2020
DOI: 10.1109/jsyst.2020.2964436
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Computational Tools for Modeling and Analysis of Power Generation and Transmission Systems of the Smart Grid

Abstract: The traditional power generation and distribution systems will be supplanted by the Internet of Energy, which accelerates the necessity to know the appropriate computation tools to perform any research in this future smart grid arena. However, there is a plethora of computational tools in this area, which challenges the researchers to find an appropriate tool based on their research objectives. Therefore, this article presents a comprehensive study about existing simulation tools related to electrical power ge… Show more

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Cited by 19 publications
(4 citation statements)
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“…Typical analysis methods for power system simulation are represented by multi-area production simulation (MAPS), Balmorel, Energy Plan, Wilmar Planning Tool, multienergy power system operation simulation, and renewable energy production simulation (REPS) [31][32][33][34]. These tools have more advantages in mathematical precision and powerful functions and are good at engineering-oriented long period simulation for a large-scale regional power system.…”
Section: Feasibility Rationality and Novelty Of This Methodologymentioning
confidence: 99%
“…Typical analysis methods for power system simulation are represented by multi-area production simulation (MAPS), Balmorel, Energy Plan, Wilmar Planning Tool, multienergy power system operation simulation, and renewable energy production simulation (REPS) [31][32][33][34]. These tools have more advantages in mathematical precision and powerful functions and are good at engineering-oriented long period simulation for a large-scale regional power system.…”
Section: Feasibility Rationality and Novelty Of This Methodologymentioning
confidence: 99%
“…The overview of the computational tools for modelling, analysis and simulation of the component layer is described in (Mahmud et al, 2020). Moreover, computational tools are also mapped in the component layer of the SGAM model.…”
Section: Mapping Of Mathematical Models In the Sgam Architecturementioning
confidence: 99%
“…Smart grids, that could forecast energy consumption is essential need. This Figure 1: Overview of CPS systems could be achieved with the applications of Machine Learning (ML) algorithm [7][8][9] on the generated data from the grid system. Smart grids could assist in making the electricity price much cheaper and reducing pollution [10].…”
Section: Introductionmentioning
confidence: 99%