Optimal power flow management in a photovoltaic nanogrid with batteries

Author(s):  
Su Sheng ◽  
Peng Li ◽  
Chung-Ti Tsu ◽  
Brad Lehman
Author(s):  
P Annapandi ◽  
R Banumathi ◽  
NS Pratheeba ◽  
A Amala Manuela

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.


Author(s):  
Chandrashekhar N Bhende ◽  
Swasti Panda ◽  
Sukumar Mishra ◽  
Arun Narayanan ◽  
Tero Kaipia ◽  
...  

Abstract This paper presents optimal power flow management in real time for grid connected photovoltaic (PV)–battery system. The objective is the real time, dynamic and optimal scheduling of battery storage which reduces grid power consumption and achieves the peak load shaving. For this purpose, two strategies are developed; one is rule-based and other is optimization algorithm based. Two strategies are compared, pros and cons of those strategies are established. Though rule-based technique is simple & easy to implement, the optimization technique provides more optimal regulation of battery which provides the lesser electricity cost. Forecasted PV/load powers are used to get optimal value of battery power. In order to handle uncertainties due to forecasted data, fuzzy-based corrective strategy is developed to modify the reference battery power as per the present values of PV/load powers. The proposed analysis is carried out for over one exemplary day. The simulations are presented using typical load/PV data of India and Finland as a part of research collaboration. Experimental results are also carried out using proposed scheme.


2011 ◽  
Vol 2 (3) ◽  
pp. 309-320 ◽  
Author(s):  
Y Riffonneau ◽  
S Bacha ◽  
F Barruel ◽  
S Ploix

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