Hybrid Energy Routing Approach for Energy Internet

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.

RETRACTED: Recent Trends, Challenges, and Future Aspects of P2P Energy Trading Platforms in Electrical-Based Networks Considering Blockchain Technology: A Roadmap Toward Environmental Sustainability

“…Interactions among contributing prosumers are crucial to facilitating such a trading mechanism (Paudel et al, 2020). P2P's cost-saving performance may be increased even more if the system's batteries engage in the market (Hebal et al, 2021). It is worth noting that P2P trading can help prosumers save money in a variety of ways, such as remote systems and open-urban markets (Alturki et al, 2020), completely decentralized systems (Ahmad et al, 2020), and community microgrids (Moura et al, 2020).…”

“…The system's operator is allowed a degree of discretion in this allocation phase to achieve cost recovery. Besides cost allocation, adopting an efficient power routing technique (Hebal et al, 2021) might be another intriguing approach for reducing loss during peer-to-peer trading. The feasibility is to improve the power dispatch by lowering the power losses among the electricity parties involved inside the P2P network, as illustrated by Bracco et al (2017).…”

“…It is for the reason that, in P2P trading, prosumers are believed to trade their system's energy with each other with less influence on a centralized controller, formulating P2P platforms as a trustfree system. As a result, encouraging prosumers to collaborate in such a trusted environment is a difficult challenge (Hebal et al, 2021). Furthermore, a more challenging thing is to simulate the decision mechanism aimed at numerous trading characteristics in a power system with a lot of users since their logical decisions may clash with the interests of other producers and consumers in the network (Thukral, 2021).…”

The effect of the thyristor energy router on harmonics

“…The angular frequency of the sinusoidal current is determined by the equation: 𝜔 = 2𝜋𝑓, where f = 50 Hz is the nominal frequency of the sinusoidal current. The instantaneous voltage values of the A phase of the longitudinal control module are (2),…”

“…The energy internet (EI) is considered to be the second version of the smart grid [1] and was proposed as an evolution of the energy system in order to increase its efficiency in terms of energy production, transmission and consumption [2]. Unlike the smart grid which focus on the informatization and intellectualization of the existing energy system, the energy internet is the solution to energy problems in the Internet-style through bidirectional integration of information and energy flows.…”