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The impacts of the transmission line length in an interconnected micro-grid on its performance and protection at different fault levels
Khoshkalam A., Ali D.
AbstractPower systems, in recent years, have been experiencing a dynamic rise in the amount of power obtained from distributed renewable energy sources leading to the concept of microgrids to address the distributed power grid integration issues. Microgrids, a promising means of facilitating the green transformation of power systems, allow the union operation of distributed energy resources (DER) such as combined heat and power (CHP), renewables like photovoltaic (PV), wind and fuel cells (FC), energy storage systems, diesel generators, and controllable loads, either individually or in combination. The protection of DERs within microgrids can be considered as one of the main challenges associated with such phenomenon. Short and Long power transmission lines, in case of a fault, both have particular impacts on system parameters and may result into subsequent events threatening the microgrid and renewable generation units. On the other hand, The high penetration of microgrids not only can change the power flow within the power network, but it can also affect the fault current levels and may lead to their islanding in case of a fault. Before investing in microgrids, especially those in far places, this paper develops a tool to be used in investigating the influence of the interconnecting transmission line length as well as the type/severity of fault on the microgrid performance. The toolbox was developed using MATLAB/Simulink Toolbox. The developed tool was then validated on a case study microgrid and results show that the length of the interconnecting transmission line and the fault severity directly impact the microgrid performance (i.e. voltage and power deviations). In that case, interconnection or islanded mode is contingent upon the decision of the utility operator which also depends on the sensitivity of the equipment used in the microgrid.
Analyzing energy consumption of nature-inspired optimization algorithms
Jamil M.N., Kor A.
Nature-Inspired Optimization (NIO) algorithms have become prevalent to address a variety of optimization problems in real-world applications because of their simplicity, flexibility, and effectiveness. Some application areas of NIO algorithms are telecommunications, image processing, engineering design, vehicle routing, etc. This study presents a critical analysis of energy consumption and their corresponding carbon footprint for four popular NIO algorithms. Microsoft Joulemeter is employed for measuring the energy consumption during the runtime of each algorithm, while the corresponding carbon footprint of each algorithm is calculated based on the UK DEFRA guide. The results of this study evidence that each algorithm demonstrates different energy consumption behaviors to achieve the same goal. In addition, a one-way Analysis of Variance (ANOVA) test is conducted, which shows that the average energy consumption of each algorithm is significantly different from each other. This study will help guide software engineers and practitioners in their selection of an energy-efficient NIO algorithm. As for future work, more NIO algorithms and their variants can be considered for energy consumption analysis to identify the greenest NIO algorithms amongst them all. In addition, future work can also be considered to ascertain possible relationships between NIO algorithms and the energy usage of hardware resources of different CPU architectures.
