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Long-termed investment planning model for a generation company operating in both bilateral contract and day-ahead markets

  • Berna Tektas Sivrikaya*
  • , Ferhan Cebi
  • *Corresponding author for this work
  • Istanbul Technical University

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

This paper presents a modelling framework for generation capacity expansion planning (GEP) applicable to independent investor generation companies (GenCos) in the context of a hybrid electricity wholesale market. The proposed model is novel in the sense that the operations of the GenCo in bilateral contracts market (BCM) and day-ahead market (DAM) are incorporated. Also, the environmental considerations are modelled through the incorporation of carbon tax and carbon dioxide (CO2) cap regulations. At the end of existing generation units' useful life, refurbishment decisions are employed. In this way, conversion of old units to units with lower operation costs and/or green house gases emissions is modelled. The effect of uncertainties in electricity market prices, fuel costs, environmental regulations, budget, and the effect of the GenCos long-termed strategic behaviour in participating in BCM and DAM on the planning decisions are illustrated by sensitivity analysis.

Original languageEnglish
Pages (from-to)24-52
Number of pages29
JournalInternational Journal of Information and Decision Sciences
Volume8
Issue number1
DOIs
Publication statusPublished - 2016

Bibliographical note

Publisher Copyright:
Copyright © 2016 Inderscience Enterprises Ltd.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Bilateral contracts market
  • Carbon dioxide emission cap
  • Carbon tax
  • Day-ahead market
  • Generation capacity expansion planning
  • Long-termed investment planning
  • Mixed-integer linear programming hybrid electricity market

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