62 results found
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.
Moya D, Budinis S, Giarola S, et al., 2020, Agent-based scenarios comparison for assessing fuel-switching investment in long-term energy transitions of the India’s industry sector, Applied Energy, Vol: 274, Pages: 1-26, ISSN: 0306-2619
This paper presents the formulation and application of a novel agent-based integrated assessment approach to model the attributes, objectives and decision-making process of investors in a long-term energy transition in India’s iron and steel sector. It takes empirical data from an on-site survey of 108 operating plants in Maharashtra to formulate objectives and decision-making metrics for the agent-based model and simulates possible future portfolio mixes. The studied decision drivers were capital costs, operating costs (including fuel consumption), a combination of capital and operating costs, and net present value. Where investors used a weighted combination of capital cost and operating costs, a natural gas uptake of ~12PJ was obtained and the highest cumulative emissions reduction was obtained, 2 Mt CO2 in the period from 2020 to 2050. Conversely if net present value alone is used, cumulative emissions reduction in the same period was lower, 1.6 Mt CO2, and the cumulative uptake of natural gas was equal to 15PJ. Results show how the differing upfront investment cost of the technology options could cause prevalence of high-carbon fuels, particularly heavy fuel oil, in the final mix. Results also represent the unique heterogeneity of fuel-switching industrial investors with distinct investment goals and limited foresight on costs. The perception of high capital expenditures for decarbonisation represents a significant barrier to the energy transition in industry and should be addressed via effective policy making (e.g. carbon policy/price).
Huntington HG, Bhargava A, Daniels D, et al., 2020, Key findings from the core North American scenarios in the EMF34 intermodel comparison, Energy Policy, Vol: 144, Pages: 1-23, ISSN: 0301-4215
Within Canada, Mexico or the United States, policy-making organizations are evaluating energy markets and energy trade within their own borders often by ignoring how these countries’ energy systems are integrated with each other. These analytical gaps provided the main motivation for the Energy Modeling Forum (EMF) 34 study on North American energy integration and trade. This paper compares North American results from 17 models and discusses their policy motivation. Oil and natural gas production in the three major countries are modestly sensitive to crude oil and natural gas price changes, although these elasticities are below unity. Carbon taxes displace coal and some natural gas with renewables within all three power markets. Lower natural gas prices replace coal and some renewables with natural gas within electric generation. Higher intermittent renewable penetration in the power sector displaces coal and some natural gas. A key conclusion is that much remains to be done in integrating future analyses and in sharing and improving the quality and consistency of the underlying data.
Speirs J, Jalil-Vega F, Cooper J, et al., 2020, The flexibility of gas - what is it worth?, White Paper 5: The Flexibility of gas – what is it worth?, London, UK, Publisher: Sustainable Gas Institute, Imperial College London, 5
What is the evidence on the flexibility value that gas vectors and gas networks can provide to support the future energy system?There is an increasing debate regarding the use of gas networks in providing support for the decarbonisation of energy systems.The perceived value of gas “vectors” – encompassing natural gas, hydrogen and biomethane – is that they may provide flexibility, helping to support daily and seasonal variation in energy demand, and increasingly intermittent electricity supply as renewable electricity generation increases as a proportion of the electricity mix.Arguments in support of gas suggest that electricity systems will find it difficult to maintain flexibility on their own, whilst also reducing greenhouse gas emissions and increasing production to meet new demand for heating and transport. Gas, on the other hand, is expected to provide flexibility at relatively low cost, and may be produced and used with relatively low greenhouse gas emissions.White Paper 5 investigates the evidence surrounding the flexibility provided by gas and gas networks and the cost of, and value provided by gas to the future energy system.
Garcia Kerdan I, Giarola S, Hawkes A, 2020, Implications of future natural gas demand on sugarcane production, land use Change and related emissions in Brazil, Journal of Sustainable Development of Energy, Water and Environment Systems, Vol: 8, Pages: 304-327, ISSN: 1848-9257
Due to its low share of energy-related emissions, energy systems models have overlooked the implications of technological transition in the agricultural sector and its interaction in the wider energy system. This paper explores the role of agriculture intensification by using a novel agricultural-based energy systems model. The aim is to explore the future role of Brazil’s agriculture and its dynamics with other energy sectors under two carbon constraint scenarios. The main focus has been to study resource competition between sugarcane and natural gas at a country level. Results show that in order to meet the future food and bioenergy demand, the agricultural sector would start intensifying by 2030, improving productivity at the expense of higher energy demand, however, land-related emissions would be minimised due to freed-up pasture land and reduction in deforestation rates. Additionally, the development of balanced bioenergy and natural gas markets may help limit the sugarcane expansion rates, preserving up to 12.6 million hectares of forest land, with significant emissions benefits.
Lyrio de Oliveira L, García Kerdan I, de Oliveira Ribeiro C, et al., 2020, Modelling the technical potential of bioelectricity production under land use constraints: A multi-region Brazil case study, Renewable and Sustainable Energy Reviews, Vol: 123, Pages: 1-15, ISSN: 1364-0321
In Brazil, bioelectricity generation from sugarcane bagasse and black liquor is regarded as a sustainable electricity supply option. However, questions regarding land use, investment decisions, and demand for paper, ethanol and sugar make its future role uncertain. The aim of this paper is to present a novel modelling framework based on a soft-link between a multi-sectoral Brazilian integrated assessment model (MUSE-Brazil) and an electricity portfolio optimisation model (EPOM). The proposed framework is capable of dynamically simulating sectoral electricity demand, regional bioenergy production under land use constraints and optimal power sector technological shares in each of the electricity subsystems. Considering Brazil under a 2 °C carbon budget, two scenarios based on economic attractiveness of producing second-generation ethanol have been investigated. Under the scenario where second-generation ethanol is not produced, outputs indicate that by 2050, Brazil would increase sugarcane and wood production by 68% and 49% respectively without causing direct or indirect deforestation. Agriculture intensification is evidenced as an alternative for reducing land use disruptions. Bioelectricity share is projected to remain around 9–10%. However, if second generation ethanol becomes cost-effective, thus limiting bagasse availability, the share of bioelectricity production would decrease to approximately 7.7%, with natural gas-fired plants playing a stronger role in the future power system expansion, causing an increase on electricity sector emissions.
Luh S, Budinis S, Giarola S, et al., 2020, Long-term development of the industrial sector – case study about electrification, fuel switching, and CCS in the USA, Computers & Chemical Engineering, Vol: 133, Pages: 1-14, ISSN: 0098-1354
In the urgent quest for solutions to mitigate climate change, the industry is one of the most challenging sectors to decarbonize. In this work, a novel simulation framework is presented to model the investment decisions in industry, the Industrial Sector Module (ISM) of the ModUlar energy system Simulation Environment (MUSE). This work uses the ISM to quantify effects of three combined measures for CO2 emission reduction in industry, i.e. fuel switching, electrification, and adoption of Carbon Capture and Storage (CCS) and to simulate plausible scenarios (base scenario and climate ambitious scenario) for curbing emissions in the iron and steel sector in the USA between 2010 and 2050. Results show that when the climate ambitious scenario is applied, the cumulative emissions into the atmosphere (2,158 Mt CO2) are reduced by 40% in comparison to the base scenario (3,608 Mt CO2). This decarbonization gap between both scenarios intensifies over time; in the year 2050, the CO2 intensity in the climate ambitious scenario is 81% lower in comparison to the base scenario. The study shows that major contributions to industry decarbonization can come from the further uptake of secondary steel production. Results show also that a carbon tax drives the decarbonization process but is not sufficient on its own. In addition, the uptake of innovative low-carbon breakthrough technologies is necessary. It is concluded that industrial electrification is counterproductive for climate change mitigation, if electricity is not provided by low-carbon sources. Overall, fuel switching, industrial electrification, and CCS adoption as single measures have a limited decarbonization impact, compared to an integrated approach that implements all the measures together providing a much more attractive solution for CO2 mitigation.
Panteli A, Giarola S, Shah N, 2020, Strategic Biorefining Supply Chain Design for Novel Products in Immature Markets, Editors: Pierucci, Manenti, Bozzano, Manca, Publisher: ELSEVIER SCIENCE BV, Pages: 1579-1584
García Kerdan I, Jalil-Vega F, Toole J, et al., 2019, Modelling cost-effective pathways for natural gas infrastructure: A southern Brazil case study, Applied Energy, Vol: 255, ISSN: 0306-2619
Currently, natural gas in Brazil represents around 12.9% of the primary energy supply, with consistent annual growth during the last decade. However, Brazil is entering a time of uncertainty regarding future gas supply, mainly as import from Bolivia is being renegotiated. As such, diversification of gas supply sources and routes need to be considered. Energy systems and infrastructure models are essential tools in assisting energy planning decisions and policy programmes at regional and international levels. In this study, a novel combination of a simulation-based integrated assessment model (MUSE-South_Brazil) and the recently-developed Gas INfrastructure Optimisation model (GINO) is presented. The Brazilian region represented by the five southern states served by the Bolivian gas pipeline (GASBOL) has been investigated. Modelled projections suggest that regional gas demand would increase from 38.8 mcm/day in 2015 to 104.3 mcm/day by 2050, mainly driven by the increasing demand in the industry and power sectors. Therefore existing regional gas infrastructure would be insufficient to cover future demands. Three different renegotiation scenarios between Brazil and Bolivia were modelled, obtaining distinct cost-optimal infrastructure expansion pathways. Depending on the scenario, the model expects gas demand to be covered by other supply options, such as an increase in pre-salt production, LNG imports and imports from a new Argentinian pipeline.
García Kerdan I, Giarola S, Hawkes A, 2019, A novel energy systems model to explore the role of land use and reforestation in achieving carbon mitigation targets: A Brazil case study, Journal of Cleaner Production, Vol: 232, Pages: 796-821, ISSN: 0959-6526
Due to its low global share of direct energy consumption and greenhouse gas emissions (1–2%), the implications of technological transitions in the agricultural and forestry sector on the energy system have been overlooked. This paper introduces the Agriculture and Land Use Sector module part of the ModUlar energy System Environment (MUSE), a novel energy system simulation model. The study presents a generalisable method that enables energy modellers to characterise agricultural technologies within an energy system modelling framework. Different mechanisation processes were characterised to simulate intensification/extensification transitions in the sector and its wider implications in the energy and land use system aiming at providing reliable non-energy outputs similarly to those found in dedicated land use models. Additionally, a forest growth model has been integrated to explore the role of reforestation alongside decarbonisation measures in the energy system in achieving carbon mitigation pathways. To illustrate the model's capabilities, Brazil is used as case study. Outputs suggest that by 2030 under a 2 °C mitigation scenario, most of Brazil agricultural production would move from ‘transitional’ to ‘modern’ practices, improving productivity and reducing deforestation rates, at the expense of higher energy and fertiliser demand. By mid-century Brazil has the potential to liberate around 24.4 Mha of agricultural land, where large-scale reforestation could have the capacity to sequester around 5.6 GtCO2, alleviating mitigation efforts in the energy system, especially reducing carbon capture and storage technology investments in the industry and power sector.
Sachs J, Moya D, Giarola S, et al., 2019, Clustered spatially and temporally resolved global heat and cooling energy demand in the residential sector, Applied Energy, Vol: 250, Pages: 48-62, ISSN: 0306-2619
Climatic conditions, population density, geography, and settlement structure all have a strong influence on the heating and cooling demand of a country, and thus on resulting energy use and greenhouse gas emissions. In particular, the choice of heating or cooling system is influenced by available energy distribution infrastructure, where the cost of such infrastructure is strongly related to the spatial density of the demand. As such, a better estimation of the spatial and temporal distribution of demand is desirable to enhance the accuracy of technology assessment. This paper presents a Geographical Information System methodology combining the hourly NASA MERRA-2 global temperature dataset with spatially resolved population data and national energy balances to determine global high-resolution heat and cooling energy density maps. A set of energy density bands is then produced for each country using K-means clustering. Finally, demand profiles representing diurnal and seasonal variations in each band are derived to capture the temporal variability. The resulting dataset for 165 countries, published alongside this article, is designed to be integrated into a new integrated assessment model called MUSE (ModUlar energy systems Simulation Environment)but can be used in any national heat or cooling technology analysis. These demand profiles are key inputs for energy planning as they describe demand density and its fluctuations via a consistent method for every country where data is available.
Sachs J, Meng Y, Giarola S, et al., 2019, An agent-based model for energy investment decisions in the residential sector, Energy, Vol: 172, Pages: 752-768, ISSN: 0360-5442
Energy-related investment decisions in the buildings sector are heterogeneous in that the outcome for each individual varies according to budget, values, and perception of a technology, even if an apparently identical decision task is faced. In particular, the rate of adoption of new energy-efficient technologies is often hard to model and underlines the need for an advanced approach to capture diversity in decision-making, and enable the inclusion of economic, comfort, environmental and social aspects. This paper presents an enhanced agent-based model that captures several characteristics of consumer behaviour that influence investment decisions. Multiple agents with different objectives, search strategies, and decision methods are implemented. A case study is presented which illustrates the benefits of the approach for the residential sector in the UK. The agent-based method shows diversity in investment decisions, without requiring the constraints on uptake needed in many models. This leads to a range of technologies in the market during a transition phase, continuous investment in low capital cost technologies, and eventually the emergence of a low carbon system based on new mass market technologies. The system that emerges is vastly different from one observed when economically rational investment is assumed and uptake constraints are applied.
Panteli A, Giarola S, Shah N, 2018, Supply chain mixed integer linear program model integrating a biorefining technology superstructure, Industrial & Engineering Chemistry Research, Vol: 57, Pages: 9849-9865, ISSN: 0888-5885
A crucial element of the quest of curbing carbon dioxide emissions is deemed to rely on a biobased economy, which will rely on the development of financially sustainable biorefining systems enabling a full exploitation of lignocellulosic biomass (and its macrocomponents such as cellulose, hemicellulose, and lignin) for the coproduction of biofuels and bioderived platform chemicals. In this work, a general modeling framework conceived to steer decision-making regarding the strategic design and systematic planning of advanced biorefining supply networks is presented. The design task is formulated as a mixed integer linear program which accounts for the maximization of the supply chain profit, considering multiechelon, multiperiod, multifeedstock, and multiproduct aspects as well as spatially explicit features. The applicability of the proposed model, along with the use of a bilevel decomposition approach, are demonstrated with a case study of lignocellulose-based biorefining production systems in the South-West of Hungary. Results show the effectiveness of the tool in the decision-making regarding the systematic design of advanced biorefining SC networks. An economic analysis of different design configurations (i.e., centralized and distributed scenarios) through a holistic evaluation of the entire biobased SC, integrating technology superstructure, shows that both instances generate profitable investment decisions that could be equally trusted by the decision-maker unless regional restrictions are applied.
Crow DJG, Giarola S, Hawkes AD, 2018, A dynamic model of global natural gas supply, Applied Energy, Vol: 218, Pages: 452-469, ISSN: 0306-2619
This paper presents the Dynamic Upstream Gas Model (DYNAAMO); a new, global, bottom-up model of natural gas supply. In contrast to most “static” supply-side models, which bracket resources by average cost, DYNAAMO creates a range of dynamic outputs by simulating investment and operating decisions in the upstream gas industry triggered in response to investors’ expectations of future gas prices. Industrial data from thousands of gas fields is analysed and used to build production and expenditure profiles which drive the economics of supply at field level. Using these profiles, a novel methodology for estimating supply curves is developed which incorporates the size, age and operating environment of gas fields, and treats explicitly the fiscal, abandonment, exploration and emissions costs of production. The model is validated using the US shale gas boom in the 2000s as a historic case study. It is found that the modelled market share of supply by field environment replicates the observed trend during the period 2000–2010, and that the model price response during the same period – due to lower capacity margins and the financing of new projects – is consistent with market behaviour.
Giarola S, Forte O, Lanzini A, et al., 2018, Techno-economic assessment of biogas-fed solid oxide fuel cell combined heat and power system at industrial scale, Applied Energy, Vol: 211, Pages: 689-704, ISSN: 0306-2619
Wastewater treatment plants (WWTP) are currently very energy and greenhouse gas intensive processes. An important opportunity to reduce both of these quantities is via the use of biogas produced within the treatment process to generate energy. This paper studies the optimal energy and economic performance of a wastewater treatment facility fitted with a solid oxide fuel cell (SOFC) based combined heat and power (CHP) plant. An optimisation framework is formulated and then applied to determine cost, energy and emissions performance of the retrofitted system when compared with conventional alternatives.Results show that present-day capital costs of SOFC technology mean that it does not quite compete with the conventional alternatives. But, it could become interesting if implemented in thermally-optimised WWTP systems. This would increase the SOFC manufacturing volumes and drive a reduction of capital and fixed operating costs.
Sechi S, Giarola S, Lanzini A, et al., 2018, An optimization method to estimate the SOFC market in waste water treatment, Editors: Friedl, Klemes, Radl, Varbanov, Wallek, Publisher: ELSEVIER SCIENCE BV, Pages: 415-420
Sachs J, Hidayat S, Giarola S, et al., 2018, The role of CCS and biomass-based processes in the refinery sector for different carbon scenarios, Editors: Friedl, Klemes, Radl, Varbanov, Wallek, Publisher: ELSEVIER SCIENCE BV, Pages: 1365-1370
Garcia Kerdan I, Hawkes AD, Giarola S, 2018, Implications of Future Natural Gas Infrastructure on Bioenergy Production, Land Use Change and Related Emissions: A Brazil Case Study, 1st SDEWES Latin America
Due to its low global share of direct energy consumption (3-5%) and greenhouse gas emissions (1-2%), energy systems models (ESM) have unfairly overlooked the implications of technological transitions in the agricultural sector. In fact, if the demand of agrochemicals and land use changes (LUC) due to expansion of bioenergy crops and increasing food demand are considered, the sector is indirectly responsible for up to 30% of global emissions. This paper introduces the Agriculture and Land Use Sector Simulation Module (Ag&LU-SM) which is integrated in a novel ESM, called MUSE, the ModUlar energy systems Simulation Environment. The Ag&LU-SM simulates the investments in agricultural energy technologies through the concept of mechanisation diffusion to meet the demand of sector’s commodities, such as crops, animal and forestry products, as well as the implications due to LUC when arable or forest land is allocated to bioenergy crops. The aim is to study the sector’s dynamics and resource competition between bioenergy and natural gas at a country level. Brazil, one of the major bioenergy producers and with large amounts of oil and natural gas reserves, is used as a case study to study the implications in terms of land use change in two different scenarios. One scenario explores a ten-fold expansion of bioenergy production by 2050, which means a 6% annual growth rate. The second scenario explores the expansion of natural gas production while halving bioenergy production (3% annual growth rate). Results show that, in order to meet the future food and bioenergy demand, the agricultural sector should move from transitional to modern agricultural practices, improve the productivity at the expense of higher energy consumption, invest in efficient agricultural practices to reduce land-related emissions and have the opportunity to liberate crop and pasture land that could be used for dedicated energy crops. Finally, the development of a gas infrastructure coul
Budinis S, Giarola S, Sachs J, et al., 2017, Modelling the impacts of investors' decision making on decarbonisation pathways in industry, 10th Annual Meeting of the IAMC, Publisher: IAMC
The Paris Climate agreement calls for dramatic changes in the energy system. This will be challenging for demand sectors like industry, which is notoriously energy intensive. Although increased efficiency has proven to be suitable options to reduce energy and environmental impacts, stringent regulations on carbon will require this sector to undergo an unprecedented innovation effort, which will go well beyond cost efficiency measures to include the deployment of novel technologies and, most likely, of carbon capture and storage (CCS).This manuscript focuses on the uptake of novel technologies in the industrial sector and the barriers which might prevent or slow down the pace of innovation. Some of these barriers are technological as they depend on the availability and the technology readiness level of a specific technology. Others are instead related to the attitude that investors show towards innovative and the inherent level of risk. Among the many innovation options in the industrial sector, the focus here is on the uptake of the carbon capture and storage technologies.The industrial sector is modelled including the top-energy intensive industries, such as those manufacturing pulp and paper, iron and steel, chemicals and petrochemicals, the non-ferrous metals as well as non-metallic minerals. The simulations are carried out using a novel energy systems model, MUSE, the Modular energy systems Simulation Environment.
Panteli A, Giarola S, Shah N, 2017, Biobased Supply Chain Optimisation Model under Uncertainties, 27th European Symposium on Computer-Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 961-966, ISSN: 1570-7946
Sechi S, Giarola S, Lanzini A, et al., 2017, Techno-economic assessment of the effects of biogas rate fluctuations on industrial applications of solid-oxide fuel cells, ESCAPE-27, Publisher: Elsevier, ISSN: 1570-7946
Wastewater treatment is an energy and greenhouse gas intensive process. An important opportunity to reduce both of these quantities is via the use of biogas in co-generation systems. Solid-oxide fuel cells (SOFCs) are the generator types studied in this work.The feasibility of the retrofitting of a wastewater treatment facility fitted with a SOFC combined heat and power energy provision system is assessed including effects of uncertainties in biogas availability on cost and energy performance. A two-stage stochastic optimization framework is proposed to provide feedback on the energy co-generation system design.Results quantify standard deviations in the biogas rate beyond which the SOFC capacity factor might drop below 80 % and change the optimal size of the modules to install.Keywords: solid-oxide fuel cells, stochastic optimization, wastewater treatment, biogas.
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