Flexible Transmission in the Smart Grid
- Author(s): Hedman, Kory Walter
- Advisor(s): Oren, Shmuel S
- et al.
There is currently a national push to create a smarter electric grid; introducing new technologies that will create a more controllable and flexible grid is part of the smart grid concept and integral to its success. The full control of transmission assets are not currently built into electric energy dispatch optimization models. Optimal transmission switching is a straightforward way to leverage grid controllability: to make better use of the existing system and meet growing demand with existing infrastructure. Previous research has shown that transmission switching as a corrective mechanism can help relieve line overloading, voltage violations, etc. However, there has been limited focus on the use of transmission switching as a means to improve the economic efficiency of the network by incorporating the control of transmission assets into the overall economic dispatch problem.
This research discusses the ways that the modeling of flexible transmission assets can benefit the multi-trillion dollar electric industry. It presents and analyzes novel formulations by which the operator can incorporate this flexibility into the economic dispatch formulation. This research focuses on modeling transmission assets so that they can be temporarily taken out of service, i.e., by opening breakers, or kept in service, i.e., by keeping the breakers closed. By incorporating this control into the network optimization problem, this provides the ability for the operator to consider the state of a transmission line as a decision variable instead of treating it as a static asset, which is the current practice today. The possible benefits demonstrated from this research indicate that the benefits to society are substantial. On the contrary, the benefits to individual market participants are uncertain; some will benefit and other will not. Consequently, this research also analyzes the impacts that optimal transmission switching may have on market participants as well as the policy implications. Methods to improve the solution time of this difficult problem are discussed as well.