Optimum expansion planning of an unconventional generation system operating in parallel with a large scale network

Kabouris, J; Contaxis, GC

dc.contributor.author	Kabouris, J	en
dc.contributor.author	Contaxis, GC	en
dc.date.accessioned	2014-03-01T01:08:28Z
dc.date.available	2014-03-01T01:08:28Z
dc.date.issued	1991	en
dc.identifier.issn	0885-8969	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/10514
dc.subject	EXPANSION PLANNING	en
dc.subject	WIND GENERATORS	en
dc.subject	PHOTOVOLTAIC PANELS	en
dc.subject	COMPUTER PACKAGE	en
dc.subject.classification	Energy & Fuels	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Electric Power Generation	en
dc.subject.other	Mathematical Programming, Dynamic	en
dc.subject.other	Meteorology	en
dc.subject.other	Large scale networks	en
dc.subject.other	Local grids	en
dc.subject.other	Meteorological data	en
dc.subject.other	Unconventional generation systems	en
dc.subject.other	Electric Power Systems	en
dc.title	Optimum expansion planning of an unconventional generation system operating in parallel with a large scale network	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/60.84312	en
heal.identifier.secondary	http://dx.doi.org/10.1109/60.84312	en
heal.language	English	en
heal.publicationDate	1991	en
heal.abstract	This paper describes a package developed at the National Technical University of Athens which determines the optimal expansion policy over a period of N years for a limited size generation system consisting of wind generators (WECs) and photovoltaic (PV) panels operating in parallel with a large scale network. The produced energy from the wind generators and the photovoltaic panels is directly injected to the local grid or transmitted to the interconnected system. Given the meteorological data of the installation area, historical load data, the characteristics of the proposed additions (WECs and PV panels), the cost of the energy and the associated escalation rate, the package finds the optimal expansion policy for the period of next N years, utilizing a dynamic programming algorithm.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Energy Conversion	en
dc.identifier.doi	10.1109/60.84312	en
dc.identifier.isi	ISI:A1991FZ03600008	en
dc.identifier.volume	6	en
dc.identifier.issue	3	en
dc.identifier.spage	394	en
dc.identifier.epage	400	en