Analysis of the network structure characteristics of virtual power plants based on a complex network

2022 ◽  
Vol 204 ◽  
pp. 107717
Author(s):  
Yue Meng ◽  
Hongli Zhang ◽  
Wenhui Fan
Keyword(s):  
Complex Network ◽  
Network Structure ◽  
Power Plants ◽  
Virtual Power ◽  
Structure Characteristics ◽  
Virtual Power Plants

scholarly journals Blockchain-Based Decentralized Virtual Power Plants of Small Prosumers

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 29490-29504
Author(s):  
Tudor Cioara ◽  
Marcel Antal ◽  
Vlad T. Mihailescu ◽  
Claudia D. Antal ◽  
Ionut M. Anghel ◽  
...  
Keyword(s):  
Power Plants ◽  
Virtual Power ◽  
Virtual Power Plants

Optimal Scheduling of Commercial Demand Response by Technical Virtual Power Plants

2021 ◽  
Author(s):  
Matthew Gough ◽  
Sergio F. Santos ◽  
Joao M. B. A. Matos ◽  
Juan M. Home-Ortiz ◽  
Mohammad S. Javadi ◽  
...  
Keyword(s):  
Demand Response ◽  
Power Plants ◽  
Optimal Scheduling ◽  
Virtual Power ◽  
Virtual Power Plants

scholarly journals Planning of Electric Power Systems Considering Virtual Power Plants with Dispatchable Loads Included: An Inexact Two-Stage Stochastic Linear Programming Model

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Changyu Zhou ◽  
Guohe Huang ◽  
Jiapei Chen
Keyword(s):  
Linear Programming ◽  
Power System ◽  
Electric Power ◽  
Power Supply ◽  
Power Plants ◽  
Electricity Demand ◽  
Virtual Power ◽  
Stochastic Linear Programming ◽  
Two Stage ◽  
Virtual Power Plants

In this study, an inexact two-stage stochastic linear programming (ITSLP) method is proposed for supporting sustainable management of electric power system under uncertainties. Methods of interval-parameter programming and two-stage stochastic programming were incorporated to tackle uncertainties expressed as interval values and probability distributions. The dispatchable loads are integrated into the framework of the virtual power plants, and the support vector regression technique is applied to the prediction of electricity demand. For demonstrating the effectiveness of the developed approach, ITSLP is applied to a case study of a typical planning problem of power system considering virtual power plants. The results indicate that reasonable solutions for virtual power plant management practice have been generated, which can provide strategies in mitigating pollutant emissions, reducing system costs, and improving the reliability of power supply. ITSLP is more reliable for the risk-aversive planners in handling high-variability conditions by considering peak-electricity demand and the associated recourse costs attributed to the stochastic event. The solutions will help decision makers generate alternatives in the event of the insufficient power supply and offer insight into the tradeoffs between economic and environmental objectives.

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