RT Journal Article
T1 Prescribing net demand for two-stage electricity generation scheduling
A1 Morales-González, Juan Miguel
A1 Muñoz, Miguel Ángel
A1 Pineda-Morente, Salvador
K1 Electricidad - Europa
AB We consider a two-stage generation scheduling problem comprising a forward dispatch and a real-time re-dispatch. The former must be conducted facing an uncertain net demand that includes non-dispatchable electricity consumption and renewable power generation. The latter copes with the plausible deviations with respect to the forward schedule by making use of balancing power during the actual operation of the system. Standard industry practice deals with the uncertain net demand in the forward stage by replacing it with a good estimate of its conditional expectation (usually referred to as a point forecast), so as to minimize the need for balancing power in real time. However, it is well known that the cost structure of a power system is highly asymmetric and dependent on its operating point, with the result that minimizing the amount of power imbalances is not necessarily aligned with minimizing operating costs. In this paper, we propose a bilevel program to construct, from the available historical data, a prescription of the net demand that does account for the power system’s cost asymmetry. Furthermore, to accommodate the strong dependence of this cost on the power system’s operating point, we use clustering to tailor the proposed prescription to the foreseen net-demand regime. By way of an illustrative example and a more realistic case study based on the European power system, we show that our approach leads to substantial cost savings compared to the customary way of doing.
PB Elsevier
YR 2023
FD 2023
LK https://hdl.handle.net/10630/25811
UL https://hdl.handle.net/10630/25811
LA eng
NO European Research Council (ERC) under the EU Horizon 2020 research and innovation program (grant agreement No. 755705); Spanish Ministry of Science and Innovation (AEI/10.13039/501100011033) through project PID2020-115460GB-I00 and through the State Training Subprogram 2018 of the State Program for the Promotion of Talent and its Employability in R&D&I, within the framework of the State Plan for Scientific and Technical Research and Innovation 2017–2020 (with the support of the European Social Fund), reference PRE2018-083722 and ENE2017-83775-P);Junta de Andalucía (JA) and the European Regional Development Fund (FEDER) through the research project P20_00153; Partial funding for open access charge: Universidad de Málaga / CBUA .
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026