Keeping the bus voltage within acceptable limits depends on dispatching reactive power. Power quality improves as a result of creating an effective power flow system, which also helps to reduce power loss. Therefore, optimal reactive power dispatch (ORPD) studies aim at designing appropriate system configurations to enable a reliable operation of power systems. Establishment of such a configuration is handled through control variables in power systems. Various control variables, such as adjusting generator bus voltages, transformer tap locations, and switchable shunt capacitor sizes, are utilized to achieve this objective. Additionally, the integration of wind power can greatly impact power quality and mitigate power loss. In this study, the Grey Wolf Optimization (GWO) approach was applied to the ORPD issue for the first time to discover the best placement of newly installed wind power in the power system while taking into account tap changer settings, shunt capacitor sizes, and generated power levels. The main objective was to determine optimal wind placement to minimize power loss and voltage deviation, while maintaining control variables within specified limits. On the basis of IEEE 30-bus and IEEE 118-bus systems, the performance of the proposed method was investigated. The results demonstrated the superiority of GWO in multiple scenarios. In IEEE-30, GWO outperformed the PSO, GA, ABC, OGSA, HBMO, and HFA methods, reducing total loss by 10.36%, 18.03%, 9.19%, 7.13%, 5.23%, and 7.73%, respectively, and voltage deviation by 68.00%, 1.59%, 36.34%, 41.97%, 46.29%, and 71.08%, respectively. In wind integration scenarios, GWO achieved the simultaneous reduction of power loss and voltage deviation. In IEEE-118, GWO outperformed the ABC, PSO, GSA, and CFA methods, reducing power loss by approximately 19.91%, 16.83%, 14.09%, and 4.36%, respectively, and voltage deviation by 8.50%, 14.15%, 16.19%, and 7.17%, respectively. These promising results highlighted the potential of the GWO algorithm to facilitate the integration of renewable energy sources, and its role in promoting sustainable energy solutions. In addition, this study conducted an analysis to investigate site-specific wind placement by using the Weibull distribution function and commercial wind turbines.

In recent years, sustainable and clean renewable energy resources are widely used instead of fossil fuel energy resources in electrical energy generation systems. Especially, wind and solar energy conversion systems are utilized together in stand-alone systems. In this study, reliability analysis of a hybrid system installed in Davutpasa Campus of Yildiz Technical University is investigated. The system includes a wind turbine, PV panels, a hybrid charge regulator, a MPPT charge controller, an inverter, battery group and loads. Reliability indexes are calculated for analyzed system. The obtained results are examined and presented in this paper.

A secure and reliable supply of energy is important for economic stability and even in social life. Increasing human population, industrialization, and rising living standards lead to increased electrical energy demand. Uncertainties in oil prices, shortage of fossil fuel reserves, and environmental pollution from conventional fuels leads solar energy as an alternative resource for electricity production. The share of installed photovoltaic (PV) capacity as a percent of total installed power generating capacity is increasing every year. In this study, an improved methodology to design large-scale PV power plant is proposed. The proposed methodology is performed for designing optimal configurations of PV power plants. The design methodology is performed using commercially available PV modules and inverters. In addition, solar radiation, ambient temperature, wind speed, shadow effect, and location and shape of plant field are taken into consideration as input parameters. The alternatives and parameters are evaluated with the purpose of minimizing the levelized cost of generated electricity (LCOE). The methodology includes the use of a genetic algorithm (GA) for determining the optimal number of PV modules and inverters, optimum tilt angle of PV modules, required installation area for the plant and optimum cable cross section and lengths. In the paper, the methodology is implemented, and case studies and results using pvsyst software for the same case studies are compared with each other.

In the deregulated power industry, effective procurement of the Ancillary Services (AS) is essential in order to both reliable supply to customer and power system security. AS are used in order to operate the system reliably within enterprise safety along with the criteria regarding supply quality and operating conditions. Demand decrease set Spinning Reserve (SR) for power systems and capital cost investments and for all plants. Influential control of SR supply important cost decrease for large power systems. This study propose that set a reserve with the governor action and load shedding function depending on demand. This make possible the reliability of individual units and the uncertainty of the load forecast to the considered for short-term scheduling. While it is easy to implement decisive criterion, this situation does not conform to the structure prediction problems. Thus, the technique have been proposed for determining SR capacity depending on demand.