# Optimal Management of High-Voltage Line Congestions Using Power Source Redispatching
## 4 Calculation Results and Discussion
### Computational Case
In general, it can be said that the operator may decide to make the value of the power limitation in RESs dependent on the degree of line congestion or another indicator. In this way, this procedure seems to be more objective and expected from the point of view of investors. This means that source G-113 has the greatest influence on the overload of relation lines 16-17 (\(I_{\text{soverload\_16-17}}=3\%\)) and 17-113 (\(I_{\text{soverload\_17-113}}=26\%\)), source G-24 has the greatest influence on the overload of relation lines 23-24 (\(I_{\text{soverload\_23-24}}=10\%\)), and source G-103 has the greatest influence on the overload of relation lines 94-95 (\(I_{\text{soverload\_94-95}}=7\%\)) and 100-103 (\(I_{\text{soverload\_100-103}}=35\%\)). Thus, the contribution (\(c\)) of each source to the line congestion can be determined as follows:  
\[ \begin{split}& c_{113}=\frac{I_{\text{soverload\_16-17+1}}+I_{ \text{soverload\_17-113}}}{I_{\text{soverload\_16-17+1}}+I_{\text{soverload\_17 -113}}+I_{\text{soverload\_23-24}}+I_{\text{soverload\_94-95}}+I_{\text{soverload\_100 -103}}}\\ & c_{113}=\frac{3\cdot 26}{3+26+10+7+35}=0.358\\ & c_{24}=\frac{I_{\text{soverload\_16-17+1}}+I_{\text{soverload\_17 -113}}+I_{\text{soverload\_23-24}}+I_{\text{soverload\_94-95}}+I_{\text{soverload\_100 -103}}}{c_{24}}\\ & c_{24}=\frac{10}{3+26+10+7+35}=0.123\\ & c_{103}=\frac{I_{\text{soverload\_94-95}}+I_{\text{soverload\_ 100-103}}}{I_{\text{soverload\_16-17+1}}+I_{\text{soverload\_17-113}}+I_{\text{soverload\_23-24}}+I_{\text{soverload\_94-95}}+I_{\text{soverload\_100 -103}}}\\ & c_{103}=\frac{7+35}{3+26+10+7+35}=0.519\\ \end{split}  \tag{16}\]  
Based on the obtained values, it can be stated that the smallest share in line congestion is from source G-24 and the largest is from G-103. Therefore, generation in source G-24 should be limited to the smallest extent, and in source G-103, it should be limited to the greatest extent. Therefore, source G-103 should have the smallest weight, and source G-24 should have the largest. Various weight values were analyzed, and it turns out that only the weight value (\(w_{3}\)) for source G-103 equal to 0.06 and lower ensures a smaller reduction of power in source G-24 compared to the results obtained previously. For example, for weight values equal to \(w_{1}=0.38\), \(w_{2}=0.56\), and \(w_{3}=0.06\), the optimal power values are \(P_{24}\) = 40 MW, \(P_{113}=36\) MW, and \(P_{103}=38\) MW. For weights equal to \(w_{1}=0.39\), \(w_{2}=0.56\), and \(w_{3}=0.05\), the optimal power values are \(P_{24}=45\) MW, \(P_{113}=36\) MW, and \(P_{103}=0\) MW. This means that, in the analyzed case, the optimization results are more favorable for the G-24 source only after the G-103 source is switched off. The optimal power value in source G113 does not change, which means the maximum value from the point of view of eliminating line congestion is between nodes 16 and17 and 17 and 113. If the weight value (\(w_{2}\)) for the G-24 source is less than 0.16 (np. \(w_{1}=0.75\), \(w_{2}=0.15\), \(w_{3}=0.1\)), then the optimal power values are \(P_{24}=0\) MW, \(P_{113}=45\) MW, and \(P_{103}=44\) MW. This means that the optimal power value for the G113 source is higher but at the cost of switching off the G-24 source. In general, at G-24 weight values lower than 0.19 the optimal G-113 power starts to increase, and at values lower than 0.16, it reaches its maximum value (with G-24 disabled). For example, for \(w_{1}=0.72\), \(w_{2}=0.18\), and \(w_{3}=0.1\), the optimal power values are \(P_{24}=35\) MW, \(P_{113}=37\) MW, and \(P_{103}=48\) MW. Increasing the weight for G-103 (\(w_{3}\)) does not increase its generation in relation to the value obtained using the objective function \(F_{\text{obj1}}\). Of course, each case should be analyzed individually. Priorities should be established after a thorough analysis of the given situation. The calculation time depends on the number of decision variables, the number of iterations, the size of the population and the size of the model of the network under analysis.