Modelling of the economic feasibility of largescale electricity storage technologies : a german case study
Resumen
Electricity storage is often portrayed as the solution for the challenges that an increasing capacity of
intermittent generation brings. If the electricity storage facilities are to be introduced in the grid by
private investors though, just like any other asset, they require a business case. This study is part of
the DNV GL StRe@M project whose goals include the modelling of the economic feasibility of
electricity storage facilities in future German electricity grid scenarios from a price-taking investor’s
perspective by comparing costs and revenues. The two revenue streams considered in the StRe@M
project come from the spot and reserve market, and this study focuses on modelling the latter for
Germany. This thesis also provides a cost and revenue framework to assess the revenues from both
markets and the resulting profits. First a qualitative study maps the German reserve market and the
characteristics of its products to identify opportunities for electricity storage and the impacts of
regulation thereon. Next a quantitative model is designed to assess the revenue potential of the
future secondary reserve market by forecasting its demand and price levels. The modelling scope is
limited to the secondary reserve (energy) market (named aFRR in Germany) only because of its
relative market size, the low number of participants and data availability. A bottom-up approach was
tried by looking for a quantified relation between (1) historical time series of forecast errors for load
and solar and wind generation and (2) system imbalances or activated aFRR directly – a positive
causal relation which often appears in literature. As no quantified relation could be found an
alternative top-down stochastic approach then used the historical probability distribution of
activated aFRR in 2015 to establish a stochastic function for aFRR demand in future scenarios up to a
few years, preserving the properties of the historical probability distribution. An effort was made to
scale this stochastic function for an increasing renewable penetration but no workable scaling could
be obtained. The future prices to accompany the forecasted volumes were determined from a
regression analysis on historical aFRR price time series. Regression components included the aFRR
volume and the spot price. The design of the cost and revenue framework, used to process the
potential revenues from the spot and reserve market, was based on comparing samples of a
stochastic reserve market revenue with a deterministic spot market revenue and aggregating this
into a distribution for the profit. To conclude the first dispatch and profit results of the StRe@M
modelling are presented for a German electricity scenario in February 2020 with an 80% RES share,
which should be used with great caution. The modelled lithium-ion battery technology and variablespeed
PSH show positive profits on average, but the fixed-speed PSH does not. The main limitation of
this model is the lack of the scaling effect for renewable penetration, for which a scenario analysis is
probably most suited.
Trabajo Fin de Máster
Modelling of the economic feasibility of largescale electricity storage technologies : a german case studyTitulación / Programa
Master in the Electric Power IndustryMaterias/ UNESCO
33 Ciencias tecnológicas3306 Ingeniería y tecnología eléctrica
330606 Fabricación de equipo eléctrico
53 Ciencias económicas
5312 Economía sectorial
531205 Energía
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