A multi-objective optimization for energy management in a renewable micro-grid system: A data mining approach

2014 ◽  
Vol 6 (2) ◽  
pp. 023127 ◽  
Author(s):  
Mehdi Parvizimosaed ◽  
Farid Farmani ◽  
Ashkan Rahimi-Kian ◽  
Hassan Monsef
2014 ◽  
Vol 651-653 ◽  
pp. 1037-1045
Author(s):  
Ming Xu ◽  
Wen Bin Xiang

With the development of distributed generation technology rapidly, a large number of wind, solar and other renewable energy access to access system . Since renewable energy is intermittent and stochastic, which posed economic dispatch system a serious challenge. Consider the system operating costs and sewage expenses, the paper constructs multi-objective micro-grid system economic dispatch model composed by the wind turbine, diesel engine, battery and load. And through MATLAB / Simulink simulation, model is established to verify the correctness and effectiveness.


2021 ◽  
pp. 1-24
Author(s):  
Sanjay Kumar ◽  
R. K. Saket ◽  
P. Sanjeevikumar ◽  
Jens Bo Holm‐Nielsen

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 403
Author(s):  
Deyaa Ahmed ◽  
Mohamed Ebeed ◽  
Abdelfatah Ali ◽  
Ali S. Alghamdi ◽  
Salah Kamel

Optimal inclusion of a photovoltaic system and wind energy resources in electrical grids is a strenuous task due to the continuous variation of their output powers and stochastic nature. Thus, it is mandatory to consider the variations of the Renewable energy resources (RERs) for efficient energy management in the electric system. The aim of the paper is to solve the energy management of a micro-grid (MG) connected to the main power system considering the variations of load demand, photovoltaic (PV), and wind turbine (WT) under deterministic and probabilistic conditions. The energy management problem is solved using an efficient algorithm, namely equilibrium optimizer (EO), for a multi-objective function which includes cost minimization, voltage profile improvement, and voltage stability improvement. The simulation results reveal that the optimal installation of a grid-connected PV unit and WT can considerably reduce the total cost and enhance system performance. In addition to that, EO is superior to both whale optimization algorithm (WOA) and sine cosine algorithm (SCA) in terms of the reported objective function.


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