Real time simulator for microgrids

Magro, Micaela Caserza; Giannettoni, M.; Pinceti, P.; Vanti, M.

doi:10.1016/j.epsr.2018.03.018

Cited by 30 publications

(19 citation statements)

References 9 publications

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“…In the design stage, it is necessary to calculate dynamic behavior of the microgrid, debug the communication system and I/O, debug and validate different control methods, and tune control parameter. A well‐known double approach is to define the architecture, size the devices, and analyze the performance of the system in the area of energy, cost, and power quality in software simulation then verify and validate control and communication system in RT simulator Real‐time simulations Based on previous researches, RT simulation can be classified as shown in Figure .…”

Section: Real‐time Modeling and Simulationmentioning

confidence: 99%

“… Design and implementation of hardware in the loop Several sophisticated control strategies are developed to handle microgrid control and management and maintain its stability. While in the grid‐connected operation mode, the main aim is to optimize energy efficiency and maximizing integration level of RES generation, in islanded mode there are several technical issues like availability, reliability, and power quality that must be considered . The increasing complexity of microgrids caused an ongoing demand for more detail studies and even in some cases use of HIL platforms .…”

Section: Real‐time Modeling and Simulationmentioning

confidence: 99%

“…Grid connected Microgrid trades power with the main grid. [12][13][14][15][16][17][18][19][20][21][22][23][24]36 Islanded Consumers loads are supplied uninterrupted without electrical connection of microgrid and main grid. [21][22][23][24][25][26][27][28][29][30][31][32][33][34] Transition Process of islanding microgrid by upstream switches at the PCC during disturbances in main grid or resynchronization with the main grid once the disturbance is removed [36][37][38][39][40] FIGURE 2 Sample reconfiguration process flowchart 45…”

Section: Operation Mode Description Referencesmentioning

confidence: 99%

“…In this context, real‐time (RT) simulations and hardware‐in‐the‐loop (HIL) technology are beneficial mainly because of their easily reconfigurable test environment. In the latter, all system variables are accessible, and there is a good possibility of testing different scenarios and cases with the same hardware setup . It is also worth mentioning that an RT simulation is a promising approach for validating advance and complex control strategies designed for microgrid and also determining exact values of control parameters and debugging them.…”

Section: Introductionmentioning

confidence: 99%

“…In the latter, all system variables are accessible, and there is a good possibility of testing different scenarios and cases with the same hardware setup. 12,13 It is also worth mentioning that an RT simulation is a promising approach for validating advance and complex control strategies designed for microgrid and also determining exact values of control parameters and debugging them. As a result, significant cost reduction can be achieved by eliminating control system errors.…”

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confidence: 99%

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A review on real‐time simulation and analysis methods of microgrids

Ahmadiahangar

Rosin

Niaki

et al. 2019

Int Trans Electr Energ Syst

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Summary Microgrid is a recently developed concept for future power systems. The main characteristics of the microgrid are the capability of integration of renewable energy sources and the ability to operate in two grid‐connected and islanded modes. A significant challenge of microgrid implementation is developing comprehensive control methods to ensure efficient, stable, and reliable operation. Real‐time studies are a promising approach in this case. In this paper, various real‐time energy management approaches have been thoroughly explained following a new categorization of them. A significant literature review of real‐time simulation and modeling methods has also been presented. A review of different applications of hardware‐in‐the‐loop testing of the microgrid is included in the present study. Finally, a discussion on demand for further research has been made. The presented work is organized to allow a reader to understand the importance of real‐time studies of microgrids and highlight trends in literary works without delving deeply into each one.

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Section: Real‐time Modeling and Simulationmentioning

confidence: 99%

Section: Real‐time Modeling and Simulationmentioning

confidence: 99%

Section: Operation Mode Description Referencesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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A review on real‐time simulation and analysis methods of microgrids

Ahmadiahangar

Rosin

Niaki

et al. 2019

Int Trans Electr Energ Syst

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An efficient FBI‐iForest approach‐based home energy management system with RES under internet of things framework

Rani

Burthi

2022

Intl J of Energy Research

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Summary In this manuscript proposes an efficient hybrid approach for home energy management with distribution system based on Internet of things (IoT). The proposed hybrid approach is the joint execution of Forensic‐Based Investigation (FBI) and Isolation Forest, hence named as FBI‐iForest approach. The main purpose of the proposed method is to optimally manage the power and resources of the distribution system. The proposed approach considers two main factors like user satisfaction and cost of energy utilization. The proposed approach is designed under the environment of smart grid, which consists of photovoltaic (PV), wind turbine (WT), micro turbine (MT), and battery. The household appliance management is one of the important factors for smart grid system for cost saving purpose. The proposed system, data acquisition module of IoT is interfaced to every home appliance provides an IP address. The demand response of each device is collected by the IoT object transmitted to the centralized server. The transmitted data is operated through the FBI‐iForest approach. The IoT‐based energy management provides flexibility of these networks as well as optimum use of available resources. At last, the proposed model is realized on MATLAB/Simulink platform. The cost of the proposed method for case 1, 2 and 3 achieves $2.8, $340 and $1100.

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