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Renewable power plants must comply with certain codes and requirements to be connected to the grid, being the ramp-rate compliance one of the most challenging requirements, especially for photovoltaic or wind energy generation plants. Battery-based energy storage systems represent a promising solution due to the fast dynamics of electrochemical storage systems, besides their scalability and flexibility. However, large-scale battery energy storage systems are still too expensive to be a mass market solution for the renewable energy resources integration. Thus, in order to make battery investment economically viable, the use of second life batteries is investigated in the paper. This paper proposes a method to determine the optimal sizing of a second life battery energy storage system (SLBESS). SLBESS performance is also validated and, as an ultimate step, the power exchanged with the batteries is calculated during one-year operation. The power profile obtained is further used to define the cycling patterns for laboratory testing of second life batteries and to study their ageing evolution when used for the power smoothing renewable integration application. Real photovoltaic energy generation data from a Spanish plant were used for the study. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]