In this paper, the impact of clustering multiple microgrids during blackouts, on their stability and supply availability, will be investigated. Microgrids have the capability of satisfying their emergency loads during blackouts. However, distributed energy resources (DERs)-dominated microgrids are affected by the uncertainty of their input energy supply, e.g.impact of solar irradiance on photovoltaic (PV) output.Moreover, an individual islanded microgrid is prone to instability issues due to large sudden load/generation changes.In order to increase the supply security, and enhance system stability, we propose to use the existing distribution grid infrastructure, if applicable, during blackouts to form microgrid clusters. The paper discusses the required control hierarchy required to manage the microgrid clusters, and communicate with the Distribution Network Operator (DNO).A case study based on the 13-bus standard distribution feeder, and two microgrid models, is presented. Results show that microgrids clustering helps improve their performance and that the microgrid generator inertia has a direct impact on the stability of the microgrid cluster.
Centralized communication-based control is one of the main methods that can be implemented to achieve autonomous advanced energy management capabilities in DC microgrids. However, its major limitation is the fact that communication bandwidth and computation resources are limited in practical applications. This can be often improved by avoiding redundant communications and complex computations. In this paper, an autonomous communication-based hybrid state/event driven control scheme is proposed. This control scheme is hierarchical and heuristic, such that on the primary control level, it encompasses state-driven local controllers, and on the secondary control level, an event-driven MG centralized controller (MGCC) is used. This heuristic hybrid control system aims at reducing the communication load and complexity, processor computations, and consequently system cost while maintaining reliable autonomous operation during all possible scenarios. A mathematical model for the proposed control scheme using Finite State Machines (FSM) has been developed and used to cover all the possible modes/submodes of operation, and assure seamless transitions among them during various events. Results of some case studies involving severe operational scenarios were presented and discussed. Results verify the validity and effectiveness of the proposed communication-based control scheme. Index Terms-Communication-based control, DC microgrids, finite state machine, hybrid state/event driven control. I. NOMENCLATURE DC/DC bidirectional converter: ℎ () Charging current controller transfer function. * q-axis component of the measured AC current. q-axis reference current for the reactive current controller.
This paper provides a review of the research conducted on complex network analysis (CAN) in electric power systems. Moreover, a new approach is presented to find optimal locations for microgrids (MGs) in electric distribution systems (EDS) utilizing complex network analysis. The optimal placement in this paper points to the location that will result in enhanced grid resilience, reduced power losses and line loading, better voltage stability, and a supply to critical loads during a blackout. The criteria used to point out the optimal placement of the MGs were predicated on the centrality analysis selected from the complex network theory, the center of mass (COM) concept from physics, and the recently developed controlled delivery grid (CDG) model. An IEEE 30 bus network was utilized as a case study. Results using MATLAB (MathWorks, Inc., Nattick, MA, USA) and PowerWorld (PowerWorld Corporation, Champaign, IL, USA) demonstrate the usefulness of the proposed approach for MGs placement.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.