Implementation and Optimal Sizing of TCSC for the Solution of Reactive Power Planning Problem Using Quasi-Oppositional Salp Swarm Algorithm

2021 ◽  
Vol 10 (2) ◽  
pp. 74-103
Author(s):  
Saurav Raj ◽  
Sheila Mahapatra ◽  
Chandan Kumar Shiva ◽  
Biplab Bhattacharyya
Keyword(s):  
Reactive Power ◽  
Transmission Loss ◽  
Optimal Placement ◽  
Planning Problem ◽  
Index Method ◽  
Salp Swarm Algorithm ◽  
Optimal Coordination ◽  
Swarm Algorithm ◽  
Reactive Power Planning ◽  
Bus System

In this article, innovative algorithms named as salp swarm algorithm (SSA) and hybrid quasi-oppositional SSA (QOSSA) techniques have been proposed for finding the optimal coordination for the solution of reactive power planning (RPP). Quasi-oppositional based learning is a promising technique for improving convergence and is implemented with SSA as a new hybrid method for RPP. The proposed techniques are successfully implemented on standard test systems for deprecation of real power losses and overall cost of operation along with retention of bus voltages under acceptable limits. Optimal planning has been achieved by minimizing reactive power generation and transformer tap settings with optimal placement and sizing of TCSC. Identification of weakest branch in the power network is done for optimal TCSC placement and is tendered through line stability index method. Optimal TCSC placement renders a reduction in transmission loss by 8.56% using SSA and 8.82% by QOSSA in IEEE 14 bus system and 7.57% using SSA and 9.64% by QOSSA in IEEE 57 bus system with respect to base condition.

A Hybrid GWO-PSO technique for the solution of Reactive Power Planning Problem

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
New England ◽  
Reactive Power ◽  
Heuristic Algorithms ◽  
Transmission Loss ◽  
Operating Cost ◽  
Optimal Solution ◽  
Planning Problem ◽  
Power Sources ◽  
Solution Strategies ◽  
Reactive Power Planning

Over the years the optimization in various areas of power system has immensely attracted the attention of power engineers and researchers. RPP problem is one of such areas. This is done by the placement of reactive power sources in the weak buses and thereafter minimizing the operating cost of the system which is directly dependent on the system transmission loss. The work proposed in this article utilizes FVSI method to detect the weak bus. GWO-PSO is proposed in the current work for providing optimal solution to RPP problem. To test the efficacy of the proposed technique, comparative analysis is then performed among the variants of PSO and hybrid GWO-PSO. The optimal solution rendered by the proposed method is compared with other heuristic algorithms. The proposed method of GWO-PSO generates a reduction of 4.25% in operating cost for IEEE 30 bus and 5.99% for New England 39 bus system. The comparison thus yields that the GWO-PSO hybrid method is superior in generating optimality, diversity and is efficient to generate solution strategies for RPP even in a practical power network.

A Hybrid GWO-PSO technique for the solution of Reactive Power Planning Problem

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
New England ◽  
Reactive Power ◽  
Heuristic Algorithms ◽  
Transmission Loss ◽  
Operating Cost ◽  
Optimal Solution ◽  
Planning Problem ◽  
Power Sources ◽  
Solution Strategies ◽  
Reactive Power Planning

Over the years the optimization in various areas of power system has immensely attracted the attention of power engineers and researchers. RPP problem is one of such areas. This is done by the placement of reactive power sources in the weak buses and thereafter minimizing the operating cost of the system which is directly dependent on the system transmission loss. The work proposed in this article utilizes FVSI method to detect the weak bus. GWO-PSO is proposed in the current work for providing optimal solution to RPP problem. To test the efficacy of the proposed technique, comparative analysis is then performed among the variants of PSO and hybrid GWO-PSO. The optimal solution rendered by the proposed method is compared with other heuristic algorithms. The proposed method of GWO-PSO generates a reduction of 4.25% in operating cost for IEEE 30 bus and 5.99% for New England 39 bus system. The comparison thus yields that the GWO-PSO hybrid method is superior in generating optimality, diversity and is efficient to generate solution strategies for RPP even in a practical power network.

scholarly journals Optimal Nonlinear Adaptive Control for Voltage Source Converters via Memetic Salp Swarm Algorithm: Design and Hardware Implementation

Processes ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 490 ◽  
Author(s):  
Yueping Jiang ◽  
Xue Jin ◽  
Hui Wang ◽  
Yihao Fu ◽  
Weiliang Ge ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Reactive Power ◽  
Voltage Source ◽  
Voltage Source Converter ◽  
Control Performance ◽  
Parameter Uncertainties ◽  
Nonlinear Adaptive Control ◽  
Salp Swarm Algorithm ◽  
Operation Conditions ◽  
Swarm Algorithm

Voltage source converter (VSC) has been extensively applied in renewable energy systems which can rapidly regulate the active and reactive power. This paper aims at developing a novel optimal nonlinear adaptive control (ONAC) scheme to control VSC in both rectifier mode and inverter mode. Firstly, the nonlinearities, parameter uncertainties, time-varying external disturbances, and unmodelled dynamics can be aggregated into a perturbation, which is then estimated by an extended state observer (ESO) called high-gain perturbation observer (HGPO) online. Moreover, the estimated perturbation will be fully compensated through state feedback. Besides, the observer gains and controller gains are optimally tuned by a recent emerging biology-based memetic salp swarm algorithm (MSSA), the utilization of such method can ensure a desirably satisfactory control performance. The advantage of ONAC is that even though the operation conditions are constantly changing, the control performance can still be maintained to be globally consistent. In addition, it is noteworthy that in rectifier mode only the reactive power and DC voltage are required to be measured, while in inverter mode merely the reactive power and active power have to be measured. At last, in order to verify the feasibility of ONAC in practical application, a hardware experiment is implemented.

scholarly journals Loss Minimization in Optimal Reactive Power Planning (ORPP) Based on Whale Optimization Algorithm

2018 ◽  
Vol 7 (3.15) ◽  
pp. 192
Author(s):  
Muhammad Hakimin Nasru ◽  
Ismail Musirin ◽  
Mohamad Khairuzzaman Mohamad Zamani ◽  
Siti Rafidah Abdul Rahim ◽  
Muhamad Hatta Hussain ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Optimal Allocation ◽  
Reactive Power ◽  
Transmission Loss ◽  
Whale Optimization Algorithm ◽  
Loss Minimization ◽  
Power Scheduling ◽  
Whale Optimization ◽  
Reactive Power Planning ◽  
Better Than

The key of RPP is the optimal allocation of reactive power considering location and size. This paper presents the loss minimization in optimal reactive power planning (ORPP) based on Whale Optimization Algorithm (WOA). The objective is to minimize transmission loss by considering several load conditions at bus 3, bus 15 and bus 21. Reactive Power Scheduling (RPS) and Transformer Tap Changer Setting (TTCS) were set as the control variables. Validation was conducted on the IEEE 30 Bus RTS. Results from the study indicate that the proposed WOA can minimize transmission loss better than Evolutionary Programming (EP). 

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