Towards Resilient Operation of Multimicrogrids: An MISOCP-Based Frequency-Constrained Approach

Abstract

High penetration of distributed energy resources (DERs) is transforming the paradigm in power system operation. The ability to provide electricity to customers while the main grid is disrupted has introduced the concept of microgrids (µGs) with many challenges and opportunities. Emergency control of dangerous transients caused by the transition between the gridconnected and island modes in µGs is one of the main challenges in this context. To address this challenge, this paper proposes a comprehensive optimization and real-time control framework for maintaining frequency stability of multi-µG networks under an islanding event and for achieving optimal load shedding and network topology control with AC power flow constraints. The paper also develops a strong mixed-integer second-order cone programming (MISOCP)-based reformulation and a cutting plane algorithm for scalable computation. We believe this is the first time in the literature that such a framework for multi-µG network control is proposed, and its effectiveness is demonstrated with extensive numerical experiments.Index Terms-Islanding, microgrid, mixed-integer second order cone programming, resilience, under frequency load shedding.arXiv:1809.00054v1 [math.OC]

Optimal Allocation and Operation of Droop-Controlled Islanded Microgrids: A Review

“…Due to the many benefits a radial network topology offers compared to a meshed structure in terms of design simplicity, low implementation cost, and ease of protection, almost all reconfiguration problems in DCIMG often insist on some sort of radiality constraint where the radial topology of the network should remain intact before and after tie switches opening or closing [109,110,[114][115][116][117][118]. Reconfiguration of DCIMG can have a notable impact on MG stability margin minimization.…”

“…Hence, the authors in [115] used a social-based metaheuristic technique to achieve optimal stability by means of network reconfiguration, while [116] relied on a physics-inspired optimization method to obtain the same outcome. Furthermore, reducing the coupling of power to divide multiple microgrids into clusters was another target for DCIMG reconfiguration [99,119], as were the distribution line losses' reduction [109,110,118] as well as maximizing the number of loads served [114,117,120].…”

“…Control problems combined with dispatch and scheduling problems form the bases for optimal EMS problems, which are responsible for implementing the hierarchal control strategy of DCIMG. Therefore, solving an EMS problem acts as a buffer to serve a variety of technical [33,35,54,59,85,91,92,117,134,148,154,[163][164][165][166], economic [28][29][30][75][76][77][78][79][80][81]84,85,91,[124][125][126][127][128][129][130][131][132][133]135,144,145,[148][149][150][151]167,168], and environmental [84,…”

“…Many reconfiguration studies went on to maximize loadability besides other objectives such as losses [120] and minimal switching operation [114], while others have only considered load-served maximization as the sole objective [117]. Furthermore, several EDP problems aimed at achieving the OPF with maximum customer satisfaction ratings [85,86,[159][160][161][162][163], while other dispatch problems were focused on eliminating the need for communication infrastructure (such as MGCC) to maximize the social welfare of DCIMG [94,134].…”

Resilient distribution system leveraging distributed generation and microgrids: a review

“…The frequency response of droop‐controlled inverters at steady state after islanding is considered in [140 ], where the droop control gains are co‐optimised with other control commands. In [141 ], a further improvement by considering the dynamic frequency response constraint in addition to the steady state is proposed. Most studies employ a low‐order frequency response model and piece‐wise linearisation to encode the nonlinear frequency nadir expression into the mixed‐integer programming model, which is shown to be accurate in synchronous generator‐dominated bulk grids [142 ].…”