This page has only limited features, please log in for full access.

Unclaimed
Derek Bunn
Department of Management Science and Operations, London Business School, Regent's Park, London NW1 4SA, UK

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 23 August 2021 in Applied Energy
Reads 0
Downloads 0

With the rapid adoption of Electric Vehicles (EVs), numerous lithium-ion batteries (LIBs) are reaching retirement age, leading to increasing concerns about the sustainable industrial development. To promote the recycling of LIBs, a reward-penalty mechanism is proposed in this work and analyzed by using the Stackelberg game theory. Six collection modes are considered and compared, including the collection activities undertaken by different stakeholders, i.e. the EV manufacturer, the EV retailer, the third-party enterprise, and the pairwise partners of them. The results show that: (i) a partnership between the manufacturer and retailer can achieve the highest actual collection rate and the total welfare; (ii) although increasing the reward-penalty intensity can contribute to higher collection rates, the total welfare can still fall, due to the negative influences of policy expenditure and implementation cost; (iii) the impact of raising the collection rate target is similar to the reward-penalty intensity, which can first promote and then restrain the growth of total welfare, and the drop is mainly due to the negative influences of corporate profits and implementation cost.

ACS Style

Qi Zhang; Yanyan Tang; Derek Bunn; Hailong Li; Yaoming Li. Comparative evaluation and policy analysis for recycling retired EV batteries with different collection modes. Applied Energy 2021, 303, 117614 .

AMA Style

Qi Zhang, Yanyan Tang, Derek Bunn, Hailong Li, Yaoming Li. Comparative evaluation and policy analysis for recycling retired EV batteries with different collection modes. Applied Energy. 2021; 303 ():117614.

Chicago/Turabian Style

Qi Zhang; Yanyan Tang; Derek Bunn; Hailong Li; Yaoming Li. 2021. "Comparative evaluation and policy analysis for recycling retired EV batteries with different collection modes." Applied Energy 303, no. : 117614.

Journal article
Published: 12 August 2021 in Energies
Reads 0
Downloads 0

An important revenue stream for electric battery operators is often arbitraging the hourly price spreads in the day-ahead auction. The optimal approach to this is challenging if risk is a consideration as this requires the estimation of density functions. Since the hourly prices are not normal and not independent, creating spread densities from the difference of separately estimated price densities is generally intractable. Thus, forecasts of all intraday hourly spreads were directly specified as an upper triangular matrix containing densities. The model was a flexible four-parameter distribution used to produce dynamic parameter estimates conditional upon exogenous factors, most importantly wind, solar and the day-ahead demand forecasts. These forecasts supported the optimal daily scheduling of a storage facility, operating on single and multiple cycles per day. The optimization is innovative in its use of spread trades rather than hourly prices, which this paper argues, is more attractive in reducing risk. In contrast to the conventional approach of trading the daily peak and trough, multiple trades are found to be profitable and opportunistic depending upon the weather forecasts.

ACS Style

Ekaterina Abramova; Derek Bunn. Optimal Daily Trading of Battery Operations Using Arbitrage Spreads. Energies 2021, 14, 4931 .

AMA Style

Ekaterina Abramova, Derek Bunn. Optimal Daily Trading of Battery Operations Using Arbitrage Spreads. Energies. 2021; 14 (16):4931.

Chicago/Turabian Style

Ekaterina Abramova; Derek Bunn. 2021. "Optimal Daily Trading of Battery Operations Using Arbitrage Spreads." Energies 14, no. 16: 4931.

Journal article
Published: 01 August 2021 in Management Science
Reads 0
Downloads 0

Increasing variable renewable power generation (e.g., wind) is expected to reduce wholesale electricity prices by virtue of its low marginal production cost. This merit-order effect of renewables displacing incumbent conventional (e.g., gas) generation forms the theoretical underpinning for investment decisions and policy in the power industry. This paper uses a game-theoretic market model to investigate how intermittently available wind generation affects electricity prices in the presence of forward markets, which are widely used by power companies to hedge against revenue variability ahead of near-real-time spot trading. We find that in addition to the established merit-order effect, renewable generation affects power prices through forward-market hedging. This forward effect reinforces the merit-order effect in reducing prices for moderate amounts of wind generation capacity but mitigates or even reverses it for higher capacities. For moderate wind capacity, uncertainty over its output increases hedging, and these higher forward sales lead to lower prices. For higher capacities, however, wind variability conversely causes power producers to behave less aggressively in forward trading for fear of unfavorable spot-market positions. The lower sales counteract the merit-order effect, and prices may then paradoxically increase with wind capacity despite its lower production cost. We confirm the potential for such reversals in a numerical study, suggesting new empirical questions while providing potential explanations for previously contradictory observed effects of market fundamentals. We conclude that considering the conventional merit-order effect alone is insufficient for evaluating the price impacts of variable renewable generation in the presence of forward markets. This paper was accepted by Vishal Gaur, operations management.

ACS Style

Heikki Peura; Derek W. Bunn. Renewable Power and Electricity Prices: The Impact of Forward Markets. Management Science 2021, 67, 4772 -4788.

AMA Style

Heikki Peura, Derek W. Bunn. Renewable Power and Electricity Prices: The Impact of Forward Markets. Management Science. 2021; 67 (8):4772-4788.

Chicago/Turabian Style

Heikki Peura; Derek W. Bunn. 2021. "Renewable Power and Electricity Prices: The Impact of Forward Markets." Management Science 67, no. 8: 4772-4788.

Special issue
Published: 29 June 2021 in Production and Operations Management
Reads 0
Downloads 0

This is an invited commentary on the keynote paper by Sheridan Titman concerning the drivers of risk transmission across supply chains that have fundamental commodity inputs. The focus is upon how demand and supply elasticities at the upstream, midstream and downstream stages influence the price volatilities, their mutual volatility spillovers and, as a consequence, their hedging challenges. Further observations are offered in this note regarding the endogeneity of price impacts, structural changes and the need for model switching. The interaction with financial markets through the so-called financialization of commodities can cause commodity prices, eg oil, to have less of a mean-reverting and more of a random walk characteristic. Finally, strategic hedging through corporate vertical integration needs to be considered as a further complication in the way that the elasticities transmit the price risks.

ACS Style

Derek W Bunn. Observations on Risk Transmission Across Supply Chains. Production and Operations Management 2021, 1 .

AMA Style

Derek W Bunn. Observations on Risk Transmission Across Supply Chains. Production and Operations Management. 2021; ():1.

Chicago/Turabian Style

Derek W Bunn. 2021. "Observations on Risk Transmission Across Supply Chains." Production and Operations Management , no. : 1.

Journal article
Published: 23 March 2021 in IEEE Transactions on Power Systems
Reads 0
Downloads 0

Regulatory support for transmission investment by private investors follows a complex process of dialogue, information sharing, commitments, and incentives. Whilst this process has attracted substantial research, the formulation of efficient solutions still remains an open question and this has become more complex with the emergence of new intermittent and battery-storage resources. We propose an optimal incentive solution in which the private transmission company earns congestion rents and an incentive fee, set by agreement with the regulator. This fee is set in the context of assessing the impact of current and future generation resources (conventional, intermittent, and batteries) on the congestion rents. The welfare-optimizing solution follows from a mixed integer, nonlinear, bilevel optimization problem, which is computationally challenging. We re-cast the problem for tractability and devise a disjunctive-based decomposition algorithm. Its performance has been successfully demonstrated on two standard IEEE case studies.

ACS Style

Dina Khastieva; Saeed Mohammadi; Mohammad Reza Hesamzadeh; Derek W Bunn. Optimal Transmission Investment With Regulated Incentives Based Upon Forward Considerations of Firm and Intermittent Resources With Batteries. IEEE Transactions on Power Systems 2021, 36, 4420 -4434.

AMA Style

Dina Khastieva, Saeed Mohammadi, Mohammad Reza Hesamzadeh, Derek W Bunn. Optimal Transmission Investment With Regulated Incentives Based Upon Forward Considerations of Firm and Intermittent Resources With Batteries. IEEE Transactions on Power Systems. 2021; 36 (5):4420-4434.

Chicago/Turabian Style

Dina Khastieva; Saeed Mohammadi; Mohammad Reza Hesamzadeh; Derek W Bunn. 2021. "Optimal Transmission Investment With Regulated Incentives Based Upon Forward Considerations of Firm and Intermittent Resources With Batteries." IEEE Transactions on Power Systems 36, no. 5: 4420-4434.

Journal article
Published: 19 October 2020 in Energies
Reads 0
Downloads 0

This paper develops a new approach to short-term electricity forecasting by focusing upon the dynamic specification of an appropriate calibration dataset prior to model specification. It challenges the conventional forecasting principles which argue that adaptive methods should place most emphasis upon recent data and that regime-switching should likewise model transitions from the latest regime. The approach in this paper recognises that the most relevant dataset in the episodic, recurrent nature of electricity dynamics may not be the most recent. This methodology provides a dynamic calibration dataset approach that is based on cluster analysis applied to fundamental market regime indicators, as well as structural time series breakpoint analyses. Forecasting is based upon applying a hybrid fundamental optimisation model with a neural network to the appropriate calibration data. The results outperform other benchmark models in backtesting on data from the Iberian electricity market of 2017, which presents a considerable number of market structural breaks and evolving market price drivers.

ACS Style

Rodrigo A. De Marcos; Derek W. Bunn; Antonio Bello; Javier Reneses. Short-Term Electricity Price Forecasting with Recurrent Regimes and Structural Breaks. Energies 2020, 13, 5452 .

AMA Style

Rodrigo A. De Marcos, Derek W. Bunn, Antonio Bello, Javier Reneses. Short-Term Electricity Price Forecasting with Recurrent Regimes and Structural Breaks. Energies. 2020; 13 (20):5452.

Chicago/Turabian Style

Rodrigo A. De Marcos; Derek W. Bunn; Antonio Bello; Javier Reneses. 2020. "Short-Term Electricity Price Forecasting with Recurrent Regimes and Structural Breaks." Energies 13, no. 20: 5452.

Chapter
Published: 11 September 2020 in The Interrelationship Between Financial and Energy Markets
Reads 0
Downloads 0

Electricity networks are now more complex to manage as a consequence of the rapid development of renewable and distributed resources, as well as the emerging electrification of heat and transport. The ageing distribution networks are becoming less fit-for-purpose, triggering a need for the stakeholders involved to consider how to upgrade and adapt to the new market requirements. Smart technologies can provide more efficient asset utilisation and smart markets can facilitate aggregated small-scale participants to sell various flexibility services to the distribution network operators. Thus, existing planning assumptions are being challenged as conventional asset investment may not be the least cost solution, and may even be the most risky. This chapter reviews the approaches that distribution system operators (DSOs) can adopt to enable a greater volume of demand, generation, and storage to be connected in a smarter and more active setting, thereby meeting local network investment requirements in a more efficient way.

ACS Style

Derek W. Bunn; Jesus Nieto-Martin. The Emergence of Smart and Flexible Distribution Systems. The Interrelationship Between Financial and Energy Markets 2020, 491 -519.

AMA Style

Derek W. Bunn, Jesus Nieto-Martin. The Emergence of Smart and Flexible Distribution Systems. The Interrelationship Between Financial and Energy Markets. 2020; ():491-519.

Chicago/Turabian Style

Derek W. Bunn; Jesus Nieto-Martin. 2020. "The Emergence of Smart and Flexible Distribution Systems." The Interrelationship Between Financial and Energy Markets , no. : 491-519.

Journal article
Published: 11 August 2020 in IEEE Transactions on Power Systems
Reads 0
Downloads 0

This research analyses the non-linear and complex effects of drivers of system imbalance prices in the GB electricity market. Unlike day-ahead prices, the balancing settlement prices are comparatively under-researched, yet their importance is growing with greater market risks. The fundamental drivers of these prices are analysed over 2016-2019. The result of a non-linear modelling approach reveals that system imbalance price exhibits a regime-switching behaviour, driven by weather and demand forecast errors, as well as other system effects. Surprisingly, balancing prices are predictable out of sample and a regime switching specification is more accurate than a linear model for prediction.

ACS Style

Derek W. Bunn; John N. Inekwe; David MacGeehan. Analysis of the Fundamental Predictability of Prices in the British Balancing Market. IEEE Transactions on Power Systems 2020, 36, 1309 -1316.

AMA Style

Derek W. Bunn, John N. Inekwe, David MacGeehan. Analysis of the Fundamental Predictability of Prices in the British Balancing Market. IEEE Transactions on Power Systems. 2020; 36 (2):1309-1316.

Chicago/Turabian Style

Derek W. Bunn; John N. Inekwe; David MacGeehan. 2020. "Analysis of the Fundamental Predictability of Prices in the British Balancing Market." IEEE Transactions on Power Systems 36, no. 2: 1309-1316.

Journal article
Published: 05 August 2020 in IEEE Transactions on Power Systems
Reads 0
Downloads 0

In this paper, three single-stage stochastic programs are proposed and compared for optimal dispatch by a System Operator (SO) into balancing markets (BM). The motivation for the models is to represent the requirement to undertake system balancing with increasing amounts of intermittent renewable generation. The proposed optimization models are reformulated as tractable Mixed Integer Linear Programs (MILPs). The proposed MILP models consider both fuel cost and intermittency cost of the generators while activating the up- or down-regulation bids. The three proposed models are based on the main approaches seen in practice: dual-imbalance pricing, single imbalance pricing and single imbalance pricing with spot reversion. A scenario generation algorithm based on predictive conditional dynamic density distributions is also proposed. We perform a comparative analysis of these three proposed models in terms of how they help the SO to optimize their balancing market actions considering intermittent-renewable generators. The single imbalance pricing is found to be the most market efficient.

ACS Style

Priyanka Shinde; Mohammad Reza Hesamzadeh; Paresh Date; Derek W. Bunn. Optimal Dispatch in a Balancing Market With Intermittent Renewable Generation. IEEE Transactions on Power Systems 2020, 36, 865 -878.

AMA Style

Priyanka Shinde, Mohammad Reza Hesamzadeh, Paresh Date, Derek W. Bunn. Optimal Dispatch in a Balancing Market With Intermittent Renewable Generation. IEEE Transactions on Power Systems. 2020; 36 (2):865-878.

Chicago/Turabian Style

Priyanka Shinde; Mohammad Reza Hesamzadeh; Paresh Date; Derek W. Bunn. 2020. "Optimal Dispatch in a Balancing Market With Intermittent Renewable Generation." IEEE Transactions on Power Systems 36, no. 2: 865-878.

Journal article
Published: 05 February 2020 in Energies
Reads 0
Downloads 0

Intra-day price spreads are of interest to electricity traders, storage and electric vehicle operators. This paper formulates dynamic density functions, based upon skewed-t and similar representations, to model and forecast the German electricity price spreads between different hours of the day, as revealed in the day-ahead auctions. The four specifications of the density functions are dynamic and conditional upon exogenous drivers, thereby permitting the location, scale and shape parameters of the densities to respond hourly to such factors as weather and demand forecasts. The best fitting and forecasting specifications for each spread are selected based on the Pinball Loss function, following the closed-form analytical solutions of the cumulative distribution functions.

ACS Style

Ekaterina Abramova; Derek Bunn. Forecasting the Intra-Day Spread Densities of Electricity Prices. Energies 2020, 13, 687 .

AMA Style

Ekaterina Abramova, Derek Bunn. Forecasting the Intra-Day Spread Densities of Electricity Prices. Energies. 2020; 13 (3):687.

Chicago/Turabian Style

Ekaterina Abramova; Derek Bunn. 2020. "Forecasting the Intra-Day Spread Densities of Electricity Prices." Energies 13, no. 3: 687.

Journal article
Published: 23 March 2019 in Energy Policy
Reads 0
Downloads 0

Despite the emergence of the green bond market, the Energy Service Company (ESCO) model and green investment banks, the opportunities which the world's capital markets present to increase the pool of potential investors and reduce project financing costs for renewable, energy efficient and low carbon assets remain under-exploited. This has been a persistent concern for policy-makers. We review the appeal of this sector to different classes of investor and assess the successes and failures of several innovative products including securitisations, yieldcos, green bonds, green investment banks and crowdfunding. We analyse the experiences with these products and suggest that policy needs to recognise how fiscal initiatives can leverage their inherent appeal.

ACS Style

Celine McInerney; Derek W. Bunn. Expansion of the investor base for the energy transition. Energy Policy 2019, 129, 1240 -1244.

AMA Style

Celine McInerney, Derek W. Bunn. Expansion of the investor base for the energy transition. Energy Policy. 2019; 129 ():1240-1244.

Chicago/Turabian Style

Celine McInerney; Derek W. Bunn. 2019. "Expansion of the investor base for the energy transition." Energy Policy 129, no. : 1240-1244.

Journal article
Published: 19 November 2018 in IEEE Transactions on Power Systems
Reads 0
Downloads 0

The rise of distributed energy resources (DERs) can enhance the efficiency of system operations by providing flexibility services to the different agents involved, but they also pose a major resource allocation problem. This study considers three different agents procuring DER services: distribution system operators (DSOs) for local congestion management, transmission system operators (TSOs) for system-wide reserve deployment, and retailers for hedging against network usage tariffs based upon peak-load pricing. A variety of market mechanisms are identified to co-ordinate these needs, and three schemes are developed in detail. These are separate markets for each agent, co-ordinated Shapley value allocations for TSO and DSO, and a co-ordinated mechanism including retailers. These designs are evaluated on a realistic distribution network in Britain for two operational days. The results show a more efficient dispatch from the TSO-DSO co-ordinated procurement over independent sequential procurements. However, the inclusion of retailers in the joint dispatch is surprisingly less attractive due to the lack of improvement in social welfare and the undesirable impacts on the DSO.

ACS Style

Alejandro Vicente-Pastor; Jesus Nieto-Martin; Derek W. Bunn; Arnaud Laur. Evaluation of Flexibility Markets for Retailer–DSO–TSO Coordination. IEEE Transactions on Power Systems 2018, 34, 2003 -2012.

AMA Style

Alejandro Vicente-Pastor, Jesus Nieto-Martin, Derek W. Bunn, Arnaud Laur. Evaluation of Flexibility Markets for Retailer–DSO–TSO Coordination. IEEE Transactions on Power Systems. 2018; 34 (3):2003-2012.

Chicago/Turabian Style

Alejandro Vicente-Pastor; Jesus Nieto-Martin; Derek W. Bunn; Arnaud Laur. 2018. "Evaluation of Flexibility Markets for Retailer–DSO–TSO Coordination." IEEE Transactions on Power Systems 34, no. 3: 2003-2012.

Journal article
Published: 05 October 2018 in Energies
Reads 0
Downloads 0

This paper applies a multi-factor, stochastic latent moment model to predicting the imbalance volumes in the Austrian zone of the German/Austrian electricity market. This provides a density forecast whose shape is determined by the flexible skew-t distribution, the first three moments of which are estimated as linear functions of lagged imbalance and forecast errors for load, wind and solar production. The evaluation of this density predictor is compared to an expected value obtained from OLS regression model, using the same regressors, through an out-of-sample backtest of a flexible generator seeking to optimize its imbalance positions on the intraday market. This research contributes to forecasting methodology and imbalance prediction, and most significantly it provides a case study in the evaluation of density forecasts through decision-making performance. The main finding is that the use of the density forecasts substantially increased trading profitability and reduced risk compared to the more conventional use of mean value regressions.

ACS Style

Derek W. Bunn; Angelica Gianfreda; Stefan Kermer. A Trading-Based Evaluation of Density Forecasts in a Real-Time Electricity Market. Energies 2018, 11, 2658 .

AMA Style

Derek W. Bunn, Angelica Gianfreda, Stefan Kermer. A Trading-Based Evaluation of Density Forecasts in a Real-Time Electricity Market. Energies. 2018; 11 (10):2658.

Chicago/Turabian Style

Derek W. Bunn; Angelica Gianfreda; Stefan Kermer. 2018. "A Trading-Based Evaluation of Density Forecasts in a Real-Time Electricity Market." Energies 11, no. 10: 2658.

Journal article
Published: 01 October 2018 in Operations Research
Reads 0
Downloads 0

The wide range of models needed to support the various short-term operations for electricity generation demonstrates the importance of accurate specifications for the uncertainty in market prices. This is becoming increasingly challenging, since hourly price densities for electricity exhibit a variety of shapes, with their characteristic features changing substantially within the day and evolving over time. Furthermore, the influx of renewable power, wind, and solar, in particular, has made these density shapes very weather dependent. We develop a general four-parameter stochastic model for hourly prices, in which the four moments of the density function are dynamically estimated as latent state variables and, furthermore, modelled as functions of several plausible exogenous drivers. This provides a transparent and credible model that is sufficiently flexible to capture the shape-shifting effects, particularly with respect to the wind and solar output variations causing dynamic switches in the upside and downside risks. Extensive testing on German wholesale price data, benchmarked against quantile regression and other models in out-of-sample backtesting, validated the approach and its analytical appeal.The e-companion is available at https://doi.org/10.1287/opre.2018.1733.

ACS Style

Angelica Gianfreda; Derek Bunn. A Stochastic Latent Moment Model for Electricity Price Formation. Operations Research 2018, 66, 1189 -1203.

AMA Style

Angelica Gianfreda, Derek Bunn. A Stochastic Latent Moment Model for Electricity Price Formation. Operations Research. 2018; 66 (5):1189-1203.

Chicago/Turabian Style

Angelica Gianfreda; Derek Bunn. 2018. "A Stochastic Latent Moment Model for Electricity Price Formation." Operations Research 66, no. 5: 1189-1203.

Journal article
Published: 17 November 2016 in Energies
Reads 0
Downloads 0

This paper proposes a new approach to hybrid forecasting methodology, characterized as the statistical recalibration of forecasts from fundamental market price formation models. Such hybrid methods based upon fundamentals are particularly appropriate to medium term forecasting and in this paper the application is to month-ahead, hourly prediction of electricity wholesale prices in Spain. The recalibration methodology is innovative in seeking to perform the recalibration into parametrically defined density functions. The density estimation method selects from a wide diversity of general four-parameter distributions to fit hourly spot prices, in which the first four moments are dynamically estimated as latent functions of the outputs from the fundamental model and several other plausible exogenous drivers. The proposed approach demonstrated its effectiveness against benchmark methods across the full range of percentiles of the price distribution and performed particularly well in the tails.

ACS Style

Antonio Bello; Derek Bunn; Javier Reneses; Antonio Muñoz. Parametric Density Recalibration of a Fundamental Market Model to Forecast Electricity Prices. Energies 2016, 9, 959 .

AMA Style

Antonio Bello, Derek Bunn, Javier Reneses, Antonio Muñoz. Parametric Density Recalibration of a Fundamental Market Model to Forecast Electricity Prices. Energies. 2016; 9 (11):959.

Chicago/Turabian Style

Antonio Bello; Derek Bunn; Javier Reneses; Antonio Muñoz. 2016. "Parametric Density Recalibration of a Fundamental Market Model to Forecast Electricity Prices." Energies 9, no. 11: 959.

Journal article
Published: 01 August 2016 in European Journal of Operational Research
Reads 0
Downloads 0

Highlights•Formal analysis of why companies may trade production facilities•Computational learning algorithm for trading production facilities•Trading production facilities increases market concentration•The degree of foresight influences the choice of equilibrium•Realistic application to the GB electricity market evolution AbstractIn this paper we analyze a particular aspect of capacity planning that is concerned with the active trading of production facilities. For a homogenous product market we provide a theoretical rationale for the valuation and trading of these assets based on a metric of strategic slack. We show that trading production assets with non-additive portfolio profitability involves complex coordination with multiple equilibria and that these equilibria depend on the foresight in the planning horizon. Using the concept of strategic slack we have analyzed the dynamics of market structure, the impact of asset trading on the level of production of the industry, and to derive boundaries on the value of the traded assets. Moreover, through computational learning, the formulation is applied to a large oligopolistic electricity market, showing that plant trading tends to lead to increased market concentration, high prices, lower production and a decrease in consumer surplus.

ACS Style

Derek W. Bunn; Fernando S. Oliveira. Dynamic capacity planning using strategic slack valuation. European Journal of Operational Research 2016, 253, 40 -50.

AMA Style

Derek W. Bunn, Fernando S. Oliveira. Dynamic capacity planning using strategic slack valuation. European Journal of Operational Research. 2016; 253 (1):40-50.

Chicago/Turabian Style

Derek W. Bunn; Fernando S. Oliveira. 2016. "Dynamic capacity planning using strategic slack valuation." European Journal of Operational Research 253, no. 1: 40-50.

Journal article
Published: 01 May 2016 in European Journal of Operational Research
Reads 0
Downloads 0
ACS Style

Janne Kettunen; Derek W. Bunn. Risk induced resource dependency in capacity investments. European Journal of Operational Research 2016, 250, 914 -924.

AMA Style

Janne Kettunen, Derek W. Bunn. Risk induced resource dependency in capacity investments. European Journal of Operational Research. 2016; 250 (3):914-924.

Chicago/Turabian Style

Janne Kettunen; Derek W. Bunn. 2016. "Risk induced resource dependency in capacity investments." European Journal of Operational Research 250, no. 3: 914-924.

Journal article
Published: 01 January 2016 in Energy Policy
Reads 0
Downloads 0
ACS Style

Derek W. Bunn; José I. Muñoz. Supporting the externality of intermittency in policies for renewable energy. Energy Policy 2016, 88, 594 -602.

AMA Style

Derek W. Bunn, José I. Muñoz. Supporting the externality of intermittency in policies for renewable energy. Energy Policy. 2016; 88 ():594-602.

Chicago/Turabian Style

Derek W. Bunn; José I. Muñoz. 2016. "Supporting the externality of intermittency in policies for renewable energy." Energy Policy 88, no. : 594-602.

Book chapter
Published: 03 October 2013 in Markets for Carbon and Power Pricing in Europe
Reads 0
Downloads 0
ACS Style

Derek W. Bunn; Carlo Fezzi. A Vector Error Correction Model of the Interactions Among Gas, Electricity and Carbon Prices: An Application to the Cases of Germany and the United Kingdom. Markets for Carbon and Power Pricing in Europe 2013, 1 .

AMA Style

Derek W. Bunn, Carlo Fezzi. A Vector Error Correction Model of the Interactions Among Gas, Electricity and Carbon Prices: An Application to the Cases of Germany and the United Kingdom. Markets for Carbon and Power Pricing in Europe. 2013; ():1.

Chicago/Turabian Style

Derek W. Bunn; Carlo Fezzi. 2013. "A Vector Error Correction Model of the Interactions Among Gas, Electricity and Carbon Prices: An Application to the Cases of Germany and the United Kingdom." Markets for Carbon and Power Pricing in Europe , no. : 1.

Research
Published: 31 January 2013 in Climate Policy
Reads 0
Downloads 0

How does financial performance risk affect investments in low-carbon electricity-generating technologies to achieve climate policy targets? A detailed risk simulation of price formation in the Great Britain wholesale power market is used to show that the increasing replacement of fossil facilities with wind, ceteris paribus, may cause a deterioration of the financial risk–return performance metrics for incremental investments. Low-carbon investments appear to be high risk, low return, and as such may require a progressively higher level of support over time than envisaged by the conventional degression trajectories. The increasing riskiness of the wholesale market will to some extent offset the benefits of lower capital costs and operational efficiencies if investors need to satisfy cautious debt coverage ratios alongside positive expected returns. This increased risk is additional to the well-known ‘merit order effect’ of low-carbon investments progressively depressing wholesale prices and hence their expected investment returns. Policy relevance Policy support for renewable technologies such as wind is usually based upon levelized costs and is expected to reduce over time as capital costs and operational efficiencies improve. However, levelized costs do not take full account of the risk aversion that investors may have in practice. Expected policy support reductions may be moderated to some extent by the increased financial performance risk that intermittent technologies bring to the power market. The annual risk-return profiles for incremental investments deteriorate for all technologies as wind replaces fossil fuels. This extra risk premium will need to be incorporated into evaluating policy incentives for new investments in a decarbonizing power market.

ACS Style

José I. Muñoz; Derek W. Bunn. Investment risk and return under renewable decarbonization of a power market. Climate Policy 2013, 13, 87 -105.

AMA Style

José I. Muñoz, Derek W. Bunn. Investment risk and return under renewable decarbonization of a power market. Climate Policy. 2013; 13 (sup01):87-105.

Chicago/Turabian Style

José I. Muñoz; Derek W. Bunn. 2013. "Investment risk and return under renewable decarbonization of a power market." Climate Policy 13, no. sup01: 87-105.