Dynamic Distribution System Reconfiguration Considering Distributed Renewable Energy Sources and Energy Storage Systems

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...

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Bibliographic Details
Published in:IEEE systems journal Vol. 16; no. 3; pp. 3723 - 3733
Main Authors: Santos, Sergio, Gough, Matthew, Fitiwi, Desta Z., Pogeira, Jose, Shafie-khah, Miadreza, Catalao, Joao
Format: Journal Article
Language:English
Published: New York IEEE 01.09.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Alternative energy sources
Costs
Distribution systems
Electric power distribution
Electric power systems
Energy resources
Energy storage
energy storage systems (ESSs)
Load modeling
Network topologies
New technology
Power system dynamics
Reconfiguration
Renewable energy sources
renewable power generation
Renewable resources
Smart grid
Smart grid technology
stochastic mixed-integer linear programming (SMILP)
Stochastic processes
Storage systems
Switches
Switching
Uncertainty
ISSN:1932-8184, 1937-9234
Online Access:Get full text
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Summary: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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ISSN:1932-8184
1937-9234
DOI:10.1109/JSYST.2021.3135716