Downloads / Energy modelling

Spatio-temporal analysis of PV diffusion patterns: an integrated neural networks and agent-based model

Ali Alderete Peralta, Cranfield University Photovoltaic (PV) panels offer significant potentials for contributing to the UK’s energy policy goals relating to decarbonisation of the energy system, security of supply and affordability. The substantive drop in the cost of panels since 2007, coupled with the introduction of the Feed-in Tariff (FiT) Scheme in 2010, has resulted in a rapid increase in installation of PV panels in the UK from 16.1MW in 2010 January to 12.4GW by 2017 December. Yet, spatial and temporal diffusion of PVs show significant differences across the UK. By creating reverse flows on the networks, especially at low voltage distribution networks, domestic PVs present a key challenge for network operators to manage the grid such that there is enough capacity and voltage headroom available to accommodate these flows. That’s why understanding spatio-temporal diffusion of PVs can provide valuable insights to both network operators and policy makers with a view to predict and shape their future deployment. To date, different approaches have been used for analysing PV diffusion process, including (i) spatial regression, (ii) agent-based modelling (ABM) and (iii) Read more…

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AlderetePeralta_SPATIO-TEMPORAL_ANALYSIS_OF_PV_DIFFUSION_PATTERNS.pptx 1.79 MBPeralta-Spatio-temporal-analysis-of-PV-diffusion-patterns.pdf 503.89 KB
18th
Sep
2018

Renewable energy deployment and costs in the UK: spatial analysis taking into account policy, social and environmental land use constraints

Ms Marianne  Zeyringer, UCL Energy Institute, United Kingdom Dr Dennis Konadu, UCL Energy Institute,United Kingdom Dr James Price, UCL Energy Institute, United Kingdom Dr Sheila Samsatli, Imperial College London, United Kingdom Dr Zenaida Sobral-Mourao, University of Cambridge,United Kingdom The UK is committed to reduce its GHG emissions by at least 80% in 2050 from 1990 levels (Parliament of the United Kingdom, 2008). Pacala, (2004) states that the portfolio of energy technologies to tackle the climate problem in the next 50 years is already industrially available. This assumption implies large scale deployment of nuclear energy and/or renewable energy sources (RES). The location of RES determines the total output and the timing of production. This means that the LCOE and integration costs are location dependent. There is a significant body of literature that analyses spatially the potential of RES in the UK: Gooding et al., (2013) for PV; Aylott et al., (2010), Tenerelli and Carver, (2012) and Lovett et al., (2014) for biomass energy; Drew et al., (2013) and Samsatli et al., (2016) for wind turbines. Evidence also exists in the literature that landscape is very important Read more…

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Zeyringer-Renewable-energy-deployment-and-costs-in-the-uk.pdf 1.68 MBZeyringer-Renewable-energy-deployment-in-the-UK-spatial-analysis-of-opportunities-and-threats.pdf 646.39 KB
22nd
Sep
2016

Optimal Storage Investment and Management under Uncertainty – It is costly to avoid outages!

Mr Joachim  Geske, Imperial College, London, United Kingdom Prof Richard Green, Imperial College Business School, United Kingdom Overview: Storage has the technical potential to increase efficiency of electrical systems significantly – especially in the context of integrating intermittent renewable technologies. This is achieved by shifting energy from periods of low demand to periods of high demand. Thus, the utilization of medium load power plants is increased and the utilization of peak load power plants is reduced. The full extent of efficiency gain is achieved if generation capacity is adapted to the “equilibrated” load situation – with a higher base load and lower peak load share. In this case, the installed fossil generation capacity falls below peak load level. Since the amount of energy stored is generally limited, there is a risk of outages in cases of prolonged demand peaks. This problem does not occur in perfect foresight based analyses that are still the paradigm of electrical system analysis. The subject of this analysis is to show how storage is operated optimally under renewable and load uncertainty in the system context. Methodology: We Read more…

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GeskeGreen-Optimal-Storage-Management-Under-Uncertainty1.pdf 893.03 KBGeskeGreen-Optimal-Storage-Management-Under-Uncertainty.pdf 687.17 KB
22nd
Sep
2016

How disruptive could storage be?

Dr Philipp Grunewald, EPSRC Fellow. ECI, University of Oxford Electricity storage has long been argued to be highly valuable to future low carbon energy systems. The underlying assumption is that storage is used for the common good and the benefit of the system. In this paper we will explore what could possibly go wrong. What if storage is not deployed under economically optimal conditions? What if storage operation fails to consider potential downsides for stakeholders, who have no influence over it, but might suffer costs of its impact on the system? The rapid fall in costs of both PV and storage technologies could lead to an unanticipated defection from grid supply in favour of ‘self sufficiency’. Such moves may still be economically disadvantageous for individuals and are often driven by ideological motivations. Their impact on grid utilisation and the allocation of network charges could however be dramatic. Distributed generation and storage outside the control of system operators could make load prediction and plant scheduling more difficult in future. Furthermore, storage could open opportunities for gaming and abuse within ever more regulated Read more…

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Grunewald-How-disruptive-could-storage-be.pdf 999.36 KBGrunewald-Storage-what-could-possibly-go-wrong.pdf 626.84 KB
22nd
Sep
2016

The energy ladder: A model for projecting energy demand

Dr Tashi  Erdmann, Shell Global Solutions International Mr Martin Haigh, Shell International Shell’s scenarios team develops long-term scenarios to explore the future of energy in the world. The scenarios are intended to draw attention to potential future developments affecting Shell’s business environment, such as innovation and disruptions in the energy sector, or economic and geopolitical developments. A core element of Shell’s World Energy Model for projecting energy demand in these scenarios is the so-called energy ladder, describing the relation between energy demand and economic development. This talk describes the methods used to develop these energy ladders, the way they are used for quantifying Shell’s energy scenarios, and the implications they have for long-term energy demand in the world. In its World Energy Model, Shell’s scenarios team uses separate energy ladders for all end-use sectors in  100 different countries and regions, each represented by an S-shaped curve. As a country develops, its energy demand tends to shift from industrial sectors to the services and transport sectors. The S-curve has a number of different parameters that allow it to be different across countries Read more…

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Erdmann-The-Energy-Ladder-v21.pdf 1.61 MBErdmann-The-Energy-Ladder-v2.pdf 55.86 KB
21st
Sep
2016

Rebound Effect for Energy Services: The Case of UK Households

Dr Mona  Chitnis, University of Surrey, United Kingdom Prof Steve Sorrell, London School of Economics, United Kingdom Dr Roger Fouquet, London School of Economics, United Kingdom Improved energy efficiency is widely expected to play a key role in reducing energy consumption and GHG emissions. However, the energy and emissions savings from such improvements may be less than simple calculations suggest, owing to a variety of economic mechanisms that go under the heading of rebound effects. Direct rebound effects result from increased consumption of relatively cheaper energy services: for example, an efficient boiler lowers the cost of space heating so households may choose to increase internal temperatures and/or leave the heating on for longer. Indirect rebound effects result from induced changes in consumption of other goods and services, the provision of which necessarily involves energy use and GHG emissions. For example, the money saved on space heating may be spent instead on increased lighting, or on electronic goods. Re-spending therefore may lead to additional energy use and emissions, which offset the original energy and emission savings. This study estimates the direct and indirect rebound Read more…

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Chitnis-Rebound-effect-for-energy-services-the-case-of-UK-households.pdf 608.72 KBChitnisFouquetSorrell-ReboundEffectsForHouseholdEnergyServicesInTheUK.pdf 846.64 KB
21st
Sep
2016

Shell Scenarios

Jeremy Bentham Vice President Global Environment .  Shell uses scenarios to explore the future.  These scenarios are not mechanical forecasts. They recognise that people hold beliefs and make choices that can lead down different paths. They reveal different possible futures that are plausible and challenge people’s assumptions.

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Shell-scenarios-12.pdf 1.55 MB
19th
Sep
2012

Managing Low Carbon Technology Options in the Electricity Sector: A Case Study of Guangdong Province in China

Dr Xi Liang, University of Exeter The aim of this paper is to develop a decision-analytical framework for analysing technical options available in a power generation system. Guangdong province is the largest province in China in terms of gross domestic product (GDP) and permanent residents. Being one of the most developed regions in China, it has been nominated by the central government of China to pilot low-carbon development. By applying the proposed approach, we evaluate possible technical options which Guangdong province can use to facilitate its low carbon development and attempt to generate an optimal portfolio to achieve its economic and carbon intensity reduction targets up to 2020 and 2050. The study integrates five key technical options in potential new energy generation portfolios to satisfy 200 TWh incremental annual electricity demand in Guangdong from 2016-2020, including (a) natural gas combined cycle; (b) offshore wind; (c) unabated coal; (d) coal with carbon capture and storage (CCS); (e) nuclear. To simulate a wide spectrum of uncertainties, we assume the global research, development & deployment rate, GDP growth rate, fossil-fuel price, carbon price Read more…

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Managing-Low-Carbon-Technology-Options-in-the-Electricity-Sector-A-Case-Study-of-Guangdong-Province-in-China.pdf 579.66 KB
19th
Sep
2012

Transport 2050: the potential role of hydrogen

Professor Paul Ekins, UCL Bearing in mind that transport is part of the wider energy system, scenarios and models to 2050 can help examine a range of potential developments, which all have implications for the future energy system, including the role of: hybrids; electric vehicles; energy storage; fuel cells; biofuels; infrastructure requirements; and transport behaviours. UK MARKEL runs have considered carbon targets and scenarios, carbon emissions, and sectoral analysis (carbon, demand, transport, fuel, biofuels), suggesting that fuels and technologies are very sensitive to a range of assumptions (carbon, technology costs, discount rates and timescale). Consideration of the role for accelerated technology development (ATD) of hydrogen and fuel cells, suggests a need for more public policy attention, taking account of factors such as which technologies to support and to what extent, the need to consider infrastructure requirements and the impact of behaviour and patterns of mobility. Preliminary results suggest that: transport technology choices are sensitive to assumed patterns of demand and that changes in the transport sector have significant impacts on the overall energy system; there are trade-offs between biofuels and Read more…

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Transport 2050 the potential role of hydrogen 2011.pdf 1 MB
22nd
Sep
2011

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