Assessment of Voltage Stability Using Network Equivalent

 In this paper a fast system voltage stability index (FSVSI) has been proposed to assess overall system voltage stability of a multi-bus power system at a particular operating point using the concept of two bus network equivalent.  A universal direct voltage stability index has also been explored to assess local (DVSI) as well as overall system voltage stability (DSVSI). An index called system transmission quality factor (STQF) has been developed to assess the power transmission quality of the overall system in the context of voltage stability. Two FACTS controllers, TCSC and STATCOM have also been incorporated in the present study to observe their effectiveness to ensure voltage stabilty. STATCOM has been found to be superior in order to improve voltage stability of power system as compared to TCSC. The developed concept has been validated using practical India Easten Grid (WBSEB system) and it has a high potential of on-line application

Hybrid solar cell with TiO2 film: BBOT polymer and copper phthalocyanine as sensitizer

An organic-inorganic hybrid solar cell was fabricated using Titanium dioxide (TiO2): 2,5-bis(5-tert-butyl-2-benzoxazolyl) thiophene (BBOT) film and Copper Phthalocyanine (CuPc) as a sensitizer. BBOT was used in photodetector in other reported research works, but as per best of our knowledge, it was not implemented in solar cells till date. The blend of TiO2: BBOT blend was used to fabricate the film on ITO-coated glass and further a thin layer of CuPc was coated on the film. This was acted as photoanode and another ITO coated glass with a platinum coating was used as a counter electrode (cathode). An optimal blend of acetonitrile (solvent) (50-100%), 1,3-dimethylimidazolium iodide (10-25%), iodine (2.5-10%) and lithium iodide, pyridine derivative and thiocyanate was used as electrolytes in the hybrid solar cell. The different structural, optical and electrical characteristics were measured. The Hybrid solar cell showed a maximum conversion efficiency of 6.51%

Improvement of Distribution Network Performance by Optimally Allocating EV Charging Station

With zero emissions to the environment, electric vehicles (EVs) are the most environmentally friendly mode of transportation. The placement of EV charging stations (EVCS) in the Radial Distribution Network (RDN) is necessary to satisfy the demand of charging in various places while minimizing power loss on the power system networks. In the distribution system, distributed generation (DG) not only reduces power loss but also enhances power quality. To fully utilize the benefits of DG, it is necessary to find the optimal location and size in the distribution system. In this work, the ideal installation of EVCS has been consistently demonstrated in the IEEE 33 bus distribution network. In order to provide widespread charging facilities, the RDN has been split into three regions, and it has been established that each area has one charging station placed. The main purpose is to minimize the Active Power Loss and Voltage Deviation Index (VDI) to maintain a healthy power system network. Adding DG to the appropriate EV Station is obtained through optimization. This problem has been formulated as a problem of optimization for finding the best location to install EVCS in the IEEE 33 bus RDN by using the Symbiotic Organisms Search (SOS) algorithm. The obtained results have been validated and compared using the Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA)

Voltage Stability Prediction on Power Networks using Artificial Neural Networks

 The objective of this paper is to predict the secure or the insecure state of the power system network using a hybrid technique which is a combination of Artificial Neural Network (ANN) and voltage stability indexes. Voltage collapse or an uncontrollable drop in voltage occurs in a system when there is a change in the condition of the system or a system is overloaded. A Transference Index (TI) which acts as a voltage stability indicator has been formulated from the equivalent two-bus network of a multi-bus power system network, which has been tested on a standard IEEE 30-bus system and the result is validated with a standard Fast Voltage Stability Index (FVSI). FACTS devices in the critical bus have been considered for the improvement of the voltage stability of the system. An ANN based supervised learning algorithm has been conferred in this paper alongside Contingency Analysis (CA) for the prediction of voltage security in an  IEEE 30 - bus power system network.

Water evaporation algorithm: A new metaheuristic algorithm towards the solution of optimal power flow

A relatively new technique to solve the optimal power flow (OPF) problem inspired by the evaporation (vaporization) of small quantity water particles from dense surfaces is presented in this paper. IEEE 30 bus and IEEE 118 bus test systems are assessed for various objectives to determine water evaporation algorithm’s (WEA) efficiency in handling the OPF problem after satisfying constraints. Comparative study with other established techniques demonstrate competitiveness of WEA in treating varied objectives. It achieved superior results for all the objectives considered. The algorithm is found to minimize its objective values by great margins even in case of large test system. Statistical analysis of all the cases using Wilcoxon’s signed rank test resulted in p-values much lower than the required value of 0.05, thereby establishing the robustness of the applied technique. Best performance of the algorithm are obtained for voltage deviation minimization and voltage stability index minimization objectives in case of IEEE 30 and IEEE 118 bus test systems respectively