Economic MPC applied to generation scheduling in CSP plants

Abstract

This paper proposes a model-based predictive control (MPC) approach with economic objective function to face the scheduling problem in concentrating solar power (CSP) plants with thermal energy storage (TES) in a day-ahead energy market context. By this approach, the most recent energy prices, weather forecast and the current plant’s state can be used by the proposed economic MPC approach to reschedule the generation conveniently from time to time. The proposed approach is applied, in a simulation context, to a 50 MW parabolic trough collector-based CSP with TES under the assumption of perfect price forecast and participation in the Spanish day-ahead energy market. A case study based on a four-month period to test several meteorological conditions is performed. In this study, a complete economic analysis is carried out using actual values of energy price, penalty cost, solar resource data and its forecast. Results show an economic improvement in comparison with a traditional day-ahead scheduling strategy.