Short term scheduling in a wind/diesel autonomous energy system

Contaxis George, C; Kabouris, J

dc.contributor.author	Contaxis George, C	en
dc.contributor.author	Kabouris, J	en
dc.date.accessioned	2014-03-01T01:08:32Z
dc.date.available	2014-03-01T01:08:32Z
dc.date.issued	1991	en
dc.identifier.issn	0885-8950	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/10554
dc.subject	AUTONOMOUS SYSTEM	en
dc.subject	WIND DIESEL GENERATORS	en
dc.subject	FORECASTING	en
dc.subject	UNIT COMMITMENT	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Diesel Electric Power Plants	en
dc.subject.other	Wind Power	en
dc.subject.other	Autonomous energy systems	en
dc.subject.other	Short-term scheduling	en
dc.subject.other	Wind generators	en
dc.subject.other	Wind/diesel energy systems	en
dc.subject.other	Electric Power Systems	en
dc.title	Short term scheduling in a wind/diesel autonomous energy system	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/59.119261	en
heal.identifier.secondary	http://dx.doi.org/10.1109/59.119261	en
heal.language	English	en
heal.publicationDate	1991	en
heal.abstract	An algorithm is developed for determining the optimal operation scheduling over a period of T hours for an autonomous energy system consisting of diesel units and wind generators. The proposed algorithm requires the load and wind velocity statistics during the scheduling period. Thus, the solution procedure involves the sequential execution of two separate algorithms solving the following two problems: (a) the short term forecasting of load and wind speed, and (b) the short term unit commitment. The simulation period is divided into m intervals of duration t minutes each. For each interval the mean value and standard deviation of the load and wind velocity are estimated using ARMA models. The unit commitment problem is solved by a heuristic algorithm based on a predetermined loading priority list of diesel units. The algorithm decomposes the problem into subproblems that are sequentially solved. Reliability constraints and technical constraints involving the operation of the units are taken into consideration. For the simulation of the generating system, probabilistic techniques are utilized.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Power Systems	en
dc.identifier.doi	10.1109/59.119261	en
dc.identifier.isi	ISI:A1991HA44600035	en
dc.identifier.volume	6	en
dc.identifier.issue	3	en
dc.identifier.spage	1161	en
dc.identifier.epage	1167	en