Exogenous Cost Allocation in Peer-to-Peer Electricity Markets

Baroche, Thomas; Pinson, Pierre; Latimier, Roman Le Goff; Ahmed, Hamid Ben

doi:10.1109/tpwrs.2019.2896654

Cited by 252 publications

(171 citation statements)

References 31 publications

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“…Besides, the MBED problem with product differentiation may allow to readily account for network charges, defined in either endogenous or exogenous manner, which will readily affect multi-bilateral negotiation to account for network topology, see e.g. [23]. Eventually, the MBED approach shall be generalized so as to account for congestion, reactive power compensation, losses, etc.…”

Section: Impact Of Product Differentiationmentioning

confidence: 99%

Consensus-Based Approach to Peer-to-Peer Electricity Markets With Product Differentiation

Sorin

Bobo

Pinson

2019

IEEE Trans. Power Syst.

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410

240

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With the sustained deployment of distributed generation capacities and the more proactive role of consumers, power systems and their operation are drifting away from a conventional top-down hierarchical structure. Electricity market structures, however, have not yet embraced that evolution. Respecting the high-dimensional, distributed and dynamic nature of modern power systems would translate to designing peerto-peer markets or, at least, to using such an underlying decentralized structure to enable a bottom-up approach to future electricity markets. A peer-to-peer market structure based on a Multi-Bilateral Economic Dispatch (MBED) formulation is introduced, allowing for multi-bilateral trading with product differentiation, for instance based on consumer preferences. A Relaxed Consensus+Innovation (RCI) approach is described to solve the MBED in fully decentralized manner. A set of realistic case studies and their analysis allow us showing that such peerto-peer market structures can effectively yield market outcomes that are different from centralized market structures and optimal in terms of respecting consumers preferences while maximizing social welfare. Additionally, the RCI solving approach allows for a fully decentralized market clearing which converges with a negligible optimality gap, with a limited amount of information being shared.

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Section: Impact Of Product Differentiationmentioning

confidence: 99%

Consensus-Based Approach to Peer-to-Peer Electricity Markets With Product Differentiation

Sorin

Bobo

Pinson

2019

IEEE Trans. Power Syst.

Self Cite

410

240

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“…They presented a reinforcement learning based energy trading scheme that applied the deep Q-network (DQN) to improve the utility of the microgrid for the case with a large number of the connected microgrids. In [19], the consensus alternating direction method of multipliers (ADMM) algorithm is used to apply a novel cost allocation policy in peer-to-peer electricity markets. In this work the market participants have knowledge about the ISO charges prior to the negotiation process enabling them to anticipate on the network trade cost.…”

Section: A Related Workmentioning

confidence: 99%

A Self-Governed Online Energy Management and Trading for Smart Micro/Nano-Grids

Latifi

Rastegarnia

Khalili

et al. 2020

IEEE Trans. Ind. Electron.

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Joint energy consumption and trading management is still a major challenge in smart (micro-) grids. The main goal of solving such problems is to flatten the aggregate power consumption-generation curve and increase the local direct power trading among the participants as much as possible. Here, an inclusive formulation for energy management and trading of a Micro/Nano-grid (M/NG) is proposed. Subsequently, a holistic solution to jointly optimizing the internal energy consumption management and external local energy trading for a smart grid including several M/NGs is provided. As the problem is computationally intractable, the proposed approach involves three hierarchical stages. Firstly, a game-theoretic online stochastic energy management model is provided with a reinforcement learning solution by which the M/NGs can schedule their power consumptions. Secondly, an effective incentive-compatible doubleauction is formulated by which the M/NGs can directly trade with each other. Thirdly, the central controller develops an optimal power allocation program to reduce the power transmission loss and the destructive effects of local energy trading. The simulation results validate the efficiency of the proposed framework.

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“…Although the variation in power losses due to the energy exchanges is evaluated, the impacts of each transaction on voltage and network capacity issues are not considered. More recently, works like that of [6] and [7] used decomposition techniques to solve an optimal power flow in a distributed fashion for P2P energy trading. In a similar context, an alternative approach to account for network constraints and attribution of network usage cost is proposed in [8].…”

Section: Introductionmentioning

confidence: 99%

Decentralized P2P Energy Trading Under Network Constraints in a Low-Voltage Network

Guerrero

Chapman

Verbič

2019

IEEE Trans. Smart Grid

485

282

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The increasing uptake of distributed energy resources (DERs) in distribution systems and the rapid advance of technology have established new scenarios in the operation of lowvoltage networks. In particular, recent trends in cryptocurrencies and blockchain have led to a proliferation of peer-to-peer (P2P) energy trading schemes, which allow the exchange of energy between the neighbors without any intervention of a conventional intermediary in the transactions. Nevertheless, far too little attention has been paid to the technical constraints of the network under this scenario. A major challenge to implementing P2P energy trading is that of ensuring that network constraints are not violated during the energy exchange. This paper proposes a methodology based on sensitivity analysis to assess the impact of P2P transactions on the network and to guarantee an exchange of energy that does not violate network constraints. The proposed method is tested on a typical UK low-voltage network. The results show that our method ensures that energy is exchanged between users under the P2P scheme without violating the network constraints, and that users can still capture the economic benefits of the P2P architecture.

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Exogenous Cost Allocation in Peer-to-Peer Electricity Markets

Cited by 252 publications

References 31 publications

Consensus-Based Approach to Peer-to-Peer Electricity Markets With Product Differentiation

Consensus-Based Approach to Peer-to-Peer Electricity Markets With Product Differentiation

A Self-Governed Online Energy Management and Trading for Smart Micro/Nano-Grids

Decentralized P2P Energy Trading Under Network Constraints in a Low-Voltage Network

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