Assessing the optimal generation technology mix determination considering demand response and EVs

Hassan Haes Alhelou, Seyed Jamal Mirjalili, Reza Zamani, Pierluigi Siano

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

This paper proposes a novel, generation technology mix determination method considering short term demand response, energy storage systems, and electric vehicles to provide more flexibility to the future power systems. In the proposed method, new models of both electric vehicles and energy storage technologies for contributing to generation mix determination studies are suggested. The integration of the different emerging technologies, i.e. demand response, energy storage systems, and electric vehicles into traditional generation mix determination is done firstly by adopting mix complementary programing method. Then, to overcome the problems of such integration and to avoid its complexity, it is converted to quadric complimentary programing model. The proposed generation mix determination framework is tested on the Spanish power system with real data. The outputs of the proposed method are the optimal capacities of the conventional generating units, the different types of energy storages and wind turbines. Simulation results demonstrate the effectiveness of the proposed method in determining the optimal generation mix of future power systems with high penetration level of wind energy resources. Moreover, the results verify the potential of the proposed method in providing better flexibility services to power system if compared with other methods.

Original languageEnglish
Article number105871
JournalInternational Journal of Electrical Power and Energy Systems
Volume119
DOIs
Publication statusPublished - Jul 2020
Externally publishedYes

Keywords

  • Demand response
  • Electric vehicles
  • Energy storage
  • Optimal generation mix
  • Renewable energy resource

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