Loss Allocation in Joint Transmission and Distribution Peer-to-Peer Markets

Moret, Fabio; Tosatto, Andrea; Baroche, Thomas

doi:10.1109/tpwrs.2020.3025391

Cited by 33 publications

(26 citation statements)

References 22 publications

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“…It is assumed that all the PV and ESS capacities are 4 kW and 10 kWh, respectively for Case-1 and Case-2. Furthermore, capacities of PV and ESS for Case-3 are randomly generated between the boundaries [3,6] kW and [5,15] kWh, respectively. The probabilistically generated PV power scenarios are depicted in Fig.…”

Section: A Input Datamentioning

confidence: 99%

A Novel Multi-Hierarchical Bidding Strategy for Peer-to-Peer Energy Trading Among Communities

2022

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Recently, several market types and regulations have been developed in an attempt to handle the increased carbon effect. End-users can also actively participate in the existing distribution system thanks to Peer-to-Peer (P2P) energy trading, which is one of the new emerging market types. In this paper, a novel dual bidding strategy for multi-hierarchical P2P energy trading that includes both intra community and inter communities is proposed considering uncertainties in solar irradiance and temperature. While lower-level problem consists of both optimal bids of households to the own Local Market Operators (LMO) for intra community trades and optimal bids of LMOs to the Central Market Operator (CMO) for inter community trades, profit of both the LMOs and CMO is maximized by clearing the market prices at the upper-level problem. To prove the validity of the devised model, a set of case studies are created. Moreover, the results suggest that the proposed bi-level model is robust and a remarkable amount of cost savings could be provided by integrating the model.

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Section: A Input Datamentioning

confidence: 99%

A Novel Multi-Hierarchical Bidding Strategy for Peer-to-Peer Energy Trading Among Communities

2022

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“…In this case, the bid-in cost function of the DSO is first determined based on the formulation in (5). The DSO's total (minimal) operating costs at different output power levels are shown in Fig.…”

Section: B Participation Through the Dsomentioning

confidence: 99%

“…The share of the DSO is 1.2 MW. In order to determine the share of the market participants in the DSO market, we need to substitute the parameter in the parametric optimization given in (5) which results in a simple optimization problem. The results of this optimization problem are given in Table . V. By comparing Tables.…”

Section: B Participation Through the Dsomentioning

confidence: 99%

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ISO and DSO Coordination: A Parametric Programming Approach

Mousavi¹,

Wang²

2022

Preprint

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In this paper, a framework is proposed to coordinate the operation of the independent system operator (ISO) and distribution system operator (DSO) to leverage the wholesale market participation of distributed energy resources (DERs) aggregators while ensuring secure operation of distribution grids. The proposed coordination framework is based on parametric programming. The DSO builds the bid-in cost function based on the distribution system market considering its market player constraints and distribution system physical constraints including the power balance equations and voltage limitation constraints. The DSO submits the resulting bid-in cost function to the wholesale market operated by the ISO. After the clearance of the wholesale market, the DSO determines the share of its retail market participants (i.e., DER aggregators). Case studies are performed to verify the effectiveness of the proposed method.

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“…An improved average LA method for distribution network is proposed by Zhang et al [3]; which is especially suitable for harmonic loss. Moret et al [4] presented an analysis of LA policies for avoiding market outcomes which categorizes agents for geographical location. It also suggests inclusion of system operator in both transmission and distribtion level.…”

Section: Literature Reviewmentioning

confidence: 99%

Graph Theoretic Loss Allocation Method for Microgrids having Variable Generation

Bharti

2021

IJE

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Loss Allocation in Joint Transmission and Distribution Peer-to-Peer Markets

Cited by 33 publications

References 22 publications

A Novel Multi-Hierarchical Bidding Strategy for Peer-to-Peer Energy Trading Among Communities

A Novel Multi-Hierarchical Bidding Strategy for Peer-to-Peer Energy Trading Among Communities

ISO and DSO Coordination: A Parametric Programming Approach

Graph Theoretic Loss Allocation Method for Microgrids having Variable Generation

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