Multilevel inverters (MLI) have been commonly used in industry especially to get quality output voltage in terms of total harmonic distortion (THD). In addition, development in semiconductor technology and advanced modulation techniques make MLI implementation more attractive. Selective Harmonic Elimination (SHE) that can be applied MLI at desired switching frequency offers elimination of harmonics in the output voltage. Also, by using SHE technique with cascaded multilevel inverters, the necessity of using filter in the output can be minimized. In this paper, SHE equations have been solved by using of Genetic Algorithm (GA) Toobox&Matlab and it has been aimed to eliminate desired harmonic orders at fundamental output voltage. Simulation results have clearly demonstrated that GA based SHE techniques can eliminate the demanded harmonic orders.

Wind is an effective renewable power source suitable for localized electricity production when regional environmental factors have substantial impact on system output. The research studies the best wind turbine placement through wind speed variability studies conducted with calibrated anemometers and data loggers that assess site conditions. A data-based assessment method creates the research's main contribution which facilitates the optimization of wind power potential measurement for enhanced energy efficiency. The research methodology includes continuous Vantage Pro2 equipment together with anemometers at different heights for wind speed observation while performing accuracy-based calibration analysis. The research shows that elevating the turbine from seven meters to ten meters leads to a 12 percent growth in the amount of power produced. The power output of wind energy decreases as wind speed changes because of environmental conditions so proper installation locations become essential. Energy performance increases best when selecting sites which feature reliable and elevated wind speeds. This research provides useful knowledge about enhancing decentralized power generation through wind energy but it cannot be easily scaled up to bigger systems. The study demonstrates that specific site assessments together with practical recommendations will enhance the efficiency of small-scale wind energy systems.

Son yıllarda dağıtık enerji üretiminin artması ile birlikte alçak gerilim (AG) tarafta, tüketici geriliminde yükselmeler meydana gelmektedir. Aynı zamanda ters güç akışı, şebeke dengesizliği gibi problemler ile birlikte gerilimdeki yükselme, enerji hatları üzerinde kayıplara yol açarak sistemi veriminin düşmesine neden olmaktadır. Bu makalede, AG mikro şebekeler için gerilim problemlerinin çözümüne yönelik, mikro şebeke önüne statik voltaj regülatörü (SVR) bağlanmıştır ve SVR gerilim kontrol algoritması geliştirilmiştir. Gerilim kontrol algoritmasının mikro şebeke için önerilen Kural Tabanlı ve Optimizasyon Tabanlı Enerji Yönetimi Sistemleri (EYS) ile birlikte uygulanmasına yönelik benzetim çalışması yapılmıştır. IEEE 13 bara test sistemi ve önerilen algoritmalar Simulink/MATLAB ortamında oluşturulmuştur. Optimizasyon tabanlı EYS sonuçları, Python programlama dili kullanılarak elde edilmiştir. Gerçek gerilim ve yük profili otomatik sayaç okuma sistemi (OSOS) verilerinden alınmıştır ve elde edilen sonuçlar SVR gerilim kontrol algoritmasının, mikro şebekelerinin gerilimini istenilen seviyeye indirilmesinde etkili bir şekilde kullanılabileceğini göstermiştir. Aynı zamanda Optimizasyon Tabanlı EYS ile mikro şebekelerin daha efektif bir şekilde yönetilebileceği benzetim çalışması sonuçları ile doğrulanmıştır.

This paper compares the performance of a Sliding Mode Control (SMC) and Proportional-Integral (PI) controller under different voltage and load conditions. The study's findings underscore the need to account for load variations in system designs and to continuously seek system optimization irrespective of the controller type chosen. PI controller demonstrates effectiveness under certain circumstances. However, significant drops in voltage and current during abrupt load changes are obtained. On the other hand, SMC enables superior adaptability, efficiently managing voltage transients and load variations without any electrical disturbances, thereby maintaining system stability. A comparative analysis further emphasizes the SMC's superior time response and robustness against reference voltage changes. Consequently, SMC is proven to be a preferable choice over the PI controller in systems experiencing frequent voltage and load variations. However, both controllers achieve the potential for further response time optimization and stability.