Decision modelling tools for utilities in the deregulated energy market

 |  Login

Show simple item record

dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Makkonen, Simo
dc.date.accessioned 2012-02-17T07:17:50Z
dc.date.available 2012-02-17T07:17:50Z
dc.date.issued 2005-10-28
dc.identifier.isbn 951-22-7863-4
dc.identifier.issn 0782-2030
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/2622
dc.description.abstract This thesis examines the impact of the deregulation of the energy market on decision making and optimisation in utilities and demonstrates how decision support applications can solve specific encountered tasks in this context. The themes of the thesis are presented in different frameworks in order to clarify the complex decision making and optimisation environment where new sources of uncertainties arise due to the convergence of energy markets, globalisation of energy business and increasing competition. This thesis reflects the changes in the decision making and planning environment of European energy companies during the period from 1995 to 2004. It also follows the development of computational performance and evolution of energy information systems during the same period. Specifically, this thesis consists of studies at several levels of the decision making hierarchy ranging from top-level strategic decision problems to specific optimisation algorithms. On the other hand, the studies also follow the progress of the liberalised energy market from the monopolistic era to the fully competitive market with new trading instruments and issues like emissions trading. This thesis suggests that there is an increasing need for optimisation and multiple criteria decision making methods, and that new approaches based on the use of operations research are welcome as the deregulation proceeds and uncertainties increase. Technically, the optimisation applications presented are based on Lagrangian relaxation techniques and the dedicated Power Simplex algorithm supplemented with stochastic scenario analysis for decision support, a heuristic method to allocate common benefits and potential losses of coalitions of power companies, and an advanced Branch-and-Bound algorithm to solve efficiently non-convex optimisation problems. The optimisation problems are part of the operational and tactical decision making process that has become very complex in the recent years. Similarly, strategic decision support has also faced new challenges. This thesis introduces two applications involving multiple criteria decision making methods. The first application explores the decision making problem caused by the introduction of 'green' electricity that creates additional value for renewable energy. In this problem the stochastic multi-criteria acceptability analysis method (SMAA) is applied. The second strategic multi-criteria decision making study discusses two different energy-related operations research problems: the elements of risk analysis in the energy field and the evaluation of different choices with a decision support tool accommodating incomplete preference information to help energy companies to select a proper risk management system. The application is based on the rank inclusion in criteria hierarchies (RICH) method. en
dc.format.extent 22, [81]
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Helsinki University of Technology en
dc.publisher Teknillinen korkeakoulu fi
dc.relation.ispartofseries Research reports / Helsinki University of Technology, Systems Analysis Laboratory. A en
dc.relation.ispartofseries 93 en
dc.relation.haspart Lahdelma R., Makkonen S., 1996, Interactive Graphical Object-Oriented Energy Modeling and Optimization. In: Proceedings of the International Symposium of ECOS'96, Efficiency, Cost, Optimization, Simulation and Environmental Aspects of Energy Systems, June 25-27, Stockholm, Sweden, pp. 425-431.
dc.relation.haspart Makkonen S., Lahdelma R., 1998, Stochastic Simulation in Risk Analysis of Energy Trade. In: Steward, van den Honert (Eds.), Trends in Multicriteria Decision Making, Proceedings of the 13th International Conference on Multiple Criteria Decision Making, Lecture Notes in Economics and Mathematical Sciences (465), Springer, Berlin, pp. 146-156.
dc.relation.haspart Makkonen S., Lahdelma R., 2001, Analysis of Power Pools in the Deregulated Energy Market through Simulation. Decision Support Systems 30 (3), pp. 289-301.
dc.relation.haspart Makkonen S., Lahdelma R., Asell A.-M., Jokinen A., 2003, Multi-criteria Decision Support in the Liberalized Energy Market. Journal of Multi-Criteria Decision Analysis 12 (1), pp. 27-42.
dc.relation.haspart Makkonen S., Lahdelma R., 2005, Non-Convex Power Plant Modelling in Energy Optimisation. European Journal of Operational Research, to appear (Article in press, Available online 10 March 2005).
dc.relation.haspart Ojanen O., Makkonen S., Salo A., 2005, A Multi-Criteria Framework for the Selection of Risk Analysis Methods at Energy Utilities. International Journal of Risk Assessment and Management 5 (1), pp. 16-35.
dc.subject.other Energy en
dc.subject.other Economics en
dc.title Decision modelling tools for utilities in the deregulated energy market en
dc.type G5 Artikkeliväitöskirja fi
dc.description.version reviewed en
dc.contributor.department Department of Engineering Physics and Mathematics en
dc.contributor.department Teknillisen fysiikan ja matematiikan osasto fi
dc.subject.keyword deregulated energy market en
dc.subject.keyword multi-criteria decision making en
dc.subject.keyword optimisation en
dc.subject.keyword modelling en
dc.identifier.urn urn:nbn:fi:tkk-005827
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.type.ontasot Doctoral dissertation (article-based) en
dc.contributor.lab Systems Analysis Laboratory en
dc.contributor.lab Systeemianalyysin laboratorio fi


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search archive


Advanced Search

article-iconSubmit a publication

Browse

My Account