This work focuses on the study of the most suitable energy management strategies for solar power plants based on the integration of a concentrating solar power (CSP) plant with thermal energy storage and a concentrating photovoltaic (CPV) power plant with electrochemical storage. Due to the presence of the energy storage system, these integrated CSP-CPV plants are able to produce electricity with scheduled profiles as well as to provide ancillary services at distribution level. The algorithm for the optimal plant management uses weather forecast data to schedule the optimum generation profile by maximizing the power production of the integrated plant, while different constraints due to equipment limits are satisfied. A comparative analysis is carried out by means of the implementation of a deterministic or a stochastic approach to take into account the uncertainties in weather forecast. A time horizon of 48 h is imposed in the optimization problem with an updating of the input data and results each 24 h. The integrated CSP-CPV power plant here analyzed refers to the solar pilot facility that is currently under construction in the industrial district of Ottana (Sardinia, Italy). The facility consists of a CSP plant based on linear Fresnel collectors using thermal oil as heat transfer fluid, a two-tank thermal energy storage system (capacity of about 15 MWh), a 600 kWe ORC power plant, a 400 kWe CPV power plant and an electrochemical storage system with a capacity of 430 kWh. The results of the study demonstrate that the use of a stochastic approach instead of a deterministic one allows to generate more robust solutions. In particular, with the proposed stochastic approach unexpected phenomena and the variation in the foreseen conditions only marginally affect the scheduling planning, which results in an improvement of about 3-5% in the yearly power production.

Optimal energy management strategy for CSP-CPV integrated power plants with energy storage

CAU, GIORGIO;COCCO, DANIELE;PETROLLESE, MARIO
2015

Abstract

This work focuses on the study of the most suitable energy management strategies for solar power plants based on the integration of a concentrating solar power (CSP) plant with thermal energy storage and a concentrating photovoltaic (CPV) power plant with electrochemical storage. Due to the presence of the energy storage system, these integrated CSP-CPV plants are able to produce electricity with scheduled profiles as well as to provide ancillary services at distribution level. The algorithm for the optimal plant management uses weather forecast data to schedule the optimum generation profile by maximizing the power production of the integrated plant, while different constraints due to equipment limits are satisfied. A comparative analysis is carried out by means of the implementation of a deterministic or a stochastic approach to take into account the uncertainties in weather forecast. A time horizon of 48 h is imposed in the optimization problem with an updating of the input data and results each 24 h. The integrated CSP-CPV power plant here analyzed refers to the solar pilot facility that is currently under construction in the industrial district of Ottana (Sardinia, Italy). The facility consists of a CSP plant based on linear Fresnel collectors using thermal oil as heat transfer fluid, a two-tank thermal energy storage system (capacity of about 15 MWh), a 600 kWe ORC power plant, a 400 kWe CPV power plant and an electrochemical storage system with a capacity of 430 kWh. The results of the study demonstrate that the use of a stochastic approach instead of a deterministic one allows to generate more robust solutions. In particular, with the proposed stochastic approach unexpected phenomena and the variation in the foreseen conditions only marginally affect the scheduling planning, which results in an improvement of about 3-5% in the yearly power production.
CSP; CPV; Thermal energy storage; Energy storage system; EMS.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11584/134451
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