Transmission-constrained optimal allocation of price-maker wind-storage units in electricity markets
Chabok, Hossein; Aghaei, Jamshid; Sheikh, Morteza; Roustaei, Mahmoud; Zare, Mohsen; Niknam, Taher; Lehtonen, Matti; Shafie-khah, Miadreza; Catalão, João P.S. (2022-03-15)
Chabok, Hossein
Aghaei, Jamshid
Sheikh, Morteza
Roustaei, Mahmoud
Zare, Mohsen
Niknam, Taher
Lehtonen, Matti
Shafie-khah, Miadreza
Catalão, João P.S.
Elsevier
15.03.2022
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2023020926648
https://urn.fi/URN:NBN:fi-fe2023020926648
Kuvaus
vertaisarvioitu
© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Tiivistelmä
This paper proposes an optimal allocation of a Wind-Storage Unit (WSU). Since transmission lines congestion varies according to the size, the location, and the operation of a generation unit in power systems, we assess the optimal location of a unit as a function of its variable operating condition. An independently operated wind-storage unit is assumed as a price-maker that seeks to maximize its market payoff without any prior information on optimally locating the wind and storage units. The main problem is provided as a tri-level optimization problem in which the first level is the WSU profit maximization, the second level is the power system operation cost minimization from the perspective of the independent system operator (ISO), and the third level is the maximization of the robustness of the system by using an appropriate transmission switching interval robust based chance constrained (TSIRC) method in order to minimize the operation cost of the system and transmission lines congestion problem. The tri-level model is converted to a bi-level optimization model by using Karush-Kuhn-Tucker (KKT) conditions provided as a Mathematical Programming with Equilibrium Constraint (MPEC). An effective binary particle swarm optimization algorithm (BPSO) is used in order to find the optimal location of the wind and storage units. Unscented Transform (UT) as a key element is suggested to model the uncertainties associated with the output power of the wind turbines. The proposed method is tested on an IEEE 24-bus test system and the results reveal the validity of this work.
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