| Issue |
E3S Web Conf.
Volume 181, 2020
2020 5th International Conference on Sustainable and Renewable Energy Engineering (ICSREE 2020)
|
|
|---|---|---|
| Article Number | 03002 | |
| Number of page(s) | 4 | |
| Section | Power and Energy Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202018103002 | |
| Published online | 24 July 2020 | |
CO2 emission reduction and energy management for an integrated smart grid — Case of study: Rwandan electrical network
1 Electrical and Electronics Engineering department, University of Rwanda,, Rwanda
2 ACE-ESD, University of Rwanda, Rwanda
3 Electrical and electronics engineering, University of Dar es Salaam, Tanzania
* Corresponding author: mufabianos@gmail.com
Many scholars have been focusing on the energy management by Integrating a smart grid into a conventional electrical grid. They have showed that to meet a certain power demand of the consumers, using energy management, the electric utility can turn on some generators, which may have the least operation cost, while the generators with high operation cost are left to supply extra load demand in specific peak periods. Henceforth, the operation cost of its generation units is minimized. The issue remains at a level of relating the energy management to CO2 emission. The present paper briefly discusses the Rwandan electrical network that still integrates the use of diesel generators. It estimates the amount of CO2 emission that can be avoided once a PV system is integrated into the electrical network. The paper as well proposes an algorithm for energy management with consideration of CO2 emission.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.