RT Journal Article
T1 Calculating the profits of an economic MPC applied to CSP plants with thermal storage system
A1 Vasallo Vázquez, Manuel Jesús
A1 Bravo Caro, José Manuel
A1 Cojocaru, Emilian Gelu
A1 Gegúndez Arias, Manuel Emilio
AB Electricity producers participating in a day-ahead energy market aim to maximize profits derived fromelectricity sales. The daily generation schedule has to be offered in advance, usually the previous daybefore a certain moment in time. The development of an economically-optimal generation schedule isthe core of the generation scheduling problem. To solve this problem, renewable energy plant ownersneed, besides energy prices forecast, weather prediction. Among renewable energy sources, concentratedsolar power (CSP) plants with thermal energy storage (TES) may find it easier to participate in electricitymarkets due to their semi-dispatchable generation. In any case, the limited accuracy of forecasting solarresource brings about the risk of penalties that may be imposed to CSP plants for deviation from the submittedschedule. This paper proposes a model-based predictive control (MPC) approach with an economicobjective function to tackle the scheduling problem in CSP plants with TES. By this approach,the most recent forecast and the current status of plant can be used by the proposed economic MPCapproach to reschedule the generation conveniently at regular time intervals. On the other hand, a morefeasible generation schedule for the next day is performed at the appropriate time thanks to the use ofshort-term forecast. The proposed approach is applied, in a simulation context, to a 50 MW parabolictrough collector-based CSP plant with TES under the assumptions of perfect price forecasts and participationin the Spanish day-ahead energy market. A case study based on a half-year period to test severalmeteorological conditions is performed. In this study, an economic analysis is carried out using actualvalues of energy price, penalty cost, solar resource data and its day-ahead forecast. Results show an economicimprovement in comparison with a traditional day-ahead scheduling strategy, especially in periodswith a bad weather forecast. To overcome the lack of short-term weather forecast data for this study,a synthetic short-term predictor, whose accuracy level can be tuned by means of a parameter, is used.Sweeping this accuracy level between the situation with no forecast improvement and perfect shorttermforecast, the MPC strategy reaches an improvement in total profits during the six months periodbetween 13.9% and 33.3% of the maximum room for improvement. This maximum ideal improvementis defined as the difference in profits between the MPC strategy with perfect forecasts and the dayaheadscheduling strategy.
PB Elsevier
SN 0038-092X
YR 2017
FD 2017
LK http://hdl.handle.net/10272/18901
UL http://hdl.handle.net/10272/18901
LA eng
NO Vasallo, M. J., Bravo, J. M., Cojocaru, E. G., & Gegúndez, M. E. (2017). Calculating the profits of an economic MPC applied to CSP plants with thermal storage system. Solar Energy, 155, 1165–1177. https://doi.org/10.1016/j.solener.2017.07.033
NO This research has been supported by DPI2016-76493-C3-2-RProject of Ministerio de Economía y Competitividad (Spain). Theauthors would like to thank Acciona Energa S.A. for expressinginterest in the project
DS Repositorio Institucional de la Universidad de Huelva
RD 1 jun 2026