Power Forecasting, Power Sharing & Real Time Grid Monitoring in an Electrically Tied Grid Interconnected System: A Review

被引:0
作者
Divya, R. [1 ]
Nair, Ashitha R. [1 ]
Harisankar, S. [1 ]
Sai, Sree V. G. [1 ]
Nair, Manjula G. [1 ]
机构
[1] Amrita Vishwa Vidyapeetham, Dept Elect & Elect Engn, Amritapuri, India
来源
2022 6TH INTERNATIONAL CONFERENCE ON GREEN ENERGY AND APPLICATIONS (ICGEA 2022) | 2022年
关键词
renewable energy sources; artificial neural network; feed forward neural network; internet of things; energy trading; SMART; INTEGRATION;
D O I
10.1109/ICGEA54406.2022.9791968
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In today's world, power industry is exponentially advancing in terms of the improvements made in making the same more reliable, secure, independent and smart; but the need to ensure grid reliability by cutting down non-renewable and pollution causing resources appears to be a major concern of the era. Renewable Energy Sources (RES) could effectively tackle the issue to a great extent. One such major step to get the best out of RES is to integrate the same to a grid, to support the grid at the time of power shortages, where the RES needs to be assessed, processed, and analyzed properly to ensure its compatibility with the system to which it is to be connected. This paper presents a detailed review on the concepts of power forecasting, power sharing, grid integration and real time grid monitoring, to detail on how the same is affecting the grid modernization strategies in the near future.
引用
收藏
页码:199 / 203
页数:5
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