Flexibility Forecast and Resource Composition Methodology for Virtual Power Plants

Iraklis, Christos; Smend, Joshua; Almarzooqi, Ali; Mnatsakanyan, Ashot

doi:10.1109/icecet52533.2021.9698658

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…Alternatively, the spatio-temporal characteristics of data can be analyzed and extracted [39][40][41]. Iraklis C amplified seasonal data to enhance possible instability of renewable energy production, then predicted the day-ahead flexibility provided by VPP in distributed energy systems [42]. Bandara K used MSTL and a multi-period time series decomposition algorithm to remove the effect of seasonality [43], and proposed a three-layer forecasting framework called LSTM-MSNet.…”

Section: Related Workmentioning

confidence: 99%

An Improved Method for Photovoltaic Forecasting Model Training Based on Similarity

et al. 2023

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Photovoltaic (PV) power generation is the most widely adopted renewable energy source. However, its inherent unpredictability poses considerable challenges to the management of power grids. To address the arduous and time-consuming training process of PV prediction models, which has been a major focus of prior research, an improved approach for PV prediction based on neighboring days is proposed in this study. This approach is specifically designed to handle the preprocessing of training datasets by leveraging the results of a similarity analysis of PV power generation. Experimental results demonstrate that this method can significantly reduce the training time of models without sacrificing prediction accuracy, and can be effectively applied in both ensemble and deep learning approaches.

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Section: Related Workmentioning

confidence: 99%

An Improved Method for Photovoltaic Forecasting Model Training Based on Similarity

et al. 2023

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“…VPPs are receiving increasing attention from academia, industry and the ecological design field, and many researchers are further investigating the concept. At present, the research on VPP mainly includes the integration and optimal dispatching of resources [16][17][18][19][20][21][22][23][24][25], operation management [26][27][28][29][30][31][32] and market transaction and control mechanisms [33][34][35][36][37]. Among them, the selection aggregation and optimal dispatching of VPP resources in the project planning stage have been extensively researched.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Social Network Matching Model for Virtual Power Plants and Distributed Energy Resources with Probabilistic Linguistic Information

Cai

Hu²,

Wang³

et al. 2022

Sustainability

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Virtual power plants (VPPs) offer an effective means to address the imbalance issue between electricity supply and demand to advance the world’s low-carbon development. To fully utilize the limited resources in the virtual power plant planning stage, a two-sided match between VPPs and distributed energy companies is needed to better implement resource aggregation management. Because of the vagueness in this matching environment, the probabilistic linguistic term set (PLTS) is necessary to apply to express the decision makers’ preference. Considering the complex social relationships and intense competition among companies, a dynamic social network two-sided matching model is proposed for solving the multi-attribute two-sided matching decision-making problem. Firstly, we present a matching satisfaction degree described by PLTS. A dynamic social trust degree based on the sliding time concept is proposed. Secondly, the social trust network relationships are built based on the direct and indirect dynamic trust degree among companies. This relationship is then combined with an improved trust rank algorithm to identify the most authoritative and the most trusted company to provide the target company with a recommendation for the next moment. Besides, given that companies compete for limited resources, we further define the competitive satisfaction degree and apply the two-sided matching model. Additionally, then a two-sided matching model is developed. Finally, our model is tested numerically to ensure its accuracy and reliability.

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The Role of Flexibility in the Integrated Operation of Low-Carbon Gas and Electricity Systems: A Review

Amiri,

Ameli,

Strbac

et al. 2024

Energies

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The integration of gas and electricity networks has emerged as a promising approach to enhance the overall flexibility of energy systems. As the transition toward sustainable and decarbonized energy sources accelerates, the seamless coordination between electricity and gas infrastructure becomes increasingly crucial. This paper presents a comprehensive review of the state-of-the-art research and developments concerning the flexibility in the operation of low-carbon integrated gas and electricity networks (IGENs) as part of the whole system approach. Methods and solutions to provide and improve flexibility in the mentioned systems are studied and categorized. Flexibility is the system’s ability to deal with changes and uncertainties in the network while maintaining an acceptable level of reliability. The presented review underscores the significance of this convergence in facilitating demand-side management, renewable energy integration, and overall system resilience. By highlighting the technical, economic, and regulatory aspects of such integration, this paper aims to guide researchers, policymakers, and industry stakeholders toward effective decision-making and the formulation of comprehensive strategies that align with the decarbonization of energy systems.

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Flexibility Forecast and Resource Composition Methodology for Virtual Power Plants

Cited by 3 publications

References 18 publications

An Improved Method for Photovoltaic Forecasting Model Training Based on Similarity

An Improved Method for Photovoltaic Forecasting Model Training Based on Similarity

A Dynamic Social Network Matching Model for Virtual Power Plants and Distributed Energy Resources with Probabilistic Linguistic Information

The Role of Flexibility in the Integrated Operation of Low-Carbon Gas and Electricity Systems: A Review

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