Publications
121 results found
Schmidt O, Gambhir A, Staffell IL, et al., 2017, Future cost and performance of water electrolysis: An expert elicitation study, International Journal of Hydrogen Energy, Vol: 42, Pages: 30470-30492, ISSN: 0360-3199
The need for energy storage to balance intermittent and inflexible electricity supply with demand is driving interest in conversion of renewable electricity via electrolysis into a storable gas. But, high capital cost and uncertainty regarding future cost and performance improvements are barriers to investment in water electrolysis. Expert elicitations can support decision-making when data are sparse and their future development uncertain. Therefore, this study presents expert views on future capital cost, lifetime and efficiency for three electrolysis technologies: alkaline (AEC), proton exchange membrane (PEMEC) and solid oxide electrolysis cell (SOEC). Experts estimate that increased R&D funding can reduce capital costs by 0–24%, while production scale-up alone has an impact of 17–30%. System lifetimes may converge at around 60,000–90,000 h and efficiency improvements will be negligible. In addition to innovations on the cell-level, experts highlight improved production methods to automate manufacturing and produce higher quality components. Research into SOECs with lower electrode polarisation resistance or zero-gap AECs could undermine the projected dominance of PEMEC systems. This study thereby reduces barriers to investment in water electrolysis and shows how expert elicitations can help guide near-term investment, policy and research efforts to support the development of electrolysis for low-carbon energy systems.
Heuberger CF, Rubin ES, Staffell I, et al., 2017, Power Generation Expansion Considering Endogenous Technology Cost Learning, 27th European Symposium on Computer Aided Process Engineering, Publisher: Elsevier
We present a mixed-integer linear formulation of a long-term power generation capacityexpansion problem including endogenous learning of technology investment cost. Weconsider a national-scale power system composed of up to 2000 units of 15 differentpower supply technologies, including international interconnectors for electricity importand export, and grid-level energy storage. We reformulate the non-convex learning curvemodel into a piecewise linear representation of the cumulative investment cost as a functionof cumulative installed capacity. The model is applied to a power system representativeof Great Britain for the years 2015 to 2050. We find that the consideration oftechnology cost learning rate influences the optimal capacity expansion and has systemicimplications on the profitability of the power units.
Heuberger C, Staffell I, Shah N, et al., 2017, An MILP modeling approach to systemic energy technology valuation in the 21st Century energy system, 13th International Conference on Greenhouse Gas Control Technologies, Publisher: Elsevier, Pages: 6358-6365, ISSN: 1876-6102
New cannot be measured with old. The transformation of the electricity system from a network of fossil-based dispatchable power plants to one with large amounts of intermittent renewable power generation, flexible loads and markets, requires a concurrent development of new evaluation tools and metrics. The focus of this research is to investigate the value of power technologies in order to support decision making on optimal power system design and operation. Technology valuation metrics need to consider the complexity and interdependency of environmental and security objectives, rather than focusing on individual cost-competitiveness of technologies outside of the power system. We present the System Value as a new technology valuation metric, based on a mixed-integer linear program (MILP) formulation of a national-scale electricity system. The Electricity System Optimization model is able to capture detailed technical operation of the individual power plants as well as environmental and security requirements on the system level. We present a case study on the System Value of onshore wind power plants in comparison with Carbon Capture and Storage (CCS) equipped gas-fired power plants in a 2035 UK electricity system. Under the given emission constraints, the deployment of both technologies reduce total system cost of electricity generation. In the case of CCS-equipped power plants the reductions in total system cost are 2 to 5 times higher than for the deployment of onshore wind capacity.
Heuberger C, Staffell I, Shah N, et al., 2017, What is the Value of CCS in the Future Energy System?, 13th International Conference on Greenhouse Gas Control Technologies, Publisher: Elsevier, Pages: 7564-7572, ISSN: 1876-6102
Ambitions to produce electricity at low, zero, or negative carbon emissions are shifting the priorities and appreciation for new types of power generating technologies. Maintaining the balance between security of energy supply, carbon reduction, and electricity system cost during the transition of the electricity system is challenging. Few technology valuation tools consider the presence and interdependency of these three aspects, and nor do they appreciate the difference between firm and intermittent power generation. In this contribution, we present the results of a thought experiment and mathematical model wherein we conduct a systems analyses on the effects of gas-fired power plants equipped with Carbon Capture and Storage (CCS) technology in comparison with onshore wind power plants as main decarbonisation technologies. We find that while wind capacity integration is in its early stages of deployment an economic decarbonisation strategy, it ultimately results in an infrastructurally inefficient system with a required ratio of installed capacity to peak demand of nearly 2.. Due to the intermittent nature of wind power generation, its deployment requires a significant amount of reserve capacity in the form of firm capacity. While the integration of CCS-equipped capacity increases total system cost significantly, this strategy is able to achieve truly low-carbon power generation at 0.04 tCO2/MWh. Via a simple example, this work elucidates how the changing system requirements necessitate a paradigm shift in the value perception of power generation technologies.
Heuberger C, Rubin ES, Staffell I, et al., 2017, Power Capacity Expansion Planning Considering Endogenous Technology Cost Learning, Applied Energy, Vol: 204, Pages: 831-845, ISSN: 0306-2619
We present an power systems optimisation model for national-scale power supply capacity expansion considering endogenous technology cost reduction (ESO-XEL). The mixed-integer linear program minimises total system cost while complying with operational constraints, carbon emission targets, and ancillary service requirements. A data clustering technique and the relaxation of integer scheduling constraints is evaluated and applied to decrease the model solution time. Two cost learning curves for the different power technologies are derived: one assuming local learning effects, the other accounting for global knowledge spill-over. A piece-wise linear formulation allows the integration of the exponential learning curves into the ESO-XEL model. The model is applied to the UK power system in the time frame of 2015 to 2050. The consideration of cost learning effects moves optimal investment timings to earlier planning years and influences the competitiveness of technologies. In addition, the maximum capacity build rate parameter influences the share of power generation significantly; the possibility of rapid capacity build-up is more important for total system cost reduction by 2050 than accounting for technology cost reduction.
Grams CM, Beerli R, Pfenninger S, et al., 2017, Balancing Europe's wind power output through spatial deployment informed by weather regimes, Nature Climate Change, Vol: 7, Pages: 557-562, ISSN: 1758-678X
As wind and solar power provide a growing share of Europe's electricity1, understanding and accommodating their variability on multiple timescales remains a critical problem. On weekly timescales, variability is related to long-lasting weather conditions, called weather regimes2-5, which can cause lulls with a loss of wind power across neighbouring countries6. Here we show that weather regimes provide a meteorological explanation for multi-day fluctuations in Europe's wind power and can help guide new deployment pathways which minimise this variability. Mean generation during different regimes currently ranges from 22 GW to 44 GW and is expected to triple by 2030 with current planning strategies. However, balancing future wind capacity across regions with contrasting inter-regime behaviour - specifically deploying in the Balkans instead of the North Sea - would almost eliminate these output variations, maintain mean generation, and increase fleet-wide minimum output. Solar photovoltaics could balance low-wind regimes locally, but only by expanding current capacity tenfold. New deployment strategies based on an understanding of continent-scale wind patterns and pan-European collaboration could enable a high share of wind energy whilst minimising the negative impacts of output variability.
Bosch J, Staffell, Hawkes AD, 2017, Temporally-explicit and spatially-resolved global onshore wind energy potentials, Energy, Vol: 131, Pages: 207-217, ISSN: 0360-5442
Several influential energy systems models indicate that renewable energy must provide a significant share of the world's electricity to limit global temperature rises to below 2 °C this century. To better represent the costs and other implications of this shift, it is important that these models realistically characterise the technical and economic potential of renewable energy technologies. Towards this goal, this paper presents the first temporally-explicit Geospatial Information System (GIS) methodology to characterise the global onshore wind energy potential with respect to topographical features, land use and environmental constraints. The approach combines the hourly NASA MERRA-2 global wind speed data set with the spatially-resolved DTU Global Wind Atlas. This yields high resolution global capacity factors for onshore wind, binned into seasonal and diurnal time-slices to capture the important temporal variability. For each country, the wind power generation capacity available for various capacity factor ranges is produced, and made freely available to the community. This data set can be used to assess the economically viable wind energy potential on a global or per-country basis, and as an input to various energy systems models.
Schmidt O, Hawkes A, Gambhir A, et al., 2017, The future cost of electrical energy storage based on experience rates, Nature Energy, Vol: 2
Heuberger CF, Staffell I, Shah N, et al., 2017, The changing costs of technology and the optimal investment timing in the power sector
Vijay A, Fouquet N, Staffell IL, et al., 2017, The value of electricity and reserve services in low carbon electricity systems, Applied Energy, Vol: 201, Pages: 111-123, ISSN: 1872-9118
Decarbonising electricity systems is essential for mitigating climate change. Future systems will likely incorporate higher penetrations of intermittent renewable and inflexible nuclear power. This will significantly impact on system operations, particularly the requirements for flexibility in terms of reserves and the cost of such services. This paper estimates the interrelated changes in wholesale electricity and reserve prices using two novel methods. Firstly, it simulates the short run marginal cost of generation using a unit commitment model with post-processing to achieve realistic prices. It also introduces a new reserve price model, which mimics actual operation by first calculating the day ahead schedules and then letting deviations from schedule drive reserve prices. The UK is used as a case study to compare these models with traditional methods from the literature. The model gives good agreement with and historic prices in 2015. In a 2035 scenario, increased renewables penetration reduces mean electricity prices, and leads to price spikes due to expensive plants being brought online briefly to cope with net load variations. Contrary to views previously held in literature, a renewable intensive scenario does not lead to a higher reserve price than a fossil fuel intensive scenario. Demand response technology is shown to offer sizeable economic benefits when maintaining system balance. More broadly, this framework can be used to evaluate the economics of providing reserve services by aggregating decentralised energy resources such as heat pumps, micro-CHP and electric vehicles.
Green RJ, Staffell IL, 2017, “Prosumage” and the British electricity market, Economics of Energy and Environmental Policy, Vol: 6, Pages: 33-49, ISSN: 2160-5882
Domestic electricity consumers with PV panels have become known as “prosumers”; some of them also have energy storage and we have named the combination “prosumage”. The challenges of renewable intermittency could be offset by storing power, and many engineering studies consider the role and value of storage which is properly integrated into the ‘smart grid’. Such a system with holistic optimal control may fail to materialise for regulatory, economic, or behavioural reasons. We therefore model the impact of naïve prosumage: households which use storage only to maximise self-consumption of PV, with no consideration of the wider system. We find it is neither economicfor arbitrage nor particularly beneficial for shaving peaks and filling troughs in national net demand. The extreme case of renewable self-sufficiency, becoming completely independent of the grid, is still prohibitively expensive in Britain and Germany, and even in a country like Spain with a much better solar resource.
Staffell IL, 2017, Measuring the progress and impacts of decarbonising British electricity, Energy Policy, Vol: 102, Pages: 463-475, ISSN: 1873-6777
Britain’s ambitious carbon targets require that electricity be immediately and aggressively decarbonised, so it is reassuring to report that electricity sector emissions have fallen 46% in the three years to June 2016, their lowest since 1960. This paper analyses the factors behind this fall and the impacts they are having.The main drivers are: demand falling 1.3% per year due to efficiency gains and mild winters; gas doubling its share to 60% of fossil generation due to the carbon price floor; and the dramatic uptake of wind, solar and biomass which now supply up to 45% of demand. Accounting conventions also play their part: imported electricity and biomass would add 5% and 2% to emissions if they were included.The pace of decarbonisation is impressive, but raises both engineering and economic challenges. Falling peak demand has delayed fears of capacity shortage, but minimum net demand is instead becoming a problem. The headroom between inflexible nuclear and intermittent renewables is rapidly shrinking, with controllable output reaching a minimum of just 5.9 GW as solar output peaked at 7.1 GW. 2015 also saw Britain’s first negative power prices, the highest winter peak prices for six years, and the highest balancing costs.
Green RJ, Pudjianto D, Staffell I, et al., 2016, Market Design for Long-Distance Trade in Renewable Electricity, Energy Journal, Vol: 37, Pages: 5-22, ISSN: 0195-6574
While the 2009 EU Renewables Directive allows countries to purchase some of their obligation fromanother member state, no country has yet done so, preferring to invest locally even where load factors arevery low. If countries specialised in renewables most suited to their own endowments and expandedinternational trade, we estimate that system costs in 2030 could be reduced by 5%, or €15 billion a year,after allowing for the costs of extra transmission capacity, peaking generation and balancing operationsneeded to maintain electrical feasibility.Significant barriers must be overcome to unlock these savings. Countries that produce more renewablepower should be compensated for the extra cost through tradable certificates, while those that buy fromabroad will want to know that the power can be imported when needed. Financial Transmission Rightscould offer companies investing abroad confidence that the power can be delivered to their consumers.They would hedge short-term fluctuations in prices and operate much more flexibly than the existingsystem of physical point-to-point rights on interconnectors. Using FTRs to generate revenue fortransmission expansion could produce perverse incentives to under-invest and raise their prices, sorevenues from FTRs should instead be offset against payments under the existing ENTSO-Ecompensation scheme for transit flows. FTRs could also facilitate cross-border participation in capacitymarkets, which are likely to be needed to reduce risks for the extra peaking plants required.
Pfenninger S, DeCarolis J, Hirth L, et al., 2016, The importance of open data and software: Is energy research lagging behind?, Energy Policy, Vol: 101, Pages: 211-215, ISSN: 0301-4215
Energy policy often builds on insights gained from quantitative energy models and their underlying data. As climate change mitigation and economic concerns drive a sustained transformation of the energy sector, transparent and well-founded analyses are more important than ever. We assert that models and their associated data must be openly available to facilitate higher quality science, greater productivity through less duplicated effort, and a more effective science-policy boundary. There are also valid reasons why data and code are not open: ethical and security concerns, unwanted exposure, additional workload, and institutional or personal inertia. Overall, energy policy research ostensibly lags behind other fields in promoting more open and reproducible science. We take stock of the status quo and propose actionable steps forward for the energy research community to ensure that it can better engage with decision-makers and continues to deliver robust policy advice in a transparent and reproducible way.
Hdidouan D, Staffell IL, 2016, The impact of climate change on the levelised cost of wind energy, Renewable Energy, Vol: 101, Pages: 575-592, ISSN: 1879-0682
Society's dependence on weather systems has broadened to include electricity generation from wind turbines. Climate change is altering energy flows in the atmosphere, which will affect the economic potential of wind power. Changes to wind resources and their upstream impacts on the energy industry have received limited academic attention, despite their risks earning interest from investors.We propose a framework for assessing the impact of climate change on the cost of wind energy, going from the change in hourly wind speed distributions from radiative forcing through to energy output and levelised cost of electricity (LCOE) from wind farms. The paper outlines the proof of concept for this framework, exploring the limitations of global climate models for assessing wind resources, and a novel Weibull transfer function to characterise the climate signal.The framework is demonstrated by considering the UK's wind resources to 2100. Results are mixed: capacity factors increase in some regions and decrease in others, while the year-to-year variation generally increases. This highlights important financial and risk impacts which can be adopted into policy to enhance energy system resilience to the impacts of climate change. We call for greater emphasis to be placed on modelling wind resources in climate science.
Pfenninger S, Staffell IL, 2016, Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data, Energy, Vol: 114, Pages: 1251-1265, ISSN: 0360-5442
Solar PV is rapidly growing globally, creating difficult questions around how to efficiently integrate it into national electricity grids. Its time-varying power output is difficult to model credibly because it depends on complex and variable weather systems, leading to difficulty in understanding its potential and limitations. We demonstrate how the MERRA and MERRA-2 global meteorological reanalyses as well as the Meteosat-based CM-SAF SARAH satellite dataset can be used to produce hourly PV simulations across Europe. To validate these simulations, we gather metered time series from more than 1000 PV systems as well as national aggregate output reported by transmission network operators. We find slightly better accuracy from satellite data, but greater stability from reanalysis data. We correct for systematic bias by matching our simulations to the mean bias in modeling individual sites, then examine the long-term patterns, variability and correlation with power demand across Europe, using thirty years of simulated outputs. The results quantify how the increasing deployment of PV substantially changes net power demand and affects system adequacy and ramping requirements, with heterogeneous impacts across different European countries. The simulation code and the hourly simulations for all European countries are available freely via an interactive web platform, www.renewables.ninja.
Staffell IL, Pfenninger S, 2016, Using bias-corrected reanalysis to simulate current and future wind power output, Energy, Vol: 114, Pages: 1224-1239, ISSN: 0360-5442
Reanalysis models are rapidly gaining popularity for simulating wind power output due to their convenience and global coverage. However, they should only be relied upon once thoroughly proven. This paper reports the first international validation of reanalysis for wind energy, testing NASA's MERRA and MERRA-2 in 23 European countries. Both reanalyses suffer significant spatial bias, overestimating wind output by 50% in northwest Europe and underestimating by 30% in the Mediterranean. We derive national correction factors, and show that after calibration national hourly output can be modelled with R2 above 0.95. Our underlying data are made freely available to aid future research.We then assess Europe's wind resources with twenty-year simulations of the current and potential future fleets. Europe's current average capacity factor is 24.2%, with countries ranging from 19.5% (Germany) to 32.4% (Britain). Capacity factors are rising due to improving technology and locations; for example, Britain's wind fleet is now 23% more productive than in 2005. Based on the current planning pipeline, we estimate Europe's average capacity factor could increase by nearly a third to 31.3%. Countries with large stakes in the North Sea will see significant gains, with Britain's average capacity factor rising to 39.4% and Germany's to 29.1%.
Mechleri E, Staffell I, Lawal A, et al., 2016, Evaluation of Process Control Strategies for Normal, Flexible and Upset Operation Conditions of CO2 Post Combustion Capture Processes, 2016/07
This project focuses on performing an evaluation of process control strategies for normal and flexible operation conditions of CO2 post-combustion capture (PCC) processes. PCC is a promising, near-term technology for large-scale deployment for the decarbonisation of the power generation and other sectors. However, the integration of this technology imposes a well-known efficiency penalty on the power plant with which it is integrated. Once an optimal process design has been identified, this energy penalty can be somewhat reduced via application of an appropriate control strategy to the PCC plant. An appropriate process control strategy is also fundamental to guarantee the safety and feasibility of the process under flexible operating conditions that the power plants may be subject to.The aim of this project is to develop the process control strategy, to select appropriate control variables for a PCC process, and design efficient control structures for operation of a post-combustion capture process with minimum energy requirements for coal and natural gas power plants. The control structures are developed for power plant operating ranges of around 50% to 100% load.
Mechleri E, Rivotti P, Staffell I, et al., 2016, Evaluation of Process Control Strategies for Normal, Flexible and Upset Operation Conditions of CO2 Post Combustion Capture Processes
Mechleri E, Staffell I, Lawal A, Ramos A, Shah N, Mac Dowell Nclose, 2016, Evaluation of Process Control Strategies for Normal, Flexible and Upset Operation Conditions of CO2 Post Combustion Capture Processes, 2016/07
Staffell IL, Rustomji M, 2016, Maximising the value of electricity storage, Journal of Energy Storage, Vol: 8, Pages: 212-225, ISSN: 2352-152X
Grid-scale energy storage promises to reduce the cost of decarbonising electricity, but is not yeteconomically viable. Either costs must fall, or revenue must be extracted from more of the servicesthat storage provides the electricity system. To help understand the economic prospects forstorage, we review the sources of revenue available and the barriers faced in accessing them. Wethen demonstrate a simple algorithm that maximises the profit from storage providing arbitragewith reserve under both perfect and no foresight, which avoids complex linear programmingtechniques. This is made open source and freely available to help promote further research.We demonstrate that battery systems in the UK could triple their profits by participating in thereserve market rather than just providing arbitrage. With no foresight of future prices, 75-95% ofthe optimal profits are gained. In addition, we model a battery combined with a 322 MW wind farmto evaluate the benefits of shifting time of delivery. The revenues currently available are notsufficient to justify the current investment costs for battery technologies, and so further revenuestreams and cost reductions are required.
Mac Dowell N, Shah N, Staffell I, et al., 2016, Quantifying the Value of CCS for the Future ElectricitySystem, Energy & Environmental Science, Vol: 9, Pages: 2497-2510, ISSN: 1754-5706
Many studies have quantified the cost of Carbon Capture and Storage (CCS) power plants, butrelatively few discuss or appreciate the unique value this technology provides to the electricity system.CCS is routinely identified as a key factor in least-cost transitions to a low-carbon electricitysystem in 2050, one with significant value by providing dispatchable and low-carbon electricity.This paper investigates production, demand and stability characteristics of the current and futureelectricity system. We analyse the Carbon Intensity (CI) of electricity systems composed of unabatedthermal (coal and gas), abated (CCS), and wind power plants for different levels of windavailability with a view to quantifying the value to the system of different generation mixes. As athought experiment we consider the supply side of a UK-sized electricity system and compare theeffect of combining wind and CCS capacity with unabated thermal power plants. The resultingcapacity mix, system cost and CI are used to highlight the importance of differentiating betweenintermittent and firm low-carbon power generators. We observe that, in the absence of energystorage or demand side management, the deployment of intermittent renewable capacity cannotsignificantly displace unabated thermal power, and consequently can achieve only moderatereductions in overall CI. A system deploying sufficient wind capacity to meet peak demand canreduce CI from 0.78 tCO2/MWh, a level according to unabated fossil power generation, to 0.38tCO2/MWh. The deployment of CCS power plants displaces unabated thermal plants, and whilstit is more costly than unabated thermal plus wind, this system can achieve an overall CI of 0.1tCO2/MWh. The need to evaluate CCS using a systemic perspective in order to appreciate itsunique value is a core conclusion of this study.
Heuberger CF, Staffell I, Shah N, et al., 2016, Levelised Value of Electricity - A Systemic Approach to Technology Valuation, 26th European Symposium on Computer Aided Process Engineering - ESCAPE 26
Green RJ, Staffell, 2016, Electricity in Europe: exiting fossil fuels?, Oxford Review of Economic Policy, Vol: 32, Pages: 282-303, ISSN: 1460-2121
There are many options for generating electricity with low carbon emissions, and the electrification of heatand transport can decarbonise energy use across the economy. This places the power sector at the forefrontof any move away from fossil fuels, even though fossil-fuelled generators are more dependable and flexiblethan nuclear reactors or intermittent renewables, and vital for the second-by-second balancing of supply anddemand. Renewables tend to supplement, rather than replace, fossil capacity, although output from fossilfuelledstations will fall and some will have to retire to avoid depressing wholesale power prices. At times oflow demand and high renewable output prices can turn negative, but electricity storage, long-distanceinterconnection and flexible demand may develop to absorb any excess generation. Simulations for GreatBritain show that while coal may be eliminated from the mix within a decade, natural gas has a long-termrole in stations with or without carbon capture and storage, depending on its cost and the price of carbon.
Mac Dowell N, Staffell I, 2016, The role of flexible CCS in the UK's future energy system, International Journal of Greenhouse Gas Control, Vol: 48, Pages: 327-344, ISSN: 1750-5836
That CCS will be required to operate in a flexible and load following fashion in the diverse energy landscape of the 21st century is well recognised. However, what is less well understood is how these plants will be dispatched at the unit generator scale, and what effect this will have on the performance and behaviour of the plant at the individual unit operation level. To address this gap, we couple an investment and unit commitment energy system model with a detailed plant-level model of a super-critical coal-fired power station integrated with an amine-based post-combustion CO2 capture process. We provide insight into the likely role of coal and gas CCS plants in the UK's energy system in the 2030s, 2040s and 2050s. We then evaluate the impact that this has on the performance of an individual coal CCS plant operating in this system, and chart its evolution throughout this period. Owing to the increased frequency and duration of part-load operation, asset utilisation and average efficiency suffer, leading to a substantially increased LCOE, implying that CCS costs will need to decrease more rapidly than is currently expected. Further, as a direct consequence of the dynamic operation, the interaction of the CCS plants with the downstream CO2 transport network is characterised by highly transient behaviour, including periods during which no CO2 is injected to the transport network, implying that the transport system must therefore be designed to incorporate this variability of supply.
Fletcher T, Thring RH, Watkinson M, et al., 2016, Comparison of Fuel Consumption and Fuel Cell Degradation using an Optimised Controller, Fuel Cell Seminar and Energy Exposition, Publisher: ELECTROCHEMICAL SOC INC, Pages: 85-97, ISSN: 1938-5862
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Samsatli S, Staffell I, Samsatli NJ, 2015, Optimal design and operation of integrated wind-hydrogen-electricity networks for decarbonising the domestic transport sector in Great Britain, International Journal of Hydrogen Energy, Vol: 41, Pages: 447-475, ISSN: 1879-3487
This paper presents the optimal design and operation of integrated wind-hydrogen-electricity networks using the general mixed integer linear programming energy network model, STeMES (Samsatli and Samsatli, 2015). The network comprises: wind turbines; electrolysers, fuel cells, compressors and expanders; pressurised vessels and underground storage for hydrogen storage; hydrogen pipelines and electricity overhead/underground transmission lines; and fuelling stations and distribution pipelines.The spatial distribution and temporal variability of energy demands and wind availability were considered in detail in the model. The suitable sites for wind turbines were identified using GIS, by applying a total of 10 technical and environmental constraints (buffer distances from urban areas, rivers, roads, airports, woodland and so on), and used to determine the maximum number of new wind turbines that can be installed in each zone.The objective is the minimisation of the total cost of the network, subject to satisfying all of the demands of the domestic transport sector in Great Britain. The model simultaneously determines the optimal number, size and location of each technology, whether to transmit the energy as electricity or hydrogen, the structure of the transmission network, the hourly operation of each technology and so on. The cost of distribution was estimated from the number of fuelling stations and length of the distribution pipelines, which were determined from the demand density at the 1 km level.Results indicate that all of Britain's domestic transport demand can be met by on-shore wind through appropriately designed and operated hydrogen-electricity networks. Within the set of technologies considered, the optimal solution is: to build a hydrogen pipeline network in the south of England and Wales; to supply the Midlands and Greater London with hydrogen from the pipeline network alone; to use Humbly Grove underground storage for seasonal storage and pressurised ve
Staffell IL, Bossmann T, 2015, The Shape of Future Electricity Demand: Exploring Load Curves in 2050s Germany and Britain, Energy, Vol: 90, Pages: 1317-1333, ISSN: 0360-5442
National demand for electricity follows a regular and predictable daily pattern. This pattern is setto change due to efficiency improvements, de-industrialisation and electrification of heat andtransport. These changes are independent of renewable infeed and are not well understood:contemporary studies assume that electricity load curves will retain their current shape, scalingequally in all hours. Changes to this shape will profoundly affect the electricity industry: increasingthe requirements for flexible and peaking capacity, and reducing asset utilisation and profitability.This paper explores the evolution of load curves to 2050 in Germany and Britain: two countriesundergoing radically different energy transformations. It reviews recent developments in Europe’selectricity demand, and introduces two models for synthesising future hourly load curves: eLOADand DESSTinEE. Both models are applied to a decarbonisation scenario for 2050, and consistentlyshow peak loads increasing by about 23% points above the change in annual demand, to 103 GWin Germany and 92 GW in Britain. Sensitivities around electrification show that a million extra heatpumps or electric vehicles add up to 1.5 GW to peak demand.The structure and shape of the future load curves are analysed, and impacts on the nationalelectricity systems are drawn.
Staffell I, Brett DJL, Brandon NP, et al., 2015, Domestic Microgeneration: Renewable and distributed energy technologies, policies and economics, ISBN: 9780415810418
Microgeneration - producing energy for the home, in the home - is a substantial improvement over the current centralised and detached energy model employed the world over. Domestic Microgeneration is the first in-depth reference work for this exciting and emerging field of energy generation. It provides detailed reviews of ten state-of-the-art technologies: including solar PV and thermal, micro-CHP and heat pumps; and considers them within the wider context of the home in which they are installed and the way that they are operated. Alongside the many successes, this book highlights the common pitfalls that beset the industry. It offers best-practice guidance on how they can be avoided by considering the complex linkages between technology, user, installer and government. This interdisciplinary work draws together the social, economic, political and environmental aspects of this very diverse energy ‘genre’ into a single must-have reference for academics and students of sustainability and energy related subjects, industry professionals, policy makers and the growing number of energy-literate householders who are looking for ways to minimise their environmental footprint and their energy bills with microgeneration.
Staffell I, 2015, Zero carbon infinite COP heat from fuel cell CHP, Applied Energy, Vol: 147, Pages: 373-385, ISSN: 0306-2619
Staffell I, Green R, 2015, Is There Still Merit in the Merit Order Stack? The Impact of Dynamic Constraints on Optimal Plant Mix, IEEE Transactions on Power Systems, Vol: 31, Pages: 43-53, ISSN: 1558-0679
The merit order stack is used to tackle a wide variety of problems involving electricity dispatch. The simplification it relies on is to neglect dynamic issues such as the cost of starting stations. This leads the merit order stack to give a poor representation of the hourly pattern of prices and under-estimate the optimal level of investment in both peaking and inflexible baseload generators, and thus their run-times by up to 30%. We describe a simple method for incorporating start-up costs using a single equation derived from the load curve and station costs. The technique is demonstrated on the British electricity system in 2010 to test its performance against actual outturn, and in a 2020 scenario with increased wind capacity where it is compared to a dynamic unit-commitment scheduler. Our modification yields a better representation of electricity prices and reduces the errors in capacity investment by a factor of two.
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