# A Review of Harmonic Detection, Suppression, Aggregation, and Estimation Techniques
## 6 Conclusions  
Harmonic detection, suppression, aggregation, and estimation are essential for managing harmonic content in modern power systems. The rise of non-linear devices, like electric vehicles and renewable energy sources, has significantly increased the risk of harmonic distortions, making advanced and adaptable methods necessary. Traditional techniques, such as Fourier and wavelet transforms, are foundational in harmonic detection, but newer methods like machine learning models and adaptive filters offer enhanced accuracy and flexibility, especially in handling dynamic and non-stationary conditions.  
As power systems become more complex with the increased integration of renewable energy, the ability to control and suppress harmonics will be crucial for maintaining system reliability and efficiency. Hybrid filters, combining passive and active components, are an effective solution for mitigating the negative impacts of harmonics. These filters, along with real-time harmonic estimation techniques, are vital for adapting to the evolving grid conditions. In particular, active and adaptive filters are more flexible than passive filters, as they can adjust to changing harmonic conditions, making them more suitable for modern power grids.  
Harmonic aggregation refers to the process of combining harmonic signals to represent the overall harmonic content in a system, often through techniques like the harmonic mean, geometric mean, or root mean square. Additionally, harmonic sensitivity--how a system responds to harmonic distortions--must be considered during power system design, as high distortion levels can damage equipment and reduce performance. Estimation techniques that are tailored to signal characteristics play a critical role in determining harmonic content.  
Future efforts to manage harmonic content in low-voltage distribution networks must contend with the increasing complexity introduced by high-power, non-linear loads and distributed energy storage. This review emphasizes, the tools/techniques of harmonic assessment that can provide bases to enhance harmonic models by incorporating data from photovoltaic systems and battery storage, thus improving the network's adaptability to near-zero energy buildings and electric vehicle charging. Expanding harmonic estimation to include network impedance measurements across multiple frequencies would provide valuable insights into the effects of harmonics on system parameters. As the hosting capacity of power/distribution networks for renewable sources is a topic under extensive research presently, this harmonic review can offer a crucial basis for assessing policies and technology integration. Addressing harmonic sensitivity remains essential in managing increasingly complex grid conditions.  
All in all, traditional and innovative techniques for harmonic detection, suppression, aggregation, sensitivity analysis, and estimation will continue to evolve, playing a central role in ensuring the stability and efficiency of power systems as they integrate more renewable energy sources. Future research should focus on refining these methods and their application in large-scale grids with diverse energy sources.  
Conceptualization, K.D. and M.N.I.; methodology, H.A.R. and N.S.; software, M.U.S. and M.N.I.; validation, K.D., M.N.I. and N.S.; formal analysis, K.D. and H.A.R.; investigation, N.S. and M.U.S.; resources, L.K. and K.D.; data curation, H.A.R. and M.N.I.; writing--original draft preparation, M.N.I. and K.D.; writing--review and editing, K.D. and N.S.; visualization, M.U.S. and H.A.R.; supervision, L.K. and N.S.; project administration, L.K. and M.N.I.; funding acquisition, L.K. and N.S. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the Estonian Research Council grant PRG2055, PSG142 and EU Commission through H2020 project FinEST Twins grant No. 856602.  
Not applicable.  
The authors declare no conflicts of interest.