Toward a MILP Modeling Framework for Distribution System Restoration

Chen, Bin; Ye, Zhigang; Chen, Chen; Wang, Jianhui

doi:10.1109/tpwrs.2018.2885322

Cited by 101 publications

(47 citation statements)

References 27 publications

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“…Therefore, it is unnecessary to check the technical constraints in each time step. In this paper, the energization statuses of loads and DGs (19), remote-controlled switchable lines (20), manually switchable lines (21) and non-switchable lines (22) at energization steps tc T are determined, and the technical constraints are only checked at tc T instead of all time steps. The difference between time step and energization step is shown in Fig.…”

Section: ) Energization Path and Timetablementioning

confidence: 99%

“…However, most of existing studies only focused on the final configuration from the DRM model [7]- [12], which will result in final configuration infeasible if any constraints violation made during the switching stages. Therefore, several research attempted to integrate the switching sequence into the DRM model, solving by heuristic methods (e.g., tabu search method [16], fuzzy algorithm [17], and expert system [18]) and mathematical optimization (e.g., MILP in references [14], [19] and [20]). These studies have made considerable progress in generating the switching sequence for the independent DRM.…”

mentioning

confidence: 99%

“…However, when the DRM, MCDM and RCDM are co-optimized, new challenges have arisen to obtain the optimal configuration and corresponding switching sequence. For example, the manual switch operation is constrained by the RC routing problem; and the different time scales of DRM, MCDM and RCDM need to be addressed because employing small time steps for solution will increase the computational burden, whereas using large time steps for solution will render an inefficient solution [19].…”

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confidence: 99%

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Sequential Disaster Recovery Model for Distribution Systems With Co-Optimization of Maintenance and Restoration Crew Dispatch

Zhang

et al. 2020

IEEE Trans. Smart Grid

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To efficiently restore electricity customers from a large-scale blackout, this paper proposes a novel mixedinteger linear programing (MILP) model for the optimal disaster recovery of power distribution systems. In the proposed recovery scheme, the maintenance crews (MCs) are scheduled to repair damaged components, and the restoration crews (RCs) are dispatched to switch on the manual switches. Then, the MC and RC dispatch models are integrated into the disaster recovery scheme, which will generate an optimal sequence of control actions for distributed generation (DG), controllable load, and remote/manual switches. Besides, to address the time scale related challenges in the model formulation, the technical constraints for system operation are investigated in each energization step rather than time step, hence the co-optimization problem is formulated as an "event-based" model with variable time steps. Consequently, the disaster recovery, MC dispatch and RC dispatch are properly cooperated, and the whole distribution systems can be restored step by step. Last, the effectiveness of the co-optimization model is validated in the modified IEEE 123 bus test distribution system. 1

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Section: ) Energization Path and Timetablementioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Sequential Disaster Recovery Model for Distribution Systems With Co-Optimization of Maintenance and Restoration Crew Dispatch

Zhang

et al. 2020

IEEE Trans. Smart Grid

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“…Now, we have finished the processing of radial constraints in failure restoration. Then, we can obtain the deterministic failure restoration model which consists of objective function (1), operation constraints (2)-(28), fictitious network constraints (30)- (32), and radial constraints (33)(36).…”

Section: Topology Constraintsmentioning

confidence: 99%

A Robust Formulation Model for Multi-Period Failure Restoration Problems in Integrated Energy Systems

2019

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The risks faced by modern energy systems are increasing, primarily caused by natural disasters. As a new form of multi-level energy complimentary utilization, integrated energy systems are attracting more and more attention for their high-efficiency and low-cost. However, due to the deep coupling relationship between systems, they are more susceptible to natural disasters, resulting in a cascading failure. To enhance the resilience of the integrated electricity-gas system, this paper proposes a failure restoration strategy after a natural disaster occurs. First, the temporal constraints of the dispatching model are considered, and the failure restoration problem is molded into a multi-period mixed-integer linear programme, aiming to recover the interrupted loads as much as possible. Second, since the uncertain output of distributed generation sources (DGs) such as wind turbines and photovoltaic systems will threat the reliability of restoration results, the robust formulation model is incorporated to cope with this problem. Third, we propose a new modeling method for radial topology constraints towards failure restoration. Moreover, the Column and Constraints Generation (C&CG) decomposition method is utilized to solve the robust model. Then, the piecewise linearization technique and the linear DistFlow equations are utilized to eliminate the nonlinear terms, providing a model that could be easily solved by an off-shelf commercial solver. The obtained results include the sequence of line/pipeline switchgear actions, the time-series dispatching results of electricity storage system, gas storage system, and the coupling devices including the gas-fired turbine, power to gas equipment. Finally, the effectiveness of the proposed restoration strategy is verified by numerical simulation on a 13-6 node integrated energy system.

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“…Another important issue to consider in this article is the use of backup feeders for system restoration. Backup feeders are only used in References for the restoration problem. In Reference , load shedding and islanding state are not considered for restoration.…”

Section: Introductionmentioning

confidence: 99%

Self‐healing optimization in active distribution network to improve reliability, and reduction losses, switching cost and load shedding

Choopani

Hedayati

Effatnejad

2020

Int Trans Electr Energ Syst

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Summary Self‐healing refers to the specific ability of the smart grid that takes precautionary actions before the fault. It also performs fault location, isolation, and service restoration to minimize network damage after the fault. This process is performed with the help of communications infrastructure and remote control. The main components of this article include the use of graph theory and binary particle swarm optimization algorithm for optimal switching, the use of particle swarm optimization algorithm and forward‐backward sweep load flow for load shedding and distributed generation rescheduling, investigating the effect of self‐healing on improved reliability, power losses reduction, and load shedding reduction and the present a new approach for self‐healing optimization and a new mathematical model. The problem of self‐healing due to nonlinear and unbounded constraints is one of the nonconvex mixed integer nonlinear programming optimization problems. The optimization problem becomes a convex mixed integer linear programming optimization problem using the proposed scheme. Due to the nonlinearity and the nonconvexity of the problem, commercial solvers are not able to solve this problem. Even the Baron solver, which is used to solve nonconvex nonlinear problems, cannot achieve the optimal global solution. However, the proposed method is easily able to achieve the optimal solution by eliminating the nonlinear and nonconvex element. A modified RBTS‐4 distribution system is used as a test system. The IEEE 33‐bus distribution system is used to validate the proposed method. The results of case studies demonstrate the effectiveness of the proposed methodology.

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Toward a MILP Modeling Framework for Distribution System Restoration

Cited by 101 publications

References 27 publications

Sequential Disaster Recovery Model for Distribution Systems With Co-Optimization of Maintenance and Restoration Crew Dispatch

Sequential Disaster Recovery Model for Distribution Systems With Co-Optimization of Maintenance and Restoration Crew Dispatch

A Robust Formulation Model for Multi-Period Failure Restoration Problems in Integrated Energy Systems

Self‐healing optimization in active distribution network to improve reliability, and reduction losses, switching cost and load shedding

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