Optimization of the battery size for PV systems under regulatory rules using a Markov-Chains approach. (January 2016) - Cervone, A.; Carbone, G.; Santini, E.; Teodori, S.
Abstract: In the last decade a high amount of photovoltaic and wind power generators have been connected to the electric grid, introducing operational problems for transmission and distribution system operators due to the variability and the non-programmability of solar radiation and wind. The paper concerns an analysis on the benefits in adopting storage systems to reduce the imbalance costs associated to renewable energy sources. An analysis on a photovoltaic system has been performed considering different battery technologies. Discrete-time Markov chains have been used to generate a 20 years' time series of irradiance, that has been used to calculate the PV power production. Markov simulation parameters have been deeply studied in order to optimize them and obtain reliable synthetic data of ground irradiance. This data was then used as input of a hybrid PV and storage model allowing to obtain realistic economic and technical results, improving thus the results respect to the methods based on probabilistic weather simulations. An imbalance tariff has been assumed and its cost has been analysed in relation to the storage system costs. An optimal size for the different battery technology has been investigated considering the reduction of variability of the photovoltaic production and the economic convenience of the hybrid system. The use of Markov chains for the optimization of the battery size can be considered as the major novelty of the proposed approach. Highlights: We considered penalties for unbalanced production due to PV intrinsic variability. Markov chains have been used systematically for weather simulation. Mathematical model of the PV power plant and of the batteries in the storage system. Power flow calculation has been performed when the plant is connected to the network. Accurate economical analysis took into account: storage system, production, penalties.