access deny [1301]
access deny [1026]
An effective way to improve distribution system reliability is to place switches and protective equipment in the optimal location. Commonly, in the placement problem, the use of equipment in the designated location is assumed to be possible. But in practice, to establish protection coordination between the equipment, it is necessary to remove or relocate some of the equipment. This paper aims to increase distribution companies' profits and reduce customer interruption costs through a feasible solution. A new hybrid method for equipment placement has been proposed that simultaneously solves the protection coordination problem. While determining the optimal number and location of reclosers and sectionalizers, the proposed method ensures prot
Reliability improvement is a fundamental issue in electric distribution network (EDN) operation. In this regard, providing the most efficient maintenance policy can dramatically assist the electric utility companies in reducing the failure rate of EDN components. In the present study, a novel probabilistic reliability‐centred maintenance (RCM) approach is proposed in which the reliability level of the EDN components are evaluated according to the three‐state Markov model (MM). Using the MM, this study presents a trade‐off between the corrective maintenance and the preventive maintenance (PM) actions and finally determines the precedence of EDN components in PM financial resource allocation. Through the method presented in this study,
This paper studies electric vehicle (EV) charging coordination in the presence of uncertainty. Considering that EVs usage are of considerable uncertainties, first, a probabilistic mechanism to model driving and charging patterns of EV owners utilizing Markov chain Monte Carlo (MCMC) is presented. Then a model predictive control (MPC) approach named online MPC (OL-MPC) is proposed to adaptively and intelligently coordinate the EV charging process which is able to cover both centralized and decentralized infrastructures concurrently. Technically, discrete-time manner, re-optimization characteristic, looking ahead and signal tracking are the main features of the proposed method which make it well-suited to address high uncertainties concerning
Paying attention to the modularity feature of electric distribution systems improves their performance against severe events and makes an outstanding opportunity for resiliency enhancement. In this paper, a novel framework based on the modularity concept is proposed in which, by deploying smart grid technologies and forming efficient modules, effective and robust energy in distribution systems is provided. Optimal placement of distributed generation (DG) resources, load control options, switching devices, and tie lines are simultaneously incorporated in the proposed linear allocation model. To consider electrical and topological characteristics in the independent functioning of the formed modules, a path‐based method is employed. The eff
Due to specific characteristics of electric distribution systems and their high vulnerability against natural disasters, providing appropriate methods for resiliency analysis and identifying system weaknesses is of great importance. Increasing penetration of distributed generation (DG) resources and developing microgrid (MG) technology provide modularity to distribution networks. Since the system capability in splitting into multi-independent sub-sections benefits its performance in severe circumstances, the level of modularization can be construed as a measure for resiliency analysis. In this study, a novel framework based on the modularity idea is proposed for quantifying the resiliency level of electric distribution systems. Utilizing gr
Resect severe economic losses caused by distribution system equipment outage have highlighted the importance of improving the system resiliency and reliability. In active distribution networks (ADNs), the distributed energy resources (DERs) managed by dynamic isolated microgrids in contingency mode provide an alternative approach to enhance the system resiliency and continue supplying critical loads after equipment outage. How to incorporate this ADNs capability into a short-term DERs scheduling is a challenging issue. In response to this challenge, in this paper, a two stage risk based decision making framework for operation of ADNs is proposed to coordinate 24-h DERs’ scheduling and outage management scheme, in a way to be immune agains
The advent of distributed energy resources (DERs) in distribution networks, referred to as active distribution networks (ADNs), brings in new opportunities for distribution network operators (DNOs) to improve the network reliability. The contribution of DERs in reliability enhancement generally depends on the island mode operation of DERs. Optimal placement of sectionalizing switches (SSs) enables ADNs to be operated more reliably by islanding the faulted part of the system in the form of flexible micro-grids (FMGs). However, practical methods are needed to handle the complex problem of the SS placement in ADNs. This paper presents a risk-based two-stage mixed-integer linear programming (MILP) model for the optimal placement of the network-
Vulnerability mitigation and redundancy improvement are of the solutions for creating resilient distribution networks aims to prevent the uncontrollable outage propagation. In this paper a comparative study is proposed for optimal feeder routing problem and HV substation placement considering cost and resilience. At the first case the network is planned based on cost minimization, and then the proposed resilience index is calculated for the planned network. While at the second case the network is designed based on resilience enhancement and afterward the planned network cost is calculated. In case of resilient-based planning, the studied area is divided into small sites with different wind speed to evaluate the geospatial characteristics of