Decision-making optimization of power system extended black-start coordinating unit restoration with load restoration

Wang, Dajiang; Gu, Xueping; Zhou, Guangqi; Li, Shaoyan; Liang, Haiping

doi:10.1002/etep.2367

Cited by 20 publications

(21 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where N k is the number of load nodes in the system; N p is the number of feeders belonging to load l. ω lk is the weight of load in feeder k of load l. The weight is determined by Analytic Hierarchy Process with the type of load by Wang D. et al [18], or even set according to the need and preference of the dispatcher. In summary, two objectives are coupled with each other through time variable t. The objective function of the model is as follow:…”

Section: Objective Of Load Restorationmentioning

confidence: 99%

An Optimal Source-Load Coordinated Restoration Method Considering Double Uncertainty

Jiang

Chen

2018

Energies

View full text Add to dashboard Cite

Abstract:The security of power system restoration is severely affected by uncertain factors, especially the start-up time of generating unit and the amount of load pick-up. Solving the optimization restoration problem is challenging since it needs to determine different priorities in which units and loads are restored with the consideration of double uncertainty. Therefore, an optimal source-load coordinated restoration method that is based on information gap decision theory (IGDT) is proposed. Firstly, the time-domain restoration characteristics of black-start unit (BSU), non-black-start unit (NBSU), and load are described with analysis of double uncertainty. On this basis, a coupled multi-objective optimization model is built with double uncertainty, in which source-load coordinated restoration is realized. Then, IGDT is adopted to convert the uncertainty optimization model to a certain one with robustness, which tolerates the most uncertainty and still meets the desired requirement. Finally, the optimization model is solved by non-dominated genetic algorithm II (NSGA-II). The effectiveness and robustness of the proposed method is further illustrated through a case study based on the IEEE 39-bus system.

show abstract

Section: Objective Of Load Restorationmentioning

confidence: 99%

An Optimal Source-Load Coordinated Restoration Method Considering Double Uncertainty

Jiang

Chen

2018

Energies

View full text Add to dashboard Cite

show abstract

“…For the importance of nodal load, load capacity and load level are mainly considered in this paper. Loads are generally divided into three levels [24]. For the nodes with the same number of loads, the higher the load level is, the more outage loss and the greater the importance of load will be.…”

Section: Node Importance Degreementioning

confidence: 99%

A Parallel Restoration for Black Start of Microgrids Considering Characteristics of Distributed Generations

et al. 2017

View full text Add to dashboard Cite

Abstract:The black start capability is vital for microgrids, which can potentially improve the reliability of the power grid. This paper proposes a black start strategy for microgrids based on a parallel restoration strategy. Considering the characteristics of distributed generations (DGs), an evaluation model, which is used to assess the black start capability of DGs, is established by adopting the variation coefficient method. Thus, the DGs with good black start capability, which are selected by a diversity sequence method, are restored first in parallel under the constraints of DGs and network. During the selection process of recovery paths, line weight and node importance degree are proposed under the consideration of the node topological importance and the load importance as well as the backbone network restoration time. Therefore, the whole optimization of the reconstructed network is realized. Finally, the simulation results verify the feasibility and effectiveness of the strategy.

show abstract

“…On the other hand, implementing fuzzy logic requires numerous and time‐consuming experiments. In Reference , multiobjective optimization method is proposed to coordinate unit restarting with load restoration. The lexicographic method with the improved bacterial foraging algorithm is used to solve the optimization model.…”

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

View full text Add to dashboard Cite

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.

show abstract

Decision-making optimization of power system extended black-start coordinating unit restoration with load restoration

Cited by 20 publications

References 34 publications

An Optimal Source-Load Coordinated Restoration Method Considering Double Uncertainty

An Optimal Source-Load Coordinated Restoration Method Considering Double Uncertainty

A Parallel Restoration for Black Start of Microgrids Considering Characteristics of Distributed Generations

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

Contact Info

Product

Resources

About