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Publication . Article . Conference object . 2022

A Modified Progressive Hedging Approach for Multistage Intraday Trade of EV Aggregators

Priyanka Shinde; Iasonas Kouveliotis-Lysikatos; Mikael Amelin; Meng Song;
Open Access
Published: 01 Nov 2022
Publisher: KTH, Elkraftteknik
Country: Sweden

The growing prominence of electric vehicle (EV) aggregators in the modern power system is drawing more attention towards modeling their behavior in the short-term electricity markets. The demand-side flexibility offered by the EVs can be leveraged to reduce their charging costs. In this paper, the participation of an EV aggregator in the intraday and balancing market is modeled as a multistage stochastic programming problem. The computational complexity introduced by the peculiarities of the intraday market is solved by a progressive hedging algorithm (PHA), a scenario-based decomposition technique. A randomized scenario sampling approach is implemented to accelerate the PHA which is further improved with a parallel randomized PHA. Finally, an asynchronous version of the parallel randomized PHA is leveraged to speed up the multistage model of EV aggregator trading. We compare the computation time of the modified versions of the PHA algorithm with the conventional PHA for the proposed EV aggregator model. Furthermore, we also show the value of EV aggregator trading in the intraday and balancing markets by comparing its cost to baseline models. QC 20220629

Subjects by Vocabulary

ACM Computing Classification System: Hardware_MEMORYSTRUCTURES


Intraday electricity market, randomized progressive hedging, multistage stochastic programming, Electrical Engineering, Electronic Engineering, Information Engineering, Elektroteknik och elektronik, Electrical and Electronic Engineering, Energy Engineering and Power Technology

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