Publications
85 results found
Nikas A, Frilingou N, Heussaff C, et al., 2024, Three different directions in which the European Union could replace Russian natural gas, Energy, Vol: 290, ISSN: 0360-5442
Russia's invasion of Ukraine fuelled an energy crisis, which considerably impacted Europe given its heavy reliance on Russian natural gas imports. This study uses an ensemble of four global integrated assessment models, which are further soft-linked to two sectoral models, and explores the synergies and trade-offs among three approaches to living without Russian gas in Europe: (a) replacing with other gas imports, (b) boosting domestic energy production, and (c) reducing demand and accelerating energy efficiency. We find that substituting Russian gas from other trade partners would miss an opportunity to accelerate decarbonisation in end-use sectors while risking further fossil-fuel lock-ins, despite featuring the lowest gas price spikes and potentially reducing heating costs for end-users in the near term. Boosting domestic, primarily renewable, energy production on the other hand would instead require considerable investments, potentially burdening consumers. Energy demand reductions, however, could offer considerable space for further emissions cuts at the lowest power-sector investment costs; nonetheless, an energy efficiency-driven strategy would also risk relocation of energy-intensive industries, an aspect of increasing relevance to EU policymakers.
Carboni M, Dall-Orsoletta A, Hawkes A, et al., 2024, The future of road freight transport and alternative technologies: a case study for Italy, Energy Conversion and Management, Vol: 299, ISSN: 0196-8904
The truck sector produces one-fourth of the greenhouse gas emissions in Italy. Therefore, it calls for an urgent emission reduction to achieve the national mid-century net-zero pledges. In this work, a methodology is developed, based on a model for estimating the long-term energy transitions, the ModUlar energy system Simulation Environment (MUSE), to project the long-term freight heavy-duty sector evolution in Italy. The methodology applies a bottom-up description of the sector, where technologies are characterised in terms of costs, efficiencies, and emissions. Results show that efficiency improvements and technological cost reduction due to learning can only reduce the sector emissions by a limited amount. In fact, although, lowering costs of alternative powertrains and fuels will have a significant effect on reducing tailpipe emissions, this should occur alongside a ban of internal combustion engines. Additional renewable generation should need to grow between 30 and 64 TW/y to substantially reduce emissions and leading to a zero-tailpipe truck sector by 2050. The replacement of conventional engines by alternative powertrains remains dependent on distribution and fuelling infrastructure expansion, which should go hand in hand with the promotion of electric and hydrogen-fuelled vehicles.
Moya D, Arroba C, Castro C, et al., 2024, Long-Term Sustainable Energy Transition of Ecuador’s Residential Sector Using a National Survey, Geospatial Analysis with Machine Learning, and Agent-Based Modeling, Congress on Research, Development, and Innovation in Renewable Energies, Publisher: Springer Nature Switzerland, Pages: 23-40, ISBN: 9783031521706
Contreras Fregoso JA, Tremari Romero F, Carbonell Peláez M, et al., 2023, Modelling large-scale hydrogen uptake in the Mexican refinery and power sectors, Energy Reports, Vol: 9, Pages: 48-53
Due to the emissions reduction commitments that Mexico compromised in the Paris Agreement, several clean fuel and renewable energy technologies need to penetrate the market to accomplish the environmental goals. Therefore, there is a need to develop achievable and realistic policies for such technologies to ease the decision-making on national energy strategies. Several countries are starting to develop large-scale green hydrogen production projects to reduce the carbon footprint of the multiple sectors within the country. The conversion sectors, namely power and refinery, are fundamental sectors to decarbonise due to their energy supply role. Nowadays, the highest energy consumables of the country are hydrocarbons (more than 90%) causing a particular challenge for deep decarbonisation. The purpose of this study is to use a multi-regional energy system model of Mexico to analyse a decarbonisation scenario in line with the latest National Energy System Development Program. Results show that if the country wants to succeed in reducing 22% of its GHG emissions and 51% of its short-lived climate pollutants emissions, green hydrogen could play a role in power generation in regions with higher energy demand growth rates. These results show, regarding the power sector, that H2 could represent 13.8 GW or 5.1% of the total installed capacity by 2050, while for the refinery sector H2 could reach a capacity of 157 PJ/y, which is around 31.8% of the total share, and it is mainly driven by the increasing demands of the transport, industry, and power sectors. Nevertheless, as oil would still represent the largest energy commodity, CCS technologies would have to be deployed for new and retrofitted refinery facilities.
Rojas Obregón A, De Kerpel Ramírez A, Giarola S, et al., 2023, The role of hydrogen in a decarbonised future transport sector: A case study of Mexico, Energy Reports, Vol: 9, Pages: 26-31
In recent years, several approaches and pathways have been discussed to decarbonise the transport sector; however, any effort to reduce emissions might be complex due to specific socio-economic and technical characteristics of different regions. In Mexico, the transport sector is the highest energy consumer, representing 38.9% of the national final energy demand, with gasoline and diesel representing 90% of the sector´s total fuel consumption. Energy systems models are powerful tools to obtain insights into decarbonisation pathways to understand costs, emissions and rate of deployment that could serve for energy policy development. This paper focuses on the modelling of the current Mexican transport system using the MUSE-MX multi-regional model with the aim to project a decarbonisation pathway through two different scenarios. The first approach being business as usual (BAU) which aims to analyse current policies implementation and the second being a goal of net zero carbon emissions by 2050. Under the considered net zero scenario, results show potential deployment of hydrogen-based transport technologies, especially for subsectors such as lorries (100% H2 by 2050) and freight train (25% H2 by 2050), while cars and buses tend to full electrification by 2050.
Moya Pinta DA, Copara D, Olivo A, et al., 2023, MUSE-RASA captures human dimension in climate-energy-economic models via global geoAI-ML agent datasets, Scientific Data, Vol: 10, ISSN: 2052-4463
This article provides a combined geospatial artificial intelligence-machine learning, geoAI-ML, agent-based, data-driven, technology-rich, bottom-up approach and datasets for capturing the human dimension in climate-energy-economy models. Seven stages were required to conduct this study and build thirteen datasets to characterise and parametrise geospatial agents in 28 regions, globally. Fundamentally, the methodology starts collecting and handling data, ending with the application of the ModUlar energy system Simulation Environment (MUSE), ResidentiAl Spatially-resolved and temporal-explicit Agents (RASA) model. MUSE-RASA uses AI-ML-based geospatial big data analytics to define eight scenarios to explore long-term transition pathways towards net-zero emission targets by mid-century. The framework and datasets are key for climate-energy-economy models considering consumer behaviour and bounded rationality in more realistic decision-making processes beyond traditional approaches. This approach defines energy economic agents as heterogeneous and diverse entities that evolve in space and time, making decisions under exogenous constraints. This framework is based on the Theory of Bounded Rationality, the Theory of Real Competition, the theoretical foundations of agent-based modelling and the progress on the combination of GIS-ABM.
Wachsmuth J, Warnke P, Gambhir A, et al., 2023, Co-creating socio-technical scenarios for net-zero emission pathways: Comparison of five national case studies, Renewable and Sustainable Energy Transition, Vol: 4
The extent to which modelled future pathways support effective policymaking for sustainability transitions has been questioned for a long time, with one major issue being the insufficient integration with the perspectives of policymakers and other stakeholders. One proposal to address this issue has been to set up facilitative dialogues with stakeholders to extend model-based pathways to socio-technical scenarios. This paper presents the results of a first series of such co-creation workshops, where stakeholders discussed bottlenecks for model-based decarbonisation pathways and ways to overcome these bottlenecks through tailored policy mixes. The workshops took place in five countries: Brazil, Canada, Greece, Germany, and the UK, each with a specific sector focus. In all five workshops, it became clear that substantial tensions exist between the “ideal” modelled decarbonisation pathways and the real-world situation on the ground. Also, adverse political framework conditions, uncertainty of future policies and resistance of powerful actors were emphasised as overarching bottlenecks in most workshops. At the same time, in several instances stakeholders pointed out important aspects of transformative trajectories that are not covered by the models. Some challenges and solutions stand out in all countries in spite of the strong diversity of contexts: allocation of capital towards massive investments into low-carbon solutions; infrastructure development for generation and transport of hydrogen, capture and use of CO2 as well as electricity grid and storage adapted to renewable energy solutions; stakeholder and citizen dialogues, where agreement is reached on cornerstones of long-term decarbonisation trajectories; and demand-side measures complementing investments into low-carbon processes.
Giarola S, Kell A, Sechi S, et al., 2023, Sustainability Education: Capacity Building Using the MUSE Model, ENERGIES, Vol: 16
van de Ven D-J, Mittal S, Gambhir A, et al., 2023, A multimodel analysis of post-Glasgow climate targets and feasibility challenges, NATURE CLIMATE CHANGE, Vol: 13, Pages: 570-+, ISSN: 1758-678X
- Author Web Link
- Cite
- Citations: 3
Moya D, Arroba C, Castro C, et al., 2023, A Methodology to Estimate High-Resolution Gridded Datasets on Energy Consumption Drivers in Ecuador's Residential Sector during the 2010-2020 Period, ENERGIES, Vol: 16
Philip S, Kell A, Giarola S, et al., 2022, Transport decarbonisation in the UK: an agent-based modelling study
Kell A, Giarola S, Hawkes A, 2022, An investigation of the impact of bounded rationality on the decarbonisation of Kenya's power system, Fourteenth IAMC Annual Meeting 2021
How can we transition to a low-carbon energy supply to limit the effects of climate change?The methodology of quantitative energy models can have an impact on the advice inferred. We compare Kenya’s electricity system transition to 2050 with a 2-model inter-comparison. To explore the uncertainty, we use an agent-based simulation model (MUSE) and an optimisation model (OSeMOSYS).
Sechi S, Giarola S, Leone P, 2022, Taxonomy for Industrial Cluster Decarbonization: An Analysis for the Italian Hard-to-Abate Industry, ENERGIES, Vol: 15
- Author Web Link
- Cite
- Citations: 2
Giarola S, Sachs J, d'Avezac M, et al., 2022, MUSE: An open-source agent-based integrated assessment modelling framework, Energy Strategy Reviews, Vol: 44, Pages: 1-21, ISSN: 2211-467X
Integrated assessment models (IAMs) are a cornerstone of an effective approach toclimate change mitigation. Despite the variety of methodologies for characterisingthe energy system, land use change, economics, and climate response, the modellingcommunity has an open and urgent request for tools capable of more realistic interpretation of the energy transition, capturing human behaviour, and embodying theprinciples of transparency, reproducibility, and flexibility of use.This paper presents an open-source modelling framework designed to fill thatgap. Named MUSE (ModUlar energy systems Simulation Environment), this newagent-based model supports flexible characterisation of agent decision-making, including individual goals, bounded-rationality, imperfect foresight, and limited knowledge during the decision process. MUSE integrates this agent-based approach in apartial-equilibrium framework and enables a technology-rich description of the energy systems with an unprecedented degree of flexibility for including technological,temporal, and geographical granularity. The structure of MUSE creates the abilityto produce climate change mitigation assessments that are more grounded, and moretangible model outputs for conceiving effective approaches to mitigation. MUSE isavailable open source under a GNU General Public License v3.0 on GitHub at thislink https://github.com/SGIModel/MUSE_OS.
van de Ven D-J, Nikas A, Koasidis K, et al., 2022, COVID-19 recovery packages can benefit climate targets and clean energy jobs, but scale of impacts and optimal investment portfolios differ among major economies, One Earth, Vol: 5, Pages: 1042-1054, ISSN: 2590-3322
To meet the Paris temperature targets and recover from the effects of the pandemic, many countries have launched economic recovery plans, including specific elements to promote clean energy technologies and green jobs. However, how to successfully manage investment portfolios of green recovery packages to optimize both climate mitigation and employment benefits remains unclear. Here, we use three energy-economic models, combined with a portfolio analysis approach, to find optimal low-carbon technology subsidy combinations in six major emitting regions: Canada, China, the European Union (EU), India, Japan, and the United States (US). We find that, although numerical estimates differ given different model structures, results consistently show that a >50% investment in solar photovoltaics is more likely to enable CO2 emissions reduction and green jobs, particularly in the EU and China. Our study illustrates the importance of strategically managing investment portfolios in recovery packages to enable optimal outcomes and foster a post-pandemic green economy.
Moya D, Copara D, Borja A, et al., 2022, Geospatial and temporal estimation of climatic, end-use demands, and socioeconomic drivers of energy consumption in the residential sector in Ecuador, Energy Conversion and Management, Vol: 261, Pages: 115629-115629, ISSN: 0196-8904
It is widely acknowledged that the drivers for energy consumption in the residential sector are ambient temperature, energy demand, population density, and socio-economic conditions. However, there are no studies in the literature assessing the temporal and spatial distribution of these drivers for a region or country. The decision-making process of the energy transition will be enhanced by using geospatial-resolved and temporal-explicit energy consumption drivers. This study estimates the climatic, end-use demands, and socio-economic drivers of energy consumption in the residential sector of Ecuador at a high spatio-temporal resolution between 2010 and 2020. This research uses publicly available datasets to calculate seven energy consumption drivers in the residential sector of Ecuador: (1) calibrated gridded population density at 1 km2 resolution; (2) validated gridded space heating demand at 1 km2 resolution; (3) validated gridded space cooling demand at 1 km2 resolution; (4) validated gridded water heating demand at 1 km2 resolution; (5) calibrated gridded gross domestic product at 1 km2 resolution; (6) calibrated gridded gross domestic product per capita at 1 km2 resolution; and (7) calibrated regional human development index, at city level. Disaggregation of the drivers at a high spatial resolution for the entire country in a range of 10 years was considered. The final high-1 km2 resolution results can be used for the evaluation of different energy policies in terms of long-term planning and in techno-economic modelling of energy systems and decarbonisation pathways.
Panoutsou C, Giarola S, Ibrahim D, et al., 2022, Opportunities for low indirect land use biomass for biofuels in Europe, Applied Sciences-Basel, Vol: 12, ISSN: 2076-3417
Sustainable biofuels are an important tool for the decarbonisation of transport. This is especially true in aviation, maritime, and heavy-duty sectors with limited short-term alternatives. Their use by conventional transport fleets requires few changes to the existing infrastructure and engines, and thus their integration can be smooth and relatively rapid. Provision of feedstock should comply with sustainability principles for (i) producing additional biomass without distorting food and feed markets and (ii) addressing challenges for ecosystem services, including biodiversity, and soil quality. This paper performs a meta-analysis of current research for low indirect land use change (ILUC) risk biomass crops for sustainable biofuels that benefited either from improved agricultural practices or from cultivation in unused, abandoned, or severely degraded land. Two categories of biomass crops are considered here: oil and lignocellulosic. The findings confirm that there are significant opportunities to cultivate these crops in European agro-ecological zones with sustainable agronomic practices both in farming land and in land with natural constraints (unused, abandoned, and degraded land). These could produce additional low environmental impact feedstocks for biofuels and deliver economic benefits to farmers
Sesini M, Giarola S, Hawkes AD, 2022, Solidarity measures: Assessment of strategic gas storage on EU regional risk groups natural gas supply resilience, Applied Energy, Vol: 308, Pages: 1-15, ISSN: 0306-2619
This paper focuses on strategic storage as a solidarity measure in response to short-term “high-impact, low-probability” (HILP) disruptions in the European Union (EU) gas supply from major suppliers (i.e., Ukraine, Russia, Norway, and North Africa), assuming its implementation in selected Member States. A two-stage stochastic cost minimization gas transport model is used to evaluate the impact of HILP events on the level of demand curtailment, survival time, and the natural gas supply mix of EU regional risk group. Results show that geographic proximity alone, without solidarity measures, is inadequate in providing system resilience. In contrast, solidarity measures lead to a longer survival time for regional risk groups (14 days) and to a reduction in system (15%) and LNG (70%) costs relative to a base scenario with no strategic storage. The analysis stresses the value of the coordinated use of strategic storage in balancing the natural gas network during emergencies, and provides further evidence supporting the EU legislative path towards an Energy Union.
Moya D, Giarola S, Hawkes A, 2022, Geospatial Big Data analytics to model the long-term sustainable transition of residential heating worldwide, 2021 IEEE International Conference on Big Data (Big Data), Publisher: IEEE, Pages: 4035-4046
Geospatial big data analytics has received much attention in recent years for the assessment of energy data. Globally, spatial datasets relevant to the energy field are growing rapidly every year. This research has analysed large gridded datasets of outdoor temperature, end-use energy demand, end-use energy density, population and Gros Domestic Product to end with usable inputs for energy models. These measures have been recognised as a means of informing infrastructure investment decisions with a view to reaching sustainable transition of the residential sector. However, existing assessments are currently limited by a lack of data clarifying the spatio-temporal variations within end-use energy demand. This paper presents a novel Geographical Information Systems (GIS)-based methodology that uses existing GIS data to spatially and temporally assess the global energy demands in the residential sector with an emphasis on space heating. Here, we have implemented an Unsupervised Machine Learning (UML)-based approach to assess large raster datasets of 165 countries, covering 99.6% of worldwide energy users. The UML approach defines lower and upper limits (thresholds) for each raster by applying GIS-based clustering techniques. This is done by binning global high-resolution maps into re-classified raster data according to the same characteristics defined by the thresholds to estimate intranational zones with a range of attributes. The spatial attributes arise from the spatial intersection of re-classified layers. In the new zones, the energy demand is estimated, so-called energy demand zones (EDZs), capturing complexity and heterogeneity of the residential sector. EDZs are then used in energy systems modelling to assess a sustainable scenario for the long-term transition of space heating technology and it is compared with a reference scenario. This long-term heating transition is spatially resolved in zones with a range of spatial characteristics to enhance the assessment
Sognnaes I, Gambhir A, van de Ven D-J, et al., 2021, A multi-model analysis of long-term emissions and warming implications of current mitigation efforts, Nature Climate Change, Vol: 11, Pages: 1055-1062, ISSN: 1758-678X
Most of the integrated assessment modelling literature focuses on cost-effective pathways towards given temperature goals. Conversely, using seven diverse integrated assessment models, we project global energy CO2 emissions trajectories on the basis of near-term mitigation efforts and two assumptions on how these efforts continue post-2030. Despite finding a wide range of emissions by 2050, nearly all the scenarios have median warming of less than 3 °C in 2100. However, the most optimistic scenario is still insufficient to limit global warming to 2 °C. We furthermore highlight key modelling choices inherent to projecting where emissions are headed. First, emissions are more sensitive to the choice of integrated assessment model than to the assumed mitigation effort, highlighting the importance of heterogeneous model intercomparisons. Differences across models reflect diversity in baseline assumptions and impacts of near-term mitigation efforts. Second, the common practice of using economy-wide carbon prices to represent policy exaggerates carbon capture and storage use compared with explicitly modelling policies.
Sesini M, Giarola S, Hawkes AD, 2021, Strategic natural gas storage coordination among EU member states in response to disruption in the trans Austria gas pipeline: A stochastic approach to solidarity, Energy, Vol: 235, Pages: 1-13, ISSN: 0360-5442
The 2019 EU energy security agenda has led to the concept of solidarity: a coordinated response of Member States to “high-impact, low-probability” events jeopardizing the EU energy supply. At the core of this paper is a modeling analysis of storage as a non-market-based solidarity measure (the so-called strategic storage) considering whether it could be economically desirable to secure gas supply in case of disruption to the EU network. A two-stage stochastic cost minimization gas transport model was developed to study the short-term resilience of the network to supply shocks, such as a natural gas pipeline rupture, and the cost effective system response, in terms of transmission of gas flows, capacity use, and storage utilization in an interconnected gas system, taken the EU as a reference. Relative to a base scenario with no strategic storage, results show that gas import loss up to 80% on multiple different pipelines could lead to a +76% in total costs when no coordinated strategic storage is in place, compared with a −30% in total cost and a −60% in liquefied natural gas cost, when in use, emphasizing the cost-effectiveness achieved with strategic storage in securing energy to the system in emergency.
Giarola S, Mittal S, Vielle M, et al., 2021, Challenges in the harmonisation of global integrated assessment models: a comprehensive methodology to reduce model response heterogeneity, Science of the Total Environment, Vol: 783, ISSN: 0048-9697
Harmonisation sets the ground to a solid inter-comparison of integrated assessment models. A clear and transparent harmonisation process promotes a consistent interpretation of the modelling outcomes divergences and, reducing the model variance, is instrumental to the use of integrated assessment models to support policy decision-making. Despite its crucial role for climate economic policies, the definition of a comprehensive harmonisation methodology for integrated assessment modelling remains an open challenge for the scientific community.This paper proposes a framework for a harmonisation methodology with the definition of indispensable steps and recommendations to overcome stumbling blocks in order to reduce the variance of the outcomes which depends on controllable modelling assumptions. The harmonisation approach of the PARIS REINFORCE project is presented here to layout such a framework. A decomposition analysis of the harmonisation process is shown through 6 integrated assessment models (GCAM, ICES-XPS, MUSE, E3ME, GEMINI-E3, and TIAM). Results prove the potentials of the proposed framework to reduce the model variance and present a powerful diagnostic tool to feedback on the quality of the harmonisation itself.
Nikas A, Elia A, Boitier B, et al., 2021, Where is the EU headed given its current climate policy? A stakeholder-driven model inter-comparison., Science of the Total Environment, Vol: 793, Pages: 148549-148549, ISSN: 0048-9697
Recent calls to do climate policy research with, rather than for, stakeholders have been answered in non-modelling science. Notwithstanding progress in modelling literature, however, very little of the scenario space traces back to what stakeholders are ultimately concerned about. With a suite of eleven integrated assessment, energy system and sectoral models, we carry out a model inter-comparison for the EU, the scenario logic and research questions of which have been formulated based on stakeholders' concerns. The output of this process is a scenario framework exploring where the region is headed rather than how to achieve its goals, extrapolating its current policy efforts into the future. We find that Europe is currently on track to overperforming its pre-2020 40% target yet far from its newest ambition of 55% emissions cuts by 2030, as well as looking at a 1.0-2.35 GtCO2 emissions range in 2050. Aside from the importance of transport electrification, deployment levels of carbon capture and storage are found intertwined with deeper emissions cuts and with hydrogen diffusion, with most hydrogen produced post-2040 being blue. Finally, the multi-model exercise has highlighted benefits from deeper decarbonisation in terms of energy security and jobs, and moderate to high renewables-dominated investment needs.
Doukas H, Spiliotis E, Jafari MA, et al., 2021, Low-cost emissions cuts in container shipping: thinking inside the box, Transportation Research Part D: Transport and Environment, Vol: 94, ISSN: 1361-9209
Container shipping has become an emission-intensive industry; existing regulations, however, continue to display limitations. Technical emissions reduction measures require large, long-term investments, while operational measures may negatively impact transportation costs and supply-chain practices. For container shipping to become more sustainable, innovative, low-cost technological solutions are required. This study discusses such a technological game-changer which utilizes a lighter container type that, contrary to conventional ones, does not require wood in its floor. In this regard, emissions reductions are achieved both due to lower fuel consumption and tree savings. We estimate the global impact of this technology until 2050 using an integrated assessment model and considering different projections about future characteristics of the container fleet. Our results indicate that the adoption of the examined technology can reduce emissions by 4.7–18.8% depending on the main fuel used in container shipping lines, saving also a total of about 44 million trees.
Giarola S, Molar-Cruz A, Vaillancourt K, et al., 2021, The role of energy storage in the uptake of renewable energy: a model comparison approach, Energy Policy, Vol: 151, ISSN: 0301-4215
The power sector needs to ensure a rapid transition towards a low-carbon energy system to avoid the dangerous consequences of greenhouse gas emissions. Storage technologies are a promising option to provide the power system with the flexibility required when intermittent renewables are present in the electricity generation mix. This paper focuses on the role of electricity storage in energy systems with high shares of renewable sources. The study encompasses a model comparison approach where four models (GENeSY S-MOD, MUSE, NAT EM, and urbs−MX) are used to analyse the storage uptake in North America. The analysis addresses the conditions affecting storage uptake in each country and its dependence on resource availability, technology costs, and public policies. Results show that storage may promote emissions reduction at lower costs when renewable mandates are in place whereas in presence of carbon taxes, renewables may compete with other low-carbon options. The study also highlights the main modelling approach shortcomings in the modelling of electricity storage in integrated assessment models.
Sechi S, Giarola S, Lanzini A, et al., 2021, A bottom-up appraisal of the technically installable capacity ofbiogas-based solid oxide fuel cells for self power generation in wastewatertreatment plants, Journal of Environmental Management, Vol: 279, Pages: 1-15, ISSN: 0301-4797
This paper proposes a bottom-up method to estimate the technical capacity of solid oxide fuel cells to be installed in wastewater treatment plants and valorise the biogas obtained from the sludge through an efficient conversion into electricity and heat. The methodology uses stochastic optimisation on 200 biogas profile scenarios generated from industrial data and envisages a Pareto approach for an a posteriori assessment of the optimal number of generation unit for the most representative plant configuration sizes. The method ensures that the dominant role of biogas fluctuation is included in the market potential and guarantees that the utilization factor of the modules remains higher than 70% to justify the investment costs. Results show that the market potential for solid oxide fuel cells across Europe would lead up to 1,300 MW of installed electric capacity in the niche market of wastewater treatment and could initiate a capital and fixed costs reduction which could make the technology comparable with alternative combined heat and power solutions.
Brown M, Siddiqui S, Avraam C, et al., 2021, North American energy system responses to natural gas price shocks, Energy Policy, Vol: 149, Pages: 1-11, ISSN: 0301-4215
As of 2020, North American natural gas extraction and use in the electricity sector have both reached all-time highs. The combination of North America's increased reliance on natural gas with a potential disruption to the natural gas market has several energy security implications. Additionally, policymakers interested in economic resiliency will find this study's results useful for informing the implications of the energy sectors' long-term planning and investment decisions. This paper evaluates how both the electricity and natural gas sectors could respond to hypothetical gas price shocks under different system configurations. We impose unforeseen natural gas price shocks under reference and alternative configurations resulting from a renewable generation mandate or variations to renewable capacity costs. Results from several different models are presented for the electricity and natural gas sectors separately for Canada, Mexico, and the United States. Generally, the US becomes more (less) reliant on electricity imports from Canada given a high (low) gas price shock but increases (decreases) exports to Mexico. The renewable mandate is demonstrated to buffer electricity price increases under high price shocks but price reductions under the low price shocks are dampened given less flexibility to take advantage of the low-priced natural gas. The United States is demonstrated to reduce natural gas production and net exports with high natural gas price shocks given a reduction in demand.
García Kerdan I, Giarola S, Skinner E, et al., 2020, Modelling future agricultural mechanisation of major crops in China: an assessment of energy demand, land use and emissions, Energies, Vol: 13, Pages: 6636-6636, ISSN: 1996-1073
Agricultural direct energy use is responsible for about 1–2% of global emissions and is the major emitting sector for methane (2.9 GtCO2eq y−1) and nitrous oxide (2.3 GtCO2eq y−1). In the last century, farm mechanisation has brought higher productivity levels and lower land demands at the expense of an increase in fossil energy and agrochemicals use. The expected increase in certain food and bioenergy crops and the uncertain mitigation options available for non-CO2 emissions make of vital importance the assessment of the use of energy and the related emissions attributable to this sector. The aim of this paper is to present a simulation framework able to forecast energy demand, technological diffusion, required investment and land use change of specific agricultural crops. MUSE-Ag & LU, a novel energy systems-oriented agricultural and land use model, has been used for this purpose. As case study, four main crops (maize, soybean, wheat and rice) have been modelled in mainland China. Besides conventional direct energy use, the model considers inputs such as fertiliser and labour demand. Outputs suggest that the modernisation of agricultural processes in China could have the capacity to reduce by 2050 on-farm emissions intensity from 0.024 to 0.016 GtCO2eq PJcrop−1 (−35.6%), requiring a necessary total investment of approximately 319.4 billion 2017$US.
Sesini M, Giarola S, Hawkes AD, 2020, The impact of liquefied natural gas and storage on the EU natural gas infrastructure resilience, Energy, Vol: 209, Pages: 1-13, ISSN: 0360-5442
As the energy system progresses towards full decarbonization, natural gas could play an important role in it with its relatively low carbon characteristics and its abundant supply. At the core of the paper is a modelling analysis of the European Union (EU) natural gas network resilience in case of short-term supply disruption or unexpected increase in demand. The adopted linear programming model solves for the most cost effective transmission of gas flows, capacity and storage utilization in an interconnected EU gas system. Results presented in the paper show a significant increase in liquefied natural gas (LNG) costs (+40%) when commodity price increases (+40%) and LNG prices decreases (−20%), and an equally significant decline in transport and LNG costs (−30%,-50%) when storage volumes varies (−35%,+35%).The analysis highlights a complementary role between LNG and storage in ensuring a cost-effective response to a natural gas supply shock. It also indicates that LNG alone is inadequate in providing system resilience in case of an emergency in supply, stressing the importance of storage in the gas market and its intrinsic value in the system. The study emphasizes the need to further investigate the reliability and value of gas storage to reinforce energy security in Europe.
Budinis S, Sachs J, Giarola S, et al., 2020, An agent-based modelling approach to simulate the investment decision of industrial enterprises, Journal of Cleaner Production, Vol: 267, ISSN: 0959-6526
China is the leading ammonia producer and relies on a coal-based technology which makes the already energy intensive Haber-Bosch process, one of the most emission intensive in the world. This work is the first to propose an agent-based modelling framework to model the Chinese ammonia industry as it characterises the specific goals and barriers towards fuel switching and carbon capture and storage adoption for small, medium, and large enterprises either private or state-owned. The results show that facilitated access to capital makes investments in sustainable technologies more attractive for all firms, especially for small and medium enterprises. Without policy instruments such as carbon price, the decrease in emissions in the long-term is due to investments in natural gas-based technologies, as they typically have lower capital and operating costs, and also lower electricity consumption than coal-based production. Conversely, with policy instruments in place, a strong decrease in emissions occurs between 2060 and 2080 due to investors choosing natural gas and biomethane-based technologies, with carbon capture and storage. In the long term, natural gas and biomethane could compete, with the outcome depending on infrastructure, supply chain availability and land use constraints.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.