Realistic Multi-Scale Modeling of Household Electricity Behaviors

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...
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Gespeichert in:

Autor*in:	Lorenzo Bottaccioli [verfasserIn] Santa Di Cataldo [verfasserIn] Andrea Acquaviva [verfasserIn] Edoardo Patti [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Household load profile Non Homogeneous Semi-Markov Model Monte Carlo time use survey use of energy load modeling

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 7(2019), Seite 2467-2489
Übergeordnetes Werk:	volume:7 ; year:2019 ; pages:2467-2489

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2018.2886201

Katalog-ID:	DOAJ007148623

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callnumber-first	T - Technology
author	Lorenzo Bottaccioli
spellingShingle	Lorenzo Bottaccioli misc TK1-9971 misc Household load profile misc Non Homogeneous Semi-Markov Model misc Monte Carlo misc time use survey misc use of energy misc load modeling misc Electrical engineering. Electronics. Nuclear engineering Realistic Multi-Scale Modeling of Household Electricity Behaviors
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title	Realistic Multi-Scale Modeling of Household Electricity Behaviors
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title_sort	realistic multi-scale modeling of household electricity behaviors
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title_auth	Realistic Multi-Scale Modeling of Household Electricity Behaviors
abstract	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 the 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 behaviors and realistic households load profiles on a daily as well as on a weekly basis, for weekdays and weekends. The proposed approach overcomes the limitations of the state-of-the-art solutions that 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 to 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 by simulating realistic populations in a period covering a whole calendar year and analyze our model’s outcome at different scales. Then, we compare such results with three different data-sets that provide real load consumption at the household, national, and European levels, respectively.
abstractGer	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 the 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 behaviors and realistic households load profiles on a daily as well as on a weekly basis, for weekdays and weekends. The proposed approach overcomes the limitations of the state-of-the-art solutions that 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 to 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 by simulating realistic populations in a period covering a whole calendar year and analyze our model’s outcome at different scales. Then, we compare such results with three different data-sets that provide real load consumption at the household, national, and European levels, respectively.
abstract_unstemmed	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 the 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 behaviors and realistic households load profiles on a daily as well as on a weekly basis, for weekdays and weekends. The proposed approach overcomes the limitations of the state-of-the-art solutions that 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 to 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 by simulating realistic populations in a period covering a whole calendar year and analyze our model’s outcome at different scales. Then, we compare such results with three different data-sets that provide real load consumption at the household, national, and European levels, respectively.
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title_short	Realistic Multi-Scale Modeling of Household Electricity Behaviors
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