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Economic Optimal Implementation of Virtual Power Plants in the German Power Market

  • The burden of excess energy from the high renewable energy sources (RES) share creates a significant reduction of residual load for the future, resulting in reduced market prices. The higher the share of stochastic RES, the more often the price will be 0 €/MWh. The power market needs new methods to solve these problems. The development of virtual power plants (VPPs) is aimed at solving techno-economic problems with an increasing share of RES in the power market. This study analyses a possible implementation of stochastic and deterministic RES in a VPP to generate secured power, which can be implemented in the European Power Exchange (EPEX)/European Energy Exchange (EEX) power market using existing market products. In this study, the optimal economic VPP configuration for an RES-based power plant is investigated and implemented into standard power market products. The results show that the optimal economic VPP configuration for different market products varies, depending on the energy availability and the marginal costs of the VPP components. The size of the VPP components is positively correlated to the components’ share of the energy generated. It was also found that projecting or implementing VPPs in Germany at current market prices (EPEX/EEX prices) is not yet economically feasible for a small share of market products. However, the secured power can be marketed on the SPOT and in the futures market with higher and more stable prices compared with the status quo.
Metadaten
Author:Dodiek Ika Candra, Kilian Hartmann, Michael Nelles
URL:https://www.mdpi.com/1996-1073/11/9/2365
DOI:https://doi.org/10.3390/en11092365
Parent Title (English):MDPI energies
Document Type:Article
Language:English
Year of Completion:2018
Date of first Publication:2018/09/07
Release Date:2020/09/16
Tag:VPP; marketing; configuration; energy transition; power market; EPEX; EEX; power market products
GND Keyword:Elektrizitätsmarkt; Virtuelles Kraftwerk
Volume:11
Issue:11/09
First Page:2365
Last Page:2373
Urheberrecht:1
research focus :Intelligent Systems / Clean Tech
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International
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