Power flow management scheme of hybrid renewable energy source to maximize power transfer capability using I2HOSOA approach

2020 ◽  
Vol 39 (3) ◽  
pp. 4159-4181
Author(s):  
P. Annapandi ◽  
R. Banumathi ◽  
N.S. Pratheeba ◽  
A. Amala Manuela
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Power Flow ◽  
Reactive Power ◽  
Active Power ◽  
Grid System ◽  
Flow Management ◽  
Control Signals ◽  
Active And Reactive Power ◽  
Smart Grid System

Due to the intermittent nature of renewable sources, the generation of power is varied which is the main problem in renewable energy system. Miss-matching between the power generation and load power causes a deviation from the desired voltage and frequency in power supply. Therefore, a new efficient smart grid system is required for an optimal power flow management. In this paper, a hybrid approach is presented for power flow management of HRES connected smart grid system. The novelty of the proposed approach is the combined execution of IHHO with SOA named as I2HOSOA technique. In the established work, the HHO is integrated by crossover and mutation function, it is known as IHHO. The main contribution of the proposed strategy is to control the power flow based on source and load side parameters variations. In the proposed approach, the control signals of the voltage source are developed by the IHHO based on the variety of power exchange between the source and load side. Similarly, the online control signals are located by the SOA procedure by utilizing the parallel execution against the active and reactive power varieties. The multi-objective function is shaped by the grid required active and reactive power varieties created based on accessible source power. Here, the control parameters of the power controller are enhanced by the proposed technique based control models in light of the power flow varieties. The comparison between established and existing methods is analyzed in terms of reactive current injection, grid code, current amplitude limitation control, active power control, zero active power oscillations, and injection of active and reactive power. Furthermore, the statistical evaluation of established, and existing methods of mean, median, and standard deviation, is evaluated. Finally, the proposed model is executed in MATLAB/Simulink working platform and the execution is compared with the existing techniques.

Hybrid renewable energy systems for power flow management in smart grid using an efficient hybrid technique

2020 ◽  
Vol 42 (11) ◽  
pp. 2068-2087
Author(s):  
Kumaravel Sureshkumar ◽  
Vijayakumar Ponnusamy
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Power Flow ◽  
Search Algorithm ◽  
Energy Sources ◽  
Grid System ◽  
Flow Management ◽  
Control Signals ◽  
Smart Grid System ◽  
Hybrid Renewable Energy

Efficient approach for power flow management of hybrid renewable energy system connected smart grid system is proposed in this paper. Here, the proposed approach is the combination of both the modified elephant herding optimization algorithm with tabu search algorithm named as MEHOTSA. In the proposed technique, the modified elephant herding optimization algorithm plays out the assessment procedure to establish the exact control signals for the system and builds up the control signals database for the offline way in light of the power variety between source side and the load side. The multi-objective function is shaped by the grid required active power and reactive power varieties generated based on the accessible source power. The accomplished dataset is used to work the Tabu search algorithm on the online way and it leads the control procedure in less execution time. The proposed technique-based control model enhances the control parameters of the power controller in light of the power flow varieties. By utilizing the proposed methodology, the power flow management of the smart grid system is controlled dependent on the source side and load side parameters varieties. Additionally, the proposed methodology is in charge of controlling the energy sources so as to produce the power demanded by the grid, utilizing optimally both renewable energy sources and energy storage devices. Finally, the proposed model be actualized in MATLAB/Simulink platform and the performance are compared with other techniques.

An efficient control strategy for optimal power flow management from a renewable energy source to a generalized three-phase microgrid system: A hybrid squirrel search algorithm with whale optimization algorithm approach

2020 ◽  
Vol 42 (11) ◽  
pp. 1960-1976 ◽  
Author(s):  
M Durairasan ◽  
Divya Balasubramanian
Keyword(s):  
Energy Source ◽  
Renewable Energy ◽  
Power Flow ◽  
Reactive Power ◽  
Search Algorithm ◽  
Energy Sources ◽  
Flow Management ◽  
Control Signals ◽  
Active And Reactive Power ◽  
Whale Optimization

This paper introduces a hybrid approach for power flow management (PFM) of the hybrid renewable energy source (HRES) connected microgrid (MG) system. Here, the proposed approach is the combination of both the squirrel search algorithm (SSA) with whale optimization algorithm (WOA) named as SSAWO. Here, the SSA is developing the control signals of the voltage source inverter subject to the difference of power exchange between the source side and load side. The multi-objective function is shaped by the grid required active and reactive power varieties generated based on the accessible source power. The WOA procedures guarantee to locate the online control signals by utilizing the parallel execution against the active and reactive power varieties. The proposed technique-based control model enhances the control parameters of the power controller in light of the power flow varieties. By using the proposed methodology, the PFM of the MG system is controlled based on the source side and load side parameters variations. In order to render the power demand by the grid, the present system is accountable for dominating the energy sources using, optimally, both renewable energy sources and energy storage devices. Finally, the proposed model is implemented in MATLAB/Simulink working platform and the execution equates with the existing techniques.

An elitist control scheme for power flow management in smart grid system: a hybrid optimization scheme

2021 ◽  
pp. 1-22
Author(s):  
Ganapathia Pillai Kannayeram ◽  
Rathinam Muniraj ◽  
Nattanmai Balasubramanian Prakash ◽  
Thankaswamy Jarin ◽  
Sivadhas Rosejanet Boselin Prabhu​
Keyword(s):  
Smart Grid ◽  
Power Flow ◽  
Hybrid Optimization ◽  
Grid System ◽  
Optimization Scheme ◽  
Flow Management ◽  
System A ◽  
Control Scheme ◽  
Smart Grid System

An efficient optimal power flow management based microgrid in hybrid renewable energy system using hybrid technique

2020 ◽  
pp. 014233122096168
Author(s):  
P Annapandi ◽  
R Banumathi ◽  
NS Pratheeba ◽  
A Amala Manuela
Keyword(s):  
Renewable Energy ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Spotted Hyena ◽  
Flow Management ◽  
Control Signals ◽  
Optimal Power ◽  
Hybrid Renewable Energy

In this paper, the optimal power flow management-based microgrid in hybrid renewable energy sources with hybrid proposed technique is presented. The photovoltaic, wind turbine, fuel cell and battery are also presented. The proposed technique is the combined execution of both spotted hyena optimization and elephant herding optimization. Spotted hyena optimization is utilized to optimize the combination of controller parameters based on the voltage variation. In the proposed technique, the spotted hyena optimization combined with elephant herding optimization plays out the assessment procedure to establish the exact control signals for the system and builds up the control signals for offline way in light of the power variety between source side and load side. The objective function is defined by the system data subject to equality and inequality constraints such as real and reactive power limits, power loss limit, and power balance of the system and so on. The constraint is the availability of the renewable energy sources and power demand from the load side in which the battery is used only for lighting load. By utilizing the proposed method, the power flow constraints are restored into secure limits with the reduced cost. At that point, the proposed model is executed in the Matrix Laboratory/Simulink working platform and the execution is assessed with the existing techniques. In this article, the performance analysis of proposed and existing techniques such as elephant herding optimization, particle swarm optimization, and bat algorithm are evaluated. Furthermore, the statistical analysis is also performed. The result reveals that the power flow of the hybrid renewable energy sources by the proposed method is effectively managed when compared with existing techniques.

Ant Lion Optimizer for Solving Unit Commitment Problem in Smart Grid System

2017 ◽  
Vol 8 (1) ◽  
pp. 129 ◽  
Author(s):  
Izni Nadhirah Sam’on ◽  
Zuhaila Mat Yasin ◽  
Zuhaina Zakaria
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Unit Commitment ◽  
Energy Resources ◽  
Grid System ◽  
Renewable Energy Resources ◽  
Unit Commitment Problem ◽  
Commitment Problem ◽  
Ant Lion ◽  
Smart Grid System

<p>This paper proposed the integration of solar energy resources into the conventional unit commitment. The growing concern about the depletion of fossil fuels increased the awareness on the importance of renewable energy resources, as an alternative energy resources in unit commitment operation. However, the present renewable energy resources is intermitted due to unpredicted photovoltaic output. Therefore, Ant Lion Optimizer (ALO) is proposed to solve unit commitment problem in smart grid system with consideration of uncertainties .ALO is inspired by the hunting appliance of ant lions in natural surroundings. A 10-unit system with the constraints, such as power balance, spinning reserve, generation limit, minimum up and down time constraints are considered to prove the effectiveness of the proposed method. The performance of proposed algorithm are compared with the performance of Dynamic Programming (DP). The results show that the integration of solar energy resources in unit<em> commitment scheduling can improve the total operating cost significantly. </em></p>

scholarly journals Intelligent Automation System for Smart Grid Renewable Energy Generation on Climatic Changes

2021 ◽  
Vol 3 (3) ◽  
pp. 199-213
Author(s):  
Joy Iong-Zong Chen ◽  
Kong-Long Lai
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Energy Generation ◽  
Climatic Changes ◽  
Maintenance Cost ◽  
Automation System ◽  
Generation Process ◽  
Grid System ◽  
Smart Grid System ◽  
Renewable Energy Generation

Nature oriented power generation systems are considered as renewable energy sources. Renewable energy generations are safe to the environment and nature, in terms of minimal radiation and pollution. The space requirement, operational and maintenance cost of renewable energy generation stations are also comparatively lesser than the conventional generating stations. The new form of micro grid energy stations of 230Volt supply attract the small commercial users and the domestic users. The smart grid energy generation is widely employed in the place where the conventional energy supply is not available. Due to its simple construction process, the smart grid renewable energy stations are employed on certain national highways as charging stations for electric vehicles and as a maintenance centre. The motive of the proposed work is to alert the smart grid system with an intelligent algorithm for making an efficient energy generation process on various climatic changes. This reduces the energy wastage in the primary smart grid station and makes the system more reliable on all conditions. The performance of the proposed approach is compared with a traditional smart grid system which yielded a satisfactory outcome.

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