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“microgrids For Resilience: Ensuring Power During Natural Disasters”
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Microgrid Fundamentals: How Microgrids Will Power The Future
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Mariam Ibrahim Mariam Ibrahim Scilit Preprints.org Google Scholar 1, * and Asma Alkhraibat Asma Alkhraibat Scilit Preprints.org Google Scholar 2
Received: 2020 January 30 / Revised: 2020 February 27 / Accepted: 2020 March 2 / Published in 2020 March 6
Microgrids And The Energy Transition
Measuring the resilience of smart grid systems is one of the most important topics to ensure reliable and efficient operation during attacks. This paper presents a set of factors used to quantify the resilience of microgrid (MG) systems. A measure of the level of resistance (LoR) is determined by examining the percentage of voltage drop, the level of performance degradation (LoP).
), as measured by the percentage of service load drop, the recovery time (RT), which is the time it takes the system to detect an attack/fault and recover from it, and the time it takes to reach a power balance state (T
) in island mode. As an illustrative example, a comparison of two MG topologies based on the resilience level is given under an attack scenario.
Microgrid (MG) systems have been a topic of interest in the power industry worldwide. They efficiently integrate a combination of solar, wind and other renewable energy sources (RES). MG consists of distributed power generation facilities, load and storage systems connected through transmission lines and transformers. It can be used in two modes: utility mode or island mode. In connected mode, the MG receives power from its own generating units, but in the event of a power outage, power will be supplied from the mains. Excess power can also be sold to the main grid. In island mode, the MG acts as an independent power system.
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MG can be implemented in a variety of locations, from large buildings to isolated rural villages. Figure 1 shows the schematic diagram of the MG system. A Point of Common Connection (PCC) is a main circuit breaker (CB) that is used to switch the operating mode between grid-connected and islanded modes. With MG supporting several roles and purposes, many studies have been conducted highlighting MG as a promising research area [1, 2, 3]. An overview of the MG system as an essential key in smart energy grids is given in reference . In addition, Reference  proposes an advanced and functional MG architecture with detailed information on bottlenecks MGs may encounter, especially when switching between MG operation modes.
A list of existing MG projects worldwide is given in reference . For example, Fort Carson in Colorado Springs is one of several MG projects underway at US bases under the SPIDERS (Smart Power Infrastructure Demonstration for Energy Reliability and Security) program. SPIDERS MG consists of existing assets, a 1 MW PV array and three diesel generators totaling 3 MW, and five electric vehicles. The MG project is designed to maintain a cluster of central base units operating without grid power as an island in the event of a grid failure. Sendai MG project in Japan in 2005-2008. carried out by the New Energy and Industrial Technology Development Organization (NEDO). MG showed excellent results during 2011. earthquake and tsunami by providing power and heat to the Tohuku Fukushi University Teaching Hospital. for the two-day power outage period. MG project in Mannheim-Wallstadt, Germany, 2006. implemented by the state utility company. The main goal of this project was to create a true MG that can quickly and seamlessly switch from grid-connected mode to island mode. The system is designed for residential and commercial units and cargo.
Resilience of power systems refers to its ability to withstand faults and any unusual conditions that may cause power outages. It also allows you to perform a system restore to restore normal operation. The innovation of this paper is the introduction of Level of Resilience (LoR) as a tool to compare and evaluate different MG topologies simulated using MATLAB during a failure/attack scenario. LoR is determined by percentage of voltage drop, drop in load served and recovery time. Another advantage used to determine LoR is the time required to reach the power balance state when the main grid is not present (island mode). In this mode, we investigated the effect of the load reduction technique as a strategy to increase MG resistance during attack. It is shown that the placement of MG resources can affect MG resilience as indicated by the LoR metric. Thus, using this metric, other designs can be explored to achieve best-case resilience with a given set of resources.
The remainder of the paper is organized as follows: Section 1.1 introduces recent related work. Topologies and architecture of the proposed MG are illustrated in Section 2. Section 3 presents the formulation of the resilience measure. Chapter 4 shows how to increase resistance using the load reduction technique. The results of the experiment are presented in Chapter 5. Chapter 6 summarizes and provides some future directions.
Microgrids 101: An Introduction To Microgrids
Various microgrid (MG) system resilience measures have been investigated in the literature. For example, reference  presents a method for quantifying the resistance measure of MG based on networking, failure rate and weather factor. From a network perspective, connectivity metrics are specified by determining the nature of connectivity between deployed nodes. Other calculated metrics are load metrics that represent the load that was not disconnected due to critical events such as weather issues. The failure rate indicated the degree of robustness of the system, while the weather factor defined the effect of weather on the system’s resilience. Power supply system shutdown duration is proposed in reference  as a resilience measure. This fault can be caused by a fault in the distribution system. In this paper, it was believed that the key to the resilience of distributed systems is based on two main factors. These factors are the installed electricity distribution system infrastructure and the restoration priority scheme provided by the energy company. The proposed measure has been tested on a residential power distribution system located in the Phoenix, Arizona area. In reference , the authors evaluated a measure of MG resilience during high impact low probability (HILP) wind storms. This robustness measure is mainly based on performance degradation and other normalized metrics that are used in the robustness comparison process under different operating conditions. A real MG test site is used to study and examine the proposed methods.
A resistance quantification method, which was mainly aimed at providing uninterrupted power to a critical load, is proposed in reference . Resilience assessment is stated as a decision-making problem using multiple measures. In this study, it was quantified using two methods, which are the graph-theoretic approach and the Choquet integral. Similar to our work, the simulation of operational contingency scenarios realized in reference  confirms the fact that the power system resilience depends on the number of paths connecting the source units to the loads.
An advanced code-based metric is implemented in reference  to quantify a measure of electrical distribution system resilience. This resilience metric is specified through a modeling process based on steady-state and dynamic modeling tools. As can be seen from the results, the utilization of the output data of the proposed technique has greatly supported the reliability factor of the system in selecting the appropriate design of the power distribution system. Like our work, the scheme presented in reference  can be modified for different power system topologies. Reference  uses the Transportable Energy Storage System (TESS) concept to explore the proposed resilience metric. The authors of this paper proposed a disaster recovery framework that includes a TESS planning process and, in turn,