Stochastic long-term transmission expansion planning with HVDC links

The ever-increasing load demand all across the world has led to increasing the demand for energy. The major part of this demand is supplied through conventional power plants with fossil fuels. Recently, the concern on environmental emissions has increased, which in turn put pressure on power systems as one of the main sectors in contributing to environmental emissions. Accordingly, different countries have started installing renewable energies to alleviate these concerns and mitigate environmental emissions. These green technologies have been being installed either as centralized plants, for example, wind farms, or as distributed energy resources (DERs) in distribution networks. If such huge wind farms connect to the transmission system, they may bring severe challenges to the system, such as transmission network congestion. On the other hand, in some cases, these wind sites are located far from the main power system. Thus, it is required to expand the existing power system by constructing new corridors to connect them to the transmission system. High voltage DC technologies have also been introduced as efficient systems with numerous merits. In this regard, this dissertation seeks to address the long-term AC/DC transmission expansion planning to connect distant wind farms to the power system. The problem has been modeled both deterministically and stochastically within a multi-objective mixed-integer quadratically constrained programming framework, aimed at minimizing the total cost and transmission line loading. The total cost is comprised of the total investment cost and the total operating cost. Then, the problem is solved by using the normal boundary intersection method as an efficient mathematical multi-objective optimization technique, and the most preferred solution has been selected by utilizing the VIKOR decision maker. Different case studies have also been evaluated by simulating the problem using the Garver test system and IEEE reliability test system.