Optimal Planning and Bidding Strategy for Wind Farms in Joint Balancing and Day-Ahead Energy Markets

Due to the fact that wind farms have a meagre operating cost, it is expected that their optimum utilization in the transmission network would improve the economic and technical condition of the network. Henceforth, this work aims to allocate wind farms' locations in the transmission network while persuading the farm owners to participate in the balancing and day-ahead energy markets. The proposed scheme is formulated in the form of a bi-level optimization model. The upper-level problem aims to maximize wind farms' profit in joint day-ahead and balancing markets bounded by the location and operational constraints. On the other hand, the lower-level problem provides the operating model of the transmission network. Herein, the network operator is in authority to minimize the operational cost of non-renewable resources, considering the linearized AC power flow and technical constraints of resources. Then, the Karush-Kuhn-Tucker is adopted to extract the proposed scheme single-level model. One of the eminent novelties of this work is to propose a linear model for wind farms and to introduce an incentive plan for farm owners in the energy market by considering bidding errors. In the end, by implementing this scheme on IEEE 6-bus and 24-bus transmission networks, the numerical outcomes indicate the proposed scheme's potential to improve the economic and operational status of wind farms and the transmission network. With linear programming based on optimum utilization of wind farms, the utilization of traditional units, energy prices, energy plans, and the maximum voltage drop are reduced by 35%, 15%, 20%, and 21%, respectively, compared to the cases without wind farms penetrations.