A novel meta-heuristic approach for optimal RPP using series compensated FACTS controller

G., Swetha Shekarappa; Mahapatra, Sheila; Raj, Saurav

doi:10.1016/j.iswa.2023.200220

Cited by 4 publications

(2 citation statements)

References 20 publications

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“…Adaryani M. R. and Karami A. implemented the ABC algorithm to find the best settings of the control variables for multi-objective OPF problems in a multi-objective framework [27]. Transmission loss minimization with thyristor-controlled series compensator (TCSC) using modified harmony search optimization (MHSO) at different bus systems was presented in [28] and [29].…”

Section: S Perez-london Et Al Have Proposed Contingency Ranking By Co...mentioning

confidence: 99%

FACTS placement for reactive power planning with weak node constraints using an improved symbiotic search algorithm

Gupta,

Mishra,

Babu

2023

TESEA

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In this paper, an economically feasible and reliable operation of the IEEE 57 bus system for Optimal Power Flow (OPF) is proposed. The Improved Symbiotic Organisms Search (ISOS) algorithm is proposed for effective reactive power planning as an OPF issue. Further, the optimal position of Flexible AC Transmission Systems (FACTS) is taken into consideration, by including the existing system controlling variables like reactive power generators output, transformer tapping and capacitors connected at shunt. The objective of the work is two-fold; i.e., to reduce the energy loss and to enhance the voltage profile within the prescribed limit by ensuring the economic operation and investment cost of FACTS in the system. In this work, two FACTS devices like Static Var Compensator (SVC) and Thyristor-Controlled Series Controller (TCSC) have been taken into consideration. Voltage sensitivity indicator and reactive power flow are two tools that are utilised in order to locate weak nodes for the implementation of FACTS. Finally, the performance of the ISOS algorithm is compared with that of three other state- of-the -art optimization techniques, such as, Symbiotic Organisms Search (SOS), Differential Evolution (DE) and Teaching Learning Based Optimization (TLBO). A Non-parametric statistical analysis is also performed to investigate the dominance of the ISOS algorithm over others.

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Section: S Perez-london Et Al Have Proposed Contingency Ranking By Co...mentioning

confidence: 99%

FACTS placement for reactive power planning with weak node constraints using an improved symbiotic search algorithm

Gupta,

Mishra,

Babu

2023

TESEA

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“…Saurav et al 26 find out the best position for the Photo-Voltaic system through voltage collapse proximity index (VCPI) to reduce losses and voltage deviation with the help of ETAP. Saurav et al 27 proposed an Oppositional based Harris Hawks Optimization (OHHO) to solve reactive power planning problems through series compensation. Saurav et al 28 implemented a hybrid Chaotic Chimp Optimization Algorithm (CCOA) to reduce the operating cost under ORPD through series compensation.…”

Section: Introductionmentioning

confidence: 99%

An enhanced arithmetic optimization algorithm for optimal control of reactive power

Sahay,

Upputuri,

Kumari

et al. 2023

Optim Control Appl Methods

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In this article, an enhanced arithmetic optimization algorithm (EAOA) is utilized to resolve the optimal reactive power dispatch problem (ORPD) of power plants, which is a non‐linear, non‐smooth, complex optimization problem. Typically, it is formulated as a constrained optimal power flow problem. This paper utilizes the gamma distribution to generate initial random solutions, which improves the accuracy of the arithmetic optimization algorithm (AOA). The original mode of deviation of math optimizer accelerated (MOA) is replaced with the improved pattern of change in the prey's energy in Harris Hawk Optimization (HHO), which creates a superior balance between the exploration and exploitation of AOA. This paper implements logarithmic and exponential operators in place of division and multiplication operators, which improves the exploration ability of AOA and also utilizes the gamma distribution in the generation of random numbers, which are essential for the selection of operators in both search phase which enlarges the search area and improves the global optimum solution. A parametric analysis is performed on 10 benchmark functions for nine possible values before selecting the algorithm's initial parameters. A comparative statistical analysis along with Friedman's test is carried out on 23 benchmark functions to test the overall performance as compared to Sine‐Cosine Algorithm (SCA), Swarm‐Salp Algorithm, Grey Wolf Optimization (GWO), and basic Arithmetic Optimization Algorithm (AOA). EAOA is applied to the IEEE 57 bus system for optimal reactive power control. EAOA reports a significant reduction in a power loss of 23.2 MW, which is 18.596% smaller than the system's base case power loss of 28.5 MW as compared to Artificial Bee Colony (ABC), Firefly Algorithm (FA), Bat‐inspired Algorithm (BAT), Cuckoo Search Algorithm (CSA), and Modified Ant Lion Algorithm (MALO) which reports a reduction in a power loss of 14.73%, 15.43%, 15.43%, 16.14%, and 16.14% respectively. EAOA reduces the TVD to 0.76 pu, compared to ABC, FA, BAT, CSA, and MALO, which minimizes the TVD to 0.84, 0.82, 0.88, 0.82, and 0.79, respectively. This proves that EAOA performs better in resolving ORCP problems regarding the quality of solutions and convergence. A detailed comparative statistical analysis of EAOA with CSA, BAT, and WOA (Whale Optimization Algorithm) is conducted in terms of Probability Distribution Functions (PDF) and Cumulative Distribution Functions (CDF), along with the Wilcoxson sign rank test, which proves that EAOA gives the solution with a higher degree of precision.

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A Novel Technique for High-Performance Grid Integrated with Restricted Placement of PV-DG considering Load Change

Soliman,

Emara,

Hassan

2024

Journal of Electrical and Computer Engineering

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The distributed generation (DG) units’ penetrations in power systems are becoming more prevalent. The majority of recent studies are now focusing on how to best position and size PV-DG units to further improve grid performance. In actuality, and as a result of ideal design requirements, the size and position of the PV are chosen and executed, and no luxury for a change. In this work, the PV-DG unit sizing and location were determined and placed beforehand. Also, load change is a fact and is to be highly considered in the grid. Studying the grid performance and how to enhance it under these conditions is the main objective of this study. This examination was executed using an IEEE 15 bus system in a MATLAB environment. Distribution lines were proposed to connect the PV-DG from its restricted location to the required bus. The purpose of this study is therefore to evaluate the grid’s performance with various actual loads on each bus while connecting a PV-DG unit through a distribution line while taking the available transfer capacity (ATC) of the network into account to find the optimally connected bus. The results said that the optimally connected bus is changed by changing the load which is not doable on land. The results obtained indicate that breaking up PV-DG units into smaller units in the same location and connecting them to every bus was the best option for improving grid performance.

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A novel meta-heuristic approach for optimal RPP using series compensated FACTS controller

Cited by 4 publications

References 20 publications

FACTS placement for reactive power planning with weak node constraints using an improved symbiotic search algorithm

FACTS placement for reactive power planning with weak node constraints using an improved symbiotic search algorithm

An enhanced arithmetic optimization algorithm for optimal control of reactive power

A Novel Technique for High-Performance Grid Integrated with Restricted Placement of PV-DG considering Load Change

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