Bidding Strategy of a Wind-Thermal GENCO considering Piecewise Linear AC Power Flow and Correlated Uncertainties

In deregulated electricity markets, generation companies (GENCO) try to maximize their economic benefits considering the demand, transmission network condition, and other participants’ behaviors. The increasing penetration of renewable sources such as wind power with intermittent nature poses several challenges participation GENCOs in market. Thus, this paper presents a stochastic bilevel optimization model determine coordinated bidding strategy wind-thermal GENCO aim maximizing its profit day-ahead real-time balancing Herein, aims market upper-level problem while minimizing operation cost system lower-level problem. uncertainties demand are modeled by defining set scenarios mutual correlation using copula technique. Additionally, incorporating AC flow constraints proposed offers better solution GENCO. Further, nonlinear equations linearized piecewise approximation technique reduce computational complexity enhance accuracy optimal solution. end, developed algorithm is implemented on IEEE 24-bus RTS, simulation results provided validate efficiency applicability model. advocate that thermal unit along farm might mitigate risk uncertainties, but it causes an intense increase locational marginal price system. Importantly, indicate developing exact without compromising results. Notably, has been found would be increased 35.2% employing uncertain parameters.