Transmission expansion planning with re-design

Transmission Expansion Planning with Re-design - A Greedy Randomized Adaptive Search Procedure

Transmission expansion planning with re-design has been recently proposed in the literature to improve on the classical transmission expansion planning by allowing to cut-off circuits while expanding the network. Although the reductions in the solution costs are significant, the resulting mixed-integer linear programming formulations are very difficult to solve exactly for large networks. In th...

Transmission expansion planning based on merchandizing surplus of transmission lines

This paper proposes an optimal transmission expansion planning (TEP) which is based on determining share of each line in merchandizing surplus (MS) of system, determining by Independent System Operator (ISO). The more share of a line in MS of system denotes the priority of a line for expansion. The procedure of determining MS of each line in a power system is based on determining the MS share o...

A Transmission Expansion Planning Model for Maximizing Merchant Investment

transmission expansion planning based on merchandizing surplus of transmission lines

this paper proposes an optimal transmission expansion planning (tep) which is based on determining share of each line in merchandizing surplus (ms) of system, determining by independent system operator (iso). the more share of a line in ms of system denotes the priority of a line for expansion. the procedure of determining ms of each line in a power system is based on determining the ms share o...

Transmission Network Expansion Planning with Simulation Optimization

Within the electric power literature the transmission expansion planning problem (TNEP) refers to the problem of how to upgrade an electric power network to meet future demands. As this problem is a complex, non-linear, and non-convex optimization problem, researchers have traditionally focused on approximate models of power flows. Existing approaches are often tightly coupled to the approximat...