scholarly journals The Potential Of Simulating Energy Systems: The Multi Energy Systems Simulator Model

2021 ◽  
Author(s):  
Luigi Bottecchia ◽  
Pietro Lubello ◽  
Pietro Zambelli ◽  
Carlo Carcasci ◽  
Lukas Kranzl
Keyword(s):  
Open Source ◽  
Spatial Scales ◽  
Optimal Solution ◽  
Energy Systems ◽  
Energy Transition ◽  
Simulation Models ◽  
Energy System ◽  
System Modelling ◽  
Energy System Model ◽  
Urban Level

Energy system modelling is an essential practice to assist a set of heterogeneous stakeholders in the process of defining an effective and efficient energy transition. From the analysis of a set of open source energy system models, it has emerged that most models employ an approach directed at finding the optimal solution for a given set of constraints. On the contrary, a simulation model is a representation of a system that is used to reproduce and understand its behaviour under given conditions, without seeking an optimal solution. Given the lack of simulation models that are also fully open source, in this paper a new open source energy system model is presented. The developed tool, called Multi Energy Systems Simulator (MESS), is a modular, multi-node model that allows to investigate non optimal solutions by simulating the energy system. The model has been built having in mind urban level analyses. However, each node can represent larger regions allowing wider spatial scales to be be represented as well. MESS is capable of performing analysis on systems composed by multiple energy carriers (e.g. electricity, heat, fuels). In this work, the tool’s features will be presented by a comparison between MESS itself and an optimization model, in order to analyze and highlight the differences between the two approaches, the potentialities of a simulation tool and possible areas for further development.

scholarly journals The Potential of Simulating Energy Systems: The Multi Energy Systems Simulator Model

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5724
Author(s):  
Luigi Bottecchia ◽  
Pietro Lubello ◽  
Pietro Zambelli ◽  
Carlo Carcasci ◽  
Lukas Kranzl
Keyword(s):  
Open Source ◽  
Spatial Scales ◽  
Optimal Solution ◽  
Energy Systems ◽  
Energy Transition ◽  
Energy System ◽  
System Modelling ◽  
Energy System Model ◽  
Urban Energy ◽  
Realistic Description

Energy system modelling is an essential practice to assist a set of heterogeneous stakeholders in the process of defining an effective and efficient energy transition. From the analysis of a set of open-source energy system models, it emerged that most models employ an approach directed at finding the optimal solution for a given set of constraints. On the contrary, a simulation model is a representation of a system used to reproduce and understand its behaviour under given conditions without seeking an optimal solution. In this paper, a new open-source energy system model is presented. Multi Energy Systems Simulator (MESS) is a modular, multi-energy carrier, multi-node model that allows the investigation of non optimal solutions by simulating an energy system. The model was built for urban level analyses. However, each node can represent larger regions allowing wider spatial scales to be represented as well. In this work, the tool’s features are presented through a comparison between MESS and Calliope, a state of the art optimization model, to analyse and highlight the differences between the two approaches, the potentialities of a simulation tool and possible areas for further development. The two models produced coherent results, showing differences that were tracked down to the different approaches. Based on the comparison conducted, general conclusions were drawn on the potential of simulating energy systems in terms of a more realistic description of smaller energy systems, lower computational times and increased opportunity for participatory processes in planning urban energy systems.

Multi-Scale, Multi-Dimensional Modelling of Future Energy Systems

2015 ◽  
pp. 113-135 ◽  
Author(s):  
Catalina Spataru ◽  
Andreas Koch ◽  
Pierrick Bouffaron
Keyword(s):  
Material Science ◽  
Control Strategies ◽  
Energy Systems ◽  
Simulation Models ◽  
Energy System ◽  
System Modelling ◽  
Multi Scale ◽  
Future Challenges ◽  
Urban Energy ◽  
Power System Engineering

This chapter provides a discussion of current multi-scale energy systems expressed by a multitude of data and simulation models, and how these modelling approaches can be (re)designed or combined to improve the representation of such system. It aims to address the knowledge gap in energy system modelling in order to better understand its existing and future challenges. The frontiers between operational algorithms embedded in hardware and modelling control strategies are becoming fuzzier: therefore the paradigm of modelling intelligent urban energy systems for the future has to be constantly evolving. The chapter concludes on the need to build a holistic, multi-dimensional and multi-scale framework in order to address tomorrow's urban energy challenges. Advances in multi-scale methods applied to material science, chemistry, fluid dynamics, and biology have not been transferred to the full extend to power system engineering. New tools are therefore necessary to describe dynamics of coupled energy systems with optimal control.

Decision support for renewables deployment through spatially explicit energy system alternatives

2021 ◽  
Author(s):  
Bryn Pickering ◽  
Francesco Lombardi ◽  
Stefan Pfenninger
Keyword(s):  
Energy Systems ◽  
Energy Transition ◽  
Weather Conditions ◽  
Energy System ◽  
Spatially Explicit ◽  
Energy System Model ◽  
Modelling Framework ◽  
Wide Range ◽  
Adverse Weather ◽  
Generation Capacity

<p>A decarbonised European energy system will require a number of potentially contested decisions on where best to locate renewable generation capacity. Typically, modellers determine the “best” system based on the least cost to society, focussing on a cost-minimising energy system model result to inform planning and policy. This approach neglects potentially more desirable alternative results which might, for example, avoid problematic concentrations of onshore wind power deployment, increase national supply security, or lower the risk of system failure in adverse weather conditions.</p><p>In response, we have developed a method to generate spatially explicit, practically optimal results (SPORES) in the context of energy system optimisation. SPORES can be used to explore energy systems which may offer more socially, politically, or environmentally acceptable alternatives. Furthermore, we have developed metrics to aid identification of interesting alternatives, like those which maximise the spatial distribution of wind generation capacity or minimise exposure to multi-year demand and weather uncertainty.</p><p>In this presentation, we will detail the application of the SPORES method in two cases of energy system decarbonisation:  the Italian power system and the European energy system. We will present technology deployment strategies which are prevalent across SPORES, such as solar photovoltaics coupled with battery storage, as well as those which offer flexibility of choice in location and extent of deployment. To help with the urgent task of planning socially and politically acceptable energy system decarbonisation strategies, our implementation of SPORES in the open-source energy systems modelling framework Calliope makes it accessible to a wide range of potential users; we will also discuss how other research groups can further build on this to accelerate the energy transition.</p>

Identifying land cover suitability factors for photovoltaic installations with focus on cropland and urban areas

2021 ◽  
Author(s):  
Madhura Yeligeti ◽  
Wenxuan Hu ◽  
Yvonne Scholz ◽  
Kai von Krbek
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Energy Systems ◽  
Energy System ◽  
Climatic Conditions ◽  
System Modelling ◽  
Solar Photovoltaic ◽  
Land Cover Types ◽  
The World ◽  
Urban Settlements

<p>Solar photovoltaic (PV) systems will foreseeably be an integral part of future energy systems. Land cover area analysis has a large influence on estimatiin of long-term solar photovoltaic potential of the world in high spatial detail. In this regard, it is often seen in contemporary works, that the suitability of various land cover categories for PV installation is considered in a yes/no binary response. While some areas like natural parks, sanctuaries, forests are usually completely exempted from PV potential calculations, other land over categories like urban settlements, bare, sparsely vegetated areas, and even cropland can principally support PV installations to varying degrees. This depends on the specific land use competition, social, economic and climatic conditions, etc. In this study, we attempt to evaluate these ‘factors of suitability’ of different land cover types for PV installations.</p><p>As a basis, the openly available global land cover datasets from the Copernicus Land Monitoring Service were used to identify major land cover types like cropland, shrubland, bare, wetlands, urban settlements, forests, moss and snow etc. For open area PV installations, with a focus on cropland, we incorporated the promising technology of ‘Agri-voltaics’ in our investigation. Different crops have shown to respond positively or negatively, so far, to growing under PV panels according to various experimental and commercial sources. Hence, we considered 18 major crops of the world (covering 85% of world cropland) individually and consequently, evaluated a weighted overall suitability factor of cropland cover for PV, for three acceptance scenarios of future.</p><p>For rooftop PV installations in urban areas, various socio-economic and geographical influences come in play. The rooftop area available and further usable for PV depends on housing patterns (roof type, housing density) which vary with climate, population density and socio-economic lifestyle. We classified global urban areas into several clusters based on combinations of these factors. For each cluster, rooftop area suitability is evaluated at a representative location using the land cover maps, the Open Street Map and specific characteristics of the cluster.</p><p>Overall, we present an interdisciplinary approach to integrate technological, social and economic aspects in land cover analysis to estimate PV potentials. While the intricacies may still be insufficient for planning small localized energy systems, this can reasonably benefit energy system modelling from a regional to international scale.</p>

Selected ‘Starter Kit’ energy system modelling data for Paraguay (#CCG)

2021 ◽  
Author(s):  
Carla Cannone ◽  
Lucy Allington ◽  
Ioannis Pappis ◽  
Karla Cervantes Barron ◽  
Will Usher ◽  
...  
Keyword(s):  
Model Development ◽  
Energy System ◽  
Simple Zero ◽  
System Model ◽  
System Modelling ◽  
Local Data ◽  
Energy System Model ◽  
Starting Point ◽  
Modelling Studies ◽  
Access To Data

Abstract Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to energy system modelling, causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Paraguay, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and three stylized scenarios (Fossil Future, Least Cost and Net Zero by 2050) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.

scholarly journals Selected ‘Starter Kit’ energy system modelling data for Morocco (#CCG)

2021 ◽  
Author(s):  
Carla Cannone ◽  
Lucy Allington ◽  
Ioannis Pappis ◽  
Karla Cervantes Barron ◽  
Will Usher ◽  
...  
Keyword(s):  
Model Development ◽  
Energy System ◽  
Simple Zero ◽  
System Model ◽  
System Modelling ◽  
Local Data ◽  
Energy System Model ◽  
Starting Point ◽  
Modelling Studies ◽  
Access To Data

Abstract Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to starting energy system modelling in developing countries, thereby causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Morocco, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and two stylized scenarios (Fossil Future and Least Cost) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.

scholarly journals Selected ‘Starter Kit’ energy system modelling data for Ecuador (#CCG)

2021 ◽  
Author(s):  
Carla Cannone ◽  
Lucy Allington ◽  
Ioannis Pappis ◽  
Karla Cervantes Barron ◽  
Will Usher ◽  
...  
Keyword(s):  
Model Development ◽  
Energy System ◽  
Simple Zero ◽  
System Model ◽  
System Modelling ◽  
Local Data ◽  
Energy System Model ◽  
Starting Point ◽  
Modelling Studies ◽  
Access To Data

Abstract Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to energy system modelling, causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Ecuador, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and three stylized scenarios (Fossil Future, Least Cost and Net Zero by 2050) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.

scholarly journals Selected ‘Starter Kit’ energy system modelling data for Laos (#CCG)

2021 ◽  
Author(s):  
Lucy Allington ◽  
Carla Cannone ◽  
Ioannis Pappis ◽  
Karla Cervantes Barron ◽  
Will Usher ◽  
...  
Keyword(s):  
Model Development ◽  
Energy System ◽  
Simple Zero ◽  
System Model ◽  
System Modelling ◽  
Local Data ◽  
Energy System Model ◽  
Starting Point ◽  
Modelling Studies ◽  
Access To Data

Abstract Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to energy system modelling, causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Laos, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and three stylized scenarios (Fossil Future, Least Cost and Net Zero by 2050) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.

scholarly journals Selected ‘Starter Kit’ energy system modelling data for Togo (#CCG)

2021 ◽  
Author(s):  
Lucy Allington ◽  
Carla Cannone ◽  
Ioannis Pappis ◽  
Karla Cervantes Barron ◽  
Will Usher ◽  
...  
Keyword(s):  
Model Development ◽  
Energy System ◽  
Simple Zero ◽  
System Model ◽  
System Modelling ◽  
Local Data ◽  
Energy System Model ◽  
Starting Point ◽  
Modelling Studies ◽  
Access To Data

Abstract Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to starting energy system modelling in developing countries, thereby causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Togo, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and three stylized scenarios (Fossil Future, Least Cost and Net Zero by 2050) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.

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