Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/5940
Título: Cost Allocation Model for Distribution Networks Considering High Penetration of Distributed Energy Resources
Autor: Soares, Tiago
Pereira, Fábio
Morais, Hugo
Vale, Zita
Palavras-chave: Bialek’s tracing method
Distributed energy resources
Kirschen’s tracing method
Data: Jul-2015
Editora: Elsevier
Relatório da Série N.º: Electric Power Systems Research;Vol. 124
Resumo: The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.
Peer review: yes
URI: http://hdl.handle.net/10400.22/5940
DOI: 10.1016/j.epsr.2015.03.008
Versão do Editor: http://www.sciencedirect.com/science/article/pii/S0378779615000681
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