Two-stage coordinated operation framework for virtual power plant with aggregated multi-stakeholder microgrids in a deregulated electricity market

Chang, Weiguang; Dong, Wei; Wang, Yubin; Yang, Qingliang

doi:10.1016/j.renene.2022.09.037

Cited by 31 publications

(2 citation statements)

References 50 publications

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“…With the knowledge from the optimization, the VPP knows how much energy it can produce in the coming day and communication is done between the VPP operator and the external grid via the Day Ahead Market (DAM) operator, specifying how much electricity it will supply and how much it will sell it for to the grid. Thus, the revenue generated by the VPP is formulated as 46 . The DAM is considered in this paper.…”

Section: The Economic Modelingmentioning

confidence: 99%

Developing a three stage coordinated approach to enhance efficiency and reliability of virtual power plants

Amissah,

Abdel-Rahim,

Mansour

et al. 2024

Sci Rep

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A Virtual Power Plant (VPP) is a centralized energy system that manages, and coordinates distributed energy resources, integrating them into a unified entity. While the physical assets may be dispersed across various locations, the VPP integrates them into a virtual unified entity capable of responding to grid demands and market signals. This paper presents a tri-level hierarchical coordinated operational framework of VPP. Firstly, an Improved Pelican Optimization Algorithm (IPOA) is introduced to optimally schedule Distributed Energy Resources (DERs) within the VPP, resulting in a significant reduction in generation costs. Comparative analysis against conventional algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) demonstrates IPOA's superior performance, achieving an average reduction of 8.5% in generation costs across various case studies. The second stage focuses on securing the optimized generation data from rising cyber threats, employing the capabilities of machine learning, preferably, a convolutional autoencoder to learn the normal patterns of the optimized data to detect deviations from the optimized generation data to prevent suboptimal decisions. The model exhibits exceptional performance in detecting manipulated data, with a False Positive Rate (FPR) of 1.92% and a Detection Accuracy (DA) of 98.06%, outperforming traditional detection techniques. Lastly, the paper delves into the dynamic nature of the day ahead market that the VPP participates in. In responding to the grid by selling its optimized generated power via the day-ahead market, the VPP employs the Prophet model, another machine learning technique to forecast the spot market price for the day-ahead to mitigate the adverse effects of price volatility. By utilizing Prophet forecasts, the VPP achieves an average revenue increase of 15.3% compared to scenarios without price prediction, emphasizing the critical role of predictive analytics in optimizing economic gains. This tri-level coordinated approach adopted addresses key challenges in the energy sector, facilitating progress towards achieving universal access to clean and affordable energy.

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Section: The Economic Modelingmentioning

confidence: 99%

Developing a three stage coordinated approach to enhance efficiency and reliability of virtual power plants

Amissah,

Abdel-Rahim,

Mansour

et al. 2024

Sci Rep

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“…Virtual power plants (VPPs) can effectively aggregate distributed energy resources (DERs) of prosumers, including photovoltaic (PV), energy storage systems (ESS), and flexible loads. Existing literature has studied the management of distributed energy resources within VPPs and the participation of VPPs in various electricity markets [4][5][6]. Ref [7][8][9] utilized various heuristic algorithms for aggregation and operational optimization of distributed resources within VPPs to maximize technical or economic benefits.…”

Section: Introductionmentioning

confidence: 99%

A Two-Layer Peer-To-Peer Energy Sharing Model for Virtual Power Plants Based on Demand-Side Management

Fuyou¹,

Fu-you²,

He³

et al. 2023

Preprint

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As a transitional layer between the electricity market and prosumers, Virtual Power Plants (VPPs) can effectively integrate distributed resources of prosumers to participate in the electricity market to improve the energy economy for prosumers. This study aggregates distributed resources such as photovoltaics, energy storage, and flexible loads into a VPP within the same community microgrid. A two-layer peer-to-peer (P2P) energy sharing model within and among VPPs is established to consume PV power and construct a stable power supply system. At the VPP-layer, a comprehensive energy management model is created to optimize the scheduling of flexible loads to achieve optimal energy economic performance of the community. At the market-layer, a VPP bidding model is established to organize P2P energy sharing among VPPs. The VPP-layer scheduling provides initial information for the marketlayer to participate in energy sharing, and energy sharing results of the market-layer are fed back to the VPP-layer as boundary conditions for re-scheduling. The energy economy analysis of the proposed system shows that the community's cost is reduced by participating in P2P sharing, and the two-layer interactive mechanism can further reduce the community's cost by increasing the quantity of shared energy in the P2P market, achieving dual technological and economic benefits.

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Operation of Energy and Regulation Reserve Markets in the presence of Virtual Power Plant Including Storage System and Distributed Generation based on Unit Commitment Model

Zhu,

Zhao,

Yao

et al. 2023

J. Electr. Eng. Technol.

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Two-stage coordinated operation framework for virtual power plant with aggregated multi-stakeholder microgrids in a deregulated electricity market

Cited by 31 publications

References 50 publications

Developing a three stage coordinated approach to enhance efficiency and reliability of virtual power plants

Developing a three stage coordinated approach to enhance efficiency and reliability of virtual power plants

A Two-Layer Peer-To-Peer Energy Sharing Model for Virtual Power Plants Based on Demand-Side Management

Operation of Energy and Regulation Reserve Markets in the presence of Virtual Power Plant Including Storage System and Distributed Generation based on Unit Commitment Model

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