scholarly journals Exact relaxation of complementary constraints for optimal bidding strategy for electric vehicle aggregators

2021 ◽  
Author(s):  
Dapeng Chen ◽  
Zhaoxia Jing ◽  
Zhigang Li ◽  
Hedong Xu ◽  
Tianyao Ji
Keyword(s):  
Electric Vehicle ◽  
Bidding Strategy ◽  
Optimal Bidding

User-comfort oriented optimal bidding strategy of an electric vehicle aggregator in day-ahead and reserve markets

2020 ◽  
Vol 122 ◽  
pp. 106194 ◽  
Author(s):  
İbrahim Şengör ◽  
Alper Çiçek ◽  
Ayşe Kübra Erenoğlu ◽  
Ozan Erdinç ◽  
João P.S. Catalão
Keyword(s):  
Electric Vehicle ◽  
Bidding Strategy ◽  
Optimal Bidding ◽  
User Comfort

Bilateral bidding strategy in joint day-ahead energy and reserve electricity markets considering techno-economic-environmental measures

2021 ◽  
pp. 0958305X2110148
Author(s):  
Mojtaba Shivaie ◽  
Mohammad Kiani-Moghaddam ◽  
Philip D Weinsier
Keyword(s):  
Electricity Market ◽  
Large Scale ◽  
Search Algorithm ◽  
Power Grid ◽  
Mathematical Formulation ◽  
Test System ◽  
Bidding Strategy ◽  
Level Problem ◽  
Optimal Bidding ◽  
Environmental Measures

In this study, a new bilateral equilibrium model was developed for the optimal bidding strategy of both price-taker generation companies (GenCos) and distribution companies (DisCos) that participate in a joint day-ahead energy and reserve electricity market. This model, from a new perspective, simultaneously takes into account such techno-economic-environmental measures as market power, security constraints, and environmental and loss considerations. The mathematical formulation of this new model, therefore, falls into a nonlinear, two-level optimization problem. The upper-level problem maximizes the quadratic profit functions of the GenCos and DisCos under incomplete information and passes the obtained optimal bidding strategies to the lower-level problem that clears a joint day-ahead energy and reserve electricity market. A locational marginal pricing mechanism was also considered for settling the electricity market. To solve this newly developed model, a competent multi-computational-stage, multi-dimensional, multiple-homogeneous enhanced melody search algorithm (MMM-EMSA), referred to as a symphony orchestra search algorithm (SOSA), was employed. Case studies using the IEEE 118-bus test system—a part of the American electrical power grid in the Midwestern U.S.—are provided in this paper in order to illustrate the effectiveness and capability of the model on a large-scale power grid. According to the simulation results, several conclusions can be drawn when comparing the unilateral bidding strategy: the competition among GenCos and DisCos facilitates; the improved performance of the electricity market; mitigation of the polluting atmospheric emission levels; and, the increase in total profits of the GenCos and DisCos.

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