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An electrical islanding detection method for DC microgrid (MG) is proposed in this paper. Unlikely conventional AC MG system protection has been challenging for the DC MG system. The goal of the proposed scheme is to detect the islanding intelligently within the agent nodes. The proposed islanding detection technique detects the electrical link failure intelligently, and if any electrical link failure occurs, then the proposed technique maintains the MG operation and load sharing. Islanding detection is carried out using an injection signal and utilizes the existing communication network to check network connectivity. After checking the network connectivity, all the nodes maintain the look-up table of the connected network. This research work illustrates that the proposed electrical islanding detection technique is effective in maintaining the DC MG operation in the case of an electrical islanding/link failure scenario. The proposed scheme's performance is checked through MATLAB/Simulink for the detection of islanding and maintaining the operation. [ABSTRACT FROM AUTHOR]

The multiple uncertainties in a microgrid, such as limited photovoltaic generations, ups and downs in the market price, and controlling different loads, are challenging points in managing campus energy with multiple microgrid systems and are a hot topic of research in the current era. Microgrids deployed at multiple campuses can be successfully operated with an exemplary energy management system (EMS) to address these challenges, offering several solutions to minimize the greenhouse gas (GHG) emissions, maintenance costs, and peak load demands of the microgrid infrastructure. This literature survey presents a comparative analysis of multiple campus microgrids' energy management at different universities in different locations, and it also studies different approaches to managing their peak demand and achieving the maximum output power for campus microgrids. In this paper, the analysis is also focused on managing and addressing the uncertain nature of renewable energies, considering the storage technologies implemented on various campuses. A comparative analysis was also considered for the energy management of campus microgrids, which were investigated with multiple optimization techniques, simulation tools, and different types of energy storage technologies. Finally, the challenges for future research are highlighted, considering campus microgrids' importance globally. Moreover, this paper is expected to open innovative paths in the future for new researchers working in the domain of campus microgrids. [ABSTRACT FROM AUTHOR]

Integration of renewable energy resources and conventional grids leads to an increase in power quality issues. These power quality issues require different standards to be followed for accurate measurement and monitoring of various parameters of the power system. Conventional power quality analyzers (PQAs) are programmed to a particular standard and cannot be reconfigured by the end user. Therefore, conventional PQAs cannot meet the challenges of a rapidly changing grid. In this regard, a Compact RIO-based (CRIO-based) PQA was proposed, that can be easily reprogrammed and cope with the challenges faced by conventional PQAs. The salient features of the proposed PQA are a high processing speed, interactive interface, and high-quality data-storage capacity. Moreover, unlike conventional PQAs, the proposed PQA can be monitored remotely via the internet. In this research, a hardware-in-loop (HIL) simulation is used for performing the power-quality assessment in a systematic manner. Power quality indices such as apparent power, power factor, harmonics, frequency disturbance, inrush current, voltage sag and voltage swell are considered for validating the performance of the proposed PQA against the Fluke's PQA 43-B. [ABSTRACT FROM AUTHOR]