An Efficient Approach based Power Flow Management in Smart Grid System with Hybrid Renewable Energy Sources

2021 ◽  
Author(s):  
Suresh G. ◽  
Prasad D. ◽  
Gopila M.
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Power Flow ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Grid System ◽  
Flow Management ◽  
Efficient Approach ◽  
Smart Grid System ◽  
Hybrid Renewable Energy

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 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.

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.

Optimum utilization of grid connected hybrid renewable energy sources using hybrid algorithm

2020 ◽  
pp. 014233122091374
Author(s):  
M. Suresh ◽  
R. Meenakumari
Keyword(s):  
Renewable Energy ◽  
Tabu Search ◽  
Smart Grid ◽  
Optimization Algorithm ◽  
Renewable Energy Sources ◽  
Whale Optimization Algorithm ◽  
Computational Time ◽  
Energy Sources ◽  
Whale Optimization ◽  
Hybrid Renewable Energy

An optimal utilization of smart grid connected hybrid renewable energy sources is proposed in this paper. The hybrid technique is the combination of recurrent neural network and adaptive whale optimization algorithm plus tabu search, called AWOTS. The main objective is the RES optimum operation for decreasing the electricity production cost by hourly day-ahead and real time scheduling. Here, the load demands are predicted using AWOTS to develop the correct control signals based on power difference between source and load side. Adaptive whale optimization algorithm searching behaviour is adjusted by tabu search. The proposed technique is executed in the MATLAB/Simulink working platform. To test the performance of the proposed method, the load demand for the 24-hour time period is demonstrated. By then the power generated in the sources, such as photovoltaic, wind turbine, micro turbine and battery by the proposed technique, is analyzed and compared with existing techniques, such as genetic algorithm, particle swarm optimization and whale optimization algorithm. Furthermore, the state of charge of the battery for the 24-hour period is compared with existing techniques. Likewise, the cost of the system is compared and error in the sources also compared. The comparison results affirm that the proposed technique has less computational time (35.001703) than the existing techniques. Moreover, the proposed method is cost-effective power production of smart grid and effective utilization of renewable energy sources without wasting the available energy.

scholarly journals An Solution for Unit Commitment Problem of Wind and PV based Smart Grid using BAT Algorithm

2020 ◽  
Vol 9 (4) ◽  
pp. 120-124
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Bat Algorithm ◽  
Energy Sources ◽  
Technological Advancement ◽  
Unit Commitment Problem ◽  
Commitment Problem ◽  
Hybrid Renewable Energy

With the technological advancement, renewable energy sources are becoming more integrated to grid. With the smart grid technologies, the renewable energy sources will penetrate more into the grid. With increase of penetration of these renewable sources, will affect the unit commitment process. This paper concentrate the inducing Hybrid renewable energy sources in the smart grid. Unit commitment problem of Hybrid renewable energy sources into a smart grid is discussed in this paper . The IEEE reliable 24 bus system is considered to test the proposed unit commitment problem using bat algorithm. The paper shows the reduction of production cost when the penetration of wind power into the power system.

scholarly journals Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Arun Sukumaran Nair ◽  
Tareq Hossen ◽  
Mitch Campion ◽  
Daisy Flora Selvaraj ◽  
Neena Goveas ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Renewable Energy ◽  
Smart Grid ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Grid System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

AbstractWith the increasing integration of Distributed Energy Resources (DER) in the power grid, a decentralized approach becomes essential for scheduling and allocation of resources in a smart grid. Economic Dispatch (ED) and Unit Commitment (UC) are the two major resource allocation problems that play critical role in the safe and stable operation of a grid system. The uncertainty associated with renewable energy sources have made the resource allocation problems even more challenging for grid operators. The future grid will have a higher generation mix of renewable energy sources and a large load of Electrical vehicles, with the possibility of bi-directional power flow. This complex smart grid system necessitates the development of a decentralized approach to resource allocation problem, which allows inter-node communication and decision making. Multi-agent systems (MAS) is a promising platform to decentralize the traditional centralized resource allocation aspects of smart grid. This paper presents a comprehensive literature review on the application of MAS to Economic Dispatch (ED) and Unit Commitment (UC) in smart grids.

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