222 results found
Muuls M, Hawkes A, Hamilton J, 2023, Big oil and the energy transition: evidence from M&A, Energy Policy, Vol: 183, ISSN: 0301-4215
International Oil Companies (IOCs) represent a significant source of capital and expertise that could be deployed to contribute to the investment required to achieve the energy transition to a low carbon future. This paper sheds light on the current motivations for mergers and acquisitions (M&A) by the various energy sectors and focusses on policies and commercial contexts that would favour IOCs incorporating renewables into their core business. An empirical analysis of a twenty-year history of M&A in the energy sector, covering over 10,000 transactions, is complemented by an economic model that differentiates between investment for innovation and investment for scale and transaction benefit. The analysis confirms that in the case of renewables, IOCs are currently at the exploratory stage of business development and appear to be valuing innovation based on renewables on subset of their business. The analysis concludes that IOCs favour core investment in functioning competitive energy markets rather than in rate-of-return regulated assets, and that for IOCs in particular policies and market rules directed towards that end would favour both near- and long-term investment by them into low carbon energy.
Gambhir A, Mittal S, Lamboll R, et al., 2023, Adjusting 1.5 degree C climate change mitigation pathways in light of adverse new information, Nature Communications, Vol: 14, Pages: 1-13, ISSN: 2041-1723
Understanding how 1.5oC pathways could adjust in light of new adverse information, such as a reduced 1.5 o C carbon budget, or slower-than-expected low-carbon technology deployment, is critical for planning resilient pathways. We use an integrated assessment model to explore potential pathway adjustments starting in 2025 and 2030, following the arrival of new information. The 1.5 oC target remains achievable in the model, in light of some adverse information, provided a broad portfolio of technologies and measures is still available. If multiple pieces of adverse information arrive simultaneously, average annual emissions reductions near 3 GtCO 2/yr for the first five years followingthe pathway adjustment, compared to 2 GtCO 2 /yr in 2020 when the Covid-19 pandemic began. Moreover, in these scenarios of multiple simultaneous adverse information, by 2050 mitigation costs are 4-5 times as high as a no adverse information scenario, highlighting the criticality of developing a wide range of mitigation options, including energy demand reduction options.
Giarola S, Kell A, Sechi S, et al., 2023, Sustainability Education: Capacity Building Using the MUSE Model, Energies, Vol: 16
Education for sustainable development has among its pillars, capacity building, which equips future generations with the set of skills needed to face the challenge of the transformation of society for sustainable development. This paper presents a training course for a novel model of long-term energy planning (the ModUlar energy system Simulation Environment, MUSE), as an example of capacity building activities for sustainable development. The activities were part of the Joint Summer School on Modelling Tools for Sustainable development, held in Trieste (Italy) in 2022. This summer school was one of the first successful implementations of education and training courses in a super-hybrid mode in the post-COVID era. Describing the training activities for MUSE open-source, this paper addresses one of the challenges that education for sustainable development is expected to increasingly face in the future: the training of future professionals in the use of novel toolkits and the implementation of truly trans-disciplinary approaches.This paper discusses the pre-school online training course for MUSE, the summer school contents, and some student modeling outcomes. While doing so, it shows the importance of leveraging the abstract contents of a course with practical exercises when learning a new tool. Reflecting upon the students’ experience, this paper draws conclusions that can be used to improve future editions of the same course and be extended to the design of training courses for other tools.
van de Ven DJ, Mittal S, Gambhir A, et al., 2023, A multimodel analysis of post-Glasgow climate targets and feasibility challenges, Nature Climate Change, Vol: 13, Pages: 570-578, ISSN: 1758-678X
The COP26 Glasgow process resulted in many countries strengthening their 2030 emissions reduction targets and announcing net-zero pledges for 2050–2070 but it is not clear how this would impact future warming. Here, we use four diverse integrated assessment models (IAMs) to assess CO2 emission trajectories in the near- and long-term on the basis of national policies and pledges, combined with a non-CO2 infilling model and a simple climate model to assess the temperature implications. We also consider the feasibility of national long-term pledges towards net-zero. While near-term pledges alone lead to warming above 2 °C, the addition of long-term pledges leads to emissions trajectories compatible with a future well below 2 °C, across all four IAMs. However, while IAM heterogeneity translates to diverse decarbonization pathways towards long-term targets, all modelled pathways indicate several feasibility concerns, relating to the cost of mitigation and the rates and scales of deployed technologies and measures.
Batti MME, Machado PG, Hawkes A, et al., 2023, Land use policies and their effects on Brazilian farming production, JOURNAL FOR NATURE CONSERVATION, Vol: 73, ISSN: 1617-1381
Dubey L, Speirs J, Balcombe P, et al., 2023, Future use of natural gas under tightening climate targets, Futures, Vol: 150, Pages: 1-13, ISSN: 0016-3287
Natural gas has developed as a prominent energy source across the world over the last century. However, its use in the future will be constrained by evolving climate goals, and an optimal role for natural gas in a future 1.5 °C world is debated. We conduct a systematic review of the literature, and analysis of the Intergovernmental Panel on Climate Change SR1.5 scenarios to understand the role of natural gas in a 1.5 °C world. We also examine key factors that influence the use of gas such as Carbon Capture and Storage and Negative Emissions Technologies. We find that global gas use decreases more considerably under a 1.5 °C target than 2 °C with half of the 1.5 °C scenarios reducing gas use by at least ∼35% by 2050 and ∼70% by 2100 against 2019 consumption. We find there is no correlation between the level of Negative Emissions Technologies and the permitted gas use in Intergovernmental Panel on Climate Change scenarios, while there is a strong correlation between gas use and the deployment of Carbon Capture and Storage. Regionally, there are considerable ranges in gas use, with the Organisation for Economic Cooperation and Development & European Union seeing the greatest decrease in use and Asia increasing use until 2050. Notwithstanding this uncertainty, global natural gas use is likely to decrease in the coming decades in response to climate goals.
Dubey L, Cooper J, Hawkes A, 2023, Minimum detection limits of the TROPOMI satellite sensor across North America and their implications for measuring oil and gas methane emissions, Science of the Total Environment, Vol: 872, Pages: 1-9, ISSN: 0048-9697
Methane emissions from natural gas are of ever-increasing importance as we struggle to reach Paris climate targets. Locating and measuring emissions from natural gas can be particularly difficult as they are often widely distributed across supply chains. Satellites are increasingly used to measure these emissions, with some such as TROPOMI giving daily coverage worldwide, making locating and quantifying these emissions easier. However, there is little understanding of the real-world detection limits of TROPOMI, which can cause emissions to go undetected or be misattributed. This paper uses TROPOMI and meteorological data to calculate, and create a map of, the minimum detection limits of the TROPOMI satellite sensor across North America for different campaign lengths. We then compared these to emission inventories to determine the quantity of emissions that can be captured by TROPOMI. We find that minimum detection limits vary from 500-8800 kg/h/pixel in a single overpass to 50-1200 kg/h/pixel for a yearlong campaign. This leads to 0.04 % of a year's emissions being captured in a single (day) measurement to 14.4 % in a 1-year measurement campaign. Assuming gas sites contain super-emitters, emissions of between 4.5 % - 10.1 % from a single measurement and 35.6 % - 41.1 % for a yearlong campaign are captured.
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
There are no methodologies in the literature for estimating the temporal and spatial distribution of consumption drivers for the residential sector of a region or country. Factors such as energy requirement, population density, outdoor temperature, and socioeconomic aspects are considered the major drivers of consumption and have been found to directly influence residential energy consumption. In this study, a methodology is proposed to evaluate the impact of the above drivers in domestic energy consumption in Ecuador between 2010 and 2020 using publicly available data. This methodology aims to provide a spatiotemporal approach to estimate high-resolution gridded datasets for a 10-year period, 2010–2020, assessing seven energy drivers: (1) gridded population density, (2) gridded space heating requirements, (3) gridded space cooling requirements, (4) gridded water heating requirements, (5) gridded Gross Domestic Product (GDP), (6) gridded per capita GDP, and (7) the Human Development Index (HDI). Drivers 1 to 6 were analyzed at one square kilometer (1 km2), whereas HDI was analyzed at the city level. These results can be used to evaluate energy-planning strategies in a range of sustainable scenarios. This methodology can be used to evaluate a range of consumption drivers to evaluate long-term energy policies to reach the net-zero target by midcentury. The proposed methodology can be reproduced in other countries and regions. Future research could explore the spatiotemporal correlation of the consumption drivers provided in this study.
Dubey L, Cooper J, Staffell I, et al., 2023, Comparing satellite methane measurements to inventory estimates: a Canadian case study, Atmospheric Environment: X, Vol: 17, Pages: 1-9, ISSN: 2590-1621
Methane emissions from natural gas production are of increasing importance as they threaten efforts to mitigate climate change. Current inventory estimates carry high uncertainties due to difficulties in measuring emission sources across large regions. Satellite measurements of atmospheric methane could provide new understanding of emissions. This paper provides insight into the effectiveness of using satellite data to inform and improve methane inventories for natural gas activities. TROPOMI data are used to quantify methane emissions from natural gas within the Montney basin region of Canada and results are compared with existing inventories. Emissions estimated using TROPOMI data were 2.6 ± 2.2 kt/day which is 7.4 ± 6.4 times the inventory estimates. Pixels (7 by 7 km) that contained gas facilities had on average 11 ppb more methane than the background. 7.4% of pixels containing gas sites displayed consistently high methane levels that were not reflected in the inventory. The satellite data were not sufficiently granular to correlate with inventories on a facility scale. This illustrates the spatial limitations of using satellite data to corroborate bottom-up inventories.
Stettler MEJ, Woo M, Ainalis D, et al., 2022, Review of Well-to-Wheel lifecycle emissions of liquefied natural gas heavy goods vehicles, APPLIED ENERGY, Vol: 333, ISSN: 0306-2619
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).
Bakkaloglu S, Cooper J, Hawkes A, 2022, Life cycle environmental impact assessment of methane emissions from the biowaste management strategy of the United Kingdom: Towards net zero emissions, JOURNAL OF CLEANER PRODUCTION, Vol: 376, ISSN: 0959-6526
Parkinson B, Balcombe P, Speirs JF, et al., 2022, Levelized cost of CO2 mitigation from hydrogen production routes (vol 12, pg 19, 2019), ENERGY & ENVIRONMENTAL SCIENCE, ISSN: 1754-5692
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.
Mulugetta Y, Sokona Y, Trotter PA, et al., 2022, Africa needs context-relevant evidence to shape its clean energy future, NATURE ENERGY, Vol: 7, Pages: 1015-1022, ISSN: 2058-7546
Cooper J, Hawkes A, 2022, Cutting emissions outside borders, Nature Climate Change, Vol: 12, Pages: 965-966, ISSN: 1758-678X
Cooper J, Dubey L, Bakkaloglu S, et al., 2022, Hydrogen emissions from the hydrogen value chain-emissions profile and impact to global warming, Science of the Total Environment, Vol: 830, ISSN: 0048-9697
Future energy systems could rely on hydrogen (H2) to achieve decarbonisation and net-zero goals. In a similar energy landscape to natural gas, H2 emissions occur along the supply chain. It has been studied how current gas infrastructure can support H2, but there is little known about how H2 emissions affect global warming as an indirect greenhouse gas. In this work, we have estimated for the first time the potential emission profiles (g CO2eq/MJ H2,HHV) of H2 supply chains, and found that the emission rates of H2 from H2 supply chains and methane from natural gas supply are comparable, but the impact on global warming is much lower based on current estimates. This study also demonstrates the critical importance of establishing mobile H2 emission monitoring and reducing the uncertainty of short-lived H2 climate forcing so as to clearly address H2 emissions for net-zero strategies.
Cooper J, Dubey L, Hawkes A, 2022, The life cycle environmental impacts of negative emission technologies in North America, Sustainable Production and Consumption, Vol: 32, Pages: 880-894, ISSN: 2352-5509
Negative emission technologies (NETs) could play a key role in ensuring net-zero and longer-term net negative emission ambitions are met. However, greenhouse gas emissions (and other pollutants) will occur over the life cycle of a NET and will need to be taken into consideration when developing schemes to roll out their use. We compare five NETs: afforestation/reforestation (AR), enhanced weathering (EW), mangrove restoration (MR), bioenergy and direct air capture with carbon storage (BECCS and DAC), using life cycle assessment to determine their environmental impacts (global warming, freshwater, toxicity etc.). We find that there is a wide range in the environmental impacts estimated across the NETs and the context in which they are used will directly impact which NET has low or high environmental impacts. This is an important aspect to consider when deciding which NET to prioritise in strategies to roll out their use on large scales. If consistent removal of CO2 from the atmosphere is the goal, then AR and MR have the lowest environmental impacts. However, if large and quick CO2 removal is the goal then EW, DAC and BECCS have similar, if not lower, environmental impacts.
Bakkaloglu S, Cooper J, Hawkes A, 2022, Methane emissions along biomethane and biogas supply chains are underestimated, One Earth, Vol: 5, Pages: 724-736, ISSN: 2590-3322
Although natural gas generates lower CO2 emissions, gas extraction, processing, and distribution all release methane, which has a greater global warming potential than CO2. Biomethane and biogas that use organic wastes as a feedstock have emerged as alternatives to natural gas, with lower carbon and methane emissions. However, the extent to which methane is still emitted at various stages along biogas and biomethane supply chains remains unclear. Here, we adopt a Monte Carlo approach to systematically synthesize the distribution of methane emissions at each key biomethane and biogas supply chain stage using data collected from the existing literature. We show that the top 5% of emitters are responsible for 62% of emissions. Methane emissions could be more than two times of greater than previously estimated, with the digestate handling stage responsible for the majority of methane released. To ensure the climate benefits of biomethane and biogas production, effective methane-mitigation strategies must be designed and deployed at each supply chain stage.
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.
Cooper J, Dubey L, Hawkes A, 2022, Life cycle assessment of negative emission technologies for effectiveness in carbon sequestration, 29th CIRP Life Cycle Engineering Conference, Publisher: Elsevier, Pages: 357-361, ISSN: 2212-8271
As climate change and emissions targets tighten, negative emissions technologies (NETs) will play a crucial role in making sure global temperature rises do not exceed Paris Agreement goals. There are a variety of NETs that can be used to abate greenhouse gas (GHG) emissions, but it is uncertain which are more effective, and by how much, as well as what the net GHG removal is as all NETs will emit GHGs and other pollutants throughout their life cycles. We conducted a life cycle assessment (LCA) to compare four NETs: afforestation/reforestation, enhanced weathering, direct air capture and bioenergy with carbon capture and storage. These are compared on their life cycle impacts to climate change, land use change and toxicity (human and terrestrial). We find that the most effective NET is afforestation/reforestation for the environmental impacts considered while enhanced weathering and direct air capture are less effective. However, when the rate of carbon removal is considered, we find that afforestation/reforestation is much slower than the other NETs. Therefore, while it has the lowest impacts to the environment, either long time frames or large-scale implementation is needed for it to match the capacity of direct air capture or bioenergy with carbon capture and storage.
Edelenbosch OY, Miu L, Sachs J, et al., 2022, Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework, iScience, Vol: 25
Decarbonizing the building sector depends on choices made at the household level, which are heterogeneous. Agent-based models are tools used to describe heterogeneous choices but require data-intensive calibration. This study analyzes a novel, cross-country European household-level survey, including sociodemographic characteristics, energy-saving habits, energy-saving investments, and metered household electricity consumption, to enhance the empirical grounding of an agent-based residential energy choice model. Applying cluster analysis to the data shows that energy consumption is not straightforwardly explained by sociodemographic classes, preferences, or attitudes, but some patterns emerge. Income consistently has the largest effect on demand, dwelling efficiency, and energy-saving investments, and the potential to improve a dwellings' energy use affects the efficiency investments made. Including the various sources of heterogeneity found to characterize the model agents affects the timing and speed of the transition. The results reinforce the need for grounding agent-based models in empirical data, to better understand energy transition dynamics.
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
Yliruka MI, Moret S, Jalil-Vega F, et al., 2022, The Trade-Off between Spatial Resolution and Uncertainty in Energy System Modelling, Computer Aided Chemical Engineering, Pages: 2035-2040
In energy system models, computational tractability is often maintained by adopting a simplified temporal and spatial representation in a deterministic model formulation i.e., neglecting uncertainty. However, such simplifications have been shown to impact the optimal result. To address the question of how to prioritize the limited computational resources, the trade-off between spatial resolution and uncertainty is assessed by applying a novel method based on global sensitivity analysis to a peer-reviewed heat decarbonization model. For all output variables apart from the total system and fuel cost, spatial resolution is ranks amongst the five most important model inputs. It is the most relevant factor for investment decisions on network capacities. For the total fuel consumption and emissions, spatial resolution turns out to be more relevant than the fuel prices themselves. Compared across all outputs, the analysis suggests the impact of spatial resolution is comparable the impact of heat demand levels and the discount rate.
Mascarenhas KL, Malvezzi S, Hawkes AD, et al., 2022, University-industry-government partnership working on sustainable development goals in Brazil, International Journal of Intellectual Property Management, Vol: 12, Pages: 42-63, ISSN: 1478-9647
This paper aims to provide insights into the capabilities of a university of working cooperatively with the industry and the government, to promote the sustainable development goals (SDGs) and foster the United Nations 2030 Agenda. Through the case study of a Brazilian research centre, structured in a triple helix model (university-industry-government), the potential of this tripartite partnership is explored in the context of long-term timeframe research. The contribution of the research centre towards the SDGs is analysed through its main activities. It suggests that information and dissemination of knowledge about the impacts generated by research, business, policy and behaviour are fundamental means to kindle a new mentality aligned with the SDGs. Therefore, it indicates that the triple helix model may boost a faster and more efficient trajectory that embraces a broad spectrum from research to implementation, which enables more feasible contributions to the SDG targets.
Rai U, Oluleye G, Hawkes A, 2022, An optimisation model to determine the capacity of a distributed energy resource to contract with a balancing services aggregator, Applied Energy, Vol: 306, Pages: 1-22, ISSN: 0306-2619
Electricity systems require a real-time balance between generation and demand for electricity. In the past, changing the output of larger generators has been the primary means of achieving this balance, but more recently, smaller distributed energy resources (DERs) are becoming a contributor. As electricity generation becomes more intermittent due to the uptake of renewables, the task of balancing the electricity system is becoming more challenging. As such, there will be a greater need for DERs for grid balancing in future. DERs may be delivered via aggregators for this purpose, where several individual resources are grouped to be traded in contracts with a System Operator (SO). This paper presents a novel framework for DERs aggregators to determine by optimisation the capacity of a generating unit to contract with the SO, using mixed integer non-linear programming (MINLP). Results show the site revenue increases between 6.2% and 29.8% compared to the heuristic approach previously employed. Sensitivity analysis is performed to assess the impact of temporal resolution of demand characterisation on results, showing that increased resolution improves accuracy significantly, and reduces the estimate of capacity that the site should contract with the aggregator.
Wickham D, Hawkes A, Jalil-Vega F, 2022, Hydrogen supply chain optimisation for the transport sector – Focus on hydrogen purity and purification requirements, Applied Energy, Vol: 305, Pages: 1-48, ISSN: 0306-2619
This study presents a spatially-resolved optimisation model to assess cost optimal configurations of hydrogen supply chains for the transport sector up to 2050. The model includes hydrogen grades and separation/purification technologies, offering the possibility to assess the effects that hydrogen grades play in the development of cost-effective hydrogen supply chains, including the decisions to repurpose gas distribution networks or blending hydrogen into them. The model is implemented in a case study of Great Britain, for a set of decarbonisation and learning rate scenarios. A base case with a medium carbon price scenario shows that the total discounted cost of the hydrogen supply chain is significantly higher than shown in previous studies, largely due to the additional costs from purification/separation needed to meet hydrogen purity standards for transport applications. Furthermore, it was shown that producing hydrogen from steam methane reforming with carbon capture and storage; installing new transmission pipelines; repurposing the gas distribution network to supply 100% hydrogen; and purifying hydrogen with a pressure swing adsorption system locally at the refuelling station; is a cost optimal configuration for the given technoeconomic assumptions, providing hydrogen at £6.18 per kg at the pump. Purification technologies were found to contribute to 14% and 30% of total discounted investment and operation costs respectively, highlighting the importance of explicitly including them into hydrogen supply chain models for the transport sector.
Machado PG, Hawkes A, Ribeiro CDO, 2021, What is the future potential of CCS in Brazil? An expert elicitation study on the role of CCS in the country, International Journal of Greenhouse Gas Control, Vol: 112, Pages: 1-11, ISSN: 1750-5836
This article presents the results of an expert elicitation about the role of carbon capture and storage (CCS) in Brazil as a measure to reduce greenhouse gases emissions, its costs, and the most appropriate policies to develop this technology at a commercial scale. Experts were elicited based on a scenario oriented towards net-zero emissions in Brazil by 2050. Five parameters were elicited, and all present great uncertainty. Results show that experts believe CCS has the potential to reduce CO2 emissions in Brazil. Still, with the current lack of supporting market, policy and regulatory frameworks in place, it could take another five years to begin implementation, reaching commercial scale not earlier than 12 years from the time of writing. Experts say that the chance of Brazil reaching the elicited value of 190 million tons of CO2 per year is very low. This indicates that though CCS can play a role in achieving net-zero emissions in the country, many other measures will be necessary. Policy-wise, the experts bet on a carbon market as the most probable policy instrument to help CCS development in Brazil. The experts also estimated the total investment necessary to reach 190 million tons of CO2 per year captured at USD 58 billion. When it comes to public expenditures, experts believe the role of the government in funding CCS in the country would be approximately 25% of total investments coming from different sources of public investment.
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