• Energy Research

Abstract The COVID-19 pandemic has affected the economy of Tunisia, like that of many other countries. With electricity consumption dropping, consumption patterns changing, international fuel prices plummeting and uncertainty raging, the pandemic has affected not least the planning of investments in electricity supply. Although the government seems unlikely to revise the decarbonisation targets downwards, questions arise on whether the investments planned before the pandemic are still relevant in the changed global landscape and what effects they may have on the country’s economy.In this study, we analyse post-pandemic scenarios for the electricity supply system of Tunisia with an energy-economy modelling framework, soft-linking the energy modelling tool OSeMOSYS and an open source Input-Output model. We extract insights on the cost-competitiveness of different – previously planned and new – electricity supply solutions and their impacts on job creation and loss in the entire economy. We find that renewable solutions based on solar photovoltaic remain highly competitive with gas-fired generation under different projections of gas prices and that several low-carbon and energy efficiency solutions have high potential for job creation.

Abstract The COVID-19 pandemic has affected the economy of Tunisia, like that of many other countries. With electricity consumption dropping, consumption patterns changing, international fuel prices plummeting and uncertainty raging, the pandemic has affected not least the planning of investments in electricity supply. Although the government seems unlikely to revise the decarbonisation targets downwards, questions arise on whether the investments planned before the pandemic are still relevant in the changed global landscape and what effects they may have on the country’s economy.In this study, we analyse post-pandemic scenarios for the electricity supply system of Tunisia with an energy-economy modelling framework, soft-linking the energy modelling tool OSeMOSYS and an open source Input-Output model. We extract insights on the cost-competitiveness of different – previously planned and new – electricity supply solutions and their impacts on job creation and loss in the entire economy. We find that renewable solutions based on solar photovoltaic remain highly competitive with gas-fired generation under different projections of gas prices and that several low-carbon and energy efficiency solutions have high potential for job creation.

Abstract Energy modelling is the process of using mathematical models to develop abstractions and then seek insights into future energy systems. It can be an abstract academic activity. Or, it can insert threads that influence our development. We argue therefore, that energy modelling that provides policy support (EMoPS) should not only be grounded in rigorous analytics, but also in good governance principles. As, together with other policy actions, it should be accountable. Almost all aspects of society and much of its impact on the environment are influenced by our use of energy. In this context, EMoPS can inspire, motivate, calibrate, and ‘post assess’ energy policy. But, such modeling is often undertaken by too few analysts under time and resource pressure. Building on the advances of ‘class leaders’, we propose that EMoPS should reach for practical goals — including engagement and accountability with the communities it involves, and those it will later affect. (We use the term Ubuntu, meaning ‘I am because you are’ to capture this interdependency). We argue that Ubuntu, together with retrievability, repeatability, reconstructability, interoperability and auditability (U4RIA) of EMoPS should be used to signal the beginnings of a new default practice. We demonstrate how the U4RIA principles can contribute in practice using recent modelling of aspirational energy futures by Costa Rica as a case study. This modelling effort includes community involvement and interfaces and integrates stakeholder involvement. It leaves a trail that allows for its auditing and accountability, while building capacity and sustainable institutional memory.

Abstract Energy modelling is the process of using mathematical models to develop abstractions and then seek insights into future energy systems. It can be an abstract academic activity. Or, it can insert threads that influence our development. We argue therefore, that energy modelling that provides policy support (EMoPS) should not only be grounded in rigorous analytics, but also in good governance principles. As, together with other policy actions, it should be accountable. Almost all aspects of society and much of its impact on the environment are influenced by our use of energy. In this context, EMoPS can inspire, motivate, calibrate, and ‘post assess’ energy policy. But, such modeling is often undertaken by too few analysts under time and resource pressure. Building on the advances of ‘class leaders’, we propose that EMoPS should reach for practical goals — including engagement and accountability with the communities it involves, and those it will later affect. (We use the term Ubuntu, meaning ‘I am because you are’ to capture this interdependency). We argue that Ubuntu, together with retrievability, repeatability, reconstructability, interoperability and auditability (U4RIA) of EMoPS should be used to signal the beginnings of a new default practice. We demonstrate how the U4RIA principles can contribute in practice using recent modelling of aspirational energy futures by Costa Rica as a case study. This modelling effort includes community involvement and interfaces and integrates stakeholder involvement. It leaves a trail that allows for its auditing and accountability, while building capacity and sustainable institutional memory.

Abstract Energy system modelling can be used to develop internally consistent quantified scenarios. These provide key insights needed to mobilise finance, understand market development, infrastructure deployment, the associated role of institutions, and generally support improved policymaking. However, access to data is often a barrier to starting energy system modelling, especially in developing countries, thereby causing delays to decision making. Therefore, this article provides data that can be used to create a simple zero-order energy system model for a range of developing countries in Africa, East Asia, and South America, 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 organisations, journal articles, and existing modelling studies. This means that the datasets can be easily updated based on the latest available information or more detailed and accurate local data. As an example, these data were also used to calibrate a simple energy system model for Kenya 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 the 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 develop internally consistent quantified scenarios. These provide key insights needed to mobilise finance, understand market development, infrastructure deployment, the associated role of institutions, and generally support improved policymaking. However, access to data is often a barrier to starting energy system modelling, especially in developing countries, thereby causing delays to decision making. Therefore, this article provides data that can be used to create a simple zero-order energy system model for a range of developing countries in Africa, East Asia, and South America, 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 organisations, journal articles, and existing modelling studies. This means that the datasets can be easily updated based on the latest available information or more detailed and accurate local data. As an example, these data were also used to calibrate a simple energy system model for Kenya 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 the 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.