Resilience‐based framework for switch placement problem in power distribution systems (original) (raw)
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Optimization of Switch Allocation in Power Distribution Systems
Engineering and Industry, 2015
The electric power system with its generation, as well as its transmission and distribution networks, is one of the most complex technical systems that humanity has created. A special concern pertains to the distribution networks on which most failures occur. Improved reliability can be obtained by increased investments, reinvestments and maintenance. The goal of this study is to examine the impact of components failure on distribution reliability. The paper describes a fault restoration sequence and duration in a distribution system and interruptions frequency and duration for different components and a development procedure for simulation after a fault and calculating associated time-varying failure rates and reliability indices and customers' outage costs. The approach minimizes the costs of allocation and energy not supplied, under reliability constraints. The simulation is based on genetic algorithm concept. Case studies with a several network configurations and real-world scenarios were used to evaluate the methodology.
IET Generation, Transmission & Distribution, 2019
When a natural disaster occurs in a distribution network, a widespread power interruption may occur for a few days or weeks. This study presents a bi-level optimisation-based model for reconfiguration of the distribution network to improve the resilience of electricity distribution network against severe weather events such as storm and hurricane with the aim of minimising the cost of load outage. To achieve this, a model is first presented for evaluating the vulnerability of distribution network poles to estimate the damages imposed by the threat. Then, in the first level, according to the forecasting of possible failed lines and based on the predicted wind speed before the storm, a network reconfiguration strategy is employed to minimise the expected cost of load outage. In the second level, a new reconfiguration is carried out to restore the system loads and minimise the cost of load outage after the storm. The proposed model is then applied to a standard 33-bus radial distribution system using the GAMS software. The simulation results demonstrate the effectiveness of the proposed model in increasing network resilience and highlight the importance of network reconfiguration in the face of extreme natural disasters.
IEEE Access
This paper presents a new framework for island formation prior to windstorms, which considers tree-caused failures of distribution networks. In the proposed framework, both direct and indirect effects of windstorms on distribution lines are quantified. Thus, a novel discrete Markov chain model is proposed for representing the failure modes of trees in each time interval of windstorm duration. This model categorizes ''healthy'', ''uprooted'', ''stem breakage'', and ''branch breakage'' states of a tree. In addition, a new line-tree interaction model is presented for calculating tree-caused failure probability of overhead lines. The results of the proposed Markov model are taken as inputs by the developed line-tree interaction model. In these models, the different characteristics of windstorms are taken into account. Tree vulnerability to windstorms is characterized by different factors such as their species, height, and critical wind speeds. Windstorm duration is sectionalized into multiple time intervals, and the proposed models are applied to trees and distribution system components in each interval. Moreover, the interdependency between the intervals is captured by the Markov model. The results of the models are used by an optimization model, thereby dividing a distribution system into multiple islands before storm onset. Subsequently, the framework is extended as a two-stage stochastic optimization problem to address the uncertainties of loads. In addition, this framework considers the allocation of mobile emergency resources. The proposed models are implemented on the IEEE 33-and 123-bus test systems, as well as a practical distribution feeder, and their effectiveness is demonstrated through several case studies. INDEX TERMS Discrete Markov chain, distributed energy resources (DERs), distribution system resilience, microgrids, mobile emergency resource (MER), tree failures, windstorms.
IET Renewable Power Generation, 2018
This paper proposes a two-stage stochastic optimization model for jointly wind turbine (WT) allocation and network reconfiguration (NR) so as to increase the resiliency of distribution system in face of natural disasters. In this regard, in the first level, a possibilistic-scenario method is proposed to select the line outage scenarios. The proposed model is capable with distribution systems and considers different failure probabilities for system components subject to the intensity of natural disaster in its associated zone. After selecting the line outage scenarios, in the second level, a multi-stage optimization framework is proposed for jointly NR and WT allocation in a multi-zone and multi-fault system, considering the uncertainty of system load and wind power generation. This strategy makes an interconnection between NR and islanded WTs to increase the resiliency of system and decreases the load shedding. Different economic objectives including, costs of load shedding and power generation are considered in the model. In addition, hardening budget is taken into consideration for the transmission lines, which is minimized during the optimization process. The simulation results demonstrate the capability and necessity of proposed resiliency-oriented method and prove the importance of hardening budgets. Nomenclature Indices and sets , ij Indices for system buses.
Planning for resilience in power distribution networks: A multi‐objective decision support
IET Smart Grid
Power grid response against high-impact low-probability (HILP) events could be enhanced by (a) hardening mechanisms to boost its structural resilience and (b) corrective recovery and mitigation analytics to improve its operational resilience. Planning for structural resilience and attempts to find the optimal location of the Tie switches in radially operated power distribution networks that enable harnessing the network topology for maximised resilience against HILP disasters are focussed. This goal is achieved through a novel resilience-oriented multi-objective decision making platform, which employs a k-PEM based probabilistic power flow (PPF) algorithm. The proposed framework offers a decision making analytic embedded with the fuzzy satisfying method (FSM) that characterises the system resilience features, such as robustness, restoration agility, load criticality, and recovered capacity, to assess different network reconfiguration options and select the optimal solution for implementation. The aforementioned resilience features are formulated in nodal level and then aggregated over the entire system to characterise the system-level objective functions. The performance of the suggested framework is analysed on the IEEE 33-Bus test system under a designated HILP event, and the applicability on larger networks has been verified on the IEEE 69-bus test system. The results demonstrate the efficacy and applicability of the proposed framework in boosting the network resilience against future extremes. This is an open access article under the terms of the Creative Commons Attribution-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited and no modifications or adaptations are made.
Optimized Sectionalizing Switch Placement Strategy in Distribution Systems
Power Delivery, …, 2012
Automation is acknowledged by distribution utilities as a successful investment strategy to enhance reliability and operation efficiency. However, practical approaches that can handle the complex decision-making process faced by decision makers to justify the long-term financial effects of distribution automation have remained scarce. An automated and remote-controlled sectionalizing switch play a fundamental role in an automated distribution network. This paper introduces a new optimization approach for distribution automation in terms of automated and remotely controlled sectionalizing switch placement. Mixed-integer linear programming (MILP) is utilized to model the problem. The proposed model can be solved with large-scale commercial solvers in a computationally efficient manner. The proposed sectionalizing switch placement problem considers customer outage costs in conjunction with sectionalizing switch capital investment, installation, as well as annual operation and maintenance costs. The effectiveness of the proposed approach is tested on a reliability test system and a typical real size system. The presented results indicate the accuracy and efficiency of the proposed method.
Energies, 2019
A two-level optimization method is presented to find the optimal number and location of conventional protective devices to be upgraded to remote-controlled switches (RCSs) for an existing distribution network (DN). The effect of distributed generation (DG) on this problem is considered. In the first level, a nonlinear binary program is proposed to maximize the restored customers subject to technical and topological constraints. All feasible interchanges between protective devices and ties involved in the restoration, when a fault occurs at all possible locations are found considering switching dependencies. In the second level, a nonlinear cost function, combining the expected cost of interruptions (ECOST) and the switch cost, is minimized with respect to the location of RCSs. The expected cost function is computed based on the optimum restoration policies obtained from the first level. The optimum placement of RCSs using the proposed algorithm is tested on a 4-feeder 1069-node test...
Protective Device and Switch Allocation for Reliability Optimization With Distributed Generators
IEEE Transactions on Sustainable Energy, 2019
The location of protective devices, such as circuit breakers, reclosers, sectionalizers, and fuses, along with isolating switches in a distribution network is a key factor impacting the reliability performance. Furthermore, automatic restoration from intentional islanding with renewables-based distributed generators (DGs) or from alternate feeders can reduce outage times. In this paper, a mixed-integer linear program (MILP) formulation is proposed for protective device and switch allocation considering intentional islanding with distributed generation in distribution systems. The specific impact of each protective device type and isolating switch is modeled, e.g., momentary interruptions caused by reclosers. Efficient graph search algorithms combined with a directed graph representation of the distribution system allows for pre-processing of the network data and facilitates the formulation of an MILP. The formulation is able to efficiently compute optimal device allocations for multiple scenarios, revealing key insights, e.g., the location and capacity of DGs providing the greatest reliability benefit for a fixed protection budget. Numerical tests on realistic feeders and comparison with prior solutions show improved device allocations and lower objective function values.
Resilience Assessment in Distribution Grids: A Complete Simulation Model
Energies
For several years, the increase of extreme meteorological events due to climate change, especially in unusual areas, has focused authorities and stakeholders attention on electric power systems’ resilience. In this context, the authors have developed a simulation model for managing the resilience of electricity distribution grids with respect to the main threats to which these infrastructures may be exposed (i.e., ice sleeves, heat waves, water bombs, floods, tree falls). The simulator identifies the more vulnerable network assets by means of probabilistic indexes, thus suggesting the best corrective actions to be implemented for resilience improvement. The fulfillment of grid constraints, i.e., loading limits for branches and voltage limits for buses, under actual operating conditions, is taken into account. Load scenarios extracted from available measurements are evaluated by means of load flow analyses in order to choose, among the best solutions identified, those compatible with...