Network investment planning for high penetration of wind energy under demand response program

The role of demand response becomes more crucial when there is a large penetration of intermittent renewable energy sources into the electrical grid. Flexible demand can be arranged to follow intermittent generation balancing demand and supply. Moreover, the transmission network where renewable energy resources are accommodated can constrain the capacity of green energy sources due to congestion or other operational problems. In this paper, a probabilistic approach using Monte Carlo simulation is proposed for transmission investment planning along with demand response schedule considering high penetration of wind energy resources. This work mainly aims to answer two questions i) What are the optimum transmission capacities? ii) With which consumers should the system operator negotiate to set load curtailment contracts? Several load levels for each of which consumers may have different load curtailment bids are taken into account. Also, the volatile nature of wind power is modeled in the form of normal distribution probability density functions. The correlation between outputs of wind farms exposed by a similar wind regime is considered. The transmission planning problem is modeled in the framework of a linear optimization problem. Furthermore, a nonlinear optimization process is used to analyze Monte Carlo results and calculate the most probable optimum amount of load curtailment at each bus. The whole approach is tested on the IEEE 24 bus test system.