Procedure for optimal siting and sizing of DG units requires two levels. The first level aims to reduce the solution space by introducing a list of preliminary locations based on the sensitivity of power losses with power injections into the network buses. This significantly reduces the number of possible variants of the solution, which are searched in the second stage of the procedure. Two search techniques were used for searching: partial search of variants and metaheuristic optimization methods-GA. Simulation results on two test networks confirm the efficiency and robustness of this approach for both search techniques. However, it should be noted that the partial search technique is suitable for small distribution networks, while the GA also provides high-quality solutions for real systems with a large number of buses and potential locations for DG units.

Chapter Contents:

• 11.1 Introduction
• 11.2 Preliminary locations of DG
• 11.3 Partial search of variants
• 11.3.1 Optimal DG placement by using partial search of variants
• 11.3.2 Optimal DG sizing by using partial search of variants
• 11.4 Genetic algorithm
• 11.4.1 Optimal DG placement and sizing by using GA
• 11.5 Simulation results
• 11.5.1 IEEE 31-bus system
• 11.5.1.1 Preliminary locations—BLCs
• 11.5.1.2 Optimal DG placement and sizing by using partial search of variants
• 11.5.1.3 Optimal DG placement and sizing by using GA
• 11.5.2 Distribution network Zajecar
• 11.5.2.1 Preliminary locations—BLCs
• 11.5.2.2 Optimal DG placement and sizing
• 11.6 Educational program package
• 11.7 Conclusion
• References

Inspec keywords: genetic algorithms; distributed power generation; distribution networks; search problems

Other keywords: DG units; partial search of variants; genetic algorithm; optimal sizing procedure; distributed generation; power losses sensitivity; metaheuristic optimization methods; optimal placement procedure; network buses; search techniques; distribution networks

Subjects: Distributed power generation; Optimisation techniques; Combinatorial mathematics