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Load flow analysis is an essential tool for the reliable planning and operation of interconnected power systems. The constant increase in power demand, apart from the increased intermittency in power generation due to renewable energy sources without proportionate augmentation in transmission system infrastructure, has driven the power systems to function nearer to their limits. Though the power flow (PF) solution may exist in such circumstances, the traditional Newton–Raphson based PF techniques may fail due to computational difficulties owing to the singularity of the Jacobian Matrix during critical conditions and faces difficulties in solving ill-conditioned systems. To address these problems and to assess the impact of large-scale photovoltaic generator (PVG) integration in power systems on power flow studies, a derivative-free quasi-oppositional heap-based optimization (HBO) (QOHBO) technique is proposed in the present paper. In the proposed approach, the concept of quasi-oppositional learning is applied to HBO to enhance the convergence speed. The efficacy and effectiveness of the proposed QOHBO-PF technique are verified by applying it to the standard IEEE and ill-conditioned systems. The robustness of the algorithm is validated under the maximum loadability limits and high R/X ratios, comparing the results with other well-known methods suggested in the literature. The results thus obtained show that the proposed QOHBO-PF technique has less computation time, further enhancement of reliability in the presence of PVG, and has the ability to provide multiple PF solutions that can be utilized for voltage stability analysis. [ABSTRACT FROM AUTHOR]

The restructuring of power systems and the ever-increasing demand for electricity have given rise to congestion in power networks. The use of distributed generators (DGs) may play a significant role in tackling such issues. DGs may be integrated with electrical power networks to regulate the drift of power in the transmission lines, thereby increasing the power transfer capabilities of lines and improving the overall performance of electrical networks. In this article, an effective method based on the Harris hawks optimization (HHO) algorithm is used to select the optimum capacity, number, and site of solar-based DGs to reduce real power losses and voltage deviation. The proposed HHO has been tested with a complex benchmark function then applied to the IEEE 33 and IEEE 69 bus radial distribution systems. The single and multiple solar-based DGs are optimized for the optimum size and site with a unity power factor. It is observed that the overall performance of the systems is enhanced when additional DGs are installed. Moreover, considering the stochastic and sporadic nature of solar irradiance, the practical size of DG has been suggested based on analysis that may be adopted while designing the actual photovoltaic (PV) plant for usage. The obtained simulation outcomes are compared with the latest state-of-the-art literature and suggest that the proposed HHO is capable of processing complex high dimensional benchmark functions and has capability to handle problems pertaining to electrical distribution in an effective manner. [ABSTRACT FROM AUTHOR]

Although over 100 species of Curcuma are reported, only Curcuma longa is extensively studied. Curcuma raktakanda, a poorly studied species, is most commonly distributed in the Kerala state of India. For the first time, we examined the efficacy of different fractions (acetone, hexane, and ethyl acetate) of C. raktakanda against glioma, cervical, and breast cancer cell lines. As determined by mitochondrial reductase activity assay, the viability of cancer cells was decreased in a concentration-dependent manner by the three fractions. The half maximal inhibitory concentration (IC-50) values after the treatment of C-6 glioma cells for 48 h was found to be 32.97 µg/mL (acetone extract), 40.63 µg/mL (hexane extract), and 51.65 µg/mL (ethyl acetate extract). Of the three fractions, the acetone fraction was more effective. The long-term colony formation of cancer cells was significantly suppressed by the acetone fraction. Analyses using DAPI (4′,6-diamidino-2-phenylindole) staining, AO/PI (acridine orange/propidium iodide) staining, DNA laddering, and sub-G1 population revealed that the acetone extract induced apoptosis in glioma cells. The extract induced reactive oxygen species generation and suppressed the expression of cell survival proteins. The migration of cancer cells was also suppressed by the acetone extract. The gas chromatography-mass spectrometry (GC-MS) analysis indicated that tetracontane, dotriacontane, hexatriacontane, pentacosane, hexacosane, and eicosane are the major components in the acetone extract. Collectively, the extract from C. raktakanda exhibited anti-carcinogenic activities in cancer cells. We are exploring whether the phytoconstituents, individually, or collectively contribute to the anti-cancer activities of C. raktakanda. [ABSTRACT FROM AUTHOR]