Optimizing the transmission line cost of a fault tolerance network to promote green power usage

Green power is clean without pollution, such as solar and wind power. It has become a resolution to supplement the deficiency of today's high cost/danger energy resources. A challenge is to integrate these distributed resources into the power grid. The high cost and voltage drop of running long transmission lines motivate the way to minimize the length by serializing their connections to load centers. This introduces a risk that the loss of a transmission line section can disconnect multiple green power resources. Our previous study proposed an idea of a fault tolerance network, in which every power resource has at least two independent connections to the load centers. Preliminary studies showed that fault tolerance can be achieved with reasonable extra transmission line expenses. The objective of this paper is to develop an artificial intelligence algorithm to identify possible Steiner points into the network. The new network intends to further reduce the cost without compromising the reliability.