Repair and Resource Scheduling in Unbalanced Distribution Systems Using Neighborhood Search

Abstract

This paper proposes an optimization strategy to assist utility operators to recover power distribution systems after large outages. Specifically, a mixed-integer linear programming (MILP) model is developed for co-optimizing crews, resources, and network operations. The MILP model coordinates damage isolation, network reconfiguration, distributed generator redispatch, and crew/resource logistics. In addition, a framework for integrating different types of photovoltaic (PV) systems in the restoration process is developed. We consider two different types of crews, namely, line crews for damage repair and tree crews for obstacle removal. We also model the repair resource logistic constraints. Furthermore, a new algorithm is developed for solving the distribution system repair and restoration problem (DSRRP). The algorithm starts by solving DSRRP using an assignment-based method, then a neighborhood search method is designed to iteratively improve the solution. The proposed method is validated on modified IEEE 123-and 8500-bus distribution test systems.Active power charge/discharge of the BESS at bus i P/Q L i,ϕ,t Active/reactive load supplied at bus i, phase ϕ and time t P/Q P V i,ϕ,tThe active/reactive power output of the PV at bus i P/Q G i,ϕ,t Active/reactive power generated by DG at bus i, phase ϕ and time t P/Q K k,ϕ,t

Construction of College English Data Resources and Change of Teacher Positioning Using QoS Constraints

“…e objective function values of the two algorithms are very similar when the number of tasks is less than 40, but when the number of tasks exceeds 40, the objective function values obtained by the algorithm proposed in this paper are less than those obtained by the algorithms in [15] and [19].…”

“…Figure 6 shows that as the number of tasks grows, the time required by the three scheduling algorithms grows. However, the algorithm in [19] takes less time to complete in total than the algorithm in this paper.…”

“…Ninety percent of users of cloud computing want to get satisfactory service at the lowest possible cost. Analyzing from the constraint index of cost, the cost of the three algorithms will be higher and higher, but the cost of the algorithm in this paper is less than that of the algorithms in [15,19].…”

“…e results of simulation experiments show that the algorithm proposed in this paper is capable of selecting appropriate scheduling nodes for tasks based on users' needs and generating a satisfactory allocation scheme. e algorithm in [15] is compared to the algorithm in [19] in three ways: task completion time, cost, and the value of the e results shown in Figure 5 are the ones that were obtained.…”

“…Reference [18] examines existing cloud computing platform solutions and technologies, then designs and analyzes a job scheduling algorithm for virtualization platforms, and proposes a scheduling scheme based on the threshold dynamic scheduling model. In [19], in light of GA's flaws, an improved algorithm for optimizing scheduling is proposed, and GA with a double fitness function is considered to find nodes that reduce task scheduling's average and total times. e half-validity method, proposed in [20], is an improved method for maintaining the timing consistency of real-time data objects.…”