A Reliable Approach to Protect and Control of Wind Solar Hybrid DC Microgrids

Farooq, Umer; Yang, Fan; Jiang, Yi; Hassan, Muhammad Arshad Shehzad; Faiz, Nouman; Riaz, Muhammad Tanveer; Li, Jinxian; Shaikh, Jamshed Ali

doi:10.1109/ei247390.2019.9062101

Cited by 8 publications

(4 citation statements)

References 13 publications

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“…• Connect the Buzzer and the reset button to arduino as shown in the Figure 1. • In this algorithm, when the program runs, camera captures the images of that specific area where we want to detect the fire, instantly and repeatedly [19].…”

Section: Methodsmentioning

confidence: 99%

Image Processing and Data Storage for Fire Alarm

Rahman¹,

Waseem²,

Riaz³

et al. 2022

J. Engg. Res. & Sci.

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This paper explains the algorithm for fire alarm for the purpose of safety from any loss and property damage. Here, the designed algorithm is for the comparison of captured pictures. The purpose of comparison is to validate our results. In captured pictures, there may exist fire colour in pictures, which is the indication of fire in that specific area. Captured pictures are stored in folder and its path is stored in excel. We observed the indication of fired picture through fire alarm. When the fire is diminished, we used to reset button to stop the buzzer and to monitor the system again. The path of those pictures as well as the time and date of captured pictures will remain store in excel for later study of the failure of the system and also for the record purposes.

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Section: Methodsmentioning

confidence: 99%

Image Processing and Data Storage for Fire Alarm

Rahman¹,

Waseem²,

Riaz³

et al. 2022

J. Engg. Res. & Sci.

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“…In the United Kingdom (UK) [35], China [36], North America [37], Kuwait [38], and Turkey [39], DSM has already been engaged for covering up the losses within SG. Based on these works, the futuristic strength of DC MGs in the market can be seen clearly [40,41].…”

Section: Technique Focused Referencementioning

confidence: 98%

Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods

et al. 2022

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In view of scarcity of traditional energy resources and environmental issues, renewable energy resources (RERs) are introduced to fulfill the electricity requirement of growing world. Moreover, the effective utilization of RERs to fulfill the varying electricity demands of customers can be achieved via demand response (DR). Furthermore, control techniques, decision variables and offered motivations are the ways to introduce DR into distribution network (DN). This categorization needs to be optimized to balance the supply and demand in DN. Therefore, intelligent algorithms are employed to achieve optimized DR. However, these algorithms are computationally restrained to handle the parametric load of uncertainty involved with RERs and power system. Henceforth, this paper focuses on the limitations of intelligent algorithms for DR. Furthermore, a comparative study of different intelligent algorithms for DR is discussed. Based on conclusions, quantum algorithms are recommended to optimize the computational burden for DR in future smartgrid.

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“…The microgrid system used in this study consists of three mutually independent subsystems: a wind power generation subsystem, a photovoltaic power generation subsystem and a battery storage subsystem (used to compensate for the brief supply of electrical energy when the power generation is insufficient) [28,29]. Figure 1 shows the structure of the microgrid power generation system.…”

Section: Microgrid System Descriptionmentioning

confidence: 99%

Microgrid Optimal Dispatch Based on Distributed Economic Model Predictive Control Algorithm

Peng¹,

Jiang²,

Wei³

et al. 2023

Energies

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A microgrid cluster is composed of multiple interconnected microgrids and operates in the form of cluster, which can realize energy complementation between microgrids and significantly improve their renewable energy consumption capacity and system operation reliability. A microgrid optimal dispatch based on a distributed economic model predictive control algorithm is proposed in this paper. Firstly, the control task of the microgrid power generation system is defined, which is required to meet the load demand while reducing the economic loss of the system and realize dynamic economic optimization. The global objective function is designed based on the control task, and the detailed design method of the distributed economic model predictive controller is given. The control law is obtained by an iterative calculation using the Nash optimal method, which can effectively reduce the amount of data in the communication network. Finally, a microgrid group composed of four microgrids is used as an example for simulation verification. The simulation results show that the distributed economic model predictive control algorithm proposed in this paper has good economic benefits for microgrid dispatching.

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A Reliable Approach to Protect and Control of Wind Solar Hybrid DC Microgrids

Cited by 8 publications

References 13 publications

Image Processing and Data Storage for Fire Alarm

Image Processing and Data Storage for Fire Alarm

Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods

Microgrid Optimal Dispatch Based on Distributed Economic Model Predictive Control Algorithm

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