Resiliency assessment of the distribution system considering smart homes equipped with electrical energy storage, distributed generation and plug-in hybrid electric vehicles
Jafarpour, Pourya; Nazar, Mehrdad Setayesh; Shafie-khah, Miadreza; Catalao, Joao P.S. (2022-11-15)
Jafarpour, Pourya
Nazar, Mehrdad Setayesh
Shafie-khah, Miadreza
Catalao, Joao P.S.
Elsevier
15.11.2022
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2023020826391
https://urn.fi/URN:NBN:fi-fe2023020826391
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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 presents a novel method for resiliency assessment of the distribution system considering smart homes' arbitrage strategies in the day-ahead and real-time markets. The main contribution of this paper is that the impacts of smart homes' arbitrage strategy on the resilient operation of the distribution system are explored. The optimal commitment of smart homes in external shock conditions is another contribution of this paper. An arbitrage index is proposed to explore the impacts of this process on the system costs and resiliency of the system. A two-level optimization process is proposed for day-ahead and real-time markets. At the first stage of the first level, the optimal bidding strategies of smart homes are estimated for the day-ahead market. Then, the database is updated and the optimal bidding strategies of smart homes for real-time horizon are assessed in the second stage of the first level problem. At the first stage of the second level problem, the optimal day-ahead scheduling of the distribution system is performed considering the arbitrage and resiliency indices. At the second stage of the second level, the distribution system optimal scheduling is carried out for the real-time horizon. Finally, at the third stage of the second level, if an external shock is detected, the optimization process determines the optimal dispatch of system resources. The proposed method is assessed for the 33-bus and 123-bus IEEE test systems. The proposed framework reduced the expected values of aggregated costs of 33-bus and 123-bus systems by about 62.14 % and 32.06 % for the real-time horizon concerning the cases in which the smart homes performed arbitrage strategies. Furthermore, the average values of the locational marginal price of 33-bus and 123-bus systems were reduced by about 59.38 % and 63.98 % concerning the case that the proposed method was not implemented.
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