Multi-Time Step Service Restoration for Advanced Distribution Systems and Microgrids

Modern power systems are facing increased risk of disasters that can cause extended outages. The presence of remote control switches, distributed generators (DGs), and energy storage systems (ESS) provides both challenges and opportunities for developing post-fault service restoration methodologies. Inter-temporal constraints of DGs, ESS, and loads under cold load pickup conditions impose extra complexity on problem formulation and solution. In this paper, a multi-time step service restoration methodology is proposed to optimally generate a sequence of control actions for controllable switches, ESSs, and dispatchable DGs to assist the system operator with decision making. The restoration sequence is determined to minimize the unserved customers by energizing the system step by step without violating operational constraints at each time step. The proposed methodology is formulated as a mixed-integer linear programming model and can adapt to various operation conditions. The proposed method is validated through several case studies that are performed on modified IEEE 13-node and IEEE 123-node test feeders.

[1]  Alexis Kwasinski,et al.  Powering Through the Storm: Microgrids Operation for More Efficient Disaster Recovery , 2014, IEEE Power and Energy Magazine.

[2]  V. Kumar,et al.  DG Integrated Approach for Service Restoration Under Cold Load Pickup , 2010, IEEE Transactions on Power Delivery.

[3]  Max D. Anderson,et al.  An Analytical Method for Quantifying the Electrical Space Heating Component of a Cold Load Pick Up , 1982, IEEE Transactions on Power Apparatus and Systems.

[4]  Chen-Ching Liu,et al.  Distribution System Restoration With Microgrids Using Spanning Tree Search , 2014, IEEE Transactions on Power Systems.

[5]  Isamu Watanabe,et al.  A genetic algorithm for optimizing switching sequence of service restoration in distribution systems , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[6]  Kevin P. Schneider,et al.  Evaluating the magnitude and duration of cold load pick-up on residential distribution using multi-state load models , 2016, IEEE Transactions on Power Systems.

[7]  Y. Besanger,et al.  New Challenges in Power System Restoration With Large Scale of Dispersed Generation Insertion , 2009, IEEE Transactions on Power Systems.

[8]  Pascal Van Hentenryck,et al.  Power System Restoration With Transient Stability , 2015, AAAI.

[9]  Pascal Van Hentenryck,et al.  Transmission system restoration with co-optimization of repairs, load pickups, and generation dispatch☆ , 2015 .

[10]  F. S. Hover,et al.  Convex Models of Distribution System Reconfiguration , 2012, IEEE Transactions on Power Systems.

[11]  Felix F. Wu,et al.  Network Reconfiguration in Distribution Systems for Loss Reduction and Load Balancing , 1989, IEEE Power Engineering Review.

[12]  Fred Friend.  Cold load pickup issues , 2009, 2009 62nd Annual Conference for Protective Relay Engineers.

[13]  F. Katiraei,et al.  Diesel Plant Sizing and Performance Analysis of a Remote Wind-Diesel Microgrid , 2007, 2007 IEEE Power Engineering Society General Meeting.

[14]  J. Martí,et al.  Linear Current Flow Equations With Application to Distribution Systems Reconfiguration , 2015, IEEE Transactions on Power Systems.

[15]  David E. McNabb,et al.  Energy Policy in the U.S.: Politics, Challenges, and Prospects for Change , 2011 .

[16]  M. M. Adibi,et al.  Frequency response of prime movers during restoration , 1999 .

[17]  Kevin P. Schneider,et al.  Evaluating the Magnitude and Duration of Cold Load Pick-up on Residential Distribution Feeders Using Multi-State Load Models , 2016 .

[18]  J.A.P. Lopes,et al.  Defining control strategies for MicroGrids islanded operation , 2006, IEEE Transactions on Power Systems.

[19]  G.T. Heydt,et al.  Optimal Restoration of Distribution Systems Using Dynamic Programming , 2008, IEEE Transactions on Power Delivery.

[20]  Jizhong Zhu,et al.  An enhanced cascading failure model integrating data mining technique , 2017 .

[21]  James S. Thorp,et al.  Anatomy of power system blackouts: preventive relaying strategies , 1996 .

[22]  K. Mani Chandy,et al.  Inverter VAR control for distribution systems with renewables , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[23]  Russell Bent,et al.  Approved for public release; distribution is unlimited. Title: Vehicle Routing for the Last Mile of Power System Restoration Author(s): , 2022 .

[24]  Jianhui Wang,et al.  Resilient Distribution System by Microgrids Formation After Natural Disasters , 2016, IEEE Transactions on Smart Grid.

[25]  Ting Wu,et al.  Optimal planning and operation of energy storage systems in radial networks for wind power integration with reserve support , 2016 .

[26]  Anil Pahwa,et al.  An analytical approach for step-by-step restoration of distribution systems following extended outages , 1994 .

[27]  S. Borlase.  Smart Grids : Infrastructure, Technology, and Solutions , 2016 .

[28]  Michel Bessani,et al.  Determination of switching sequence of Service Restoration in Distribution Systems: Application and analysis on a real and large-scale radial system , 2016, 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D).

[29]  Xiaodai Dong,et al.  Service Restoration for a Renewable-Powered Microgrid in Unscheduled Island Mode , 2015, IEEE Transactions on Smart Grid.

[30]  Sylvie Thiébaux,et al.  Optimal distribution systems reconfiguration for radial and meshed grids , 2015 .

[31]  S. M. Amin,et al.  Smart Grid, Safe Grid , 2012, IEEE Power and Energy Magazine.

[32]  Richard J. Campbell,et al.  Weather-Related Power Outages and Electric System Resiliency , 2012 .

[33]  Carleton Coffrin,et al.  Planning with MIP for Supply Restoration in Power Distribution Systems , 2013, IJCAI.