Search Results (3)

The deployment of photovoltaic (PV) systems has increased globally to meet renewable energy targets. Intermittent PV power generated due to cloud-induced variability introduces reliability and grid stability issues at higher penetration levels. Variability in power generation can induce voltage fluctuations within the distribution system and cause adverse effects on power quality. Therefore, it is essential to quantify resource variability to mitigate an intermittent power supply. In this study, we propose a new scheme to classify the sky conditions that are based on two common variability metrices: daily clear-sky index and normalized aggregate ramp rates. The daily clear-sky index estimates the cloudiness in the sky, and ramp rates account for the variability introduced in the system generation due to sudden cloud movements. This classification scheme can identify clear-sky, highly variable, low intermittent, high intermittent and overcast days. By performing a Chi-square test on the training and test sets, we obtain Chi-square statistic values greater than 3 with p-value > 0.05. This indicates that the distribution of the training and test clusters are similar, indicating the robustness of the proposed sky classification scheme. We have demonstrated the applicability of the scheme with diverse datasets to show that the proposed classification scheme can be homogenously applied to any dataset globally despite their temporal resolution. Using various case studies, we demonstrate the potential applications of the scheme for understanding resource allocation, site selection, estimating future intermittency due to climate change, and cloud enhancement effects. The proposed sky classification scheme enhances the precision and reliability of solar energy forecasts, optimizing system performance and maximizing energy production efficiency. This improved accuracy is crucial for variability control and planning, ensuring optimal output from PV plants. Full article

The World Energy Council, in its 2019 World Energy Scenarios Report, advised policymakers to identify innovative opportunities for the integration of renewable energy resources into existing electrical power systems to achieve a fast and affordable solution. However, large-scale industries with cogeneration units are facing problems in handling the higher penetration levels of intermittent renewable energies. This paper addresses large-size photovoltaic power integration problems and their optimal operation. This work considers the case of a chemical industry having both cogeneration power and solar photovoltaics. Here, a modified firefly algorithm and a hybrid power resource optimization solver are proposed. The results of the proposed method are compared with other benchmark techniques, to confirm its advantages. The proposed techniques can be used in industries having cogeneration power plants with photovoltaics for better optimization and to meet the guidelines specified in IEEE 1547. The voltage ramp index is proposed to determine the voltage ramp up and down with intermittent solar irradiance. Additionally, a machine learning technique is used to predict the cogeneration plant efficiency at different loads and the solar irradiance under varying weather conditions. Finally, this paper proposes the effectiveness of the modified heuristic technique and certain guidelines, including solvers for industrial use. Full article

In this paper, the generator angle stability of several active power control schemes of a voltage-source converter (VSC)-based high-voltage DC (HVDC) is evaluated for two interconnected AC systems. Excluding frequency control, there has been no detailed analysis of interconnected grids depending upon the converter power control, so six different types of active power control of the VSC-HVDC are defined and analyzed in this paper. For each TSO (transmission system operator), the applicable schemes of two kinds of step control and four kinds of ramp-rate control with a droop characteristic are included in this research. Furthermore, in order to effectively evaluate the angle stability, the Generators-VSC Interaction Factor (GVIF) index is newly implemented to distinguish the participating generators (PGs) group which reacts to the converter power change. As a result, the transient stabilities of the two power systems are evaluated and the suitable active power control strategies are determined for two TSOs. Simulation studies are performed using the PSS^®E program to analyze the power system transient stability and various active power control schemes of the VSC-HVDC. The results provide useful information indicating that the ramp-rate control shows a more stable characteristic than the step-control for interconnected grids; thus, a converter having a certain ramp-rate slope similar to that of the other generator shows more stable results in several cases. Full article