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  • Journal article
    Chu C-T, Hawkes AD, 2020,

    Optimal mix of climate-related energy in global electricity systems

    , Renewable Energy, Vol: 160, Pages: 955-963, ISSN: 0960-1481

    Existing studies on high renewable share electricity systems are usually based on least cost optimization. Running the related models can be time-consuming when space-time resolution is high. This study investigates the optimal mix of climate-related energies for most countries in the world with optimization models based on three criteria: cost, residual load variability, and portfolio output variability. The objectives of minimizing residual load variability and portfolio output variability are to ensure the overall complementarity of the generation portfolio, which may result in less conventional dispatchable units needed in a system. Compromise solutions based on the three objectives are proposed as the optimal mix. This method can produce solutions in acceptable modelling time, and considers the portfolio output characteristics which can make higher climate-related energy penetration more practical. The results show that the compromise solutions can effectively minimize the three objective values in most countries. The results also suggest that wind power is crucial in higher renewable share systems while solar power does not reach over 50% capacity share.

  • Journal article
    Budinis S, Sachs J, Giarola S, Hawkes Aet 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.

  • Journal article
    Moya D, Budinis S, Giarola S, Hawkes Aet 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).

  • Journal article
    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.

  • Journal article
    Lyrio de Oliveira L, García Kerdan I, de Oliveira Ribeiro C, Oller do Nascimento CA, Rego EE, Giarola S, Hawkes Aet 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.

  • Journal article
    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.

  • Journal article
    Chu C-T, Hawkes AD, 2020,

    A geographic information system-based global variable renewable potential assessment using spatially resolved simulation

    , Energy, Vol: 193, Pages: 1-11, ISSN: 0360-5442

    Variable renewable energy is set to become a key energy source worldwide, but there is concern regarding the impact of the intermittency of its output when penetration is high. Energy system models need to tackle this issue by improving modelling resolution and scope. To allow for such modelling, more and better input datasets are needed on variable renewable energy potentials and yields. These need to be of global scope, of sufficient spatial and temporal resolution, and generated with transparent, consistent methods. This study develops the methods and applies it to generate these datasets at subnational and hourly resolution. The assessment is carried out for wind and solar technologies with consistent constraints including geographical, social and economic aspects. Features from the OpenStreetMap are converted into land cover and land use datasets and applied. Hourly energy output is simulated using NASA MERRA-2 meteorological datasets, reconciled with resource maps from the Global Wind Atlas and Global Solar Atlas platforms. Capacity supply curves are provided for 731 terrestrial zones and 339 offshore zones worldwide, along with corresponding hourly output profiles over a 10-year simulation period. The proposed energy potentials are relative conservative compared with other studies. The datasets can serve as input for regional or global energy system models when analyzing high variable renewable energy shares.

  • Journal article
    Luh S, Budinis S, Giarola S, Schmidt TJ, Hawkes Aet 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.

  • Journal article
    Bosch J, Staffell I, Hawkes AD, 2019,

    Global levelised cost of electricity from offshore wind

    , Energy, Vol: 189, Pages: 116357-116357, ISSN: 0360-5442

    There is strong agreement across the energy modelling community that wind energy will be a key route to mitigating carbon emissions in the electricity sector. This paper presents a Geospatial Information System methodology for estimating spatially-resolved levelised cost of electricity for offshore wind, globally. The principal spatial characteristics of capital costs are transmission distance (i.e. the distance to grid connection) and water depth, because of the disparate costs of turbine foundation technologies. High resolution capacity factors are estimated from a bottom-up estimation of global wind speeds calculated from several decades of wind speed data. A technology-rich description of fixed and floating foundation types allows the levelised cost of electricity to be calculated for 1 × 1 km grid cells, relative to location-specific annual energy production, and accounting for exclusion areas, array losses and turbine availability. These data can be used to assess the economically viable offshore wind energy potential, globally and on a country basis, and can serve as inputs to energy systems models.

  • Journal article
    García Kerdan I, Jalil-Vega F, Toole J, Gulati S, Giarola S, Hawkes Aet 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.

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