# Comparative Study of Harmony Search Algorithm and its Applications in China, Japan and Korea
## 5 Harmony Search Applications in Korea
### Engineering  
#### 5.1.1 Electrical/Electronic  
[PERSON] [56] recommended an Economic Dispatch (ED) model using a successful approach of Parameter-Setting-Free HS (PSF-HS). The PSF-HS did not need to implement the tedious method for tuning initial parameters used in standard HS, while the current algorithms needed to carefully select the algorithm parameters. It is noteworthy that PSF-HS requires algorithm parameters to account for each variable, and it is more efficient than using lumped parameters for all variables.  
In Ref. [57], a new hybrid bio-inspired solver was introduced, combining elements from the Coral Reefs Optimization (CRO) algorithm and the HS, named CRO-HS. This hybrid approach may have been used to achieve the strongest meteorological variables in a hierarchical learning computer network in situations of shorter-term wind speed predictions. Simulation tests showed that more reliable forecasts were made by the CRO-HS method than their naive optimizers of HS and CRO.  
Additionally, in Ref. [58], an optimization problem of microgrid optimal operation was solved using the hybrid Differential Evolution and HS (hybrid DE-HS) algorithm. Results show that the DE-HS performed well when solving an optimization problem.  
[PERSON] and [PERSON] [59] presented an effective HS algorithm for the charging of the green power grid ESS under time-of-use and demand charging policies. The dominance of HS over other established approaches became evident when simulating load tests and the generation profiles of modern residential customers. The ESS, which is designed for the proposed HS algorithm, demonstrated that the findings obtained were better than the GA.  
For an ideal solution of Optimal Power Flow (OPF), with non-convex and non-smooth fuel expense characteristics, [PERSON] [60] applied the DE-HS algorithm. The DE-based upgrade policies for current chromosomes were integrated into the creation of the DE-HS algorithm and the HS strategy for creating new individuals/chromosomes. The flowchart of the DE-HS algorithm is displayed in Figure 4.  
\begin{table}
\begin{tabular}{c} HS could improve the \\ degree of adaptability \\ to personal sensibility \\ \end{tabular} & [52] \\ \hline \hline \end{tabular}
\end{table}
Table 2: Cont.  
In Ref. [61], enhanced variants of the HS approach were added for energy systems and implementations of the HS algorithm were updated. Variations of the HS appear in their recent publications. Attempts were made to develop the initial HS procedure by changing the parameters of the algorithms, the search mechanism, and the combinations of certain heuristic approaches.  
[PERSON] et al. [62] addressed the problem of solving a power system's non-convex, non-linear, broad scale CHPED. A modern Multi-Player HS (MPHS) approach was implemented. The MPHS algorithm used multi-player experience and two players to enhance cooperation throughout the problem optimization phase. Two stages for the proposed MPHS method were considered by changing the values of HMCR, PAR, and BW. It was learned that the proposed approach would find the best answer with less repetition. Figure 5 shows a condensed flowchart of the proposed MPHS method and its process for optimal a solution of the CHPED problem.  
Figure 4: Process of the DE-HS algorithm for solving OPF [60].