Integrated risk management for an electricity producer

Falbo, Paolo; Felletti, Daniele; Stefani, Silvana

doi:10.1016/j.ejor.2010.06.017

Cited by 25 publications

(22 citation statements)

References 10 publications

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“…For hedging purposes the natural criterion to rank the performance of a derivative instrument is ''the more it reduces risk, the better'' (see for instance Mello and Parsons, 2000). A natural way (however, not efficient as is shown in Falbo et al, 2008) to hedge against price volatility is that of signing a bilateral contract directly with the energy producers. Derivatives, on the other hand, are the main instruments for hedging.…”

Section: Derivativesmentioning

confidence: 99%

A new index for electricity spot markets

2010

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Section: Derivativesmentioning

confidence: 99%

A new index for electricity spot markets

2010

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“…Research on implementing ISO 31000 risk management standards to improve the success of an engineering project [13]. Risk management can also reduce the impact of uncertainty about prices and costs of electricity production [14]. Risk management as a decision support tool to reduce the potential risk of cargo ship accidents on the coast and sea [15].…”

Section: Literatur Reviewmentioning

confidence: 99%

Measurement of Cost & Benefit for Implementation of Risk Management in the Production Process

Rosiawan

Singgih

Widodo

2019

IJPS

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The paper aims to measure the overhead costs and economic benefits of risk management activities in the production process-a manufacturing company. This research uses Activity Based Management (ABM) approach to allocate and track overhead costs in risk management activities. The overhead costs of risk management activities include the costs of identifying, analyzing, evaluating and controlling risks in order to achieve the quality objectives of the production process. The company obtains economic benefits, first, from reducing overhead costs incurred per period from the results of improvements to non-value-added or high-cost activities; second, cost savings obtained from the achievement of quality objectives per period. The results of this study indicate that the ABM approach used is appropriate in measuring the overhead costs and economic benefits of risk management activities in a business process.

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“…So far, this line of research has mainly focused on conventional power (e.g., Thompson et al (2004), Porchet et al (2009) or Falbo et al (2010) and the optimization of hydro power schedules (e.g., García-González et al (2007) or Densing (2013)). Also, a number of papers have valued wind power based on historical data (e.g., Green and Vasilakos (2012)).…”

Section: Introductionmentioning

confidence: 99%

Spatial dependencies of wind power and interrelations with spot price dynamics

Elberg

Hagspiel

2015

European Journal of Operational Research

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWind power has seen strong growth over the last decade and increasingly affects electricity spot prices. Generation from wind energy is stochastic, and if there is lot of wind, prices tend to be lower. Therefore, for an investor, but also for the whole electricity system, it is important to assess the value of wind power at different locations. In this paper, we develop a stochastic simulation model that captures the full spatial dependence structure of wind power by using copulas, incorporated into a structural supply and demand based model for the electricity spot price. This model is calibrated with German data. We find that the specific location of a turbine -i.e., its spatial dependence with respect to the aggregated wind power in the system -is of high relevance for its value. Many of the locations analyzed show an upper tail dependence that adversely impacts the market value. Therefore, a model that assumes a linear dependence structure would systematically overestimate the market value of wind power in many cases. This effect becomes more important for increasing levels of wind power penetration and may render the large-scale integration into markets more difficult.

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Integrated risk management for an electricity producer

Cited by 25 publications

References 10 publications

A new index for electricity spot markets

A new index for electricity spot markets

Measurement of Cost & Benefit for Implementation of Risk Management in the Production Process

Spatial dependencies of wind power and interrelations with spot price dynamics

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