An Illustrative Note on the System Price Effect of Wind and Solar Power: The German Case

Abstract

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A Note on the Inefficiency of Technology- and Region-Specific Renewable Energy Support: The German Case

“…This is also in line with the results of the numerical 'ceteris paribus' example of Jägemann (2014). However, there are several differences between the numerical 'ceteris paribus' example of Jägemann (2014) and this scenario analysis, which are shortly described.…”

“…This is also in line with the results of the numerical 'ceteris paribus' example of Jägemann (2014). However, there are several differences between the numerical 'ceteris paribus' example of Jägemann (2014) and this scenario analysis, which are shortly described. First, in contrast to the numerical 'ceteris paribus' example which uses the revenue from selling electricity on the wholesale market within one year (8760 hours) as a proxy for the M V el of wind and solar power units, the M V el derived using the electricity system optimization model corresponds to the accumulated and discounted revenue per kWh from selling electricity on the wholesale market during all hours and years of the unit's technical lifetime (20 years).…”

“…While the M C are independent of the respective technology's penetration, the N M C increase with penetration. This is due to the fact that the M V el decreases as the technology's penetration increases, which is shown in Jägemann (2014).…”

“…Referring to the theoretical analysis of Jägemann (2014), fluctuating renewable energy units (C f ) are expanded up to the point at which their marginal costs (M C) correspond to the sum of their marginal value of power supply (M V el ) and their marginal value of renewable energy supply (M V ren ) in the optimum (see Eq.…”

“…As can be seen, all technologies differ with regard to both their M C -which depend on the technology's capital costs and full load hours -and their M V el -which depends on the unit's revenue from selling electricity at the wholesale market. As such, the M V el is driven by the unit's electricity generation profile or, more specifically, by the correlation between the unit's hourly production factor profile and the wholesale price profile (i.e., the unit's 'price matching' or 'residual-load matching' capability), see also Jägemann (2014). Offshore wind power (in the North Sea (region 3) and Baltic Sea (region 4)) exhibits by far the highest M C (2.75 e ct 2010 /kWh), followed by solar power (2.37 e ct 2010 /kWh in southern Germany (region 2)), onshore wind power (1.97 e ct 2010 /kWh in northern Germany (region 1)) and low-cost biogas power plants (0.71 e ct 2010 /kWh).…”