scholarly journals A systemic approach to analyze integrated energy system modeling tools: A review of national models

2020 ◽  
Vol 133 ◽  
pp. 110195 ◽  
Author(s):  
A. Fattahi ◽  
J. Sijm ◽  
A. Faaij
IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 40095-40108 ◽  
Author(s):  
Muhammad Faizan Tahir ◽  
Chen Haoyong ◽  
Kashif Mehmood ◽  
Nauman Ali ◽  
Jameel Ahmed Bhutto

2020 ◽  
Vol 13 (1) ◽  
pp. 265
Author(s):  
Mine Isik ◽  
P. Ozge Kaplan

A thorough understanding of the drivers that affect the emission levels from electricity generation, support sound design and the implementation of further emission reduction goals are presented here. For instance, New York State has already committed a transition to 100% clean energy by 2040. This paper identifies the relationships among driving factors and the changes in emissions levels between 1990 and 2050 using the logarithmic mean divisia index analysis. The analysis relies on historical data and outputs from techno-economic-energy system modeling to elucidate future power sector pathways. Three scenarios, including a business-as-usual scenario and two policy scenarios, explore the changes in utility structure, efficiency, fuel type, generation, and emission factors, considering the non-fossil-based technology options and air regulations. We present retrospective and prospective analysis of carbon dioxide, sulfur dioxide, nitrogen oxide emissions for the New York State’s power sector. Based on our findings, although the intensity varies by period and emission type, in aggregate, fossil fuel mix change can be defined as the main contributor to reduce emissions. Electricity generation level variations and technical efficiency have relatively smaller impacts. We also observe that increased emissions due to nuclear phase-out will be avoided by the onshore and offshore wind with a lower fraction met by solar until 2050.


2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Oliver Ruhnau ◽  
Lion Hirth ◽  
Aaron Praktiknjo

Abstract With electric heat pumps substituting for fossil-fueled alternatives, the temporal variability of their power consumption becomes increasingly important to the electricity system. To easily include this variability in energy system analyses, this paper introduces the “When2Heat” dataset comprising synthetic national time series of both the heat demand and the coefficient of performance (COP) of heat pumps. It covers 16 European countries, includes the years 2008 to 2018, and features an hourly resolution. Demand profiles for space and water heating are computed by combining gas standard load profiles with spatial temperature and wind speed reanalysis data as well as population geodata. COP time series for different heat sources – air, ground, and groundwater – and different heat sinks – floor heating, radiators, and water heating – are calculated based on COP and heating curves using reanalysis temperature data. The dataset, as well as the scripts and input parameters, are publicly available under an open source license on the Open Power System Data platform.


2020 ◽  
Vol 9 (1) ◽  
pp. 2000668
Author(s):  
Roland Cunha Montenegro ◽  
Panagiotis Fragkos ◽  
Audrey Helen Dobbins ◽  
Dorothea Schmid ◽  
Steve Pye ◽  
...  

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