Optimization Models for Assessing Energy Systems in Transition

Research output: ThesisDoctoral ThesisCollection of Articles

Abstract

Energy systems are undergoing a major transition toward environmental sustainability. For instance, the European Union has implemented energy and climate policy targets for years 2020 and 2030 in order to reduce greenhouse gas emissions, increase renewable energy production and improve energy efficiency. However, because variable renewable energy sources (VRES) such as wind and solar power are intermittent, more flexibility is required from the energy system. This dissertation analyzes the present energy transition through two lenses. First, it formulates mathematical models which are solved through optimization and complementarity techniques to determine optimal investment and operational decisions, in recognition of the stakeholders' different and even conflicting objectives. Second, these models provide insights into the Western European power market and Nordic energy systems by helping in the assessment of the technical, welfare, and emissions impacts of large-scale energy storage. Much emphasis is placed on the analysis of market efficiency, because large producers, in particular, may be able to affect markets in their favor. This kind of market power is studied especially in connection with investments into and operation of energy storage as well as the production of combined heat and power (CHP). Finally, the modeling of power transmission networks gives information about the combined effects of interconnected markets and the increasing share of VRES. The models in this dissertation support energy policy-making in the present situation in which it is crucial to understand how the security of supply can be maintained without compromising sustainability and market efficiency. Overall, the models yield results which could hardly be obtained through empirical research, as the outcomes of ongoing developments and planned policies depend on the actions of all stakeholders.
Original languageEnglish
QualificationDoctor's degree
Awarding Institution
  • Aalto University
Supervisors/Advisors
  • Salo, Ahti, Supervisor
  • Salo, Ahti, Advisor
  • Siddiqui, Afzal, Advisor
Publisher
Print ISBNs978-952-60-8692-7
Electronic ISBNs978-952-60-8693-4
Publication statusPublished - 2019
MoE publication typeG5 Doctoral dissertation (article)

Keywords

  • energy systems modeling
  • optimization
  • energy storage
  • market power

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