In this paper, a hybrid power generation company consisting of a concentrated solar power unit, wind turbines, a battery system, and a demand response provider is established to take part in electricity markets. The operating strategy of the hybrid power generation company in day-ahead and adjustment (intraday) markets is determined based on their coordinated operation. To tackle the intrinsic uncertainties, for the first time, a mixed stochastic-interval model is proposed which addresses the uncertainty in demand response and solar energy via interval optimization. The examined problem is formulated as a multi-objective optimization problem in which the risk of both stochastic and interval parameters can be involved. On this basis, the proposed operating strategy covers three objective functions, namely, expected radius and midpoint of the hybrid power generation company's profit together with the conditional value-at-risk. Accordingly, the normal boundary intersection and lexicographic optimization techniques are utilized to derive feasible solutions. Lastly, numerical results are presented and the performance of the proposed framework is investigated. The results indicate that the suggested model can be efficiently used to handle the decision-maker's preference over interval and stochastic parameters, and the risk criterion associated with interval parameters becomes larger as the forecasting errors increase.

Risk-involved optimal operating strategy of a hybrid power generation company: A mixed interval-CVaR model

Siano P.
2021-01-01

Abstract

In this paper, a hybrid power generation company consisting of a concentrated solar power unit, wind turbines, a battery system, and a demand response provider is established to take part in electricity markets. The operating strategy of the hybrid power generation company in day-ahead and adjustment (intraday) markets is determined based on their coordinated operation. To tackle the intrinsic uncertainties, for the first time, a mixed stochastic-interval model is proposed which addresses the uncertainty in demand response and solar energy via interval optimization. The examined problem is formulated as a multi-objective optimization problem in which the risk of both stochastic and interval parameters can be involved. On this basis, the proposed operating strategy covers three objective functions, namely, expected radius and midpoint of the hybrid power generation company's profit together with the conditional value-at-risk. Accordingly, the normal boundary intersection and lexicographic optimization techniques are utilized to derive feasible solutions. Lastly, numerical results are presented and the performance of the proposed framework is investigated. The results indicate that the suggested model can be efficiently used to handle the decision-maker's preference over interval and stochastic parameters, and the risk criterion associated with interval parameters becomes larger as the forecasting errors increase.
2021
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4774687
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 33
  • ???jsp.display-item.citation.isi??? 29
social impact