Economic dispatch (ED) is one of the most important problems in terms of energy planning, management, and operation in power systems. This study presents a snow ablation optimizer (SAO) algorithm developed with the fuzzy-based fitness–distance balance (FFDB) method for solving ED problems in small-, medium- and large-scale electric power systems and determining the optimal operating values of fossil fuel thermal generation units. The FFDB-based SAO algorithm (FFDBSAO) controls early convergence problems through balancing exploration–exploitation and improves the solving of high-dimensional optimization problems. In the light of extensive experimental studies conducted on CEC2020, CEC2022, and classical benchmark test functions, the FFDBSAO2 algorithm has shown superior performance against its competitors. Wilcoxon and Friedman’s statistical analysis results confirm the performance and efficiency of the algorithm. Moreover, the proposed algorithm significantly reduces total fuel cost by optimizing fossil fuel thermal generation units. According to the results, the scalability and robustness of the algorithm make it a valuable tool for solving large-scale optimization problems in the planning of electric power systems.

Transmission Expansion Planning (TEP) is a key aspect in securing the reliability and efficiency of current-day power systems when dealing with the growing energy needs and energy security. This work presents an advanced optimization framework, which incorporates the Zebra Optimization Algorithm (ZOA) with two new improvement strategies: the FFDB method and OBL strategies. The FFDB mechanism improves it to balance exploitation and exploration by fine-tuning the contribution of the fitness and distance metrics using the fuzzy logic technique. At the same time, OBL increases population diversity and accelerates convergence by strategically distributing across the solution space. The combination of these elements is the FFDBZOA-OBL algorithm. The proposed algorithm was thoroughly validated in two experiment setups. First, its optimization performance was evaluated on the CEC2020 and CEC2022 benchmarks, showing a better performance than existing methods. Second, the FFDBZOA-OBL was applied to the real-world TEP problem, demonstrating the ability to minimize the costs of investment mechanisms while adjusting to the changing state of affairs in the market and supporting the resilience of local energy supply. Additionally, the robustness and significance of the proposed method are also supported by statistical analysis in the form of Wilcoxon and Friedman tests. Based on the results of the FFDBZOA-OBL approach, the obtained solution is a very competitive and adaptive one in terms of benchmark and practical power system optimization problems.

Recently, the importance of frequency and voltage stability in interconnected power systems has been raising with increasing energy demand and participation of renewable energy sources (RESs) in electric power systems. In this context, high quality, reliable, continuous and stable electrical power transmission should be made to the consumer in modern power systems. The incongruence between the power generation and load demand in sudden load changes in power systems cause undesirable oscillations in the frequency and tie-line power between generation areas. The controllers used to suppress these oscillations in load frequency control (LFC) must operate satisfactorily in line with the desired system criteria. This study proposed a powerful cascade controller structure based on the combination of the PID and FOPID controllers with fractional derivative filters (PID-FOPIDFF) to meet the desired system criteria. Moreover, the parameters of the proposed controller structure are adjusted using Slime Mold Algorithm (SMA), Gradient-based optimizer (GBO), Hunger games search (HGS), weighted mean of vectors (INFO), and RUNge Kutta optimizer (RUN) algorithms. The SMA method offers a percentile decrease of 48.5399%, 119.0483%, 155.0614%, and 200.5109% in comparison to the outcomes of the HGS, GBO, INFO, and RUN algorithms for the ITAE value utilized as the objective function in the optimization process of the proposed PID-FOPIDFF controller. The performance of the proposed controller was compared with the performances of seven different controllers most used in the literature. The PID-FOPIDFF controller, which can respond quickly and dampen frequency and power oscillations, guarantees that system performance will be improved. Three different test systems including combinations of photovoltaic (PV), fuel cell (FC), electrolyser, thermal, hydropower, gas and wind energy systems, and the TCPS from FACTS devices are used to confirm the effectiveness of the method. The simulation results reveal the advantages of the proposed PID-FOPIDFF controller over the commonly used controllers. The robustness of the proposed controller structure is confirmed by the simulation study findings, which included various load and system parameter changing scenarios.

Son zamanlarda, artan enerji talebi ve yenilenebilir enerji kaynaklarının (YEK) elektrik güç sistemlerinde yer almasıyla, enterkonnekte güç sistemlerinde frekans ve gerilim kararlılığının önemi artmaktadır. Modern güç sistemlerinde tüketiciye kaliteli, sürekli ve kararlı elektrik enerjisi iletimi sağlanmalıdır. Güç sistemlerindeki ani yük değişimlerinde güç üretimi ile yük talebi arasındaki uyumsuzluk, üretim bölgeleri arasındaki frekansta istenmeyen salınımlara neden olur. Sistemdeki frekans salınımlarını minimize etmek için yük frekans kontrolü (YFK) uygulanır. Sistemdeki salınımları bastırmak için kullanılan denetleyiciler, istenen sistem kriterleri doğrultusunda tatmin edici bir şekilde çalışmalıdır. Bu bağlamda PID ve PID+DD denetleyici yapılarından yararlanılmıştır. Denetleyici parametrelerinin optimizasyonunda literatürde sunulan GBO, BSA ve BKA algoritmaları kullanılmıştır. YFK problemi, termal, hidroelektrik, gaz, rüzgar ve dizel enerji sistemlerini içeren çok kaynaklı tek alanlı test sisteminde incelenmiştir. Test sisteminin doğrusalsızlığını artırmak için kazan dinamiği yapısı kullanılmıştır. Optimizasyon işlemi sonucunda algoritmaların denetleyici parametrelerini optimize etme başarısı kendi içinde değerlendirilmiş ve BSA algoritmasının diğer algoritmalara göre daha başarılı olduğu görülmüştür.