A Multi-Objective Approach for Available Transfer Capability Considering Capability Curve of DFIG Wind Farm

All participants in the electricity market can access to transmission network and may try to generate electricity from cheaper sources for greater revenue margins. This could result in transmission congestion, which could then violate voltage and thermal limitations, jeopardizing the security of the system. To solve this, Available Transfer Capability (ATC) must be accurately estimated to ensure system security and enable renewable energy producers to participate in the market with minimum risk. Additionally, to ensure economic and environmentally friendly power transactions in electricity markets, ATC must be accurately determined, minimizing generation and emission costs while fully utilizing installed VAR devices. Therefore, this paper presents a multi-objective approach to find the optimal solution for installed VAR devices to maximize ATC and minimize both generation and emission costs while considering voltage stability constraints and uncertainty of wind energy. Furthermore, the reactive capability curve of the Doubly fed induction generator (DFIG) of a wind turbine is fully utilized to enhance the objective of the approach. A hybrid algorithm based on the primal-dual interior point method (PDIPM) and a multi-objective grey wolf optimizer (MOGWO) is suggested for solving the problem. The performance of the proposed approach has been evaluated by its application on the IEEE 30- Reliability Test System (RTS). The results confirm that the proposed approach effectively maximizes ATC and minimizes generation and emission costs by optimizing the use of installed VAR devices and the reactive capability of wind farms. Additionally, the method can identify the most severe contingency for each wind scenario.