Optimal Load Shedding for Voltage Collapse Prevention Following Overloads in Distribution System

Load shedding is generally regarded as the final option to evade voltage collapse and blackout following major overloads. The traditional method of load shedding curtails random loads regardless of their importance until the system’s voltage is improved. Shedding random loads without considering their priority will lead to power interruption in vital infrastructures. Hence, to improve the existing power system protection scheme, development of a more effective and efficient load shedding method is necessary. In this paper, an optimal under voltage load shedding (UVLS) method is proposed for optimum prediction of amount of load shed and the best location for load curtailment. Moreover, the proposed method is designed to maintain the vital loads in the system during the load shedding process. In this work, the stability index (SI) and feed-forward backpropagation neural network (FFBPNN) were adopted to avoid voltage collapse and blackout by mitigating voltage instability following overloads in distribution system. The performance of the proposed method to several overload scenarios is investigated. Case studies performed on the IEEE 33-bus system exposed significant robustness and performance of the recommended technique. Compared to other approaches, the proposed approach is efficient in counteracting under-shedding occurrence, enhancing the voltage profile, and improving the stability of the system, whilst maintaining vital loads in the system during load sheddin

Anaerobic co-digestion of different wastes in a UASB reactor

Anaerobic co-digestion has made a greater impact on the biogas production from mixing different type of waste. In this research, sewage sludge (SS) and cow manure (CM), was used as a primary waste along with kitchen waste (KW), yard waste (YW), floral waste (FW) and dairy wastewater (DWW) as co-substrate for anaerobic digestion. Mixtures with a ratio of 1:2 ratio is fed into a single stage up-flow anaerobic sludge blanket (UASB) reactor. Digestion was carried out in a mesophilic temperature range for 20 days. pH and VFA were measured and ranged from 5 to 7.5 and 3500–500 mg/L, respectively, for all the mixtures throughout the digestion period. Percentage of COD removal efficiency after 20 days was found to be in the range of 76–86%. The maximum biogas production rate was found to be 4500 mL/day. Characterization of the final residue from each of the digesters was carried out by Scanning Electron microscope, Energy dispersive, thermogravimetric, FTIR Spectra, and Atomic microscope. Thermal analysis reveals that spent sludge can be potential waste energy sources

Quantitative detection of pharmaceuticals using a combination of paper microfluidics and wavelength modulated Raman spectroscopy

Raman spectroscopy has proven to be an indispensable technique for the identification of various types of analytes due to the fingerprint vibration spectrum obtained. Paper microfluidics has also emerged as a low cost, easy to fabricate and portable approach for point of care testing. However, due to inherent background fluorescence, combining Raman spectroscopy with paper microfluidics is to date an unmet challenge in the absence of using surface enhanced mechanisms. We describe the first use of wavelength modulated Raman spectroscopy (WMRS) for analysis on a paper microfluidics platform. This study demonstrates the ability to suppress the background fluorescence of the paper using WMRS and the subsequent implementation of this technique for pharmaceutical analysis. The results of this study demonstrate that it is possible to discriminate between both paracetamol and ibuprofen, whilst, also being able to detect the presence of each analyte quantitatively at nanomolar concentrations.Publisher PDFPeer reviewe