Abstract
In this paper, we take a look at Austria’s renewable energy targets established in the Renewable Energy Expansion Act (EAG), aiming to annually generate an additional 10 TWh of wind power by 2030. We conduct a GIS (geographic information system)-based analysis to determine average wind power density in Austria on a cellular level while considering prohibited regions, such as national parks, where building wind turbines might not be allowed. The calculated expansion potential for all remaining regions of Austria is allocated to the closest corresponding transmission nodes. Furthermore, we suggest an optimization algorithm to geographically distribute the expansion of wind power capacity to applicable transmission nodes. Finally, we conduct a case study to validate the algorithm using historical data on expansion and utilize it to predict an annual scenario for wind power expansion from 2021 to 2030 on a regional level. The total expansion required to achieve the goal of 10 TWh is assessed to be 4 GW based on predefined full load hours while assuming an exponential increase in annually added capacity (from 250 MW in 2021 to 590 MW in 2030).
Highlights
The European electricity sector is facing radical changes as the European Union (EU) aims to achieve climate neutrality by 2050
Locational information is a necessary condition for electricity economic models to determine significant load flows and identify congestions on a transmission system level. One such model is ATLANTIS, which is developed at the Institute of Electricity Economics and Energy Innovation at Graz University of Technology [3]
This paper is organized as follows: in Sect. 2, candidate areas and their wind power potentials are associated to corresponding transmission nodes; Sect. 3 describes our novel algorithm for optimizing wind power expansion planning; in Sect. 4, the algorithm is evaluated by actual wind power expansion from 1995 to 2020; in Sect. 5, the algorithm is applied to transform Austria’s 10 TWh top-down wind power target into specific annual expansion plans per transmission node
Summary
The European electricity sector is facing radical changes as the European Union (EU) aims to achieve climate neutrality by 2050 (net zero greenhouse gas emissions). 2, candidate areas and their wind power potentials are associated to corresponding transmission nodes; Sect. 5, the algorithm is applied to transform Austria’s 10 TWh top-down wind power target into specific annual expansion plans per transmission node. 2. Determining wind power potential Utilizing a GIS (geographic information system)-based analysis, we determine the average wind power density of candidate areas per transmission node on a cellular level. Step 5: Computation of available wind power potential per transmission node. From the aggregated area per node, we calculate the maximum technical potential per node Pn limiting wind power expansion in the model. 3. Utilizing optimization for annual wind power expansion Since the national target of 10 TWh annual wind power generation by 2030 represents a top-down formulation, annual expansion plans have to be derived and implemented to the model. Constraint (6) represents maximum expansion per node while considering the cooldown phase between new installations
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