012.6398593
发表时间：
2012
期刊：
--
影响因子：
--
作者：
Tsagarakis G
通讯作者：
Tsagarakis G
影响因子：
5.8
作者：
Nguyen JL;Schwartz J;Dockery DW
通讯作者：
Dockery DW