Novel procedure to formulate load profiles for off-grid rural areas

Stochastic load profile construction for the multi-tier framework for household electricity access using off-grid DC appliances

“…However, this study was primarily in the urban scenario, with contemporary loads, and considering hourly mean power levels. Mandelli et al (2016) also discuss a bottom-up approach to construct load profiles specifically for offgrid areas. While Mandelli et al (2016) come closest to creating a bottom-up methodology for constructing load profiles for rural off-grid systems, there are additional aspects that are considered in the study described in this paper, which will be incorporated in the methodology described in the "Methodology" section.…”

Transient simulation modelling and energy performance of a standalone solar-hydrogen combined heat and power system integrated with solar-thermal collectors

“…3) as taken by [9] for a similar remote household in southeast Australia (Victoria), that is at 5 kW h. This includes electrical and auxiliary appliances and excludes heating and air conditioning, as a passive house design is considered without going into the details of that. This average load profile comprises two peaks, one occurring in the morning and one in the evening similar to that in [52,53]. It is assumed to be the same for all the days during the year as space heating and air conditioning are excluded.…”

Methodology for the Energy Need Assessment to Effectively Design and Deploy Mini-Grids for Rural Electrification

“…Thus, the energy consumption modelling coming from the proposed assessment methodology is based on a bottom-up approach, which is used to model consumptions of each end-use and hence to identify areas for efficiency improvements at user level and is based on statistical or engineering models [43]. Current and forecast data are fundamental for the mini-grid development, as highlighted in literature, since power system engineering refers to load forecasting as the domain of models able to provide data for setting the best planning and operating of grids [44].…”

“…This issue has been investigated in detail also in [57], but the authors did not tackle the uncertainties in primary data acquisition and used a proxy method for getting "typical" classes of users based on their observations on already electrified peri-urban areas of Uganda. The same authors proposed a method to formulate load profiles for expected new customers in off-grid rural areas without prior access to electricity [44]. The method employs a bottom-up stochastic approach to take into account the variability of the overall time in which an appliance is functioning in a day and its functioning windows; but there is no insight on how to acquire the input data for it, and the model is validated on an already electrified site.…”