出版社：Energiewirtschaftliches Institut an der Universität zu Köln
摘要：By 2050, the European Union aims to reduce greenhouse gases by more than 80 %. The EU member states have therefore declared to strongly increase the share of renewable energy sources (RES-E) in the next decades. Given a large deployment of wind and solar capacities, there are two major impacts on electricity systems: First, the electricity system must be
exible enough to cope with the volatile RES-E generation, i.e., ramp up supply or ramp down demand on short notice. Second, sucient back-up capacities are needed during times with low feed-in from wind and solar capacities. This paper analyzes whether there is a need for additional incentive mechanisms for
exibility in electricity markets with a high share of renewables. For this purpose, we simulate the development of the European electricity markets up to the year 2050 using a linear investment and dispatch optimization model. Flexibility requirements are implemented in the model via ramping constraints and provision of balancing power dependent of current renewables feed-in. We nd that an increase in
uctuating renewables has a tremendous impact on the volatility of the residual load and consequently on the
exibility requirements. However, any market design that incentivizes investments in least (total system) cost generation investment does not need additional incentives for
exibility. The main trigger for investing in
exible resources are the achievable full load hours and the need for backup capacity. In a competitive market, the cost-ecient technologies that are most likely to be installed, i.e., gas- red power plants or
exible CCS plants, provide
exibility as a by-product. Under the condition of system adequacy,
exibility never poses a challenge in a cost-minimal capacity mix. Therefore, any market design incentivizing investments in ecient generation thus provides
exibility as an automatic complement.
关键词：Electricity; power plant ;eet optimization; renewable energy; ;exibility; market design
