Hybrid Energy Routing Approach for Energy Internet

Sara Hebal, Djamila Mechta, Saad Harous and Mohammed Dhriyyef
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Sara Hebal: LRSD Laboratory, Computer Science Department, Ferhat ABBAS Sétif 1 University, 19000 Sétif, Algeria
Djamila Mechta: LRSD Laboratory, Computer Science Department, Ferhat ABBAS Sétif 1 University, 19000 Sétif, Algeria
Saad Harous: College of Information Technology, United Arab Emirates University, Al Ain 15551, United Arab Emirates
Mohammed Dhriyyef: Smart ICT Laboratory, National School of Applied Sciences, Mohammed First University, 60000 Oujda, Morocco

Energies, 2021, vol. 14, issue 9, 1-34

Abstract: The Energy Internet (EI) has been proposed as an evolution of the power system in order to improve its efficiency in terms of energy generation, transmission and consumption. It aims to make the use of renewable energy effective. Herein, the energy router has been considered the crucial element that builds the net structure between the different EI components by connecting and controlling the bidirectional power and data flow. The increased use of renewable energy sources in EI has contributed to the creation of a new competitive energy trading market known as peer-to-peer energy trading, which enables each component to be part of the trading process. As a consequence, the concept of energy routing is increasingly relevant. In fact, there are three issues that need to be taken into account during the energy routing process: the subscriber matching, the energy-efficient path and the transmission scheduling. In this work, we first proposed a peer-to-peer energy trading scheme to ensure a controllable and reliable EI. Then, we introduced a new energy routing approach to address the three routing issues. A subscriber matching mechanism is designed to determine which producer/producers should be assigned for each consumer by optimizing the energy cost and transmission losses. This mechanism provides a solution for both mono and multi-source consumers. An improved ant colony optimization-based energy routing protocol was developed to determine a non-congestion minimum loss path. For the multi-source consumer case, an energy particle swarm optimization algorithm was proposed to choose a set of producers and to decide the amount of energy that should be collected from each producer to satisfy the consumer request. Finally, the performance of the proposed protocol, in terms of power losses, cost and computation time was compared to the best existing algorithms in the literature. Simulation results show the effectiveness of the proposed approach.

Keywords: energy cost; energy efficient path; Energy Internet; energy router; energy routing; P2P distributed energy trading; power loss; subscriber matching; transmission scheduling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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