Two-Stage Stochastic Mixed Integer Programming Approach for Optimal SCUC by Economic DR Model
Kia, Mohsen; Etemad, Reza; Heidari, Alireza; Lotfi, Mohamed; Catalão, João P. S.; Shafie-khah, Miadreza; Osório, Gerardo J. (2019-08-26)
Kia, Mohsen
Etemad, Reza
Heidari, Alireza
Lotfi, Mohamed
Catalão, João P. S.
Shafie-khah, Miadreza
Osório, Gerardo J.
IEEE
26.08.2019
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe202102195425
https://urn.fi/URN:NBN:fi-fe202102195425
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vertaisarvioitu
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Tiivistelmä
Due to influences by power system restructuring, fuel price uncertainties, future demand forecasting, and utilities and transmission lines availability, demand response (DR) programs for consumers have gained more attention. One important DR scheme is the emergency demand response program (EDRP). This paper focuses on simultaneous implementation of security-constraint unit commitment (SCUC) and EDRP by using an economic model. Moreover, a stochastic optimization method is employed for realistic modelling. Since the combined implementation of SCUC and EDRP results in a complex nonlinear optimization problem, a linearization method to ensure computational efficiency is used. The proposed model is formulated as two-stage Stochastic Mixed-Integer Programming (SMIP) model implemented using GAMS. The implemented model is tested on three case studies using the IEEE 24-bus system. Results are analyzed with a focus on the impact of demand elasticity and electricity prices.
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