Incentive cloud-based demand response program using game theory in smart grid

Yaghmaee, Mohammad Hossein; Barabadi, Behzad; Alishahi, Saeed; Zabihi, Mohsen

doi:10.1109/epdc.2016.7514800

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…The incentives might be separated from, or additional to, their retail electricity rate, which may be fixed (based on average costs) or time-varying. Load reductions are needed and requested either when the system reliability conditions are treated or when prices are too high [27].…”

Section: B Drm Optionsmentioning

confidence: 99%

A Review on Communication Aspects of Demand Response Management for Future 5G IoT- Based Smart Grids

2021

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In recent power grids, the need for having a two-way flow of information and electricity is crucial. This provides the opportunity for suppliers and customers to better communicate with each other by shifting traditional power grids to smart grids (SGs). In this paper, demand response management (DRM) is investigated as it plays an important role in SGs to prevent blackouts and provide economic and environmental benefits for both end-users and energy providers. In modern power grids, the development of communication networks has enhanced DRM programmes and made the grid smarter. In particular, with progresses in the 5G Internet of Things (IoT), the infrastructure for DRM programmes is improved with fast data transfer, higher reliability, increased security, lower power consumption, and a massive number of connections. Therefore, this paper provides a comprehensive review of potential applications of 5G IoT technologies as well as the computational and analytical algorithms applied for DRM programmes in SGs. The review holistically brings together sensing, communication, and computing (optimization, prediction), areas usually studied in a scattered way. A broad discussion on various DRM programmes in different layers of enhanced 5G IoT based SGs is given, paying particular attention to advances in machine learning (ML) and deep learning (DL) algorithms alongside challenges in security, reliability, and other factors that have a role in SGs' performance.INDEX TERMS Smart grid, demand response management, 5G , Internet of Things

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Section: B Drm Optionsmentioning

confidence: 99%

A Review on Communication Aspects of Demand Response Management for Future 5G IoT- Based Smart Grids

2021

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“…Based on the above aggregator business scheme, contract theory (CT) [21], [22] is carried out using novelty formulas to estimate interruptible power with rewards. The process considers the users' demands, electricity purchased cost, DG available capacity, and risk evaluation (uncertain renewable energy [15]) to determine the appropriate interruptible power along with the price or incentive payment [11], [23], leading to both electricity industry and user groups can get profits and rewards. Each demand aggregator can cooperate with multiple generation aggregators and use the dynamic game model (DGM) [14], [24]- [28] to evenly distribute the DG resources, such as renewable energy capacity, AC power generation capacity, and energy storage system capacity, all of which are based on user participation intention, interruptible power, user demand, and decentralized power supply risk factors.…”

Section: Introductionmentioning

confidence: 99%

Interruptible Power Estimation and Auxiliary Service Allocation Using Contract Theory and Dynamic Game for Demand Response in Aggregator Business Model

et al. 2019

IEEE Access

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The traditional power market only considers the cost for electricity users, the willingness-topay, and the priority of electricity consumption. From the perspective of the electricity industry, only stable power supply, generator equipment set expansion, new power plant construction, and the strengthening of the transmission grid can meet the requirements of electricity users. In recent years, the distributed generation (DG) and energy storage system capacity in microgrid have gradually increased, effectively reducing and suppressing the demand from traditional power sources. In addition, incentive or contractual strategies, such as time-of-use and real-time pricing, can also encourage electricity users to change their electricity consumption behaviors. If the DGs can be integrated into generation aggregators in cooperation with demand response (DR) and efficient load direct/indirect) controls, it can meet the users' demands in auxiliary service (AS) market, as well as achieve a win-win mode for the electricity industry and electricity users. Hence, this study proposes the contract theory (CT) to estimate the interruptible power of the user group (DR aggregator) for DR during peak periods. Then, according to the user group's DR, the dynamic game model (DGM) is used to effectively allocate AS power under the consideration of the DG resource risk situation. In the aggregator business market, experimental results will show that the proposed methods can suppress the use of traditional power sources, effectively activate the proportion of schedulable DG, increase system flexibility, and increase billing charges.INDEX TERMS Distributed generation (DG), demand response (DR), contract theory (CT), dynamic game model (DGM), interruptible power, auxiliary service (AS).

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“…Meanwhile, in the traditional ways of energy production and transaction, energy companies often execute lots of contracts and conduct extensive calculations, which demands high costs of transaction and risks management. The emerging blockchain technology with promising characteristics, such as decentralization, transparency, reliance and openness would contribute to alleviate aforementioned problem by distributed energy transaction [5].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Pricing for Microgrids Energy Transaction in Blockchain-based Ecosystem

Yue

et al. 2019

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)

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Microgrid (MG) is an efficient platform to integrate distributed energy resources in distribution networks.The operation of MG is also expected to take advantage of emerging smart grid technologies to improve operation and robustness. Among these emerging technologies, blockchain technology provide a big potential to rule the energy transaction in an innovative way. In this paper, a physical architecture of the ecosystem with MGs is firstly presented. Moreover, as the main parts of the blockchain technology, the operation of distributed ledger and smart contracts are introduced in the transaction process. Considering dynamic pricing scheme in the process of energy transaction in the ecosystem, we model the energy transaction between MGs and distribution system operator (DSO) to decide the trading amount and price of the energy. The welfare maximization mathematical model is established accordingly, and the formulated dual problem will be used to find the shadow price of selling renewable energy to grid and real-time retailer price from DSO. Finally, with the deployment of distribution ledger, the energy transaction process can be fully recorded, and transaction execution can be achieved with the help of smart contracts. In light of the mentioned perspective, beside demonstrated benefit brought to both MGs and DSO, the energy transaction and management based on the blockchain will result in higher reliability and improved auditability in the ecosystem.

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Incentive cloud-based demand response program using game theory in smart grid

Cited by 4 publications

References 27 publications

A Review on Communication Aspects of Demand Response Management for Future 5G IoT- Based Smart Grids

A Review on Communication Aspects of Demand Response Management for Future 5G IoT- Based Smart Grids

Interruptible Power Estimation and Auxiliary Service Allocation Using Contract Theory and Dynamic Game for Demand Response in Aggregator Business Model

Dynamic Pricing for Microgrids Energy Transaction in Blockchain-based Ecosystem

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