Transmission Expansion Planning Considering Storage, Flexible AC Transmission System, Losses, and Contingencies to Integrate Wind Power

Dany H. Huanca, Djalma M. Falcão and Murilo E. C. Bento ()
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Dany H. Huanca: Department of Electrical Engineering, Federal University of Rio de Janeiro, COPPE, Rio de Janeiro 21941-901, Brazil
Djalma M. Falcão: Department of Electrical Engineering, Federal University of Rio de Janeiro, COPPE, Rio de Janeiro 21941-901, Brazil
Murilo E. C. Bento: Department of Electrical Engineering, Federal University of Rio de Janeiro, COPPE, Rio de Janeiro 21941-901, Brazil

Energies, 2024, vol. 17, issue 7, 1-23

Abstract: To meet future load projection with the integration of renewable sources, the transmission system must be planned optimally. Thus, this paper introduces a comparative analysis and comprehensive methodology for transmission expansion planning (TEP), incorporating the combined effects of wind power, losses, N-1 contingency, a FACTS, and storage in a flexible environment. Specifically, the optimal placement of the FACTS, known as series capacitive compensation (SCC) devices, is used. The intraday constraints associated with wind power and energy storage are represented by the methodology of typical days jointly with the load scenarios light, heavy, and medium. The TEP problem is formulated as a mixed-integer nonlinear programming (MINLP) problem through a DC model and is solved using a specialized genetic algorithm. This algorithm is also used to determine the optimal placement of SCC devices and storage systems in expansion planning. The proposed methodology is then used to perform a comparison of the effect of the different technologies on the robustness and cost of the final solution of the TEP problem. Three test systems were used to perform the comparative analyses, namely the Garver system, the IEEE-24 system, and a real-world Colombian power system of 93 buses. The results indicate that energy storage and SCC devices lead to a decrease in transmission requirements and overall investment, enabling the effective integration of wind farms.

Keywords: energy storage systems; N-1 contingencies; series capacitive compensation; specialized genetic algorithm; transmission expansion planning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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