Detailed information about the potentials and costs of renewable energies is an important input factor for energy system models, as well as commercial and political decision-making processes. With its increasing locally installed capacity and hub height, wind energy plays an important role when it comes to meeting climate targets and optimizing electricity networks. Recently however, wind energy has faced more and more social barriers and land use constraints which can negatively impact both political goals and investment decisions. Therefore this work presents a bottom-up methodology based on graph-theoretical considerations to account for social barriers to estimate the socio-technical potential and the associated costs on a wind farm level. Calculations are conducted for the German federal state of Baden-Württemberg as a case study and are based on high resolution land use and wind speed data, using an algorithm to place wind parks by considering further constraints relating to land use planning. The socio-technical potential is found to be less than half that of previous studies that neglect these constraints, i.e. between 11.8 ... mehrand 29.4 TWh, with costs between 7 and 14 €ct/kWh. A sensitivity analysis reveals a strong dependency of the overall socio-technical potential as well as its distribution across the federal state. In order to test the quality of the algorithm, already existing and planned wind parks were compared to modeled wind park locations and a very good correlation could be observed. The focus in future work should lie on the development of an economic criterion, which unlike the LCOE is able to account for the system costs of a widespread wind energy development, including network expansion, balancing power and reserve energy costs.