IEE   25093
INSTITUTO DE ENERGIA ELECTRICA
Unidad Ejecutora - UE
artículos
Título:
Investment Valuation of Energy Storage Systems in Distribution Networks considering Distributed Solar Generation
Autor/es:
VARGAS, ALBERTO; FLORES, DANIELA; SAMPER, MAURICIO
Revista:
IEEE LATIN AMERICA TRANSACTIONS
Editorial:
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Referencias:
Año: 2016 vol. 14 p. 1774 - 1779
ISSN:
1548-0992
Resumen:
Due to growing global awareness of climate change, increasing penetration of distributed solar generation is to be expected worldwide. When the grid integration of these intermittent renewable technologies reaches a high penetration level, technical adaptation, such as generation back-up capacity or distribution network capacity, is required. In this sense, electrical energy storage systems (ESS) offsets variations in renewable electricity production and plays a vital role in integrating these variable generation resources into the grid. In turn, ESS can be used to store excess electricity generated during off-peak demand periods for discharge at peak hours that is known as load peak-shaving, thus saving the system?s power for when it is most needed. This paper presents a comprehensive methodology for valuing investments of ESS in distribution networks with high penetration of photovoltaic distributed generation. Specifically, it is focused on the integral assessment of ESS as a flexible option for investment deferral into the expansion planning of the power grid, considering both economic and technical constraints and mainly using the ESS for load peak-shaving. The proposed methodology is tested on a typical Latin American distribution network, particularly from the San Juan Province in Argentina. For this, two expansion planning valuation are performed: one, taking into account traditional expansion alternatives and, the other, considering ESS as flexible expansion options. Results show that the greatest contribution of ESS lies in the flexibility it gives to distribution expansion planning, mainly by deferring network reinforcements.