The Spectrum of Proactive, Resilient Multi-Microgrid Scheduling: A Systematic Literature Review

Abstract

Multi-microgrids address the need for a resilient, sustainable, and cost-effective electricity supply by providing a coordinated operation of individual networks. Due to local generation, dynamic network topologies, and islanding capabilities of hosted microgrids or groups thereof, various new fault mitigation and optimization options emerge. However, with the great flexibility, new challenges such as complex failure modes that need to be considered for a resilient operation, appear. This work systematically reviews scheduling approaches which significantly influence the feasibility of mitigation options before a failure is encountered. An in-depth analysis of identified key contributions covers aspects such as the mathematical apparatus, failure models and validation to highlight the current methodical spectrum and to identify future perspectives. Despite the common optimization-based framework, a broad variety of scheduling approaches is revealed. However, none of the key contributions provides practical insights beyond lab validation and considerable effort is required until the approaches can show their full potential in practical implementations. It is expected that the great level of detail guides further research in improving and validating existing scheduling concepts as well as it, in the long run, aids engineers to choose the most suitable options regarding increasingly resilient power systems.

Hybrid Optimization Toward Proactive Resilient Microgrid Scheduling

“…In contrast, 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. According to related work, resilience is considered as the ability to reduce the impact of potentially harmful events and includes both a fully robust but also a gracefully degraded operation [4].…”

“…A detailed review of proactive scheduling approaches is published in [4] noting that, although every algorithm follows an optimization-based methodology, a broad variety of solution approaches is observed. Common scheduling techniques include mathematical methods (like Mixed Integer Linear Programming (MILP) formulations) that can be solved by generic software components and heuristic approaches such as genetic algorithms [5].…”

“…Since control and scheduling decisions can have a considerable impact on the safe operation of a microgrid [6], some authors included physical constraints such as voltage limits in their scheduling formulations. Due to the inherently nonconvex nature of physical power flows, mostly linearization is used to fit the MILP or heuristic optimization techniques to solve the nonlinear mixed-integer problem [4]. The former technique can suffer from linearization errors causing overapproximation or reduced confidence in the eligibility of results while the latter approach can not fully utilize the potential of highly-developed solvers for mathematical programming problems.…”

“…Most work formulates the proactive scheduling problem as one monolithic set of equations without discussing external implementations of asset models in detail [4], [7]. For instance, in [8], a linearized version of the power flow equations is directly integrated into the scheduling model.…”

“…Due to the widespread application in scheduling [4], [27], [28] and the challenging network design that leads to frequent voltage violations, the whole study is based on a modified version of the well-established Baran testfeeder [29]. Since the original network does not include any generation, the feeder was extended by DG, Photovoltaics (PV), Wind Turbine (WT), and storage plants following the configuration in [27].…”