Abstract
The paradigm shift of large power systems to renewable and decentralized generation raises the question of future transmission and flexibility requirements. In this work, the German power system is brought to focus through a power transmission grid model in a high spatial resolution considering the high voltage (110 kV) level. The fundamental questions of location, type, and size of future storage units are addressed through a linear optimal power flow using today’s power grid capacities and a generation portfolio allowing a 66% generation share of renewable energy. The results of the optimization indicate that for reaching a renewable energy generation share of 53% with this set-up, a few central storage units with a relatively low overall additional storage capacity of around 1.6 GW are required. By adding a constraint of achieving a renewable generation share of at least 66%, storage capacities increase to almost eight times the original capacity. A comparison with the German grid development plan, which provided the basis for the power generation data, showed that despite the non-consideration of transmission grid extension, moderate additional storage capacities lead to a feasible power system. However, the achievement of a comparable renewable generation share provokes a significant investment in additional storage capacities.
Highlights
The increased share of variable renewable energy sources (RES) in large-scale power systems leads to new challenges regarding the integration of these
The optimization results show that no additional storage capacity is required for the referencing status quo scenario with a RES generation share of 35.4%, which could be expected due to the large thermal power plant capacities in Germany’s power system today
When applying the reduction method of a spatial k-means clustering with k = 500 grid nodes for a full-year optimization of the data model, five additional storage units with a total capacity of 1601 MW are required
Summary
The increased share of variable renewable energy sources (RES) in large-scale power systems leads to new challenges regarding the integration of these. We use the tool eTraGo which depicts the German power grid in a high spatial and temporal resolution and optimizes the extension of storage and power grid to enable RES integration. The role of flexibility and storage units in future power systems has been worked on extensively in academia regarding energy system analyses [4,5,6,7,8]. Apart from works on common storage units the role and potential forms of demand side management (DSM) as another efficient form of flexibility provision has been addressed by [9]. Demand response management as one method of DSM takes the flexibility potential of power customers into account.
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