A Conceptual Framework for Minimizing Peak Load Electricity using Internet of Things

Autor: Amira Hassan Abed, Laila Abd Elhamid, Mona Nasr
Rok vydání: 2021
Předmět:
Zdroj: International Journal of Computer Science and Mobile Computing. 10:60-71
ISSN: 2320-088X
DOI: 10.47760/ijcsmc.2021.v10i08.010
Popis: Electricity load demand converts from time to time frequently in a day. Encountering time-varying demand particularly in peak times is considered a big challenge that faces electric utilities. Persistent growth in peak load increases the prospect of power failure and increases the electricity equipping marginal cost. Therefore, balancing production and consumption of electricity or addressing peak load has become a key attention of utilities. Most previous works and researches were focused on applying Shave/Shift peak load to solve energy scarcity. In this study, we introduce four significant technologies and techniques for achieving peak load shaving, namely “Internet of Things (IoT) in Energy System”, “On-site Generation systems (Renewable Energy Resources)”, “Demand Side Management (DSM)” applications of control center and “Energy Storage Systems (ESSs)”. The impact of these four major methods for peak load shaving to the grid has been discussed in detail. Finally, we suggest a conceptual framework as guiding tool for illustrating the presented technologies of Shave/Shift peak load in energy systems.
Databáze: OpenAIRE