Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Realistic Multi-Scale Modelling of Household Electricity Behaviours
To improve the management and reliability of power distribution networks, there is a strong demand for models simulating energy loads in a realistic way. In this paper, we present a novel multi-scale model to generate realistic residential load profiles at different spatial-temporal resolutions. By taking advantage of information from Census and national surveys, we generate statistically consistent populations of heterogeneous families with their respective appliances. Exploiting a Bottom-up approach based on Monte Carlo Non Homogeneous Semi-Markov, we provide household end-user behaviours and realistic households load profiles on a daily as well as on a weekly basis, for either weekdays and weekends. The proposed approach overcomes limitations of state-of-art solutions that do not consider neither the time-dependency of the probability of performing specific activities in a house, nor their duration, or are limited in the type of probability distributions they can model. On top of that, it provides outcomes that are not limited on a per-day basis. The range of available space and time resolutions span from single household to district and from second to year, respectively, featuring multi-level aggregation of the simulation outcomes. To demonstrate the accuracy of our model, we present experimental results obtained simulating realistic populations in a period covering a whole calendar year and analyse our model’s outcome at different scales. Then, we compare such results with three different data-sets that provide real load consumption at household, national and European levels, respectively.
Realistic Multi-Scale Modelling of Household Electricity Behaviours
To improve the management and reliability of power distribution networks, there is a strong demand for models simulating energy loads in a realistic way. In this paper, we present a novel multi-scale model to generate realistic residential load profiles at different spatial-temporal resolutions. By taking advantage of information from Census and national surveys, we generate statistically consistent populations of heterogeneous families with their respective appliances. Exploiting a Bottom-up approach based on Monte Carlo Non Homogeneous Semi-Markov, we provide household end-user behaviours and realistic households load profiles on a daily as well as on a weekly basis, for either weekdays and weekends. The proposed approach overcomes limitations of state-of-art solutions that do not consider neither the time-dependency of the probability of performing specific activities in a house, nor their duration, or are limited in the type of probability distributions they can model. On top of that, it provides outcomes that are not limited on a per-day basis. The range of available space and time resolutions span from single household to district and from second to year, respectively, featuring multi-level aggregation of the simulation outcomes. To demonstrate the accuracy of our model, we present experimental results obtained simulating realistic populations in a period covering a whole calendar year and analyse our model’s outcome at different scales. Then, we compare such results with three different data-sets that provide real load consumption at household, national and European levels, respectively.
Realistic Multi-Scale Modelling of Household Electricity Behaviours
Lorenzo Bottaccioli (Autor:in) / Santa Di Cataldo (Autor:in) / Andrea Acquaviva (Autor:in) / Edoardo Patti (Autor:in) / Bottaccioli, Lorenzo / DI CATALDO, Santa / Acquaviva, Andrea / Patti, Edoardo
01.01.2019
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC:
690
Attitudes and Behavioural Change in Household Waste Management Behaviours
British Library Online Contents | 2003
|Modelling of household electricity consumption with the aid of computational intelligence methods
Taylor & Francis Verlag | 2018
|