Identification and characterization of irregular consumptions of load data

The historical information of loadings on substation helps in evaluation of size of photovoltaic (PV) generation and energy storages for peak shaving and distribution system upgrade deferral. A method, based on consumption data, is proposed to separate the unusual consumption and to form the clusters of similar regular consumption. The method does optimal partition of the load pattern data into core points and border points, high and less dense regions, respectively. The local outlier factor, which does not require fixed probability distribution of data and statistical measures, ranks the unusual consumptions on only the border points, which are a few percent of the complete data. The suggested method finds the optimal or close to optimal number of clusters of similar shape of load patterns to detect regular peak and valley load demands on different days. Furthermore, identification and characterization of features pertaining to unusual consumptions in load pattern data have been done on border points only. The effectiveness of the proposed method and characterization is tested on two practical distribution systems

Experimental investigation of dielectric barrier impact on breakdown voltage enhancement of copper wire-plane electrode systems

Non-pressurized air is extensively used as basic insulation media in medium / high voltage equipments. An inherent property of air-insulated designs is that the systems tend to become physically large. Application of Dielectric barrier can increase the breakdown voltage and therefore decrease the size of the equipments. In this paper, the impact of dielectric barrier on breakdown voltage enhancement of a copper wire-plane system is investigated. For this purpose, the copper wire is covered with different dielectric materials. Depending on the air gap and dielectric strength of the barrier the breakdown can be initiated in the solid or gas dielectric. Theoretically, free charges are affected by the electric field between the electrodes and accumulated at the dielectric surface, this leads to the reduction of electric field in air gap and enhancement of the ifield in the dielectric layer. Therefore, with appropriate selection of the barrier thickness and material, it is possible to increase the breakdown voltage of the insulation system. The influence of different parameters like inter-electrode spacing, and dielectric material on the break-down voltage is investigated for applied 50 Hz AC and DC voltages. The results indicate that up to 240% increase of the breakdown voltage can be achieved

Weather Forecasting Error in Solar Energy Forecasting

As renewable distributed energy resources (DERs) penetrate the power grid at an accelerating speed, it is essential for operators to have accurate solar photovoltaic (PV) energy forecasting for efficient operations and planning. Generally, observed weather data are applied in the solar PV generation forecasting model while in practice the energy forecasting is based on forecasted weather data. In this paper, a study on the uncertainty in weather forecasting for the most commonly used weather variables is presented. The forecasted weather data for six days ahead is compared with the observed data and the results of analysis are quantified by statistical metrics. In addition, the most influential weather predictors in energy forecasting model are selected. The performance of historical and observed weather data errors is assessed using a solar PV generation forecasting model. Finally, a sensitivity test is performed to identify the influential weather variables whose accurate values can significantly improve the results of energy forecasting

Comparative study on various dielectric barriers and their effect on breakdown voltage

Non-pressurised air is extensively used as basic insulation medium in high-voltage equipment. Unfortunately, an inherent property of air-insulated design is that the system tends to become physically large. On the other hand, the application of dielectric barriers can increase the breakdown voltage and therefore decrease the size of the equipment. In this study, the impact of dielectric barriers on breakdown voltage enhancement is investigated under both direct current (dc) and alternating current (ac) applied voltages. For this purpose, three kinds of dielectric barriers in two different high-voltage electrode structures are investigated. In the first structure, several experiments are carried out with four different electrode arrangements, keeping the inter-electrode gap constant while varying the position of the dielectric barrier between the electrodes. In the second structure, the inter-electrode gap is varied while the high-voltage electrode is covered with dielectric materials. The influences of different parameters such as inter-electrode spacing, electric field non-uniformity factor, and dielectric materials on the breakdown voltage are investigated for applied 50 Hz ac and dc voltages. In addition, a simulation model to approximately calculate the breakdown voltage is proposed and validated with the experimental results

Comparative study on various dielectric barriers and their effect on breakdown voltage

Non-pressurised air is extensively used as basic insulation medium in high-voltage equipment. Unfortunately, an inherent property of air-insulated design is that the system tends to become physically large. On the other hand, the application of dielectric barriers can increase the breakdown voltage and therefore decrease the size of the equipment. In this study, the impact of dielectric barriers on breakdown voltage enhancement is investigated under both direct current (dc) and alternating current (ac) applied voltages. For this purpose, three kinds of dielectric barriers in two different high-voltage electrode structures are investigated. In the first structure, several experiments are carried out with four different electrode arrangements, keeping the inter-electrode gap constant while varying the position of the dielectric barrier between the electrodes. In the second structure, the inter-electrode gap is varied while the high-voltage electrode is covered with dielectric materials. The influences of different parameters such as inter-electrode spacing, electric field non-uniformity factor, and dielectric materials on the breakdown voltage are investigated for applied 50 Hz ac and dc voltages. In addition, a simulation model to approximately calculate the breakdown voltage is proposed and validated with the experimental results

Signaling pathways involved in chronic myeloid leukemia pathogenesis: the importance of targeting Musashi2-Numb signaling to eradicate leukemia stem cells

Objective(s): Chronic myeloid leukemia (CML) is a myeloid clonal proliferation disease defining by the presence of the Philadelphia chromosome that shows the movement of BCR-ABL1. In this study, the critical role of the Musashi2-Numb axis in determining cell fate and relationship of the axis to important signaling pathways such as Hedgehog and Notch that are essential for self-renewal pathways in CML stem cells will be reviewed meticulously.Materials and Methods: In this review, a PubMed search using the keywords of Leukemia, signaling pathways, Musashi2-Numb was performed, and then we summarized different research works.Results: Although tyrosine kinase inhibitors such as Imatinib significantly kill and remove the cell with BCR-ABL1 translocation, they are unable to target BCR-ABL1 leukemia stem cells. The main problem is stem cells resistance to Imatinib therapy. Therefore, the identification and control of downstream molecules/ signaling route of the BCR-ABL1 that are involved in the survival and self-renewal of leukemia stem cells can be an effective treatment strategy to eliminate leukemia stem cells, which supposed to be cured by Musashi2-Numb signaling pathway.Conclusion: The control of molecules /pathways downstream of the BCR-ABL1 and targeting Musashi2-Numb can be an effective therapeutic strategy for treatment of chronic leukemia stem cells. While Musashi2 is a poor prognostic marker in leukemia, in treatment and strategy, it has significant diagnostic value

Control and Monitoring Strategies of Smart Grids Using Artificial Intelligent Methods

Several new challenges have arisen recently in the operation of power systems. First, the high penetration of renewable resources in distribution systems in the form of microgrids add uncertainty and complexity to the systems. Variability of renewable resources can violate the robustness of microgrids and cause system instability. The second challenge stems from increasing amount of power trading in the restructured power system; thus, systems are being pushed closer to their operations boundaries. In this situation, power system security can become a critical concern, since occurring contingencies in the system can lead to system blackout. The 2008 California blackout serves as an example. The research to follow has a twofold-objective: First, to address the robust and optimal operation of renewable resources in the microgrid by designing microgrid energy management; and Second, to alleviate the higher risk of operating in restructured power markets by developing online models for real-time system monitoring. In the first part, we propose distributed energy management in a two-staged energy market, with considering probability of distributed energy resources outages. The uncertainties involved in the nature of microgrids due to the variability in renewable generation is modeled using iterative Monte Carlo simulations and infused into energy management framework. A reinforcement learning algorithm is created as an AI algorithm to allow generation resources, distributed storages, and customers to develop optimal strategies for energy management and load scheduling in the microgrid system. In the second part, we develop an online power system monitoring module utilizing a state-of-the-art machine learning and a convolutional neural network based on the AI approach. In the online intelligent pattern recognition module, the data streaming of system phase angle, driven from phasor measurement units or a state estimator, is processed to assess power system stress conditions. Power system stress is an indicator about transmission lines overloading. The proposed module can reveal the hidden patterns between phase angles of buses and system stress conditions to provide fast and accurate stress status and predict the severity of system stress. The models proposed can be used to improve microgrid energy management and bulk power system security