Empowering end-use consumers of electricity to aggregate for demand-side participation

Melendez, Kevin A.; Subramanian, Vignesh; Das, Tapas K.; Kwon, Changhyun

doi:10.1016/j.apenergy.2019.04.092

Cited by 35 publications

(29 citation statements)

References 21 publications

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“…The model deals with the uncertainty by adjusting the energy schedule traded with the retailer and keeping the predefined day-ahead (DA) energy exchange profile with other buildings. The bilevel objective model in [20] minimizes the cost and ensures fairness for all p2p members involved in energy trading based on the Nash barging solution taking into account network constraints and energy scheduling in both DA and RT markets. The privacy issue regarding p2p trading has been addressed in [15] and [21].…”

Section: B Literature Reviewmentioning

confidence: 99%

“…• Relevant literature on cost-sharing methods recognizes three main categories: i) game-theory methods which are rather complex to deploy, such as [8], [16], [17], [18], ii) coalition games ( [11], [12], [20]) and iii) postevent methods which guarantee model convergence (such as BSM, MMR, SDR [22], [28], [37]). Game-theory cost-sharing methods are computationally demanding and this complexity increases exponentially with the number of peers.…”

Section: B Literature Reviewmentioning

confidence: 99%

“…• The flexibility of the end-users is often neglected or is not sufficiently modelled. Only a few papers focus on this and model both the household level batteries and controllable smart home devices, such as [8], [19], [20], [24]. Other papers either model only the battery storage or focus more on MES aspects [28]- [34].…”

Section: B Literature Reviewmentioning

confidence: 99%

“…The model analyses the impact of different flexible appliances on electricity cost reduction compared to the case with fixed consumption. The existing literature body considers the effect of uncertainty of demand or RES production on the cost [16], battery scheduling in DA and RT optimization [17], adjusting the energy schedule with RT trading with the retailer in order to keep the predefined agreed p2p volume [19], dealing with forecasting error [20], [40], the uncertainty of market prices and demand on the profit due to contract violations between the local energy system and consumers [27], optimal size of battery and PV modules [41]. However, this paper looks into pricing mechanisms stimulating final prosumers equipped with PV and flexible appliances to adjust their RT operational points to predefined DA schedules by explicitly modelling their uncertainty aspects.…”

Section: Contributionsmentioning

confidence: 99%

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Electricity Cost-Sharing in Energy Communities Under Dynamic Pricing and Uncertainty

et al. 2021

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Most of the prosumers nowadays are constrained to trade only with the supplier under a flat tariff or dynamic time-of-use price signals. This paper models and discusses the cost-saving benefits of flexible prosumers as members of energy communities who can exchange electricity among peers and on the wholesale markets through a community manager. Authors propose a novel centralized post-process sharing method by introducing a two-stage mechanism which, unlike the existing methods, guarantees benefits for prosumers joining the energy community. The first stage assesses internal price calculation in three different methods: Bill Sharing Method Net (BSMN), Mid-Market Rate Net (MMRN), and Supply-Demand Ratio Net (SDRN). In their original form, prices are calculated in a single stage and the comprehensive analyses in the paper show that some members face increased cost. To solve this issue, the paper improves the methods by introducing the second stage in which the compensation methodology is defined for the distribution of savings which ensures that all community members gain benefits. Results investigate the value of inner technical flexibility of the prosumer (flexible preferences of the final consumer can reduce the cost from 3% up to 20 %). Moreover, incentives/penalties encourage the utilization of a flexible behavior to adjust the real-time consumption of prosumers' appliances to a predefined day-ahead schedule. This type of pricing results in a lower amount of benefits sharing in the community (the reduction of 18-47% in MMRN and 49-114% in SDRN compared to existing pricing) which makes this incentives/penalties pricing more preferable. The paper concludes that prosumers with an excess PV production would not benefit from the internal energy exchange in the community under BSMN due to free energy exchange between members.INDEX TERMS cost-sharing, day-ahead market, demand response, energy community, peer-to-peer trading I. NOMENCLATUREStochastic and non-stochastic parameters are presented as bold text, while variables are a regular type of text. Where augmented with the subscripts s and t, they refer to the values they take on in scenario s and time period t, while the subscript d stands for a household and ap for a different uninterruptible flexible appliance. If not stated differently, variables and parameters are positive. Indices and Sets ap∈ AUninterruptible flexible appliances d∈ D Households d∈ D + Community members with decreased cost in the first stage d∈ D -Community members with increased cost in the first stage t ∈ T Time steps

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Section: B Literature Reviewmentioning

confidence: 99%

Section: B Literature Reviewmentioning

confidence: 99%

Section: B Literature Reviewmentioning

confidence: 99%

Section: Contributionsmentioning

confidence: 99%

See 2 more Smart Citations

Electricity Cost-Sharing in Energy Communities Under Dynamic Pricing and Uncertainty

et al. 2021

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“…A similar PV and battery-driven P2P energy trading model is also proposed in [10] through an aggregated two-stage battery control technology. Trading mechanisms that focus on empowering prosumers in the market are proposed in [11] and [12]. In the literature, integration of P2P trading in the energy market is also discussed via double-auction based [13], fairness based [14], consensus-based [15], negotiation-based [16], generalized Nash equilibrium [17], and orchestrator based [18] approaches respectively.…”

Section: Introductionmentioning

confidence: 99%

A coalition formation game framework for peer-to-peer energy trading

et al. 2020

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This paper studies social cooperation backed peer-to-peer energy trading technique by which prosumers can decide how they can use their batteries opportunistically for participating in the peer-to-peer trading. The objective is to achieve a solution in which the ultimate beneficiaries are the prosumers, i.e., a prosumer-centric solution. To do so, a coalition formation game is designed, which enables a prosumer to compare its benefit of participating in the peer-to-peer trading with and without using its battery and thus, allows the prosumer to form suitable social coalition groups with other similar prosumers in the network for conducting peer-to-peer trading. The properties of the formed coalitions are studied, and it is shown that 1) the coalition structure that stems from the social cooperation between participating prosumers at each time slot is both stable and optimal, and 2) the outcomes of the proposed peerto-peer trading scheme is prosumer-centric. Case studies are conducted based on real household energy usage and solar generation data to highlight how the proposed scheme can benefit prosumers through exhibiting prosumer-centric properties.

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Robustness assessment of the cyber‐physical system against cascading failure in a virtual power plant based on complex network theory

Gao

Yang

2021

Int Trans Electr Energ Syst

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Summary The combination of a virtual power plant (VPP) and an active distribution network (ADN) can be used to aggregate distributed energy resources of prosumers. The bi‐directional power flow and information flow between prosumers ensure close coupling and interdependence of the power system and the cyber system so that the VPP gradually evolves into a typical cyber‐physical system (CPS). However, even a small cyber attack on the CPS system significantly affects the security and integrity of the VPP. To study robustness of CPS in the VPP, a novel stochastic cascading failure model based on the complex network theory is introduced, considering the impact of various interdependencies and network relationships. First, the centralized and decentralized multi‐agent system (MAS) structures in the VPP are investigated, and the fault propagation mechanism and cascading failure process of the CPS network are established. Secondly, a simple and effective comparison method is proposed to analyze the different network relationships and coupling interdependencies. Thirdly, A new multiple‐to‐multiple inter‐links addition strategy is proposed to enhance the protection of key nodes, and mainly focus on researching the intra‐ and inter‐links addition sensitivity analysis. The numerical simulation shows that optimal network relationship, coupling interdependency, and intra‐links addition strategy are determined by the proposed robustness metrics.

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Empowering end-use consumers of electricity to aggregate for demand-side participation

Cited by 35 publications

References 21 publications

Electricity Cost-Sharing in Energy Communities Under Dynamic Pricing and Uncertainty

Electricity Cost-Sharing in Energy Communities Under Dynamic Pricing and Uncertainty

A coalition formation game framework for peer-to-peer energy trading

Robustness assessment of the cyber‐physical system against cascading failure in a virtual power plant based on complex network theory

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