Abstract
The perception of the associated impacts among possible management schemes introduces a new way to assess energy storage systems. The ability to define a specific management scheme considering the different stakeholder objectives, both technical and economic, will increase the perception of available installation options. This paper presents a multiobjective feasibility assessment methodology using an improved version of the Non-dominated Sorting Genetic Algorithm II, to optimize the placement of electric energy storage units in order to improve the operation of distribution networks. The model is applied to a case study, using lithium-ion battery technology as an example. The results show the influence of different charging/discharging profiles on the choice of the best battery location, as well as the influence that these choices may have on the different network management objectives, e.g. increasing the integration of renewable generation. As an additional outcome, the authors propose a pricing scheme for filling the present regulatory gap regarding the pricing scheme to be applied to energy storage in order to allow the exploitation of viable business models.
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Acknowledgments
This work has been framed under the Energy for Sustainability Initiative of the University of Coimbra, and supported by the Energy and Mobility for Sustainable Regions Project CENTRO-07-0224-FEDER-002004, co-funded by the European Regional Development Fund (ERDF) through the «Programa Operacional Regional do Centro 2007–2013 (PORC)», in the framework of the «Sistema de Apoio a Entidades do Sistema Científico e Tecnológico Nacional». The work was also funded by the «Fundação para a Ciência e Tecnologia» under PEst-OE/EEI/UI0308/2014.
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Gonçalves, J., Neves, L., Martins, A.G. (2015). Multiobjective Methodology for Assessing the Location of Distributed Electric Energy Storage. In: Mora, A., Squillero, G. (eds) Applications of Evolutionary Computation. EvoApplications 2015. Lecture Notes in Computer Science(), vol 9028. Springer, Cham. https://doi.org/10.1007/978-3-319-16549-3_19
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DOI: https://doi.org/10.1007/978-3-319-16549-3_19
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