Multi-attribute based prosumers prioritization for energy trading in Smart Grid

Devi, N Nandini; Thokchom, Surmila

doi:10.1109/indicon52576.2021.9691544

Cited by 3 publications

(3 citation statements)

References 19 publications

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“…This section presents the analytical result of the proposed work with 10 producers and 10 consumers. Table 3 contains the assumption of amount of energy demand, and energy surplus to analyze the proposed model and also contains the initial bidding price of consumers and producers, which is generated randomly between the grid selling (g s ) and buying (g b ) price [25]. This also contains the cost of energy per unit of the main grid (these values are referenced from the electricity price in Brisbane, Australia, as an example) [30].…”

Section: Methodsmentioning

confidence: 99%

“…They developed a three-stage game optimization problem to determine the power allocation and energy transaction pricing strategy among utilities, telecom operators, and ESP. Devi et al [25] proposed an energy trading model based on the priority values of participants considering the various parameters of participants.…”

Section: Related Workmentioning

confidence: 99%

“…In this, the consumer raises their price as shown in line 21 according to Equation (27). At the same time, the producer lowers their price by a fraction based on their negotiation power at each stage, which is shown at line 15 with respect to Equation (25), respectively. After negotiating some stages, there comes a situation where the price of the consumer is greater than the producer's price, as shown in Line 26.…”

Section: Negotiation Unitmentioning

confidence: 99%

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Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game Theory

et al. 2023

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Due to global warming and climate change, it is essential to produce power using renewable sources, such as solar, wind, fuel cells, etc. The traditional grid shifts towards the smart grid by infusing digital communication techniques and information technology. As the current power system is shifting towards a smart grid, the utility and prosumers participate in the energy trading process. Due to the distributed nature of the smart grid, providing a fair price among them is becoming a difficult task. The article introduces a model for energy trading in a smart grid by allowing participants to negotiate in multiple stages using a game-theory-based multi-stage Nash Bargaining Solution (NBS). The model’s application of game theory enables the participants to decide on a mutually acceptable price, thereby encouraging the utility, private parties and prosumers (those who are able to generate and consume energy) to participate in the trading process. Since all parties participate in the trading procedure, greenhouse gas emissions are reduced. The proposed model also balances the benefits of consumers and producers in the final agreed fixed price. To demonstrate the efficacy of the proposed work, we compare the analytical results with feed-in-tariff (FiT) techniques in terms of consumers’ energy bills and producers’ revenue. For experimental analysis, 20 participants are considered, where the percentage reduction in the bill of each consumer and the percentage increment of revenue of each producer are compared to FiT. On average, the overall bill of the consumer is reduced by 32.8%, and the producers’ revenue is increased by 64.83% compared to FiT. It has been shown further that the proposed model shows better performance as compared to FiT with an increase in the number of participants. The analysis of carbon emission reduction in the proposed model has been analyzed, where, for 10 participants, the carbon emission reduction is approximately 28.48 kg/kWh, and for 100 participants is 342.397 kg/kWh.

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Section: Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Negotiation Unitmentioning

confidence: 99%

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Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game Theory

et al. 2023

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Demcrp-et: decentralized multi-criteria ranked prosumers energy trading using distributed ledger technology

Devi,

Thokchom,

Srivastava

et al. 2023

Peer-to-Peer Netw. Appl.

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Optimal ranking-based charging station selection for electric vehicles

Devi

Panda

Thokchom

2023

International Journal of Emerging Electric Power Systems

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In recent times, as many people have started using an electric vehicle (EV) as it provides benefits such as low fuel economy, reduced emission, etc., the deployment of fixed electric vehicle charging stations has been a popular method for supplying EVs with charging services. The charging requirement of EVs varies from vehicle to vehicle. Various schemes have been introduced recently regarding electric vehicles’ energy trading, charging station deployments, etc. Selecting an optimal charging station for booking charging slots by electric vehicle is one of the main concerns to avoid inappropriate services. To address this challenge, we proposed an optimal charging station selection scheme to book charging slots by EV. The proposed method used a multi-criteria decision-making technique called technique for order performance by similarity to ideal solution (TOPSIS) based on various parameters of electric vehicle charging stations (EVCSs). In this, the performance score of each EVCS is determined, and the ranking process is made according to their performance score. Then, EV selects the EVCS with the highest ranked and books the charging slot. Further, an analysis of the proposed scheme is carried out for 10 EVCSs and 3 EVs.

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Multi-attribute based prosumers prioritization for energy trading in Smart Grid

Cited by 3 publications

References 19 publications

Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game Theory

Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game Theory

Demcrp-et: decentralized multi-criteria ranked prosumers energy trading using distributed ledger technology

Optimal ranking-based charging station selection for electric vehicles

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