Abstract
Inrecent electrical power networks a number of failures due to overloading of the transmission lines, stability problems, mismatch in supply and demand, narrow scope for expanding the transmission network and other issues like global warming, environmental conditions, etc. have been noticed. In this paper, a thyristor-controlled series compensator (TCSC) is placed at the optimum position by using two indices for enhancing the power flows as well as the voltage security and power quality of the integrated system. A fusedseverity index is proposed for the optimal positionalong with a grey wolf algorithm-based optimal tuning of the TCSC for reduction of real power losses, fuel cost with valve-point effect, carbon emissions, and voltage deviation in a modern electrical network. The voltage stability index to evaluate the power flow of the line and a novel line stability indexto assessthe line capacityare used. The TCSC is placed at the highest value of the fusedseverity index. In addition, an intermittent severity index (IMSI) is used to find the most severely affected line and is used for relocating the TCSC to a better location under different contingencies.Lognormal and Weibull probability density functions (PDFs)are utilized forassessing the output ofphotovoltaic (PV) and wind power. The proposed methodhas been implemented on the IEEE 57 bus system to validate the methodology, and the results of the integrated system with and without TCSC are comparedunder normal and contingency conditions.
Highlights
In the recent past interest in distributed generation has increased tremendously due to the cost of fuel, carbon footprint concerns, load demand, and its delivery ofclean power, etc
This paper predominantly focuses on optimal power flow-based generation reallocation of a renewable integrated power system in the absence and presence of thyristor-controlled series compensator (TCSC) utilizing a grey wolf algorithm
The multi-objective task consists of active power loss, carbon emission, voltage deviation and fuel cost with valve-point impact has been formulated for optimum tuning of TCSC using grey wolf optimization
Summary
In the recent past interest in distributed generation has increased tremendously due to the cost of fuel, carbon footprint concerns, load demand, and its delivery ofclean power, etc. The electrical power system is facing various problems like network communication, load demand, environmentalconstraints and limited expansion of lines that influencethe sustainability and reliability These issues have encouragedresearchersto utilize solar and wind generation for the reduction of transmission losses, carbon emissions and fuel cost. Bhattacharyya et al [23] demonstrated the optimal TCSC location aimed at the enhancement of power flow by setting the control parameters like generator outputs, tap changing transformers, etc.Over the last two decades, many metaheuristics algorithms have been developed. This paper predominantly focuses on optimal power flow-based generation reallocation of a renewable integrated power system in the absence and presence of TCSC utilizing a grey wolf algorithm. The multi-objective task consists of active power loss, carbon emission, voltage deviation and fuel cost with valve-point impact has been formulated for optimum tuning of TCSC using grey wolf optimization. It is verified for different conditions like normal loading andcontingency conditions
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