161 results found
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).
Miu LM, Hawkes A, 2020, Private landlords and energy efficiency: Evidence for policymakers from a large-scale study in the United Kingdom, Energy Policy, Vol: 142, ISSN: 0301-4215
Energy use in British homes is a significant contributor to national greenhouse gas emissions, and the improvement of energy efficiency in residential buildings has long been an important topic in policy discussions. The lack of investment in energy-saving measures is particularly challenging in the private rented sector, and there are significant research and data gaps in understanding the retrofit behaviour of private landlords. In this study, we present the results of a detailed survey on retrofit behaviour of 1069 British private landlords. The survey assesses the engagement of landlords with 18 different energy efficiency measures, as well as their attitudes, perceptions, norms and a number of other characteristics. We use the data collected in the survey to produce 7 behavioural “typologies” of landlord retrofitters, by clustering respondents based on their socio-demographic and business characteristics. In addition to providing descriptive evidence of landlords' retrofit behaviour, our results reveal a number of opportunities for segmenting the landlord population into target groups for future policy interventions. By tailoring retrofit incentives to the needs and motivations of these groups, policy-makers can effectively engage landlords with specific energy-saving technologies, increasing the likelihood of retrofit uptake and accelerating the transition to an energy-efficient private rented sector.
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.
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.
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.
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.
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.
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.
da Hora MABP, Asrilhant B, Accioly RMS, et al., 2019, Decision making to book oil reserves for different Brazilian fiscal agreements using dependence structure, ENERGY STRATEGY REVIEWS, Vol: 26, ISSN: 2211-467X
Miu LM, Mazur CM, Van Dam KH, et al., 2019, Going smart, staying confused: perceptions and use of smart thermostats in British homes, Energy Research and Social Science, Vol: 57, ISSN: 2214-6296
Given the significant contribution of housing to energy consumption, research into how residents use energy-saving technologies has been gathering pace. In this study, we investigate the perception and use of domestic smart heating controls by a small group of residents in London, UK. These residents are supplied by a district heat network (DHN) through underfloor heating systems, and took part in a trial where their controls were upgraded from traditional thermostats to smart thermostats. Pre- and post-trial interviews were used to assess changes in how residents interacted with and perceived their controls and heating systems. After the upgrade, more residents were satisfied with the usability of their controls and programmed heating schedules which matched their actual occupancy patterns, but they also made ad-hoc temperature and schedule adjustments more frequently. These changes provide insight into how a unique sample of residents, “twice removed” from the most intuitive methods of heating control, adjusted their behaviour and perceptions following a technology upgrade. Although the small sample size and lack of long-term monitoring limits the generalizability of our results, the findings open avenues for further research into whether smart heating controls change user behaviour in a way that improves the predictability of heating demand, a crucial aspect of improving DHN operation and reducing related emissions.
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.
Guo Y, Hawkes A, 2019, Asset stranding in natural gas export facilities: An agent-based simulation, ENERGY POLICY, Vol: 132, Pages: 132-155, ISSN: 0301-4215
Vijay A, Hawkes A, 2019, Demand side flexibility from residential heating to absorb surplus renewables in low carbon futures, Renewable Energy: An International Journal, Vol: 138, Pages: 598-609, ISSN: 0960-1481
Higher penetration of renewable sources of energy is essential for mitigating climate change. This introduces problems related to the balance of supply and demand. Instances in which the generation from intermittent and inflexible sources is in excess of system load are expected to increase in low carbon futures. Curtailment is likely to involve high constraint payments to renewable sources, and failing to curtail threatens the stability of the system. This work investigates a solution that makes use of residential heating systems to absorb the excess generation. Consumers are incentivised to increase consumption via a demand turn up mechanism that sets the electricity price to zero when excess generation occurs. The reduction in electricity price significantly weakens the economic case of dwelling-scale micro-cogeneration units. But technologies that use electricity are able to charge the thermal store when free electricity is available and discharge it when electricity prices are high. Such actions reduce the equivalent annual cost by 50 percent for a resistive heater and by 60 percent for a heat pump. Without disincentives, resistive heaters are likely to be chosen over heat pumps since they are easy to install, do not involve high upfront costs and can provide significant economic benefits.
Realmonte G, Hawkes A, Gambhir A, et al., 2019, An inter-model assessment of the role of direct air capture in deep mitigation pathways, Nature Communications, Vol: 10, ISSN: 2041-1723
The feasibility of large-scale biological CO2 removal to achieve stringent climate targets remains unclear. Direct Air CarbonCapture and Storage (DACCS) offers an alternative negative emissions technology (NET) option. Here we conduct the firstinter-model comparison on the role of DACCS in 1.5 and 2°C scenarios, under a variety of techno-economic assumptions.Deploying DACCS significantly reduces mitigation costs, and it complements rather than substitutes other NETs. The key factorlimiting DACCS deployment is the rate at which it can be scaled up. Our scenarios’ average DACCS scale-up rates of 1.5GtCO2/yr would require considerable sorbent production and up to 300 EJ/yr of energy input by 2100. The risk of assumingthat DACCS can be deployed at scale, and finding it to be subsequently unavailable, leads to a global temperature overshoot ofup to 0.8°C. DACCS should therefore be developed and deployed alongside, rather than instead of, other mitigation options.
Cooper J, Balcombe P, Hawkes A, 2019, Life cycle environmental impacts of natural gas drivetrains used in UK road freighting and impacts to UK emission targets, Science of the Total Environment, Vol: 674, Pages: 482-493, ISSN: 0048-9697
Using natural gas as a fuel in the road freight sector instead of diesel could cut greenhouse gas and air quality emissions but the switch alone is not enough to meet UK climate targets. A life cycle assessment (LCA) has been conducted comparing natural gas trucks to diesel, biodiesel, dimethyl ether and electric trucks on impacts to climate change, land use change, air quality, human health and resource depletion. This is the first LCA to consider a full suite of environmental impacts and is the first study to estimate what impact natural gas could have on reducing emissions form the UK freight sector. If LNG is used, climate change impacts could be up to 33% lower per km and up to 12% lower per kWh engine output. However, methane emissions will eliminate any benefits if they exceed 1.5–3.5% of throughput for typical fuel consumption. For non-climate impacts, natural gas exhibits lower emissions (11–66%) than diesel for all indicators. Thus, for natural gas climate benefits are modest. However, emissions of CO, methane and particulate matter are over air quality limits set for UK trucks. Of the other options, electric and biodiesel trucks perform best in climate change, but are the worst with respect to land use change (which could have significant impacts on overall climate change benefits), air quality, human toxicity and metals depletion indicators. Natural gas could help reduce the sector's emissions but deeper decarbonization options are required to meet 2030 climate targets, thus the window for beneficial utilisation is short.
Crow DJG, Balcombe P, Brandon N, et al., 2019, Assessing the impact of future greenhouse gas emissions from natural gas production, Science of the Total Environment, Vol: 668, Pages: 1242-1258, ISSN: 0048-9697
Greenhouse gases (GHGs) produced by the extraction of natural gas are an important contributor to lifecycle emissions and account for a significant fraction of anthropogenic methane emissions in the USA. The timing as well as the magnitude of these emissions matters, as the short term climate warming impact of methane is up to 120 times that of CO 2 . This study uses estimates of CO 2 and methane emissions associated with different upstream operations to build a deterministic model of GHG emissions from conventional and unconventional gas fields as a function of time. By combining these emissions with a dynamic, techno-economic model of gas supply we assess their potential impact on the value of different types of project and identify stranded resources in various carbon price scenarios. We focus in particular on the effects of different emission metrics for methane, using the global warming potential (GWP) and the global temperature potential (GTP), with both fixed 20-year and 100-year CO 2 -equivalent values and in a time-dependent way based on a target year for climate stabilisation. We report a strong time dependence of emissions over the lifecycle of a typical field, and find that bringing forward the stabilisation year dramatically increases the importance of the methane contribution to these emissions. Using a commercial database of the remaining reserves of individual projects, we use our model to quantify future emissions resulting from the extraction of current US non-associated reserves. A carbon price of at least 400 USD/tonne CO 2 is effective in reducing cumulative GHGs by 30–60%, indicating that decarbonising the upstream component of the natural gas supply chain is achievable using carbon prices similar to those needed to decarbonise the energy system as a whole. Surprisingly, for large carbon prices, the choice of emission metric does not have a significant impact on cumulative emissions.
García Kerdan I, Morillón Gálvez D, Sousa G, et al., 2019, Thermodynamic and thermal comfort optimisation of a coastal social house considering the influence of the thermal breeze, Building and Environment, Vol: 155, Pages: 224-246, ISSN: 0360-1323
Tropical coastal areas are characterised by high levels of wind and solar resources with large potentials to be utilised for low-energy building design. This paper presents a multi-objective optimisation framework capable of evaluating cost-efficient and low-exergy coastal building designs considering the influence of the thermal breeze. An integrated dynamic simulation tool has been enhanced to consider the impacts of the sea-land breeze effect, aiming at potentiating natural cross-ventilation to improve occupant's thermal comfort and reduce cooling energy demand. Furthermore, the technological database considers a wide range of active and passive energy conservation measures. As a case study, a two-storey/two-flat detached social house located in the North-Pacific coast of Mexico has been investigated. The optimisation problem has considered the minimisation of: i. annual exergy consumption, ii. life cycle cost, and iii. thermal discomfort. Optimisation results have shown that adequate building orientation and window opening control to optimise the effects of the thermal breeze, combined with other passive and active strategies such as solar shading devices, an improved envelope's physical characteristics, and solar assisted air source heat pumps have provided the best performance under a limited budget. Compared to the baseline design, the closest to utopia design has increased thermal comfort by 93.8% and reduced exergy consumption by 10.3% whilst increasing the life cycle cost over the next 50 years by 18.5% (from US$39,864 to US$47,246). The importance of renewable generation incentives is further discussed as a counter effect measure for capital cost increase as well as unlocking currently high-cost low-exergy technologies.
Guo Y, Hawkes A, 2019, The impact of demand uncertainties and China-US natural gas tariff on global gas trade, Energy, Vol: 175, Pages: 205-217, ISSN: 0360-5442
The uncertainties in gas demand levels and geopolitical issues may lead to significant changes in global gas trade. This paper uses an agent-based model to simulate the alternative market futures under two demand trajectories: a baseline following current policy pledges until 2060 and another where demand shifts to a lower level in 2030. Endogenously generated capacity investments are driven by long-term bilateral contracts between importers and exporters, where investors are assumed to evaluate the potential risks of demand changes while making their decisions. The results suggest that, when the demand decreases in 2030, the Middle East takes the dominant position in Eastern Asia, whereas this role is occupied by North America in the current policy scenario. In addition, the impacts of a 25% tariff by China on U.S. natural gas are studied for both scenarios. The revenue of North American gas trade is only marginally affected by this tariff. Under the normal demand trajectory, the tariff influences the Chinese market more notably in the longer term when global supply is tightened by decommissioning. In the case of lower global gas demand, the market share of Russia in Western Europe could be threatened by increasing North American export there.
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.
Napp TA, Few S, Sood A, et al., 2019, The role of advanced demand-sector technologies and energy demand reduction in achieving ambitious carbon budgets, Applied Energy, Vol: 238, Pages: 351-367, ISSN: 0306-2619
Limiting cumulative carbon emissions to keep global temperature increase to well below 2 °C (and as low as 1.5 °C) is an extremely challenging task, requiring rapid reduction in the carbon intensity of all sectors of the economy and with limited leeway for residual emissions. Addressing residual emissions in ‘challenging-to-decarbonise’ sectors such as the industrial and aviation sectors relies on the development and commercialization of innovative advanced technologies, currently still in their infancy. The aim of this study was to (a) explore the role of advanced technologies in achieving deep decarbonisation of the energy system and (b) provide technology-specific details of how rapid and deep carbon intensity reductions can be achieved in the energy demand sectors. This was done using TIAM-Grantham – a linear cost optimization model of the global energy system with a detailed representation of demand-side technologies. We find that the inclusion of advanced technologies in the demand sectors, together with energy demand reduction through behavioural changes, enables the model to achieve the rapid and deep decarbonisation of the energy system associated with limiting global warming to below 2 °C whilst at the same time reduces reliance on negative emissions technologies by up to ∼18% compared to the same scenario with a standard set of technologies. Realising such advanced technologies at commercial scales, as well as achieving such significant reductions in energy demand, represents a major challenge for policy makers, businesses and civil society. There is an urgent need for continued R&D efforts in the demand sectors to ensure that advanced technologies become commercially available when we need them and to avoid the gamble of overreliance on negative emissions technologies to offset residual emissions.
Balcombe P, Brierley J, Lewis C, et al., 2019, How to decarbonise international shipping: Options for fuels, technologies and policies, Energy Conversion and Management, Vol: 182, Pages: 72-88, ISSN: 0196-8904
International shipping provides 80–90% of global trade, but strict environmental regulations around NOX, SOX and greenhouse gas (GHG) emissions are set to cause major technological shifts. The pathway to achieving the international target of 50% GHG reduction by 2050 is unclear, but numerous promising options exist. This study provides a holistic assessment of these options and their combined potential to decarbonise international shipping, from a technology, environmental and policy perspective. Liquefied natural gas (LNG) is reaching mainstream and provides 20–30% CO2 reductions whilst minimising SOX and other emissions. Costs are favourable, but GHG benefits are reduced by methane slip, which varies across engine types. Biofuels, hydrogen, nuclear and carbon capture and storage (CCS) could all decarbonise much further, but each faces significant barriers around their economics, resource potentials and public acceptability. Regarding efficiency measures, considerable fuel and GHG savings could be attained by slow-steaming, ship design changes and utilising renewable resources. There is clearly no single route and a multifaceted response is required for deep decarbonisation. The scale of this challenge is explored by estimating the combined decarbonisation potential of multiple options. Achieving 50% decarbonisation with LNG or electric propulsion would likely require 4 or more complementary efficiency measures to be applied simultaneously. Broadly, larger GHG reductions require stronger policy and may differentiate between short- and long-term approaches. With LNG being economically feasible and offering moderate environmental benefits, this may have short-term promise with minor policy intervention. Longer term, deeper decarbonisation will require strong financial incentives. Lowest-cost policy options should be fuel- or technology-agnostic, internationally applied and will require action now to ensure targets are met by 2050.
Speirs J, Balcombe P, Blomerus P, et al., 2019, Can natural gas reduce emissions from transport?: Heavy goods vehicles and shipping
Schmidt O, Melchior S, Hawkes A, et al., 2019, Projecting the future levelized cost of electricity storage technologies, Joule, Vol: 3, Pages: 81-100, ISSN: 2542-4351
The future role of stationary electricity storage is perceived as highly uncertain. One reason is that most studies into the future cost of storage technologies focus on investment cost. An appropriate cost assessment must be based on the application-specific lifetime cost of storing electricity. We determine the levelized cost of storage (LCOS) for 9 technologies in 12 power system applications from 2015 to 2050 based on projected investment cost reductions and current performance parameters. We find that LCOS will reduce by one-third to one-half by 2030 and 2050, respectively, across the modeled applications, with lithium ion likely to become most cost efficient for nearly all stationary applications from 2030. Investments in alternative technologies may prove futile unless significant performance improvements can retain competitiveness with lithium ion. These insights increase transparency around the future competitiveness of electricity storage technologies and can help guide research, policy, and investment activities to ensure cost-efficient deployment.
Oluleye G, Wigh D, Shah N, et al., 2019, A framework for biogas exploitation in Italian waste water treatment plants, Chemical Engineering Transactions, Vol: 76, Pages: 991-996
Copyright © 2019, AIDIC Servizi S.r.l. Effective utilisation of biogas is an important step in increasing usage of renewable energy, due to the great flexibility that solar and wind power in particular lacks. Biogas generated through anaerobic digestion (AD) of sewage sludge addresses environmental concerns together with creating electricity generation potential. There is currently no optimisation-based decision-support framework to determine the best use of biogas from a Waste Water Treatment Plant (WWTP), and provide a market outlook for each of the options. This work proposes a novel multi-period Mixed Integer Linear Program (MILP) model for dispatch and selection of technologies capable of exploiting biogas produced from sludge. The novelty is also highlighted by extrapolating the optimised results to a broader analysis of 855 Italian WWTPs with Population Equivalent (P.E.) > 20,000. The use of real input data provides a unique added value to the work. The modelling framework is applied to several case studies. Results show that 7–23 % savings in operating costs are possible from integrating three systems to exploit biogas, and the trade-offs between capital and operating costs affect the optimal system choice. Furthermore, market driven scenarios are used to analyse how to improve the economic performance.
Parkinson B, Balcombe P, Speirs JF, et al., 2019, Levelized cost of CO2 mitigation from hydrogen production routes, ENERGY & ENVIRONMENTAL SCIENCE, Vol: 12, Pages: 19-40, ISSN: 1754-5692
Santarelli M, Gandiglio M, Acri M, et al., 2019, Results from industrial size biogas-fed SOFC plant (DeMosofC project), Pages: 107-116, ISSN: 1938-6737
© The Electrochemical Society. The EU-funded DEMOSOFC project demonstrates the technical and economic feasibility of operating a 174 kWe (+ 100 kWth) SOFC system in a wastewater treatment plant, fed by biogas. The integrated biogas-SOFC plant includes three main units: 1) the biogas clean-up and compression section; 2) the SOFC power modules, and 3) the heat recovery loop. The present work is related to the results of the operation of the SOFC system. More than 7000 hours of operation have been reached onsite. Biogas raw composition is daily measured: starting form values of around 50 ppm (Sulphur equivalent) and 1.0-1.5 ppm (siloxanes equivalent) downstream the results show zero H2S and zero siloxanes. Measured SOFC efficiency from biogas to AC power has always been higher than 52-53%, with peaks of 56%. A dedicated emissions measurements campaign shows NOx < 20 mg/m3, SO2 < 8 mg/m3 and particulate lower than ambient air values (0.01 mg/m3).
Bosch J, Staffell I, Hawkes A, 2018, Temporally explicit and spatially resolved global offshore wind energy potentials, Energy, Vol: 163, Pages: 766-781, ISSN: 0360-5442
Several influential energy systems models (ESMs) indicate that renewable energy must supply a large share of the world's electricity to limit global temperature increases to 1.5 °C. To better represent the costs and other implications of such a transition, it is important that ESMs can realistically characterise the technical and economic potential of renewable energy resources. This paper presents a Geospatial Information System methodology for estimating the global offshore wind energy potential, i.e. the terawatt hour per year (TWh/yr) production potential of wind farms, assuming capacity could be built across the viable offshore area of each country. A bottom-up approach characterises the capacity factors of offshore wind farms by estimating the available wind power from high resolution global wind speed data sets. Temporal phenomena are retained by binning hourly wind speeds into 32 time slices per year considering the wind resource across several decades. For 157 countries with a viable offshore wind potential, electricity generation potential is produced in tranches according to the distance to grid connection, water depth and average annual capacity factor. These data can be used as inputs to ESMs and to assess the economically viable offshore wind energy potential, on a global or per-country basis.
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