Multi-Objective Cooperative Scheduling for Smart Grids: (Short Paper)
CAMBLONG, Haritza
Universidad del País Vasco [Espainia] / Euskal Herriko Unibertsitatea [España] = University of the Basque Country [Spain] = Université du pays basque [Espagne] [UPV / EHU]
ESTIA INSTITUTE OF TECHNOLOGY
Universidad del País Vasco [Espainia] / Euskal Herriko Unibertsitatea [España] = University of the Basque Country [Spain] = Université du pays basque [Espagne] [UPV / EHU]
ESTIA INSTITUTE OF TECHNOLOGY
CAMBLONG, Haritza
Universidad del País Vasco [Espainia] / Euskal Herriko Unibertsitatea [España] = University of the Basque Country [Spain] = Université du pays basque [Espagne] [UPV / EHU]
ESTIA INSTITUTE OF TECHNOLOGY
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Universidad del País Vasco [Espainia] / Euskal Herriko Unibertsitatea [España] = University of the Basque Country [Spain] = Université du pays basque [Espagne] [UPV / EHU]
ESTIA INSTITUTE OF TECHNOLOGY
Idioma
EN
Communication dans un congrès
Este ítem está publicado en
On the Move to Meaningful Internet Systems. OTM 2017 Conferences - Confederated International Conferences: CoopIS, C&TC, and ODBASE 2017, Rhodes, Greece, October 23-27, 2017, Proceedings, Part I, 2017-10-23, Rhodes. 2017, vol. 10573 LNCS, p. 543-551
Springer Verlag
Resumen en inglés
In this work, we propose a multi-objective cooperative scheduling for Smart Grids (SG) consisting of two main modules: (1) the Preference-based Compromise Builder and (2) the Multi-objective Scheduler. The Preference-based ...Leer más >
In this work, we propose a multi-objective cooperative scheduling for Smart Grids (SG) consisting of two main modules: (1) the Preference-based Compromise Builder and (2) the Multi-objective Scheduler. The Preference-based Compromise Builder generates the best balance or what we call ‘the compromise' between the preferences or associations of sellers and buyers that must exchange power simultaneously. Once done, the Multi-objective Scheduler proposes a power schedule for the associations, in order to achieve optimal benefits from different perspectives (e.g., economical by reducing the electricity costs, ecological by minimizing the toxic gas emissions, and operational by reducing the peak load of the SG and its components, and by increasing their comfort). Conducted experiments showed that the proposed algorithms provide convincing results. \textcopyright 2017, Springer International Publishing AG.< Leer menos
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