6 results found
Jalil Vega F, Garcia Kerdan I, Hawkes A, 2020, Spatially-resolved urban energy systems model to study decarbonisation pathways for energy services in cities, Applied Energy, Vol: 262, ISSN: 0306-2619
This work presents the COMET (Cities Optimisation Model for Energy Technologies) model, a spatially-resolved urban energy systems model that takes into account energy service demands for heating, cooling, electricity, and transport, and finds cost-effective pathways for supplying these demands under carbon constraints, trading-off energy supply, network infrastructure, and end-use technologies. Spatially-resolved energy service demands were obtained for the city of Sao Paulo, and six scenarios were modelled. Results show that district cooling is cost-effective in the highest linear cooling density zones, with full penetration in zones with over 1100 kWh/m by 2050. This threshold diminishes with tighter carbon constraints. Heating is electrified in all scenarios, with electric boilers and air-source heat pumps being the main supply technologies for the domestic and commercial sectors respectively by 2050. In the most carbon constrained scenario with a medium decarbonised electricity grid, ground source heat pumps and hydrogen boilers appear as transition technologies between 2030 and 2045 for the commercial and domestic sectors respectively, reaching 95% and 40% of each sector’s heat installed capacity in 2030. In the transport sector, ethanol cars replace gasoline, diesel, and compressed natural gas cars; compressed natural gas buses replace diesel and electric buses; and lorries continue using diesel. In carbon constrained scenarios, higher penetrations of electric cars and buses are obtained, while no change is observed for lorries. Finally, the most expensive scenario was only 6% more expensive than the reference scenario, meaning that achieving decarbonisation targets is not much costlier when comparing scenarios from a system-wide perspective.
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, Jalil-Vega F, et al., 2019, Carbon sequestration potential from large-scale reforestation and sugarcane expansion on abandoned agricultural lands in Brazil, Polytechnica, Vol: 2, Pages: 9-25, ISSN: 2520-8497
Since 1850, over 145 ± 16 PgC (μ ± 1σ) has been emitted worldwide due to land-use change and deforestation. Besides industrial carbon capture and storage (CCS), storing carbon in forestry products and in regenerated forest has been recognized as a cost-effective carbon sequestration option, with an estimated worldwide sink potential of about 50–100 PgC (15–36 PgC from tropical forest alone). This paper proposes the expansion of a Brazilian integrated assessment model (MUSE-Brazil) by integrating a non-spatial biomass-growth model. The aim is to account for carbon sequestration potential from either reforestation or sugarcane expansion in abandoned agricultural lands. Modelling outputs suggest that Brazil has the potential to liberate up to 32.3 Mha of agricultural land by 2035, reaching 68.4 Mha by mid-century. If a sugarcane expansion policy is promoted, by 2050, the largest sequestration rates would come from above and below ground biomass pools; gradually releasing to the atmosphere around 1.6 PgC or 1.2% of the current Brazilian land carbon stock due to lower SOC carbon pools when turning agricultural lands into sugarcane crops. On the other hand, a reforestation-only scenario projects that by 2035 the baseline year carbon stock could be recovered and by 2050 the country’s carbon stock would have been increased by 3.2 PgC, reaching annual net sequestration rates of 0.1 PgC y−1, mainly supported by natural vegetation regeneration in the Cerrado biome.
Jalil Vega FA, Hawkes A, 2018, The effect of spatial resolution on outcomes from energy systems modelling of heat decarbonisation, Energy, Vol: 155, Pages: 339-350, ISSN: 0360-5442
Spatial resolution is often cited as a crucial determinant of results from energy systems models. However, there is no study that comprehensively analyses the effect of spatial resolution. This paper addresses this gap by applying the Heat Infrastructure and Technology heat decarbonisation optimisation model in six UK Local Authorities representing a range of rural/urban areas, at three levels of spatial resolution, in order to systematically compare results. Results show the importance of spatial resolution for optimal allocation of heat supply technologies and infrastructure across different urban/rural areas. Firstly, for the studied cases, differences of up to 30% in heat network uptake were observed when comparing results between different resolutions for a given area. Secondly, for areas that generally exhibit the high and low extremes of linear heat density, results are less dependent on spatial resolution. Also, spatial resolution effects are more significant when there is higher variability of linear heat density throughout zones. Finally, results show that it is important to use finer resolutions when using optimisation models to inform detailed network planning and expansion. Higher spatial resolutions provide more detailed information on zones that act as anchors that can seed network growth and on location of network supply technologies.
Jalil Vega FA, Hawkes A, 2018, Spatially resolved optimization for studying the role of hydrogen for heat decarbonization pathways, ACS Sustainable Chemistry and Engineering, Vol: 6, Pages: 5835-5842, ISSN: 2168-0485
This paper studies the economic feasibility of installing hydrogen networks for decarbonising heat in urban areas. The study uses the Heat Infrastructure and Technology (HIT) spatially-resolved optimisation model to trade-off energy supply, infrastructure and end-use technology costs for the most important heat-related energy vectors; gas, heat, electricity, and hydrogen. Two model formulations are applied to UK urban area: one with an independent hydrogen network, and one that allows for retrofitting the gas network into hydrogen. Results show that for average hydrogen price projections, cost-effective pathways for heat decarbonisation towards 2050 comprise including heat networks supplied by a combination of district level heat pumps and gas boilers in the domestic and commercial sectors, and hydrogen boilers in the domestic sector. For a low hydrogen price scenario, when retrofitting the gas network into hydrogen, a cost-effective pathway is replacing gas by hydrogen boilers in the commercial sector, and a mixture of hydrogen boilers and heat networks supplied by district level heat pumps, gas, and hydrogen boilers for the domestic sector. Compared to the first modelled year, CO2 emissions reductions of 88% are achieved by 2050. These results build on previous research on the role of hydrogen in cost-effective heat decarbonisation pathways.
Jalil Vega F, Hawkes AD, 2017, Spatially resolved model for studying decarbonisation pathways for heat supply and infrastructure trade-offs, Applied Energy, Vol: 210, Pages: 1051-1072, ISSN: 1872-9118
Heat decarbonisation is one of the main challenges of energy system decarbonisation. However, existing energy planning models struggle to compare heat decarbonisation approaches because they rarely capture trade-offs between heat supply, end-use technologies and network infrastructure at sufficient spatial resolution. A new optimisation model is presented that addresses this by including trade-offs between gas, electricity, and heat infrastructure, together with related supply and end-use technologies, with high spatial granularity. The model is applied in case studies for the UK. For the case modelled it is shown that electrification of heat is most cost-effective via district level heat pumps that supply heat networks, instead of individual building heat pumps. This is because the cost of reinforcing the electricity grid for installing individual heat pumps does not sufficiently offset heat infrastructure costs. This demonstrates the importance of considering infrastructure trade-offs. When modelling the utilisation of a decarbonised gas, the penetration of heat networks and location of district level heat supply technologies was shown to be dependent on linear heat density and on zone topology. This shows the importance of spatial aspects. Scenario-specific linear heat density thresholds for heat network penetration were identified. For the base case, penetration of high temperature heat networks was over 50% and 60% by 2050 for linear heat densities over 1500 and 2500 kWh/m. For the case when medium heat temperature networks were additionally available, a mix of both networks was observed. Medium temperature heat network penetration was over 20%, 30%, and 40% for linear heat densities of over 1500, 2500, and 3000 kWh/m, while high temperature heat network penetration was over 20% and 30% for linear heat densities of under 2000 and 1500 kWh/m respectively.
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.