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Table 3 Mean squared error presented as a sum of over- and underestimated optimal estimates (\(MSE=MSE^+ + MSE^-\)) according to equation (14) respective clustering method, renewable technology and carbon reduction target for a spatial resolution of 97 nodes. Graphically presented in Fig. 10

From: A comparison of clustering methods for the spatial reduction of renewable electricity optimisation models of Europe

\(\hbox {CO}_2\)Reduction

\(60\%\)

\(100\%\)

Technology

Wind

Solar

Wind

Solar

k-means

\(0.37+3.82\)

\(0.01+2.80\)

\(0.51+3.33\)

\(0.12+1.23\)

\(f^\mathrm {cap}(v)\)

\(0.21+0.60\)

\(0.03+1.00\)

\(0.01+2.22\)

\(0.11+0.15\)

\(f^\mathrm {time}(v)\)

\(0.04+3.17\)

\(0.08+0.79\)

\(0.55+1.94\)

\(0.26+0.28\)

Q

\(0.36+1.31\)

\(0.47+1.17\)

\(0.25+1.98\)

\(0.17+0.78\)