scholarly journals Generalized optimal placement of PMUs considering power system observability, communication infrastructure, and quality of service requirements

2020 ◽  
Vol 10 (3) ◽  
pp. 2824
Author(s):  
M. M. H. Elroby ◽  
S. F. Mekhamer ◽  
H. E. A. Talaat ◽  
M. A. Moustafa Hassan
Keyword(s):  
Power System ◽  
Minimum Spanning Tree ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Base Station ◽  
Optimal Placement ◽  
Binary Particle Swarm Optimization ◽  
Communication Infrastructure ◽  
Control Center ◽  
System Observability

This paper presents a generalized optimal placement of Phasor Measurement Units (PMUs) considering power system observability, reliability, Communication Infrastructure (CI), and latency time associated with this CI. Moreover, the economic study for additional new data transmission paths is considered as well as the availability of predefined locations of some PMUs and the preexisting communication devices (CDs) in some buses. Two cases for the location of the Control Center Base Station (CCBS) are considered; predefined case and free selected case. The PMUs placement and their required communication network topology and channel capacity are co-optimized simultaneously. In this study, two different approaches are applied to optimize the objective function; the first approach is combined from Binary Particle Swarm Optimization-Gravitational Search Algorithm (BPSOGSA) and the Minimum Spanning Tree (MST) algorithm, while the second approach is based only on BPSOGSA. The feasibility of the proposed approaches are examined by applying it to IEEE 14-bus and IEEE 118-bus systems.

scholarly journals Binary Spring Search Algorithm for Solving Various Optimization Problems

2021 ◽  
Vol 11 (3) ◽  
pp. 1286 ◽  
Author(s):  
Mohammad Dehghani ◽  
Zeinab Montazeri ◽  
Ali Dehghani ◽  
Om P. Malik ◽  
Ruben Morales-Menendez ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
High Performance ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Bat Algorithm ◽  
Search Space ◽  
Binary Particle Swarm Optimization ◽  
Dragonfly Algorithm ◽  
Grasshopper Optimization Algorithm

One of the most powerful tools for solving optimization problems is optimization algorithms (inspired by nature) based on populations. These algorithms provide a solution to a problem by randomly searching in the search space. The design’s central idea is derived from various natural phenomena, the behavior and living conditions of living organisms, laws of physics, etc. A new population-based optimization algorithm called the Binary Spring Search Algorithm (BSSA) is introduced to solve optimization problems. BSSA is an algorithm based on a simulation of the famous Hooke’s law (physics) for the traditional weights and springs system. In this proposal, the population comprises weights that are connected by unique springs. The mathematical modeling of the proposed algorithm is presented to be used to achieve solutions to optimization problems. The results were thoroughly validated in different unimodal and multimodal functions; additionally, the BSSA was compared with high-performance algorithms: binary grasshopper optimization algorithm, binary dragonfly algorithm, binary bat algorithm, binary gravitational search algorithm, binary particle swarm optimization, and binary genetic algorithm. The results show the superiority of the BSSA. The results of the Friedman test corroborate that the BSSA is more competitive.

scholarly journals Optimized Wireless Sensor Node Multidimensional Routing using Fuzzy Clustering and Chaotic Gravitational Search Algorithm

2021 ◽  
Vol 3 (1) ◽  
pp. 40-48
Author(s):  
Sivaganesan D
Keyword(s):  
Sensor Node ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Base Station ◽  
Wireless Sensor ◽  
Destination Node ◽  
Wireless Sensor Node ◽  
Search Spaces ◽  
Gravitational Search

A network of tiny sensors located at various regions for sensing and transmitting information is termed as wireless sensor networks. The information from multiple network nodes reach the destination node or the base station where data processing is performed. In larger search spaces, the clustering mechanisms and routing solutions provided by the existing heuristic algorithms are often inefficient. The sensor node resources are depleted by un-optimized processes created by reduced routing and clustering optimization levels in large search spaces. Chaotic Gravitational Search Algorithm and Fuzzy based clustering schemes are used to overcome the limitations and challenges of the conventional routing systems. This enables effective routing and efficient clustering in large search spaces. In each cluster, among the available nodes, appropriate node is selected as the cluster head. Reduction in delay, increase in energy consumption, increase in network lifetime and improvement of the network clustering accuracy are evident from the simulation results.

scholarly journals Modified SCA algorithm for SSSC damping Controller design in Power System

2017 ◽  
Vol 16 (1) ◽  
pp. 46-63 ◽  
Author(s):  
Bidyadhar Rout ◽  
B.B. Pati ◽  
S. Panda
Keyword(s):  
Power System ◽  
Transient Stability ◽  
Controller Design ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Differential Evolution Algorithm ◽  
Operating Conditions ◽  
Bench Mark ◽  
Single Machine Infinite Bus ◽  
System Stabilizer

This paper studies the improvement of transient stability of a single-Machine Infinite-Bus (SMIB) power system using Proportional Derivative (PD) type Static Synchronous Series Compensator (SSSC) and damping controllers. The design problem has been considered as optimisation problem and a modified version of recently proposed Sine Cosine Algorithm (SCA) has been employed for determining the optimal controller parameters. Proposed modified SCA (mSCA) algorithm is first tested using bench mark test functions and compared with SCA, and other heuristic evolutionary optimization algorithms like Grey Wolf optimization (GWO), Particle Swarm optimization (PSO), Gravitational Search algorithm (GSA) and Differential Evolution algorithm to show its superiority. The proposed mSCA algorithm is then applied to optimize simultaneously the PD type lead lag controller parameters pertaining to SSSC and power system stabilizer(PSS). The proposed controller provides sufficient damping for power system oscillation in different operating conditions and disturbances. Results analysis reveal that proposed mSCA technique provides higher effectiveness and robustness in damping oscillations of the power system and increases the dynamic stability more.

Optimal Placement and Sizing of TCSC using Gravitational Search Algorithm

2012 ◽  
Vol 10 (5) ◽  
Author(s):  
Purwoharjono Purwoharjono ◽  
Muhammad Abdillah ◽  
Ontoseno Penangsang ◽  
Adi Soeprijanto
Keyword(s):  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Optimal Placement ◽  
Gravitational Search
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