Journal of Green Energy Research and Innovation

Abstract In electrical distribution networks, inefficiencies and instabilities often arise from inductive loads like motors and transformers, which exhibit a lagging power factor. This reduces system capacity, increases losses, and can lead to lower voltage levels. To address these issues, integrating parallel capacitors proves effective, enhancing the power factor, improving voltage profiles, and reducing overall system losses and costs. This research explores the optimal placement of parallel capacitors within a distribution network to manage reactive power effectively, thereby minimizing losses and improving voltage stability and system efficiency. Utilizing DigSILENT Power Factory and MATLAB, a genetic algorithm optimizes the location and sizing of capacitors in a 33-bus distribution network, considering scenarios with and without distributed generation (DG) and the impact of harmonic currents. The study finds that incorrect sizing or placement of capacitors can worsen voltage deviations when higher harmonic levels are present. However, the optimization method accurately determines the best parameters for capacitor installation, ensuring compliance with voltage and harmonic constraints. Deploying more than three to four capacitors does not significantly affect outcomes, while a single busbar capacitor often fails to meet operational standards. In conclusion, strategic capacitor placement and sizing can significantly reduce losses, enhance voltage stability, and mitigate inefficiencies caused by inductive loads. Attention to harmonics is crucial to avoid negative impacts on the network. This approach offers a replicable framework for similar optimizations in other distribution systems, advancing smart grid technology implementation.

Abstract Renewable wind energy is a significant source of green energy supply that has gained considerable attention and development in numerous countries in recent years. These systems are utilized as islanded units in circumstances where it is not feasible to establish a connection to the network. Various structures exist for these systems, but the focus of many studies has been on wind energy conversion systems based on a squirrel cage induction machine with back-to-back converters. When operating in islanded mode, this structure necessitates specific control requirements, with the most crucial being the supplying of the desired voltage and frequency of the load. In this paper, two control structures are proposed and constructed to regulate the load voltage by controlling the load-side converter. Two control loops have been implemented in the first control structure. The inner loop utilizes the state feedback input-output method to control the voltage, while the outer loop employs the sliding mode method to control the power components. The objective is to derive the control law for the reference biaxial voltage of the load-side converter. The second proposed structure incorporates the voltage controller sliding mode control method in the inner loop and then the state feedback input-output method is employed in the outer loop to control the current components of the load-side converter, thus designing the system control input. The simulation results of both structures in MATLAB software have been compared by introducing various disturbances to assess the control systems' resilience to each other and the common proportional-integral linear control structure. In the suggested method, voltage and current variations manifest concurrently in the control structure predicated on power components.

Abstract In recent decades, because of some main and principle world problems such as increasing the population, global warming, climate changes, and fossil fuel sources reduction, the using of renewable energies has impressively increased that can solve and reduce the caused problems by traditional power plants, and also can control power system the important indexes such as losses, voltage drop, transferring capacity. Reactive power has an important role in controlling and minimizing of losses, the optimal distribution of reactive power in presence of Distributed generation (DG) units in distribution networks is an important and key problem. In this paper, for uncertainties modelling of DG units and optimizing the reactive power, the statistical-quality based Taguchi method and Genetic algorithm are used, respectively.  The simulation of this paper is checked and done in MATLAB and MINITAB using IEEE 57-bus standard network, and simulation results show 5.5 MW reduction of the distribution network losses.

Abstract The demand for non-renewable energy sources in power generation is crucial for residential and commercial uses, significantly impacting national development. However, with the depletion of fossil fuels, there is a shift towards renewable energy sources such as solar, water, and wind, which have seen a surge in use over recent decades. In Iran, despite abundant fossil fuel resources, solar energy is vital due to the country's favorable geographic conditions for solar exploitation. This study applies the analytic network process (ANP) and Genetic algorithm (GA) to identify optimal locations for Solar Power Plant Stations in Markazi province, Iran. Key morphological factors considered include slope, elevation, and solar radiation. The research identified the northwest and northern parts of Markazi province as the most suitable for solar photovoltaic systems, primarily due to their simpler topography. Using a genetic algorithm, which outperformed the ANP, it was found that about 24,000 km² in these areas are apt for solar power facilities, categorized into highly suitable (2,429.312 km²), moderately suitable (16,818.49 km²), and suitable (5,029.007 km²). Saveh showed the highest potential, while Ashtian, Khondab, and Shazand had the least. These findings provide crucial insights for stakeholders looking to develop solar energy projects in Markazi province.

Abstract Common sources of electricity production, such as fossil fuels, create a large amount of pollution; furthermore, these sources will run out in the future. Therefore, the use of new sources and renewable energies are very vital for electricity production. This paper provides a comprehensive study to explore and analyze new and renewable electrical energy sources for the production of electricity. The study assesses the awareness, perceptions, and preferences of individuals regarding innovative technologies and sources that have the potential to reshape the landscape of electrical power generation. In this research, various types of novel and renewable sources for electricity production are explained and the challenges, advantages, and disadvantages of each of these methods are discussed.

Abstract This research presents a comprehensive analysis of the performance of direct power control (DPC) for doubly-fed induction generator (DFIG) under both balanced and unbalanced network voltages. Voltage unbalance in three-phase systems results in the presence of positive and negative sequences in both voltages and currents. This unbalance leads to many issues, including active power ripple, reactive power ripple, and an increase in the Total Harmonic Distortion (THD) of the stator current. Therefore, it is crucial to have efficient control of the system to reduce power fluctuations. This research presents two solutions that aim to mitigate the fluctuations in both active and reactive power. The first strategy employs PI regulators within the controller system. A high selectivity filter (HSF) is employed to separate the fundamental component of stator phase currents from the harmonic components. The second option utilizes DPC (Direct Power Control) based on stator flux. The suggested method computes the active and reactive powers that correspond to positive sequence variables. Since grid unbalance has a smaller impact on stator flux compared to stator voltage, it can be demonstrated that the second suggested controller exhibits superior performance to the conventional DPC controller in unbalanced situations. To evaluate the effectiveness of the suggested techniques, a simulation is conducted on a 2MW Doubly-Fed Induction Generator (DFIG) system using the MATLAB/Simulink environment. The results demonstrate that both of the suggested DPC control approaches outperform the conventional DPC controller in terms of control system performance, even under unbalanced situations. Furthermore, these improvements are achieved without significantly increasing the complexity of the control system.