High voltage step-up is necessary in several applications, especially considering that dc-ac converters must be supplied by high dc voltages. The conventional boost converter is the most popular topology for this purpose, although the conversion efficiency is limited at high duty cycle values. In order to overcome such limitation and improve the conversion ratio, many converter topologies have been proposed so far. Within this context, this work intends to review some of the most important works regarding boost-based dc-dc converters. Some structures are covered and classified basically as converters with and without wide conversion ratio. Some of the main advantages and drawbacks regarding the existing approaches are also discussed. Finally, a proper comparison is established among the most significant converters regarding the voltage stress across the semiconductor elements, number of components, and static gain.

This paper proposes a two-stage framework to solve the long-term transmission network expansion planning (TNEP) problem ensuring user-defined reliability levels and wind curtailment over the planning horizon. In the first stage, the static TNEP (S-TNEP) problem is solved to define where a set of new lines must be installed at the end of planning horizon. In the second stage, a multistage procedure is performed to solve the dynamic TNEP (D-TNEP) in order to determine the moment that each transmission line should be built. Both S-TNEP and D-TNEP are decomposed into investment decision and performance assessment through a bi-level scheme based on Benders decomposition; thus, the reliability is considered and evaluated over the planning process. The reliability and performance indexes are obtained through the non-chronological Monte Carlo simulation considering the random behavior of transmission lines failures, load fluctuations and uncertainties over wind availability. The loss of wind probability performance index is introduced to measure the probability of wind curtailment in each connection point of the system, and it is used to prevent wind farms from being underused. The proposed methodology is tested in modified versions of the 24-bus IEEE reliability test system and the IEEE 118-bus test system. Keywords Transmission expansion planning • Wind power generation • Reliability assessment • Monte Carlo simulation • Benders decomposition • Short-term uncertainties Sets and subscripts B Set of system buses E Set of existing lines C Set of candidate lines Ω E i Set of existing lines connected to bus i Ω C i Set of candidate lines connected to bus i i System bus i j Line between buses i and j k Existing or candidate transmission lines s Operative state B A. N. de Paula

This paper proposes a framework based on the Benders decomposition to obtain a scenario-based robust static transmission expansion planning by considering N-1 security criterion, transmission losses and uncertainties in wind power generation. The model is solved by a bi-level approach that seeks to minimize investment cost as well as penalty costs of wind spill and load curtailment. The wind uncertainty is modeled by grouped historical wind series through k-means clustering technique maintaining the wind correlation between different geographic regions. Case studies are performed in the well-known power systems: IEEE-RTS 24-bus test system and an equivalent Brazilian Southern 46-bus system. In addition, a detailed tutorial case is also presented with a modified version of Garver 6-bus test system. Keywords Transmission expansion planning • Transmission active losses • Benders decomposition • N-1 security criterion • Wind power uncertainty • k-means clustering algorithm List of Symbols Subscripts and Superscripts i System bus i j Branch between terminal buses i and j ki j Transmission line in branch i j c Operational state w Wind scenario s Iteration number Variables pg iwc Active power generation at bus i, scenario w and state c (MW) rd iwc Load shedding at bus i, scenario w and state c (MW) r w iwc Wind spilled at bus i, scenario w and state c (MW) θ i jwc Angular difference between terminal buses i and j in scenario w and state c (rad) f E ki jwc Active power flow of existing line k in branch i j, for scenario w and state c (MW) f C ki jwc Active power flow of candidate line k in branch i j, for scenario w and state c (MW)

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