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Management strategy for market participation of photovoltaic power plants including storage systems

  • Andoni Saez-De-Ibarra*
  • , Victor Isaac Herrera
  • , Aitor Milo
  • , Haizea Gaztanaga
  • , Ion Etxeberria-Otadui
  • , Seddik Bacha
  • , Asun Padros
  • *Corresponding author for this work
  • IKERLAN
  • Université Grenoble Alpes
  • Acciona

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

Energy storage systems (ESS) integration with large-scale photovoltaic (PV) power plants, named intelligent PV (IPV) power plant, could contribute to improving the viability of these plants and to provide ancillary services to the main grid. The number and extension of the provided services depend not only on the size of the ESS, but also on the manner in which this storage system is managed. In this paper, the market participation based on different firming control strategies of an IPV power plant is proposed to optimize the economic exploitation based on the storage system management considering PV generation predictions. The most appropriate firming control strategy is selected to participate on the daily market, which is strengthened with an online model predictive control (MPC) to compensate the PV prediction errors participating in the intraday market. The real operation of the Iberian Peninsula market integration is also explained and analyzed. The development of this management strategy considers as a case study a real IPV plant located in Tudela (Navarre, Spain) and owned by Acciona Energía, which included a Lithium-ion based ESS from 2012 to 2013 in the framework of a European project. The results show that considering the MPC approach, an increase around 20% in the benefits is obtained by comparing with the daily market participation.

Original languageEnglish
Article number7500112
Pages (from-to)4292-4303
Number of pages12
JournalIEEE Transactions on Industry Applications
Volume52
Issue number5
DOIs
StatePublished - 1 Sep 2016
Externally publishedYes

UN SDGs

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

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Design methodology
  • energy storage
  • photovoltaic systems
  • predictive control
  • smoothing methods

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