%0 Conference Proceedings
%T Optimal Behavior of Demand Response Aggregators in Providing Balancing and Ancillary Services in Renewable-Based Power Systems
%+ Isfahan University of Technology
%+ University of Beira Interior [Portugal] (UBI)
%+ Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa (INESC-ID)
%+ Instituto Superior Técnico, Universidade Técnica de Lisboa (IST)
%A Heydarian-Forushani, E.
%A Golshan, M., H.
%A Shafie-Khah, M.
%A Catalão, João, S.
%Z Part 10: Renewable Energy
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 6th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS)
%C Costa de Caparica, Portugal
%Y Luis M. Camarinha-Matos
%Y Thais A. Baldissera
%Y Giovanni Di Orio
%Y Francisco Marques
%3 Technological Innovation for Cloud-Based Engineering Systems
%V AICT-450
%P 309-316
%8 2015-04-13
%D 2015
%R 10.1007/978-3-319-16766-4_33
%K DR aggregator
%K Demand response
%K Ancillary services markets
%K Renewable energy resources
%Z Computer Science [cs]Conference papers
%X Due to the limited predictability and associated uncertainty of renewable energy resources, renewable-based electricity systems are confronted with instability problems. In such power systems, implementation of Demand Response (DR) programs not only can improve the system stability but also enhances market efficiency and system reliability. By implementing cloud-based engineering systems the utilization of DR will be increased and consequently DR will play a more crucial role in the future. Therefore, DR aggregators can efficiently take part in energy, balancing and ancillary services markets. In this paper, a model has been developed to optimize the behavior of a DR aggregator to simultaneously participate in the mentioned markets. To this end, the DR aggregator optimizes its offering/bidding strategies based on the contracts with its customers. In the proposed model, uncertainties of renewable energy resources and the prices of electricity markets are considered. Numerical studies show the effectiveness of the proposed model.
%G English
%Z TC 5
%Z WG 5.5
%2 https://inria.hal.science/hal-01343498/document
%2 https://inria.hal.science/hal-01343498/file/336594_1_En_33_Chapter.pdf
%L hal-01343498
%U https://inria.hal.science/hal-01343498
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-WG5-5
%~ IFIP-DOCEIS
%~ IFIP-AICT-450