Impact of wind uncertainty, plug-in-electric vehicles and demand response program on transmission network expansion planning

The aim of this paper is to minimize the total cost of the system by incorporating wind power and plug-in-electric vehicles (PEVs) along with demand response (DR) program. The methodologies have proposed in contrast with the conventional algorithm in which the transmission line investment cost has been minimized without considering the dynamism of the deregulated environment. Moreover, the transmission network planning enhances the competitiveness of the power market, where more market players can participate. In this situation, the network planner has an important role in assessing the needs for transmission investments. Now-a-days practice of the network planner is to utilize more renewable power resources, PEVs and implementation of different electricity price tariffs. To achieve more benefits of PEVs and wind energy, their optimal utilization is a major concern. This paper proposes a mathematical model for solving the combined effect of PEVs and wind power integration with incentive-based DR program on static transmission network expansion planning (STNEP) problem. To solve this non-linear and non-convex problem, a nature-inspired optimization algorithm named gbest-guided artificial bee colony algorithm (GABC) is applied due to its robustness. The algorithm’s performance is evaluated through modified IEEE 24-bus, Brazilian 46-bus and Colombian 93-bus system. The test results indicate that the combined effect of DR, PEVs and wind has reduced the total system cost significantly.