Identification of congestion in transmission networks by power-flow solutions

Transmission congestion has become a new challenge in an open-access environment of electric power systems. In today´s world, electric transmission networks have been so much loaded that such a case has never been observed before. It is mainly because of deregulation in the electricity industry and utilization of renewable energy resources for power generation. Under these circumstances, management of transmission congestion is a crucial task to successfully operate power systems and to plan new additions to the current power grid. The first objective of this study is to determine maximum amount of possible power transfer between a load bus and a generator bus of interest in the running system. The second objective is to detect load centers that are not congested for power transmission from a newly-built power plant such as a wind farm, a solar power plant, and a small size hydro dam. In order to identify congestion in transmission networks, power-flow solutions have been examined for various load and generation levels. Under the condition that additional generation is supplied and the corresponding load is demanded, the power-flow program developed by the authors of the paper has been run. After a base case solution of the power flow is obtained, a load bus and a generator bus have been selected to apply incremental changes in real power and reactive power. The scenarios for simulations of this research work are based on applying equal amount of power as load and generation for the selected buses. To assess the real and reactive power capacities of a selected bus, the P-V curve and the Q-V curve for the selected bus have been plotted by running the power-flow program to get bus voltages versus real and reactive power. As a result of this process, the real and reactive power capacities of the selected bus and information about the congested parts of the power network have been obtained. Therefore, such information is provided for power utilities to manage power eff- - iciently and for power marketers to sell power economically.