scholarly journals Community-Based Virtual Power Plants: Against All Odds?

Proceedings ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 25
Author(s):  
Ruth Mourik ◽  
Sylvia Breukers ◽  
LFM Summeren ◽  
A. C. Wieczorek
Keyword(s):  
Business Model ◽  
Power Plants ◽  
Energy Transition ◽  
Institutional Context ◽  
Virtual Power ◽  
Community Based ◽  
Business Model Canvas ◽  
Model Following ◽  
Virtual Power Plants ◽  
Energy Projects

Based on a European project entitled “Community-based Virtual Power Plants’ (Interreg 2017–2010) this paper discusses opportunities for community energy projects—focusing on the example of community-based virtual power plants. Using a business model canvas as heuristic and the Dutch demonstration case as an example, we show how a business model following a community logic is unfeasible in practice. The current institutional context compels community based cVPP initiatives to partially abandon such community-based values, in order to be able to survive in the energy services market. It is concluded that more attention is needed for institutional change since the current institutional bias that hinders cVPP projects is also hindering a more inclusive energy transition.

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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