A Framework for Load Service Restoration Using Dynamic Change in Boundaries of Advanced Microgrids With Synchronous-Machine DGs

Kim, Young-Jin; Wang, Jianhui; Liu, Xiaonan

doi:10.1109/tsg.2016.2638854

Cited by 83 publications

(39 citation statements)

References 33 publications

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“…In [15]- [19], the restoration strategies are based on sectionalizing the outage area of a distribution system into several MGs. In [16], a framework is developed to dynamically change the boundaries of MGs for fault isolation and load restoration. A sequential service restoration framework is proposed in [18] to generate a sequence of control actions for switches, DGs, and switchable loads to form multiple isolated MGs.…”

Section: Set Of Phases Of Busmentioning

confidence: 99%

“…Constraint (15) represents the Ohm's law. Constraints (16) and (17) indicate that the matrix [ ] is positive semidefinite and has a rank of 1 because the matrix is a product of a non-zero vector and its conjugate transpose, i.e.,…”

Section: Clrmentioning

confidence: 99%

“…The meanings of constraints (21)- (27) are corresponding to (10)- (16). It can be seen that constraint (27) defines a second-order conic set and it is relaxed from the equation (28), the transformation of the power definition equation [33].…”

Section: Clr-misocpmentioning

confidence: 99%

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Coordinating Multiple Sources for Service Restoration to Enhance Resilience of Distribution Systems

Wang

et al. 2019

IEEE Trans. Smart Grid

195

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When a major outage occurs on a distribution system due to extreme events, microgrids, distributed generators, and other local resources can be used to restore critical loads and enhance resiliency. This paper proposes a decision-making method to determine the optimal restoration strategy coordinating multiple sources to serve critical loads after blackouts. The critical load restoration problem is solved by a two-stage method with the first stage deciding the post-restoration topology and the second stage determining the set of loads to be restored and the outputs of sources. In the second stage, the problem is formulated as a mixed-integer semidefinite program. The objective is maximizing the number of loads restored, weighted by their priority. The unbalanced three-phase power flow constraint and other operational constraints are considered. An iterative algorithm is proposed to deal with integer variables and can attain the global optimum of the critical load restoration problem by solving a few semidefinite programs in most cases. The effectiveness of the proposed method is validated by numerical simulation with the modified IEEE 13-node test feeder and the modified IEEE 123-node test feeder under plenty of scenarios. The results indicate that the optimal restoration strategy can be determined efficiently in most scenarios.

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Section: Set Of Phases Of Busmentioning

confidence: 99%

Section: Clrmentioning

confidence: 99%

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Coordinating Multiple Sources for Service Restoration to Enhance Resilience of Distribution Systems

Wang

et al. 2019

IEEE Trans. Smart Grid

195

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“…Algorithms (1) Solver Types (2) Language Types (3) Demonstration Methods (4) OS CS Solver AML GPL S I Test-Beds [4] LP GLPK Grid-connected MG [5] CONVEX MOSEK Grid-connected MG [6] MIP CPLEX Grid-connected MG [7] MIP (T-S) CPLEX Grid-connected MG [8] MIP (T-S) CPLEX Grid-connected MGs [9] MIP (T-S) Gurobi Islanded MG [10] MIP (T-S) SCIP IEEE 33-bus radial system [11] MIP CPLEX Budapest Tech Renewable System, Hungary [12] MIP CPLELX Institute of Nuclear Energy Research MG, Taiwan [13] MIP (T-S) CPLEX MG Research Lab. in Aalborg Univ., Denmark [14] MIP AOA MG Research Lab.…”

Section: Ref Optimizationmentioning

confidence: 99%

“…MGs provide an effective means to accommodate the high penetration of renewable generators and minimize power transmission losses by supplying local loads using distributed energy resources (DERs). A microgrid energy management system (MEMS) is a hierarchical supervisory control system responsible for the reliable, secure, and economical operation of MGs [1,2]. For the economical operation, the MEMS optimally coordinates the operation schedules of dispatchable DERs (e.g., micro turbines, batteries, and controllable loads), such that the MG's daily operating cost is minimized while considering the forecasted load demand and renewable generation.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study on Optimization Solvers for Implementation of a Two-Stage Economic Dispatch Strategy in a Microgrid Energy Management System

et al. 2020

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A microgrid energy management system (MEMS) optimally schedules the operation of dispatchable distributed energy resources to minimize the operation costs of microgrids (MGs) via an economic dispatch (ED). Actual ED implementation in the MEMS relies on an optimization software package called an optimization solver. This paper presents a comparative study of optimization solvers to investigate their suitability for ED implementation in the MEMS. Four optimization solvers, including commercial as well as open-source-based ones, were compared in terms of their computational capability and optimization results for ED. Two-stage scheduling was applied for the ED strategy, whereby a mixed-integer programming problem was solved to yield the optimal operation schedule of battery-based energy storage systems. In the first stage, the optimal schedule is identified one day before the operating day; in the second stage, the optimal schedule is updated every 5 min during actual operation to compensate for operational uncertainties. A modularized programming strategy was also introduced to allow for a comparison between the optimization solvers and efficient writing of codes. Comparative simulation case studies were conducted on three test-bed MGs to evaluate the optimization results and computation times of the compared optimization solvers.Commercial optimization solvers generally have superior computational capability compared with their open-source counterparts. The ED implementation environment is then programmed either in general-purpose programming languages (GPLs), e.g., Python and Julia, or in algebraic modeling languages (AMLs). AML is a high-level programming language dedicated to optimization applications. Popular AMLs include GAMS and AMPL.Numerous studies on ED have been conducted from the perspectives of its optimization algorithms [4][5][6][7][8][9][10] and actual implementation methods [11][12][13][14][15]. Table 1 summarizes the optimization algorithms, optimal solvers, programming languages, and demonstration methods used in these studies. The optimization algorithms to the ED problem have been well studied. Particularly, in references [4-10], various analytic-based optimization methods, such as linear programming (LP), mixed-integer programming (MIP), and convex optimization, have been investigated for the application to ED. In reference [4], day-ahead ED was formulated as an LP problem to determine the hourly planned operation set points (i.e., charging and discharging power references) of battery-based energy storage systems (ESSs) and electric vehicles (EVs). In reference [5], convex optimization method was used to determine the optimal charging and discharging schedules of an ESS. In reference [6], an online battery power control method based on an MIP formulation was used over a rolling horizon window. The ED strategies proposed in [4][5][6] planned the operation schedule only once and the schedule is followed without any modifications during operation. However, one-time scheduling strategies are vulne...

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Improving the resilience of distribution networks during transmission outages via integration of sectionalizing switches and private DG units: The case of Khuzestan Province

Darkhal

Mashhour

Farzin

2021

Int Trans Electr Energ Syst

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The purpose of this paper is to present a model for optimal placement of distributed generation units and sectionalizing switches (relocation of the existing switches and installation of new ones) to increase distribution network resilience against the threat of transmission system outage. The proposed model is formulated as a multi-objective optimization problem with the objectives of minimizing investment costs and maximizing load restoration. In this regard, distribution system operation during normal conditions as well as transmission system outages is considered. In addition, the unique characteristics of the real power grid in Khuzestan province in southwestern of Iran are addressed in the proposed model which makes the model applicable to the real networks with similar characteristics in many parts of the Middle East. This grid has two completely different load patterns (in terms of load curve shape and peak load) corresponding to two hot and temperate periods, which causes completely different concerns for the network's operator. The proposed model is solved using multi-objective genetic algorithm (NSGA-II), and it is implemented on the 33-node test system and the results are analyzed. Moreover, it is applied to the 327-node real-world test system in Khuzestan province

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A Framework for Load Service Restoration Using Dynamic Change in Boundaries of Advanced Microgrids With Synchronous-Machine DGs

Cited by 83 publications

References 33 publications

Coordinating Multiple Sources for Service Restoration to Enhance Resilience of Distribution Systems

Coordinating Multiple Sources for Service Restoration to Enhance Resilience of Distribution Systems

Comparative Study on Optimization Solvers for Implementation of a Two-Stage Economic Dispatch Strategy in a Microgrid Energy Management System

Improving the resilience of distribution networks during transmission outages via integration of sectionalizing switches and private DG units: The case of Khuzestan Province

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