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Risk-based preventive energy management for resilient microgrids

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A microgrid's energy management system (EMS) is typically formulated as a deterministic optimization problem. However, more risks and uncertainties are emerging due to the increasing complexity of the power system structure with intelligent distributed energy integration. As a result, different types of risks must be considered while implementing the EMS to improve system resiliency. In this paper, a risk-based EMS is introduced for islanded microgrids. A scenario-based optimization method is formulated for the EMS, where each system component's probability of failure (PoF) is considered in each scenario. In addition, the loads are classified into critical, semi-critical, and non-critical loads to prioritize serving the essential loads during a shortage of generation resources in microgrids. The nonlinear power flow equation of the new problem formulation is relaxed into a convex form to reduce the computational burden. In detail, the system's resiliency is improved by employing three functionalities in the EMS as a preventive measure: a) prioritizing to serve the critical loads, b) lowering the total amount of load served to mitigate the impact of the failure of any system component, and c) reducing the dependency on the generation resources with high PoF. The proposed preventive and risk-based EMS is validated against IEEE-14, 30, and 118 bus systems. The results demonstrate that the proposed EMS sheds more loads than the base EMS, based on the PoF of each system component, due to the knowledge that risks of failure of any component may induce a cascading failure and even blackout if only base EMS is provided. Moreover, the proposed EMS precisely considers the criticality of loads for curtailment to match the available system resources. The curtailment indirectly improves the system's resiliency by increasing the chance of sur-vivability in the islanded mode with the probability of future component failure.

Energy management systemIslanded mode of operationScenario-based optimizationRisk managementResiliencyMicrogrids

Md Isfakul Anam、Thai-Thanh Nguyen、Tuyen Vu

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Clarkson University, United States

New York Power Authority, United States

2023

International journal of electrical power and energy systems

International journal of electrical power and energy systems

EI
ISSN:0142-0615
年,卷(期):2023.154(Dec.)
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