A Distributed Electricity Trading System in Active Distribution Networks Based on Multi-Agent Coalition and Blockchain

Taha

IEEE Trans. Syst. Man Cybern, Syst.

et al. 2019

335

163

The power grid is rapidly transforming, and while recent grid innovations increased the utilization of advanced control methods, the next-generation grid demands technologies that enable the integration of distributed energy resources (DERs)and consumers that both seamlessly buy and sell electricity. This paper develops an optimization model and blockchainbased architecture to manage the operation of crowdsourced energy systems (CES), with peer-to-peer (P2P) energy trading transactions. An operational model of CESs in distribution networks is presented considering various types of energy trading transactions and crowdsourcees. Then, a two-phase operation algorithm is presented: Phase I focuses on the day-ahead scheduling of generation and controllable DERs, whereas Phase II is developed for hour-ahead or real-time operation of distribution networks. The developed approach supports seamless P2P energy trading between individual prosumers and/or the utility. The presented operational model can also be used to operate islanded microgrids. The CES framework and the operation algorithm are then prototyped through an efficient blockchain implementation, namely the IBM Hyperledger Fabric. This implementation allows the system operator to manage the network users to seamlessly trade energy. Case studies and prototype illustration are provided.

Section: B Blockchain and Energy Trading Systemsmentioning

confidence: 99%

Energy Crowdsourcing and Peer-to-Peer Energy Trading in Blockchain-Enabled Smart Grids

Taha

IEEE Trans. Syst. Man Cybern, Syst.

et al. 2019

335

163

“…The motivations include modelling the psychological behaviour of the traders, the problems of feed-in tariff (FiT), the imposition of energy dispatch limits on distributed energy generators (DEG) by some local governments [13], [15] and incentives [16], [17]. These plethora of research literature that use P2P algorithm in the energy sector can be generally grouped into three areas [13], [18]; electric vehicles [19], microgrid [3], [20] and distribution network [21]. This study focuses on the microgrid area.…”

Section: Related Workmentioning

confidence: 99%

Energy Peer-to-Peer Trading in Virtual Microgrids in Smart Grids: A Game-Theoretic Approach

Anoh

Maharjan

Ikpehai

et al. 2020

IEEE Trans. Smart Grid

268

101

In the UK, non-commodity charges account for 55-65% of energy bills [1] and network charges alone account for about 25% of that figure [2]. Peer-to-peer (P2P) energy trading offers a unique approach to produce and sell energy at the edge of the network and can help in reducing such charges. When these prosumers are coordinated using communication systems [3], [4], significant power network values could be achieved including reduced pollution and, increased energy network efficiency and security [5].Reliable communication systems play vital roles in smart grids [3], [6]. For example, communication infrastructure can be leveraged to regroup prosumers into logical clusters called virtual microgrids (VMGs) in order to improve performance and aid network management cost reduction [3], [4], [7].

“…The proposed work is different from this research work by willingly allowing or encouraging all prosumers to become sellers and self-sufficient consumers in peak hours of energy generation. Similarly, in Reference [21], the authors proposed a system of distributed energy trading to encourage P2P sharing of electricity between prosumers. There are two layers in the proposed model.…”

Section: Related Workmentioning

confidence: 99%

Blockchain Based Sustainable Local Energy Trading Considering Home Energy Management and Demurrage Mechanism

et al. 2020

With the increase in local energy generation from Renewable Energy Sources (RESs), the concept of decentralized peer-to-peer Local Energy Market (LEM) is becoming popular. In this paper, a blockchain-based LEM is investigated, where consumers and prosumers in a small community trade energy without the need for a third party. In the proposed model, a Home Energy Management (HEM) system and demurrage mechanism are introduced, which allow both the prosumers and consumers to optimize their energy consumption and to minimize electricity costs. This method also allows end-users to shift their load to off-peak hours and to use cheap energy from the LEM. The proposed solution shows how energy consumption and electricity cost are optimized using HEM and demurrage mechanism. It also provides economic benefits at both the community and end-user levels and provides sufficient energy to the LEM. The simulation results show that electricity cost is reduced up to 44.73% and 28.55% when the scheduling algorithm is applied using the Critical Peak Price (CPP) and Real-Time Price (RTP) schemes, respectively. Similarly, 65.15% and 35.09% of costs are reduced when CPP and RTP are applied with demurrage mechanism. Moreover, 51.80% and 44.37% electricity costs reduction is observed when CPP and RTP are used with both demurrage and scheduling algorithm. We also carried out security vulnerability analysis to ensure that our energy trading smart contract is secure and bug-free against the common vulnerabilities and attacks.