Demand forecasting and generation scheduling for a secure and cost-effective operation of power systems
Küçük Resim Yok
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper presents a practical approach for demand forecasting and generation scheduling in a power system with solar PV sources and a Compressed Air Energy Storage System. The demand-forecasting method is improved using an artificial neural network in the first stage. After forecasting the demand for several representative days, the cost-effective generation scheduling is achieved for PV generation units and storage systems at the second stage. The proposed forecasting and generation scheduling approaches are tested in IEEE-RTS-96 test system, and the results are discussed from a technical and economic point of view. © 2022 IEEE.
Açıklama
2022 International Conference on Power, Energy and Innovations, ICPEI 2022 -- 19 October 2022 through 21 October 2022 -- -- 185591
Anahtar Kelimeler
compressed air energy storage system, cost-effective operation, Generation scheduling, load forecasting, solar generation units
Kaynak
2022 International Conference on Power, Energy and Innovations, ICPEI 2022
WoS Q Değeri
Scopus Q Değeri
N/A
