Energy Exchange Model in Routed Energy Distribution Network

Endrjukaite, Tatiana; Dudko, Alexander; Roose, Leon L.

doi:10.1145/3360322.3361017

Cited by 4 publications

(2 citation statements)

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“…For example, 65% of energy is taken from a battery and the remaining 35% from utility line at any point of time. This can be achieved through various methods, such as by means of transformers, AC/DC converters, smart energy routers [18,19], pulse-width modulation (PWM), etc. The efficiency and choice of the mix method is outside of the scope of this paper.…”

Section: Adaptive Charging and Discharging Approachmentioning

confidence: 99%

Adaptive Charging and Discharging Strategies for Smart Grid Energy Storage Systems

Dudko,

Endrjukaite

2024

Frontiers in Artificial Intelligence and Applications

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The current state of energy generation and consumption in the world, where many countries rely on fossil fuels to meet their energy demands, poses significant challenges in terms of energy security and environmental degradation. To address these challenges, the world is shifting towards renewable energy sources (RES), which are not only environmentally sustainable but also have the potential to reduce dependence on fossil fuels. However, the intermittency and seasonality of RES arise new challenges that must be addressed. To overcome these challenges, energy storage systems (ESS) are becoming increasingly important in ensuring stability in the energy mix and meeting the demands of the electrical grid. This paper introduces charging and discharging strategies of ESS, and presents an important application in terms of occupants’ behavior and appliances, to maximize battery usage and reshape power plant energy consumption thereby making the energy system more efficient and sustainable.

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Section: Adaptive Charging and Discharging Approachmentioning

confidence: 99%

Adaptive Charging and Discharging Strategies for Smart Grid Energy Storage Systems

Dudko,

Endrjukaite

2024

Frontiers in Artificial Intelligence and Applications

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“…This paper presents an alternative way of energy distribution. It is based on our recent research paper where we proposed a new energy exchange model for a routed energy distribution system, which can perform electricity routing based on smart routing algorithm and protocols [12]. We utilized a concept of an energy router device that uses energy as an input and protocols stack to smartly route an energy between houses in the grid.…”

Section: Introductionmentioning

confidence: 99%

Open Routed Energy Distribution Network Simulation for Maui Village Case Study

Dudko¹,

Endrjukaite²,

Roose³

2020

Frontiers in Artificial Intelligence and Applications

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As the electricity generation is shifting to renewable energy sources (RES), the grid infrastructure faces multiple challenges, such as intermittency and volatility of a wide range RES. A high penetration of renewables requires profound changes to the current energy distribution system. The conventional grid is increasingly becoming a bottleneck for expanding the share of RES because of its rigid architecture, which is built around centralized energy source. We propose a new energy exchange model for a routed energy distribution system, which can perform electricity routing based on smart routing algorithms and presented protocols. We utilize a concept of an energy router device that controls energy flows and utilizes protocols stack to smartly route the energy between houses in the grid. This paper describes current results with experimental network of Maui village with multiple houses interconnected through energy routers.

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