University of Mohaghegh Ardabili Journal of Operation and Automation in Power Engineering 2322-4576 12 4 2024 12 01 Robust Optimal Coordinated Charging Bidding of Ancillary Services for the Vehicle to Grid in Regulation and Spinning Reserve Markets بهینه ساز مقاوم اتصال شارژر خدمات جانبی برای وسیله نقلیه الکتریکی متصل به شبکه جهت تنظیم و رزرو چرخان 326 336 2728 10.22098/joape.2023.11840.1884 EN S. Lotfi Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran M. Sedighizadeh Faculty of Electrical Engineering, Shahid Beheshti University, Evin, Tehran, Iran R. Abbasi Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran S.H. Hosseinian Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran Journal Article 2022 07 20 Vehicle to grid (V2G) is one the most important ways to effectively integrate electric vehicles (EVs) with electric power systems. The important benefits can be made by V2G such as reducing/increasing the cost/revenue of EV owners and technically sup-porting electric power systems. Concerning technical and regulatory constraints, EV owners must participate in electricity mar-kets via aggregators. This paper proposes a robust optimal coordinated charging (OCC) model including bidding ancillary ser-vices for regulation and spinning reserve markets. The presented work handles the uncertain behavior of the electricity market that are ancillary service prices and their deployment signals by the robust optimization approach. The aim of optimization is the maximization of the aggregator’s profits from V2G by joining the ancillary services markets. The recommended robust OCC model which is a robust linear problem (RLP) model is simulated by the CPLEX solver in GAMS software. An assumed set of 10000 EVs in the electric reliability council of Texas (ERCOT) electricity markets is considered for doing simulations.  Employ-ing the presented model in this test system shows the efficacy of the proposed model in comparison to other deterministic and stochastic models.  https://joape.uma.ac.ir/article_2728_c0793be6905d74052eab5db71853847b.pdf