Frequency Control of 5 kW Self-excited Induction Generator Using Gravitational Search Algorithm and Genetic Algorithm

Author(s):  
Swati Paliwal ◽  
Sanjay Kumar Sinha ◽  
Yogesh Kumar Chauhan
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Seyed Reza Nabavi ◽  
Vahid Ostovari Moghadam ◽  
Mohammad Yahyaei Feriz Hendi ◽  
Amirhossein Ghasemi

With the development of various applications of wireless sensor networks, they have been widely used in different areas. These networks are established autonomously and easily in most environments without any infrastructure and collect information of environment phenomenon for proper performance and analysis of events and transmit them to the base stations. The wireless sensor networks are comprised of various sensor nodes that play the role of the sensor node and the relay node in relationship with each other. On the other hand, the lack of infrastructure in these networks constrains the sources such that the nodes are supplied by a battery of limited energy. Considering the establishment of the network in impassable areas, it is not possible to recharge or change the batteries. Thus, energy saving in these networks is an essential challenge. Considering that the energy consumption rate while sensing information and receiving information packets from another node is constant, the sensor nodes consume maximum energy while performing data transmission. Therefore, the routing methods try to reduce energy consumption based on organized approaches. One of the promising solutions for reducing energy consumption in wireless sensor networks is to cluster the nodes and select the cluster head based on the information transmission parameters such that the average energy consumption of the nodes is reduced and the network lifetime is increased. Thus, in this study, a novel optimization approach has been presented for clustering the wireless sensor networks using the multiobjective genetic algorithm and the gravitational search algorithm. The multiobjective genetic algorithm based on reducing the intracluster distances and reducing the energy consumption of the cluster nodes is used to select the cluster head, and the nearly optimal routing based on the gravitational search algorithm is used to transfer information between the cluster head nodes and the sink node. The implementation results show that considering the capabilities of the multiobjective genetic algorithm and the gravitational search algorithm, the proposed method has improved energy consumption, efficiency, data delivery rate, and information packet transmission rate compared to the previous methods.


2021 ◽  
Vol 12 (3) ◽  
pp. 28-53
Author(s):  
D. Santra ◽  
A. Mukherjee ◽  
K. Sarker ◽  
S. Mondal

Genetic algorithm (GA) and gravitational search algorithm (GSA) both have successfully been applied in solving ELD problems of electrical power generation systems. Each of these algorithms has their limitations and advantage. GA's global search and GSA's local search capability are their strong points while long execution period of GA and premature of convergence of GSA hinders the possibility of optimum result when applied separately in ELD problems. To mitigate these limitations, experiment is done for the first time by combining GA and GSA suitably and applying the hybrid in non-linear ELD problems of 6, 15, and 40 unit test systems. The paper reports the details of this study including comparative analysis considering similar hybrid algorithms. The result strongly attests the quality, consistency, and overall effectiveness of the GA-GSA hybrid in ELD problems.


Author(s):  
J Rajakumar ◽  
Sujatha Balaraman

In a deregulated electricity market, it may at times become challenging to swift all the essential power which are obligatory to move along the transmission line due to congestion. This paper primly waltz up the finest allotment of thyristor-controlled series compensator in deregulated capacity setup with wind generator by considering the maximization of social welfare cost as objective function. In this work, hybrid market model has been considered and the hybrid algorithm is used as a tool, in which Gravitational Search Algorithm is used for attaining optimal location of thyristor-controlled series compensator as major issue, though Genetic Algorithm-based top-notch outflow of power minimizes operating cost after incorporating thyristor-controlled series compensator and Wind Generator as sub-optimization problem. The coherence of this prospective has been tested and analyzed on modified IEEE 14-bus system and modified IEEE 118-bus system at different loading conditions. The influences on the locational marginal pricing and system voltage have been also investigated in this work and the obtained results are compared with other globally accepted techniques reported in the literary texts.


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