Modeling competition of virtual power plants via deep learning

Due to the absence of studies of local energy communities (LECs) where the grid is represented, it is very difficult to infer implications of increased LEC integration for the distribution grid as well as for the wider society. Therefore, this paper aims to investigate holistic modelling and simulation approaches of LECs. To conduct a quantifiable assessment of different control architectures, LEC types and market frameworks, a flexible and comprehensive LEC modelling and simulation approach is needed. Modelling LECs and the environment they operate in involves a holistic approach consisting of different layers: market, controller, and grid. The controller layer is relevant both for the overall energy management system of the LEC and the controllers of single components in a LEC. In this paper, the different LEC modelling approaches in the reviewed literature are presented, several multilayered concepts for LECs are proposed, and a case study is presented to illustrate a holistic simulation where the different layers interact.

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“…The interaction problem of several such agents on wholesale electricity markets has been presented in [65]- [67].…”

Section: Refmentioning

confidence: 99%

Modelling and Simulation Approaches for Local Energy Community Integrated Distribution Networks

et al. 2022

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“…A deep-learning-based approach has also been proposed in [10] to find the optimal bidding strategy of VPP in energy and spinning reserve markets. In addition, competition among different aggregators within a VPP, such as aggregators of flexible demand and generators, has been modeled through deep learning in [11].…”

Section: Introductionmentioning

confidence: 99%

An Auction-Based Local Market Clearing for Energy Management in a Virtual Power Plant

Heydarian‐Forushani

Elghali

Zerrougui

et al. 2022

IEEE Trans. on Ind. Applicat.

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Virtual power plant (VPP) concept creates additional benefits for different stakeholders, such as system operators, distributed energy resources' owners, and aggregators. This article presents an auction-based energy management solution from VPP aggregator point of view. To this end, a network-constrained economic dispatch has been developed taking into account a comprehensive resource portfolio, including the conventional and renewable distributed generations, energy storage units, and flexible loads. The VPP aggregator aims at minimizing its expected costs through optimal dispatch of its own resources as well as purchasing and selling electricity from/to upstream network. To this end, a stochastic programming approach has been employed to consider the generation uncertainty of renewable energy resources as well as day-ahead energy market prices using a set of plausible scenarios. The payments to the prosumers are according to an auction-based pricing method that could be an efficient strategy for the VPP aggregator in order to guarantee fairness among consumers and producers within the VPP. In the auction-based pricing scheme, the electricity price at each local node can be calculated according to the demand and generation in each time slot. The proposed framework is a mixed-integer linear programming problem and solved by the CPLEX solver in the GAMS software. It is noteworthy that the effectiveness of the model has been verified, considering several numerical studies.

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Analysis of Output and Load Characteristics of VPP in Consideration of Uncertainty

Tan

et al. 2021

2021 International Conference on Applications and Techniques in Cyber Intelligence

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Modeling competition of virtual power plants via deep learning

Cited by 20 publications

References 30 publications

Modelling and Simulation Approaches for Local Energy Community Integrated Distribution Networks

Modelling and Simulation Approaches for Local Energy Community Integrated Distribution Networks

An Auction-Based Local Market Clearing for Energy Management in a Virtual Power Plant

Analysis of Output and Load Characteristics of VPP in Consideration of Uncertainty

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