1,721,004 research outputs found
An energy planning perspective about the multi-sectorial synergies and implications of the energy transition
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Dynamic Accounting for End-Use CO2 Emissions From Low-Carbon Fuels in Energy System Optimization Models
Full text linkEnergy system optimization models are widely used worldwide to assess the effectiveness of decarbonization strategies. The correct accounting of greenhouse gas emissions, mainly CO2, is crucial in this field. Sectorial emissions are typically computed using commodity-specific factors based on a given (static) fuel composition. For fuels generated by combining fossil and low-carbon commodities, however, the share of the low-carbon component can change throughout the model time horizon. As an alternative to static accounting, this work proposes a dynamic accounting method for the emissions avoided thanks to the contribution of hydrogen, biofuels and synfuels. The static accounting method provides an overestimation of the emission levels compared to the proposed accounting method results, which then helps boost new low-carbon technologies in the future energy mix
Introducing a New Sustainability Metric for the Evaluation of the Power Sector Mix in TIMES Energy System Models
No full textAmong energy system optimization models, those of the TIMES family are able to analyze scenarios based on a diverse set of socio-economic assumptions and different degrees of technological advancement. The technologically explicit and detailed nature of such models makes them a valuable tool for decision making on future energy issues. The set of parameters used to describe both supply and end-use demand technologies is devoted to produce the minimum-cost configuration of the investigated energy system. The TIMES framework allows the user to specify a set of constraints to consider the environmental impact of the supply and end-use technological mix. In a sustainability perspective, however, the analysis is limited because CO2 emissions are the only parameter considered to assess the impact on climate change. We propose here to integrate in the well-established TIMES modeling framework a sustainability metric for the evaluation of the computed supply mix, considering a set of social and environmental sustainability criteria. Those criteria are expressed by appropriate indicators, based on an evaluation of the related impacts. Eventually, the whole sustainability level of power sector technologies mix obtained by TIMES optimization is evaluated through a combination of the scores assigned to each technology, and then expressed with easily understandable sustainability labels. The resulting sustainability evaluation should then be translated into a variation of input parameters for the model, consistently with the selected quantitative indicators, and the TIMES optimization should be iterated with new input data set, with the effect to perform a sustainability optimization together with the economic
Enhancing energy transition with open-source regional energy system optimization models: TEMOA-Piedmont
Full text linkThis paper describes TEMOA-Piedmont, a model to perform long-term energy planning at regional level for Piedmont (Italy). The model has been developed from scratch within the fully open access TEMOA framework, involving a single spatial region and a time horizon extending from 2011 to 2050. The model introduces the novelty of focusing on a sub-national case study. Despite their potential, regional models are not yet diffuse in the energy programming and policy definition of the countries but are gaining their role and attention in recent years. A regional model enables consideration of local characteristics in production and consumption of energy carriers and helps to spot the barriers and opportunities for energy transition, thereby supporting both national and local policy makers. The methodology adopted for TEMOA-Piedmont in developing each sector of the model varies following the structure of the available data. The benchmark of the model was done comparing the outcomes of the model with the data of the Regional Energy and Environmental Plan and Italian transmission system operator, showing an excellent alignment, with differences limited to a few percent both for the power and demand sectors. At the same time, TEMOA-Piedmont is tested on future scenarios relevant to the peculiarities of the local energy system (local pollution issues and a relevant share of the hydroelectric resource), providing an example of the model policy relevance. Finally, the robustness of the model is tested through illustrative scenarios, and the associated results are presented
A Comprehensive Metric to Assess the Security of Future Energy Systems Through Energy System Optimization Models
No full textEnsuring energy security is one of the main objectives of energy policies of many countries worldwide. In this regard, this paper proposes a metric to evaluate energy security under medium-to-long term energy scenarios generated by the TEMOA-Italy model. Such a metric consists of an energy security index covering several dimensions of energy security. Among them, the inclusion of the supply risk of critical raw materials represents a novelty, compared to the existing literature. Moreover, critical raw materials are crucial for the decarbonization of urban energy systems, for instance through smart cities and vehicles to grid strategies. The analysis here shows how the penetration of low-carbon technologies can provide significant benefits to energy security, while their dependence on critical raw materials could represent a bottleneck for the evolution of the energy system. Accordingly, the metric presented in this paper can provide relevant policy insights on the effects of the transition from fossil fuels to low carbon sources on energy security
The Energy Transition in the Age of Open Science: Call for Regional Modelling Solutions
No full textThis work introduces a regional energy model, emphasizing the importance of localized approaches to sustainability. It highlights the significance of energy system models in guiding the energy transitions policies, underscoring the influence of open science on advancing modelling techniques. The open-source energy models can play an important role in developing regional frameworks, which offer more precise insights into the characteristics and challenges of specific areas. The paper introduces TEMOA-Piedmont, the first energy system model of the Piedmont region in Italy, developed within the TEMOA optimization tool. The model aims to bridge national and regional energy policies by providing a detailed analysis of the region's energy structure. The presented results focus on the transport sector, highly impacting the urban environments within the Piedmont region (e.g., the city of Turin) and object of the energy policies due to its criticality for the region. Developed based on totally publicly available data, TEMOA-Piedmont offers a valuable tool for policymakers and stakeholders to step towards a sustainable energy future tailored to the Piedmont region's needs
May the availability of critical raw materials affect the security of energy systems? An analysis for risk-aware energy planning with TEMOA-Italy
Full text linkThe energy transition requires the deployment of clean energy technologies, which typically requires critical raw materials. Their supply chains are characterized by high geographical concentration and political instability, thus leading to potential supply chain bottlenecks and negative impacts on the security of energy systems. However, these aspects are not considered in traditional energy security metrics. To address this lack, this paper proposes a novel energy security metric to study the impact of potential materials supply chain bottlenecks on future energy systems. First, a comprehensive metric is developed by including the supply risks associated with clean energy technologies. Second, the metric is applied to materials supply disruption scenarios. The case study is the Italian energy system, though the TEMOA-Italy open model. The results show that transport is the sector most contributing to the material consumption and mostly affected by the considered materials disruption causes, especially concerning the battery electric vehicles penetration. On the contrary, the power sector is minorly influenced by the introduction of supply disruptions except for storage technologies. Lastly, the material supply risk dimension strongly influences the overall energy security of the system, which increases in disruption scenarios when a lower consumption of critical raw materials is forced
Can We Rely on Open-Source Energy System Optimization Models? The TEMOA-Italy Case Study
Full text linkEnergy system models have become crucial to assess the effectiveness of possible energy policies in pursuing the declared environmental objectives. Among bottom-up models, the tools most widely used by researchers and institutions to perform scenario analyses and policy evaluations rely on commercial software and closed databases, limiting the transparency of the studies. The purpose of this work is to demonstrate that open-source tools, relying on open databases, can be used as a valid alternative to commercial tools, getting equivalent results not only for simple case studies as done so far, but also for complex (national, regional, or multi-regional) reference energy systems. Working on the already available open TEMOA optimization framework, a bottom-up technology-rich model is developed here for the Italian reference energy system on an extended TEMOA version, comparable in detail and complexity to the equivalent TIMES framework. The accuracy of the novel TEMOA-Italy model in a business-as-usual scenario is assessed, showing that the average relative differences with respect to the consolidated TIMES-Italy results are in the order of few percent. The open-source model, available on Github, is now ready for the test and implementation of new optimization paradigms, which was not possible in the TIMES framework
A dynamic accounting method for CO2 emissions to assess the penetration of low-carbon fuels: application to the TEMOA-Italy energy system optimization model
Full text linkA correct counting of greenhouse gas emissions, mainly CO2, is crucial in energy system optimization models, widely used to assess the effectiveness of decarbonization strategies. Sectorial emissions are typically computed at each modeled time period using commodity-specific factors based on a given static fuel composition. For fuels generated by combining fossil and low-carbon commodities, however, the share of the low-carbon component may change over time. Under certain fractions, the blending with hydrogen, biofuels, and synfuels, constitutes a viable decarbonization alternative, without the need for retrofitting the existing infrastructure. This work proposes a dynamic accounting method for the avoided emissions thanks to blending low-carbon fuels with fossil fuels as an alternative to the traditional static evaluation in energy system models. The proposed methodology is based on the application of negative process-specific factors to account for avoided emissions. This new scheme is integrated and tested in the TEMOA-Italy open model. The dynamic methodology is first compared to the static one, showing that the latter provides an overestimation of the emission levels. Then, it is proven to work properly in a very stringent decarbonization scenario for a large range of blending fractions. Finally, the results of the decarbonization scenario are deeply analyzed to provide valuable insights for future policy-relevant assessments. Even if the high penetration of blended low-carbon fuels in the energy mix quantitatively differs from the evolution foreseen by national, European, and global energy policies, such penetration reflects the crucial role of hydrogen, biofuels, and synfuels depicted in those policies, to fulfill the intermediate and long-term emission reduction targets
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