153 results found
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.
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
© 2019 The Authors The evaluation of capital and operational expenditures for deepwater oil and gas projects is a critical issue, given the uncertainty to estimate a project's net present value (NPV). To obtain the dependence structure between these variables, the copula methodology was adopted in order to avoid linear-dependence assumptions and inadequate estimation. This methodology was applied to Brazilian upstream deepwater projects, considering concession and production sharing contract (PSC) agreements. The findings indicate that oil price is the main impacting variable for the economic results. The best results for the concession and PSC agreements are the 500 million barrel and the 5000 million barrels cases, respectively. For 500 million barrels in concession contract the results were 93.0% of positive NPV for high oil prices (US$120/bbl) and 35% of positive NPV for low oil prices (US$68/bbl). For 5000 million barrel cases in PSC the results were 88% of positive NPV for high oil prices and 23% for low oil prices. It seems that the smaller fields take benefit compared to the bigger ones; because the windfall profit rent from concession agreements and profit oil from PSC agreements have less impact on cash flows. The remaining cases with uneconomic results impede booking oil reserves. The upstream deepwater projects are long-term developments and therefore there is a lag between oil prices and capex between the final investment decision and the first oil. On top of that, learning curves and contracts renegotiation must be taken into account for more comprehensive future analyses.
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.
Bosch J, Staffell I, Hawkes AD, 2019, Global levelised cost of electricity from offshore wind, Energy, 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, 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
© 2019 Elsevier Ltd This paper analyses the scale of asset stranding of global natural gas production and transmission infrastructure between 2015 and 2060 using Gas-GAME-Spot, an agent-based gas-sector model. It extends the existing modelling efforts by considering contract constraints in short-term gas sales and explicitly simulating trade in two types of spot markets. The study also contributes to the methodologies of stranded asset analysis by taking into account two aspects which are commonly overlooked: market fluctuation subject to the changing export capacities and the impacts of market signals on investor decision making. The results of the base scenario indicate that if gas demand follows current policy expectations, the scale of asset stranding is likely to be limited. This is attributed to supply capacity shortage of medium-sized exporters due to a slowing of their investment. Moreover, two alternative scenarios show that, when the markets face sudden reduction in demand, they leverage the flexibilities in their long-term contracts and opt more gas through spot trade. Though the issue of stranding is not significant globally in these scenarios, exporting regions with high short-run delivery costs, especially North America and Australia, have higher risks of asset stranding as they are arguably less competitive in spot sales.
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
© 2018 Elsevier Inc. 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.
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.
Budinis S, Krevor S, Mac Dowell N, et al., 2018, An assessment of CCS costs, barriers and potential, Energy Strategy Reviews, Vol: 22, Pages: 61-81, ISSN: 2211-467X
© 2018 Elsevier Ltd Global decarbonisation scenarios include Carbon Capture and Storage (CCS) as a key technology to reduce carbon dioxide (CO2) emissions from the power and industrial sectors. However, few large scale CCS plants are operating worldwide. This mismatch between expectations and reality is caused by a series of barriers which are preventing this technology from being adopted more widely. The goal of this paper is to identify and review the barriers to CCS development, with a focus on recent cost estimates, and to assess the potential of CCS to enable access to fossil fuels without causing dangerous levels of climate change. The result of the review shows that no CCS barriers are exclusively technical, with CCS cost being the most significant hurdle in the short to medium term. In the long term, CCS is found to be very cost effective when compared with other mitigation options. Cost estimates exhibit a high range, which depends on process type, separation technology, CO2transport technique and storage site. CCS potential has been quantified by comparing the amount of fossil fuels that could be used globally with and without CCS. In modelled energy system transition pathways that limit global warming to less than 2 °C, scenarios without CCS result in 26% of fossil fuel reserves being consumed by 2050, against 37% being consumed when CCS is available. However, by 2100, the scenarios without CCS have only consumed slightly more fossil fuel reserves (33%), whereas scenarios with CCS available end up consuming 65% of reserves. It was also shown that the residual emissions from CCS facilities is the key factor limiting long term uptake, rather than cost. Overall, the results show that worldwide CCS adoption will be critical if fossil fuel reserves are to continue to be substantively accessed whilst still meeting climate targets.
Sachs J, Massari C, Hawkes A, et al., 2018, Distributed Optimization for a Cost Efficient Operation of a Network of Island Energy Systems, Pages: 46-53
© 2018 IEEE. The accumulation of energy systems, comprising of diesel generators, storage devices and renewable sources, to a large interacting network is a promising approach to achieve a low cost energy supply in remote areas. The main potential for cost reduction is through optimized operation of the network. Power management of these networks can be challenging due to sudden variations in load demand and high fluctuations in power supplied by renewables. A distributed optimization approach for efficient operation guaranteeing improved robustness towards faults, reduced complexity, and an uninterrupted energy supply is presented. The approach includes detailed component modeling to assure the satisfaction of all operation constraints during the system operation. An extended Alternating Direction Method of Multipliers approach is used for the distributed optimization separating the mixed integer linear optimization problem into sub-problems. Case studies are carried out by using real-world data to illustrate the performance and economic benefits of the proposed method in comparison to the centralized approach. Results show the effectiveness of the optimization strategy in terms of computational feasibility, accuracy, and increased robustness towards failures of individual systems and its suitability for the integration into a distributed model predictive control.
Oluleye OO, Allison J, Hawker G, et al., 2018, A two-step optimization model for quantifying the flexibility potential of power-to-heat systems in dwellings, Applied Energy, Vol: 228, Pages: 215-228, ISSN: 0306-2619
Coupling the electricity and heat sectors is receiving interest as a potential source of flexibility to help absorb surplus renewable electricity. The flexibility afforded by power-to-heat systems in dwellings has yet to be quantified in terms of time, energy and costs, and especially in cases where homeowners are heterogeneous prosumers. Flexibility quantification whilst accounting for prosumer heterogeneity is non-trivial. Therefore in this work a novel two-step optimization framework is proposed to quantify the potential of prosumers to absorb surplus renewable electricity through the integration of air source heat pumps and thermal energy storage. The first step is formulated as a multi-period mixed integer linear programming problem to determine the optimal energy system, and the quantity of surplus electricity absorbed. The second step is formulated as a linear programming problem to determine the price a prosumer will accept for absorbing surplus electricity, and thus the number of active prosumers in the market.A case study of 445 prosumers is presented to illustrate the approach. Results show that the number of active prosumers is affected by the quantity of absorbed electricity, frequency of requests, the price offered by aggregators and how prosumers determine the acceptable value of flexibility provided. This study is a step towards reducing the need for renewable curtailment and increasing pricing transparency in relation to demand-side response.
Balcombe P, Speirs JF, Brandon NP, et al., 2018, Methane emissions: choosing the right climate metric and time horizon, Environmental Science: Processes and Impacts, Vol: 20, Pages: 1323-1339, ISSN: 2050-7895
Methane is a more potent greenhouse gas (GHG) than CO2, but it has a shorter atmospheric lifespan, thus its relative climate impact reduces significantly over time. Different GHGs are often conflated into a single metric to compare technologies and supply chains, such as the global warming potential (GWP). However, the use of GWP is criticised, regarding: (1) the need to select a timeframe; (2) its physical basis on radiative forcing; and (3) the fact that it measures the average forcing of a pulse over time rather than a sustained emission at a specific end-point in time. Many alternative metrics have been proposed which tackle different aspects of these limitations and this paper assesses them by their key attributes and limitations, with respect to methane emissions. A case study application of various metrics is produced and recommendations are made for the use of climate metrics for different categories of applications. Across metrics, CO2 equivalences for methane range from 4–199 gCO2eq./gCH4, although most estimates fall between 20 and 80 gCO2eq./gCH4. Therefore the selection of metric and time horizon for technology evaluations is likely to change the rank order of preference, as demonstrated herein with the use of natural gas as a shipping fuel versus alternatives. It is not advisable or conservative to use only a short time horizon, e.g. 20 years, which disregards the long-term impacts of CO2 emissions and is thus detrimental to achieving eventual climate stabilisation. Recommendations are made for the use of metrics in 3 categories of applications. Short-term emissions estimates of facilities or regions should be transparent and use a single metric and include the separated contribution from each GHG. Multi-year technology assessments should use both short and long term static metrics (e.g. GWP) to test robustness of results. Longer term energy assessments or decarbonisation pathways must use both short and long-term metrics and where this has a lar
Guo Y, Hawkes A, 2018, Simulating the game-theoretic market equilibrium and contract-driven investment in global gas trade using an agent-based method, Energy, Vol: 160, Pages: 820-834, ISSN: 0360-5442
To understand how the alternative US liquefied natural gas exportation strategies may affect future global gas market dynamics, a global-scale model Gas-GAME is developed using an agent-based framework. This is the first model having explicit contract-driven capacity expansion process, allowing investors to hold imperfect foresights, and simulating market power in global gas trade. With these features, Gas-GAME can analyse market development subject to the incentives and perspectives of each market player. The model simulates short-term game-theoretical market equilibrium with Mixed Complementarity Problem approach. For long-term investment decisions, bilateral contracting processes considering both import requests and export profitability are modelled. A base case is presented and validated, followed by a case study considering US export strategy. When the US stays conservative in export expansion, gas supply tightness occurs, leading to continuing European dependence on Russian gas, and a shift to pipeline-based import in the Chinese market. Conversely, when the US invests aggressively, Middle East and Australia both see significant revenue losses, and Western Europe constructs more regasification plants to provide alternatives to Russian supply. Gas-GAME captures the essential dynamics between market power, short-term prices and long-term contracts to provide a more nuanced view of global gas market.
Crow DJG, Anderson K, Hawkes AD, et al., 2018, Impact of drilling costs on the US gas industry: prospects for automation, Energies, Vol: 11, ISSN: 1996-1073
Recent low gas prices have greatly increased pressure on drilling companies to reduce costs and increase efficiency. Field trials have shown that implementing automation can dramatically reduce drilling costs by reducing the time required to drill wells. This study uses the DYNamic upstreAm gAs MOdel (DYNAAMO), a new techno-economic, bottom-up model of natural gas supply, to quantitatively assess the economic impact of lower drilling costs on the US upstream gas industry. A sensitivity analysis of three key economic indicators is presented, with results quoted for the most common field types currently producing, including unconventional and offshore gas. While all operating environments show increased profitability from drilling automation, it is found that conventional onshore reserves can benefit to the greatest extent. For large gas fields, a 50% reduction in drilling costs is found to reduce initial project breakevens by up to 17 million USD per billion cubic metres (MUSD/BCM) and mid-plateau breakevens by up to 8 MUSD/BCM. In this same scenario, additional volumes of around 160 BCM of unconventional gas are shown to become commercial due to both the lower costs of additional production wells in mature fields and the viability of developing new resources held in smaller fields. The capital efficiency of onshore projects increases by 50%-100%, with initial project net present value (NPV) gains of up to 32%.
Miu LM, Wisniewska N, Mazur C, et al., 2018, A simple assessment of housing retrofit policies for the UK: what should succeed the energy company obligation?, Energies, Vol: 11, ISSN: 1996-1073
Despite the need for large-scale retrofit of UK housing to meet emissions reduction targets, progress to date has been slow and domestic energy efficiency policies have struggled to accelerate housing retrofit processes. There is a need for housing retrofit policies that overcome key barriers within the retrofit sector while maintaining economic viability for customers, funding organizations, and effectively addressing UK emission reductions and fuel poverty targets. In this study, we use a simple assessment framework to assess three policies (the Variable Council Tax, the Variable Stamp Duty Land Tax, and Green Mortgage) proposed to replace the UK’s current major domestic retrofit programme known as the Energy Company Obligation (ECO). We show that the Variable Council Tax and Green Mortgage proposals have the greatest potential for overcoming the main barriers to retrofit policies while maintaining economic viability and contributing to high-level UK targets. We also show that, while none of the assessed schemes are capable of overcoming all retrofit barriers on their own, a mix of all three policies could address most barriers and provide key benefits such as wide coverage of property markets, operation on existing financial infrastructures, and application of a “carrot-and-stick” approach to incentivize retrofit. Lastly, we indicate that the specific support and protection of fuel-poor households cannot be achieved by a mix of these policies and a complementary scheme focused on fuel-poor households is required.
Balcombe P, Speirs J, Johnson E, et al., 2018, The carbon credentials of hydrogen gas networks and supply chains, Renewable and Sustainable Energy Reviews, Vol: 91, Pages: 1077-1088, ISSN: 1364-0321
Projections of decarbonisation pathways have typically involved reducing dependence on natural gas grids via greater electrification of heat using heat pumps or even electric heaters. However, many technical, economic and consumer barriers to electrification of heat persist. The gas network holds value in relation to flexibility of operation, requiring simpler control and enabling less expensive storage. There may be value in retaining and repurposing gas infrastructure where there are feasible routes to decarbonisation. This study quantifies and analyses the decarbonisation potential associated with the conversion of gas grids to deliver hydrogen, focusing on supply chains. Routes to produce hydrogen for gas grids are categorised as: reforming natural gas with (or without) carbon capture and storage (CCS); gasification of coal with (or without) CCS; gasification of biomass with (or without) CCS; electrolysis using low carbon electricity. The overall range of greenhouse gas emissions across routes is extremely large, from − 371 to 642 gCO 2 eq/kW h H2 . Therefore, when including supply chain emissions, hydrogen can have a range of carbon intensities and cannot be assumed to be low carbon. Emissions estimates for natural gas reforming with CCS lie in the range of 23–150 g/kW h H2 , with CCS typically reducing CO 2 emissions by 75%. Hydrogen from electrolysis ranges from 24 to 178 gCO 2 eq/kW h H2 for renewable electricity sources, where wind electricity results in the lowest CO 2 emissions. Solar PV electricity typically exhibits higher emissions and varies significantly by geographical region. The emissions from upstream supply chains is a major contributor to total emissions and varies considerably across different routes to hydrogen. Biomass gasification is characterised by very large negative emissions in the supply chain and very large positive emissions in the gasification process. Therefore, improvements in total emissions are large if even small i
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