DocumentCode :
2355013
Title :
Demand response programs definition supported by clustering and classification techniques
Author :
Ramos, Sérgio ; Morais, Hugo ; Vale, Zita ; Faria, Pedro ; Soares, João
Author_Institution :
Knowledge Eng. & Decision-Support Res. Group, Polytech. Inst. of Porto, Porto, Portugal
fYear :
2011
fDate :
25-28 Sept. 2011
Firstpage :
1
Lastpage :
6
Abstract :
The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.
Keywords :
data mining; distributed power generation; pattern classification; pattern clustering; power engineering computing; 33 bus distribution network; CSP; DG; DR capacity; DR program; ISO; Independent System Operator; VPP; classification techniques; clustering techniques; curtailment service provider; data mining techniques; demand response; demand response programs; distributed generation; environmental policy; operational constraints; power systems; renewable based energy resources; virtual power players; Classification algorithms; Clustering algorithms; Data mining; Data models; Discharges; Generators; Load management; Clustering; Data Mining; Demand Response (DR); Energy Resources Management; Mixed Integer Non-Linear Programming (MINLP);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent System Application to Power Systems (ISAP), 2011 16th International Conference on
Conference_Location :
Hersonissos
Print_ISBN :
978-1-4577-0807-7
Electronic_ISBN :
978-1-4577-0808-4
Type :
conf
DOI :
10.1109/ISAP.2011.6082185
Filename :
6082185
Link To Document :
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