Dynamic Distribution System Reconfiguration Considering Distributed Renewable Energy Sources and Energy Storage Systems
Santos, Sérgio F.; Gough, Matthew; Fitiwi, Desta Z.; Pogeira, José; Shafie-khah, Miadreza; Catalão, João P. S. (2022-01-04)
Santos, Sérgio F.
Gough, Matthew
Fitiwi, Desta Z.
Pogeira, José
Shafie-khah, Miadreza
Catalão, João P. S.
IEEE
04.01.2022
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2022112366573
https://urn.fi/URN:NBN:fi-fe2022112366573
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© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Tiivistelmä
Electric power systems are in state of transition as they attempt to evolve to meet new challenges provided by growing environmental concerns, increases in the penetration of distributed renewable energy sources (DRES) as well as the challenges associated with integrating new technologies to enable smart grids. New techniques to improve the electrical power system, including the distribution system, are thus needed. One such technique is dynamic distribution system reconfiguration (DNSR), which involves altering the network topology during operation, providing significant benefits regarding the increased integration of DRES. This paper lays out an improved model which aimed to optimize the system operation in a coordinated way, where DRES, energy storage systems (ESS) and DNSR are considered as well as the uncertainty of these resources. The objective function was modeled to incentivize the uptake of DRES by considering the cost of emissions to incentivize the decarbonization of the power system. Also, the switching costs were modeled to consider not only the switching, but also the cost of degradation of these mechanisms in the system operation. Two systems are used to validate the model, the IEEE 119-bus system, and a real system in São Miguel Island. The results of this paper show that using DNSR, DRES, and ESS can lead to a significant 59% reduction in energy demand through a 24-hour period. In addition, using these technologies results in a healthier, more efficient, and higher quality system. This shows the benefits of using a variety of smart grid technologies in a coordinated manner.
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