Document details

Distribution system state estimation using the hamiltonian cycle theory

Author(s): Leite, Jônatas Boás [UNESP] ; Mantovani, José Roberto Sanches [UNESP]

Date: 2018

Persistent ID: http://hdl.handle.net/11449/172660

Origin: Oasisbr

Subject(s): Advanced metering infrastructure (AMI); Automatic operations; Distribution management system (DMS); Hamiltonian cycle; Smart grid; State estimation; Advanced metering infrastructure (AMI); Advanced metering infrastructure (AMI); Automatic operations; Automatic operations; Distribution management system (DMS); Distribution management system (DMS); Hamiltonian cycle; Hamiltonian cycle; Smart grid; Smart grid; State estimation; State estimation


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Made available in DSpace on 2018-12-11T17:01:39Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-01-01

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Since the origin of energy management systems, state estimation applications have aided in automatic power system operations, mainly for transmission systems. Currently, however, smart grid concepts are modifying the behavior of distribution systems through a rapid increase of controllable distributed generators, demand response, and electric vehicles. Consequently, the advanced metering infrastructure is providing a large amount of synchronized metering data with high accuracy and resolution, which favors the development of state estimation procedures to sustain distribution management systems. Therefore, this paper presents the formulation of a novel algorithm for state estimation solution in distribution networks using the Hamiltonian cycle theory, where the network states are quickly obtained through a calculation scheme under the normal operating conditions.

Department of Electrical Engineering São Paulo State University (UNESP) FEIS

Department of Electrical Engineering São Paulo State University (UNESP) FEIS

FAPESP: 2013/23590-8

FAPESP: 2014/22377-1

CNPq: 305371/2012-6

Document Type Journal article
Language English
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