TY - JOUR
T1 - Electricity self-sufficiency of single-family houses in Germany and the Czech Republic
AU - Ramirez Camargo, Luis
AU - Nitsch, Felix
AU - Gruber, Katharina
AU - Dorner, Wolfgang
N1 - Funding Information:
Although the RTPV potential (as presented in Section 4.1 ) could be calculated for the whole of Europe, the spatial coverage of the analysis was restricted in two ways. Firstly, the analysis is confined to Germany and the Czech Republic since this study is part of the project “CrossEnergy: cross-border energy infrastructure – future perspectives for a region in change” [46] . This is a research project funded by the European Regional Development Fund which aims at generating a decision support system to evaluate the perspectives of the future energy system in the rural Czech-Bavarian border region. The vector data set with administrative boundaries of the countries was employed as spatial constraint. Secondly, only areas with more than zero and less than 1500 inhabitants per square kilometre were preserved for analysis. This should reflect the areas where the probability of finding SFHs is higher. The threshold value was adopted from the degree of urbanization classification as per EUROSTAT. Areas with less than 1500 inhabitants were considered “intermediate density areas” and “thinly populated areas” [47] , where SFHs are most likely to be found.
Funding Information:
This study was conducted within the framework of the project “CrossEnergy: energy infrastructure – future perspectives for a region in change” (Project number: 036), funded by the European Regional Development Fund and in the frame of the INTERREG V programme between the Federal State of Bavaria (Germany) and the Czech Republic. The COSMO-REA6 data were provided by the Hans-Ertel-Centre for Weather Research. The SC data were provided by the EUMETSAT Satellite Application Facility on Land Surface Analysis [31] .
Publisher Copyright:
© 2018 The Authors
PY - 2018/10
Y1 - 2018/10
N2 - Motivated by a research project that studies the future of the energy system in rural areas at the border between Germany and the Czech Republic, and by the publication of the COSMO-REA high-resolution regional reanalysis data sets for Europe in 2017, this study presents a methodology for generating maps indicating minimum battery and photovoltaics sizes for self-sufficient single-family houses. The methodology consists of three subsequent parts: First, spatiotemporal data sets of electricity demand for single-family houses in rural and low-density urban areas are generated. Second, spatiotemporal data sets of photovoltaics potential are computed based on (a) a technical photovoltaics model, (b) two decades of hourly solar irradiance and temperature data, and (c) snow cover data from the Land Surface Analysis Satellite Applications Facility. Third, a linear optimization model serves to define photovoltaics and battery systems sizes and to generate the corresponding maps. The resulting maps cover Germany and the Czech Republic and are generated for 18 technical and weather-dependent scenarios. The results show how challenging it could be to achieve complete independence from the grid in certain locations. Especially relevant for the sizing of the systems are long periods (several days in a row) of low photovoltaic energy generation due to overcast sky conditions or snow cover of the panels. Furthermore, the results offer a scientifically based source of information for sizing photovoltaics and battery systems in the two countries.
AB - Motivated by a research project that studies the future of the energy system in rural areas at the border between Germany and the Czech Republic, and by the publication of the COSMO-REA high-resolution regional reanalysis data sets for Europe in 2017, this study presents a methodology for generating maps indicating minimum battery and photovoltaics sizes for self-sufficient single-family houses. The methodology consists of three subsequent parts: First, spatiotemporal data sets of electricity demand for single-family houses in rural and low-density urban areas are generated. Second, spatiotemporal data sets of photovoltaics potential are computed based on (a) a technical photovoltaics model, (b) two decades of hourly solar irradiance and temperature data, and (c) snow cover data from the Land Surface Analysis Satellite Applications Facility. Third, a linear optimization model serves to define photovoltaics and battery systems sizes and to generate the corresponding maps. The resulting maps cover Germany and the Czech Republic and are generated for 18 technical and weather-dependent scenarios. The results show how challenging it could be to achieve complete independence from the grid in certain locations. Especially relevant for the sizing of the systems are long periods (several days in a row) of low photovoltaic energy generation due to overcast sky conditions or snow cover of the panels. Furthermore, the results offer a scientifically based source of information for sizing photovoltaics and battery systems in the two countries.
KW - Energy storage
KW - Photovoltaics
KW - Regional reanalysis
KW - Self-sufficient buildings
KW - Solar energy
KW - Spatiotemporal modelling
UR - http://www.scopus.com/inward/record.url?scp=85049484262&partnerID=8YFLogxK
U2 - 10.1016/j.apenergy.2018.06.118
DO - 10.1016/j.apenergy.2018.06.118
M3 - Article
AN - SCOPUS:85049484262
SN - 0306-2619
VL - 228
SP - 902
EP - 915
JO - Applied Energy
JF - Applied Energy
ER -