Multiple Virtual Power Plants Transaction Matching Strategy Based on Alliance Blockchain

Chu, Tianfeng; An, Xingchen; Zhang, Wuyang; Lu, Yang; Tian, Jiaqi

doi:10.3390/su15086939

Cited by 7 publications

(4 citation statements)

References 19 publications

(22 reference statements)

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“…For a cooperative game with distributable profits, the distribution vectors [v1, v2, …, vn] are in line with individual rationality. The cooperative alliance will only be established if and only if each participant in the alliance S obtains a distribution utility that is not less than the utility obtained when they operate independently, namely [7]:…”

Section: Solarmentioning

confidence: 99%

“…VPPs utilize advanced information and communication technology to achieve aggregation and coordinated optimization of distributed energy, energy storage systems, controllable loads, electric vehicles, etc. [6] and will actively participate in the power exchange with the main grid electricity market, resulting in profit streams that also bring certain benefits to power plants [7]. From the perspective of 2 of 28 individual rationality, the prerequisite for each entity to participate in a VPP operation is to be able to obtain excess profits [8].…”

Section: Introductionmentioning

confidence: 99%

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Two-Stage Optimization Scheduling of Virtual Power Plants Considering a User-Virtual Power Plant-Equipment Alliance Game

Gao,

Zhang

et al. 2023

Sustainability

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Distributed renewable energy, loads, and power sources can be aggregated into virtual power plants (VPPs) to participate in energy market transactions and generate additional revenue. In order to better coordinate the transaction relationships among various entities within VPPs, this paper proposes a two-stage optimization model for VPPs that considers the user-VPP-equipment alliance. Firstly, starting from the basic structure of VPP, it is proposed to divide the alliances in VPP into two alliances: demand-side user-VPP and supply-side equipment-VPP. And a VPP optimization framework considering the cooperative game of the user-VPP-equipment alliance has been established. Then, a two-stage optimization model for VPPs was established considering the cooperative game of user-VPP-equipment alliance. The day-ahead optimization model takes economic and social benefits as the dual objectives, and the intraday optimization model aims to minimize the cost of deviation penalties. Secondly, taking into account the risk levels and comprehensive marginal benefits of various entities within the VPP, a profit distribution method combining improved Shapley values and independent risk contribution theory is adopted to allocate the total revenue of the VPP. The case results show that the operating cost has been reduced by 5.75%, the environmental cost has been reduced by 4.46%, and the total profit has increased by 29.52%. The model can improve the overall efficiency of VPPs.

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Section: Solarmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Two-Stage Optimization Scheduling of Virtual Power Plants Considering a User-Virtual Power Plant-Equipment Alliance Game

Gao,

Zhang

et al. 2023

Sustainability

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“…Existing trading models for VPPs tend to focus only on economic benefits and ignore the additional environmental costs incurred in the generation of electricity by the internal units of VPPs, and on the process of purchasing electricity, which can inhibit the carbon reducing potential of VPPs. Some literature has also studied the low-carbon operation of VPPs (Chu et al, 2023). Some has considered the coordination and optimization of the environment and economy in a single VPP trading model and reducing pollution caused by VPP operations (Zhao et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Multiple game trading strategy of multiple virtual power plants considering carbon trading

Chu

Zhu

et al. 2023

Front. Energy Res.

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The large-scale access of distributed energy resources has a certain impact on the power grid, so distributed energy resources cannot participate in the power market transactions alone. The concept of the virtual power plant (VPP) has thus emerged, which can aggregate distributed power sources and controllable loads in a region for coordinated regulation. The trading of VPPs should not only consider the economy but also its degree of low carbon. Therefore, this paper constructs a unified bidding strategy for multi-VPPs that considers carbon–electricity integration trading. We design a multi-game trading strategy among multi-VPPs to achieve unified trading, after each VPP determines its internal trading strategy. Finally, through simulation, we verify that the multiple game strategy between multi-VPPs that considers carbon trading here proposed can effectively improve the efficiency and trading income of VPPs and promote the consumption of new energy.

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“…This limitation proves crucial as risks in the energy market can affect the revenue of the VPP. Furthermore, to increase the profits margin of numerous VPPs in the electricity markets 33 , proposed a double-stage model where the initial stage is for each VPP to maximize the outputs of its intrinsic units and the ability of its external units to interact with the neighboring VPP in the second stage. Engaging in the market for the day ahead 34 , analyzed the random nature of RESs and models a forecasting tool to reduce the ambiguity encountered with RESs generation to increase the marginal earnings of the VPP.…”

mentioning

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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Multiple Virtual Power Plants Transaction Matching Strategy Based on Alliance Blockchain

Cited by 7 publications

References 19 publications

Two-Stage Optimization Scheduling of Virtual Power Plants Considering a User-Virtual Power Plant-Equipment Alliance Game

Two-Stage Optimization Scheduling of Virtual Power Plants Considering a User-Virtual Power Plant-Equipment Alliance Game

Multiple game trading strategy of multiple virtual power plants considering carbon trading

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

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