Implementation of a load side management algorithm for an islanded microgrid powered by renewable energy sources

Author(s):  
S Anoop ◽  
K Ilango ◽  
J L Nandagopal ◽  
Manjula G Nair
Author(s):  
N.S. Srivatchan ◽  
P. Rangarajan

Growing demand for clean and green power has increased penetration of renewable energy sources into microgrid. Based on the demand supply, microgrid can be operated in grid connected mode and islanded mode. Intermittent nature of renewable energy sources such as solar and wind has lead to number of control challenges in both modes of operation. Especially islanded microgrid throws power quality issues such as sag, swell, harmonics and flicker. Since medical equipments, semiconductor factory automations are very sensitive to voltage variations and therefore voltage sag in an islanded microgrid is of key significance. This paper proposes a half cycle discrete transformation (HCDT) technique for fast detection of voltage sag in an islanded microgrid and thereby provides fast control action using dynamic voltage restorer (DVR) to safe guard the voltage sensitive equipments in an islanded microgrid.  The detailed analysis of simulation results has clearly demonstrated the effectiveness of proposed method detects the voltage sag in 0.04 sec and there by improves the voltage profile of islanded microgrid.


Author(s):  
Dimosthenis Verginadis ◽  
Athanasios Karlis

Background: The scope of this paper is to study the energy trading in microgrids. Microgrids are low voltage or medium voltage distribution networks, which consist of energy storage systems, electric loads, e.g. electric vehicles and Renewable Energy Sources (RES). Methods: Legacy energy grids are being transformed by the introduction of small to medium sized individual or cooperative, mostly RES invested energy producers and prosumers. Electric vehicles penetrate the market and modern power grids integrate them as ancillary services providers when there are peak domestic loads, as well as in order to balance grid voltage aiming to increase system reliability, compensating for renewable energy sources’ intermittency and volatility in energy production. Results: An elaborate management algorithm is proposed in this paper, to balance demand and local renewable energy sources microgrid supply. Conclusion: Finally, the results of simulations of different scenarios, including economic parameters and proposals for future research are presented.


Energies ◽  
2018 ◽  
Vol 11 (5) ◽  
pp. 1161 ◽  
Author(s):  
Hadi Kordkheili ◽  
Mahdi Banejad ◽  
Ali Kalat ◽  
Edris Pouresmaeil ◽  
João Catalão

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Qing Duan ◽  
Wanxing Sheng ◽  
Haoqing Wang ◽  
Caihong Zhao ◽  
Chunyan Ma

One of the main challenges in microgrid system energy management is dealing with uncertainties such as the power output from renewable energy sources. The classic two-stage robust optimization (C-TSRO) method was proposed to cope with these uncertainties. However, this method is oriented to the worst-case scenario and is therefore somewhat conservative. In this study, focusing on the energy management of a typical islanded microgrid and considering uncertainties such as the power output of renewable energy sources and the power demand of loads, an expected-scenario-oriented two-stage robust optimization (E-TSRO) method is proposed to alleviate the conservative tendency of the C-TSRO method because the E-TSRO method chooses to optimize the system cost according to the expected scenario instead, while ensuring the feasibility of the first-stage variables for all possible scenarios, including the worst case. According to the structural characteristics of the proposed model based on the E-TSRO method, a column-and-constraint generation (C & CG) algorithm is utilized to solve the proposed model. Finally, the effectiveness of the E-TSRO model and the solution algorithm are analysed and validated through a series of experiments, thus obtaining some important conclusions, i.e., the economic efficiency of system operation can be improved at about 6.7% in comparison with the C-TSRO results.


2021 ◽  
Vol 292 ◽  
pp. 116879
Author(s):  
Md. Fatin Ishraque ◽  
Sk. A. Shezan ◽  
M.M. Ali ◽  
M.M. Rashid

IEE Review ◽  
1991 ◽  
Vol 37 (4) ◽  
pp. 152
Author(s):  
Kenneth Spring

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