• Energy Research

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 Guinea, 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.

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 Burundi, 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.

Abstract This paper presents a methodological framework using a multi model approach to assess power system security. System security is viewed here as a multidimensional systemic property of the entire energy system. The paper shows that the different dimensions of a secure energy system are correlated, and hence their behaviour cannot be explained solely by an understanding of the individual dimensions or by system elements in isolation. The implication of this is that a proper assessment of the security of a power system requires a combination of different techno-economic models. The paper develops a comprehensive multi-model approach for investigating energy security issues within power systems, and applies it to a case study focussing on the Italian power sector. The core research activity involves using an energy systems model of Italy (MONET) to build a dedicated power systems model (PLEXOS_IT) and then undertaking a soft-linking exercise between the two models. The purpose is to use PLEXOS_IT to investigate the system adequacy of the power system results produced by MONET for future possible energy system scenarios.

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 Indonesia, 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.

This paper assesses through scenario analysis the future role of bioenergy in a deep mitigation context. We focus in particular on the implications for sustainability – namely, competing demands for land-use, import dependency, availability of sustainable bioenergy and economics. The analysis here is limited to one Member State, Ireland, which is an interesting case study for a number of reasons, including significant import dependency and recent acceleration in renewable energy deployment. We used the Irish TIMES model, the energy systems model for Ireland developed with the TIMES model generator, for this scenario analysis. Long term, least cost mitigation scenarios point to bioenergy meeting more than half of Ireland’s energy needs by 2050. The results of this paper point to the impact of tightened sustainability criteria and limitation on bioenergy imports, namely the increased use of indigenous bioenergy feedstocks, increased electrification in the energy system, the introduction of hydrogen and higher marginal abatement costs.

As the shares of variable renewable generation in power systems increase, so does the need for, inter alia, flexible balancing mechanisms. These mechanisms help ensure the reliable operation of the electricity system by compensating for fluctuations in supply or demand. However, a focus on short-term balancing is sometimes neglected when assessing future capacity expansions with long-term energy system models. Developing heuristics that can simulate short-term system issues is one way of augmenting the functionality of such models. To this end, we present an extended functionality to the Open Source Energy Modelling System (OSeMOSYS), which captures the impacts of short-term variability of supply and demand on system adequacy and security. Specifically, we modelled the system adequacy as the share of wind energy is increased. Further, we enable the modelling of operating reserve capacities required for balancing services. The dynamics introduced through these model enhancements are presented in an application case study. This application indicates that introducing short-term constraints in long-term energy models may considerably influence the dispatch of power plants, capacity investments, and, ultimately, the policy recommendations derived from such models.

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 Myanmar, 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.

Photovoltaic generation has reached high penetration levels in many countries. Photovoltaic like other variable renewables can have significant implications for the adequacy and operation of the power system and in general these implications can be location specific. This work focuses on the Lombardy region, in Italy, to study the implications that different penetrations of photovoltaic would have on the need for firm generation capacity and on the variability that this firm capacity would have to face. This is done by analyzing a the combination of real historical irradiance and demand data for the year 2012. Results show that even high penetrations of photovoltaic in the region would not reduce the need for firm generation. Moreover, high levels of generation from PVwould lead to higher and more frequent changes in generation. These considerations must be properly taken into account when encouraging the penetration of photovoltaic and when modeling power systems for planning purposes.