Optimal transformer loss of life management in day-ahead scheduling of wind-rich power systems at the presence of dynamic ratings

Abstract

Integration of wind power generations within today's power has faced power grid operators with challenges such as variable power generation and congestion issues. To settle these problems, the power system operators can make use of smart-grid technologies, one of which is dynamic rating of power equipment. In this paper, optimal day-ahead scheduling of wind-rich power systems is implemented at the presence of dynamic line rating (DLR) and dynamic transformer rating (DTR). Employing DTR brings about higher loading of transformer endangering its lifetime as costly instrument; hence, the thermal modeling of the transformer has been incorporated into the proposed model of this paper to avoid transformer's loss of life (LOL). All the constraints of the day-ahead AC optimal power flow have been considered to compose an optimization model which is programmed in the GAMS and optimized by appropriate solvers. Several experiments have been accomplished on the IEEE 24-bus system where the simulation results clearly demonstrate efficacy of the conducted approach.