Hybrid Optimization Toward Proactive Resilient Microgrid Scheduling

Michael H. Spiegel,Thomas I. Strasser

doi:10.1109/access.2021.3110607

Michael H. Spiegel, Thomas I. Strasser

Open Access

https://doi.org/10.1109/access.2021.3110607

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Abstract

Microgrids are one important lever to increase power system resilience and to tightly integrate renewable energies at the same time. Commonly, an optimization-based proactive scheduling controls assets in advance in a cost-effective way and ensures that contingencies may be successfully mitigated. However, often strong simplifications are introduced to manage the high computational complexity of scheduling, which can adversely impact fault mitigation. To consider essential phenomena such as power flow limitations and low-level control capabilities in detail, a novel hybrid scheduling approach is presented that integrates mathematical programming and arbitrary nonlinear constraint models via decision trees. A detailed case study compares the new method to an extended hybrid scheduling approach from literature. It is demonstrated that hybrid optimization can efficiently solve proactive resilient scheduling problems and that the tree-based algorithm provides a feasible solution, even in case the reference algorithm fails. Details on the convergence of both algorithms give further insights into the working principles and show that the novel method quickly finds a feasible solution that is successively improved afterwards. By the novel combination of highly-developed solvers for both mathematical programming and detailed asset models it is expected that this study further supports the operation of power systems and reduces costly reserve requirements.

Highlights

Microgrids are considered as one solution to increase power system resilience, to tightly integrate volatile Renewable Energy Sources (RES) and to fully leverage the economic potential of Distributed Energy Resources (DERs) [1]
In contrast to [27] that does not include details on volatile RES, this study considers the voltage control capabilities of all generation units and assumes that PV and Wind Turbine (WT) plants are limited to an apparent power SlDER of 0.1 MVA and 0.2 MVA, respectively
A case study demonstrates that the novel optimization method based on decision trees can solve the scheduling problem, even in case a sensitivity-based method extended from literature fails to deliver results at all

Summary

Introduction

Microgrids are considered as one solution to increase power system resilience, to tightly integrate volatile Renewable Energy Sources (RES) and to fully leverage the economic potential of Distributed Energy Resources (DERs) [1]. There are other definitions as well, this work follows [2] and considers microgrids as tightly controlled electrical networks that can be operated in both grid-connected and islanded mode. Due to the great flexibility that is provided by many microgrids, considerable potential is given for a scheduling algorithm to optimize the operation [3]. Resilient scheduling in emergency mode, for instance, often reduces the impact of a contingency without primarily targeting operating costs. Proactive resilient scheduling algorithms minimize the normal operation cost while no failure is observed, but at the same time, they prepare the network to gracefully degrade in case of contingencies. Resilience is considered as the ability to reduce the impact of potentially harmful events and includes both a fully robust and a gracefully degraded operation [4]

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