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.
Highlights
Due to the increase in energy demand and price, the environmental pollution resulting from conventional energy production techniques based on fossil fuel, the development of environmentally friendly energy known as renewable energy, such as solar, wind and tide, has become necessary and attracted a lot of attention.The integration of renewable energy in the energy system reduces the CO2 emissions, the transmission costs of energy and the load placed on the main grid by supplying a percentage of the demand through local energy production and consumption
In order to validate the performance of our proposed scheme, as well as to show its efficiency in solving problems related to energy routing, namely subscriber matching, efficient routing path and transmission scheduling, we compared the obtained results of different experiments to previous works in the literature
With the expanded use of renewable energy sources in Energy Internet (EI), the centralized energy supply mode has shifted to a multi-source and multi path mode leading to the peer-to-peer energy trading market
Summary
Due to the increase in energy demand and price, the environmental pollution resulting from conventional energy production techniques based on fossil fuel (coil, crud oil and natural gas), the development of environmentally friendly energy known as renewable energy, such as solar, wind and tide, has become necessary and attracted a lot of attention. This peer-to-peer mode of energy exchange gives energy producers and consumers the opportunity to create some financial benefits by selling the excess energy (generally with a lower cost than the cost of a utility company) instead of storing it for future use, which creates some power losses It decreases the consumer’s electricity bills and the reliance on the main grid (utility company). The expansion of the use of DREs in power generation with their volatility, the transformation of the generation and the injection of power from centralized to distributed manner, the peer-to-peer energy sharing and the power losses during the energy transmission process make the distribution of energy and the balancing of energy supply/demand in EI more difficult All of these variables gave rise to the key issue of the Energy Internet, which is the energy routing issue. These energy routing algorithms need to solve three main problems: the subscriber matching problem by determining the best producer for each consumer; the efficient energy routing problem by selecting the best path with the minimum power loss between these producer–consumer pairs; and scheduling these energy transmissions to prevent congestion or overflow problems
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