# Integration of High Voltage AC/DC Grids into Modern Power Systems
## 2 Integration of High Voltage AC/DC Grids into Modern Power Systems  
[PERSON], et al. [7], in their paper entitled \"Field Optimization and Electrostatic Stress Reduction of Proposed Conductor Scheme for Pliable Gas-Insulated Transmission Lines\", performs the geometric and electrostatic field optimization for Flexible Gas-Insulated Transmission Lines (FGILs) regarding stranded conductors. Also, the impact of conductor irregularity on field dispersion is investigated, and a Semiconducting Film (SCF)-coated stranded conductor is suggested as a potential candidate for FGILs. Owing to the performed optimized design, an 11 kV scaled-down model of a 132 kV FGIL is fabricated to practically investigate the electrostatic and dielectric stresses in the FGIL through an HV experimental setup. [PERSON], et al. [8], in their paper entitled \"An Improved Mixed AC/DC Power Flow Algorithm in Hybrid AC/DC Grids with MT-HVDC Systems\", proposes a mixed AC/DC Power Flow (PF) algorithm for hybrid AC/DC grids with Multi-Terminal High-Voltage Direct Current (MT-HVDC)systems. The proposed strategy is a fast and accurate method, which is capable of optimizing the AC/DC PF calculations. Except for the high accuracy and optimized performance, considering all operational constraints and control objectives of the integration of MT-HVDC systems into the large-scale AC grids is the other contribution of this paper. The calculated results by the mixed AC/DC PF problem can be used for the planning, scheduling, state estimation, small-signal stability analyses. The mixed AC/DC PF algorithm is applied to a five-bus AC grid with a three-bus MT-HVDC system and the modified IEEE 39-bus test system with two four-bus MT-HVDC systems (in two different areas), which are all simulated in MATLAB software. To check the performance of the mixed AC/DC PF algorithm, different cases are considered. [PERSON], et al. [9], in their paper entitled \"Multi-Objective Optimal Reactive Power Planning under Load Demand and Wind Power Generation Uncertainties Using \(\varepsilon\)-Constraint Method\", attempts to address Reactive Power Planning (RPP) as a probabilistic multi-objective problem to reduce the total cost of reactive power investment, minimize the active power losses, maximize the voltage stability index, and improve the loadability factor. The generators' voltage magnitude, the transformers tap settings, and the output reactive power of the VAR sources are considered as the main control variables. To deal with the probabilistic multi-objective RPP problem, the \(\varepsilon\)-constraint technique is employed. To validate the efficiency of the proposed method, the IEEE 30-bus test system is implemented in the GAMS environment under five various conditions. [PERSON], et al. [10], in their paper entitled \"Effect of Ionic Conductors on the Suppression of PTC and Carrier Emission of Semiconductive Composites\", discusses the Positive Temperature Coefficient (PTC) effects of electrical resistivity in perovskite \(La_{0.6}F_{0.4}CoO_{3}\) (LSC) particle-dispersed semiconductive composites of HVDC cables based on experimental results from Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM) and a semiconductive resistance test device. [PERSON], et al. [11], in their paper entitled \"Optimal Scheduling of Large-Scale Wind-Hydro-Thermal Systems with Fixed-Head Short-Term Model\", implements a Modified Adaptive Selection Cuckoo Search Algorithm (MASCSA) for determining the optimal operating parameters of a hydrothermal system and a wind-hydro-thermal system, to minimize the total electricity generation cost from all available thermal power plants. The fixed-head short-term model of hydropower plants is taken into consideration. All hydraulic constraints, such as initial and final reservoir volumes, the upper limit and lower limit of reservoir volume, and water balance of reservoir, are seriously considered. The proposed MASCSA competes with the conventional Cuckoo Search Algorithm (CSA) and Snap-Drift Cuckoo Search Algorithm (SDCSA).