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This article formulates the distribution generation placement and the network reconfiguration problems of distribution networks (DNs) as a composite multi‐objective optimization problem by normalizing and combining the objective functions, and suggests a new rainfall optimization (RFO) based method for solving the developed problem. The RFO, a metaheuristic optimization algorithm that models the behavior of raindrops falling down from a hill towards sea, has certain drawbacks such as removal of inactive raindrops that weakens the search process, and the possibility of choosing the same raindrop as inactive throughout the iterative process. This article also introduces modifications in the RFO for overcoming its drawbacks before adopting it in the proposed method. It considers two scenarios with seven test cases for simulation study, and compares the results of two standard DNs with existing methods for exhibiting the superior performances in respect of final solution, robustness, voltage profile, and average execution time of the proposed method. [ABSTRACT FROM AUTHOR]

In this study, a new resilience-based framework is presented for multi-period simultaneous transmission and substation expansion planning (ST&SEP) considering extreme weather-related events (EWEs). The formation of the proposed planning framework falls into a tri-level optimisation problem with the aim of strengthening power network resilience in response to the EWEs. In the lower-level problem, short-term remedial corrective strategies of the independent system operator (ISO) after the EWEs are determined by applying network reconfiguration and generation redispatch. In the intermediate-level problem, an enhanced scenario-building approach is developed to model and analyse the EWEs, as non-random uncertain events, and their subsequent detrimental effects using the notion of the fragility curves corresponding to power network components. In the upper-level problem, however, long-term remedial preventive strategies of the ISO, as network planner, after the EWEs are obtained through integrated decisions between multi-period ST&SEP and transmission switching equipment planning. The newly proposed planning framework is formulated as a large-scale mixed-integer non-linear tri-level optimisation problem and is solved by a powerful symphony orchestra search algorithm in order to obtain the final optimal solution. The proposed planning framework is examined on the real-world large-scale Iranian 400-kV power transmission network and its profitableness is assured by thorough simulation studies. [ABSTRACT FROM AUTHOR]

Evacuating residents out of affected areas is an important strategy for mitigating the impact of natural disasters. However, the resulting abrupt increase in the travel demand during evacuation causes severe congestions across the transportation system, which thereby interrupts other commuters' regular activities. In this article, a bilevel mathematical optimization model is formulated to address this issue, and our research objective is to maximize the transportation system resilience and restore its performance through two network reconfiguration schemes: contraflow (also referred to as lane reversal) and crossing elimination at intersections. Mathematical models are developed to represent the two reconfiguration schemes and characterize the interactions between traffic operators and passengers. Specifically, traffic operators act as leaders to determine the optimal system reconfiguration to minimize the total travel time for all the users (both evacuees and regular commuters), while passengers act as followers by freely choosing the path with the minimum travel time, which eventually converges to a user equilibrium state. For each given network reconfiguration, the lower‐level problem is formulated as a traffic assignment problem (TAP) where each user tries to minimize his/her own travel time. To tackle the lower‐level optimization problem, a gradient projection method is leveraged to shift the flow from other nonshortest paths to the shortest path between each origin–destination pair, eventually converging to the user equilibrium traffic assignment. The upper‐level problem is formulated as a constrained discrete optimization problem, and a probabilistic solution discovery algorithm is used to obtain the near‐optimal solution. Two numerical examples are used to demonstrate the effectiveness of the proposed method in restoring the traffic system performance. [ABSTRACT FROM AUTHOR]

In this study, multi‐objective particle swarm optimisation (MOPSO) and preference order (PO) ranking‐based multi‐objective planning model is presented for placement and sizing of wind and solar‐based distributed generators (DGs), and capacitors in the multi‐phase distribution network, under uncertainty considering network reconfiguration. Uncertainty in solar irradiance, wind speed, and load are considered using Monte Carlo simulation (MCS) with suitable probabilistic models. The planning problem is formulated considering different scenarios generated using MCS. For objective function formulation with varying demand and generation conditions, a dynamic load generation model is developed. A priority vector is proposed for DG and capacitor placement using the analytic hierarchy process to reduce the search space and computational time. The key benefits of the proposed DG placement algorithm are that it gives a single solution that is nearly optimal for all the possible network topologies and it works well for both unbalanced and balanced conditions. The proposed technique has been applied to IEEE 34‐bus and IEEE 123‐bus systems. The result shows a significant reduction in power losses, current unbalancing and improvement in reliability after the placement of DGs and capacitors. [ABSTRACT FROM AUTHOR]

Fast load restoration based on network reconfiguration is a key step to enhance the resilience of distribution systems (DSs). For DSs equipped with remote‐controlled switches (RCSs), the reconfiguration can be completed promptly. However, when the branch is equipped with manual switches only, it cannot be operated immediately, and its post‐event state is determined by its pre‐event state. Considering these facts, this study proposes a unified two‐stage reconfiguration method for the resilience enhancement of DSs. In the pre‐event stage, the allocation of RCSs and the reconfiguration of the network are determined to prepare the system for a set of possible fault scenarios caused by upcoming extreme weather. In the post‐event stage, network reconfiguration based on the placed RCSs is performed for fast load restoration to minimise the loss of load expectation (LOLE). A new mathematical expression is proposed to ensure the radial operation of DSs with islanded DSs and islanded microgrids. To improve the computational efficiency, the scenario decomposition algorithm is employed to decompose the proposed model into several subproblems, which can be solved in parallel. The results show that the proposed method can significantly reduce the LOLE caused by extreme weather events, thus enhancing the resilience of DSs. [ABSTRACT FROM AUTHOR]

The network reconfiguration of a vessel power system (VPS) is one of the most important approaches to restore its power supply and improve its survivability. The current research on the reconfiguration mainly focuses on the selection and optimisation of recovery paths, with little consideration of the influence of recovery time series. The limited capacity of the VPS, many loads of the motor load and large starting current have a great impact on the electric-energy quality of the power system. Therefore, the different recovery time series will affect the system performance and the recovery rate. The effect of the different recovery time series on the network reconfiguration and fault control has been analysed through the simulation of target network to determine the corresponding relationship between the residual power-supply capacity, the load recovery time series and the recovery rate, which can provide the basis of studying an optimal recovery strategy. [ABSTRACT FROM AUTHOR]

In this study, a comprehensive reconfiguration and operation optimisation of distribution system with flexible DC device (FDD) is discussed. The structures of distribution network with FDD are illustrated and the exact operating of FDD set-points are discussed which realised power flow control and loop closing operation of distribution system. Then, the non-linear combinational optimisation models of reconfiguration and operation optimisation with FDD are established considering different objectives and constraints. In order to solve the complicated optimisation problems, improved particle swarm algorithm and sequential AC/DC power flow method are used. Results show that the FDD have stronger ability to promote the performance of distribution system with power flow optimal adjusting and cooperation with traditional switch. [ABSTRACT FROM AUTHOR]

Abstract: Different cognitively demanding tasks recruit globally distributed but functionally specific networks. However, the configuration of core networks and their reconfiguration patterns across cognitive loads remain unclear, as does whether these patterns are indicators for the performance of cognitive tasks. In this study, we analyzed functional magnetic resonance imaging data of a large cohort of 448 subjects, acquired with the brain at resting state and executing N‐back working memory (WM) tasks. We discriminated core networks by functional interaction strength and connection flexibility. Results demonstrated that the frontoparietal network (FPN) and default mode network (DMN) were core networks, but each exhibited different patterns across cognitive loads. The FPN and DMN both showed strengthened internal connections at the low demand state (0‐back) compared with the resting state (control level); whereas, from the low (0‐back) to high demand state (2‐back), some connections to the FPN weakened and were rewired to the DMN (whose connections all remained strong). Of note, more intensive reconfiguration of both the whole brain and core networks (but no other networks) across load levels indicated relatively poor cognitive performance. Collectively these findings indicate that the FPN and DMN have distinct roles and reconfiguration patterns across cognitively demanding loads. This study advances our understanding of the core networks and their reconfiguration patterns across cognitive loads and provides a new feature to evaluate and predict cognitive capability (e.g., WM performance) based on brain networks. [ABSTRACT FROM AUTHOR]

This study proposes a two‐stage stochastic optimisation 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 optimisation 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 minimised during the optimisation process. The simulation results demonstrate the capability and necessity of proposed resiliency‐oriented method and prove the importance of hardening budgets. [ABSTRACT FROM AUTHOR]

Installation of branch switches and tie‐lines in the distribution system provides the flexibility of load restoration during the occurrence of a fault, i.e. N− 1 state. These switches and tie‐lines change the network topology to isolate the fault and restore the unaffected network. As a consequence, the relays may delay or fail to operate for a possible incoming fault, i.e. N− 1−1 state; therefore, this study proposes an optimal relay setting of overcurrent relays subject to N− 1 and N− 1−1 states. Laterally, the proposed model maximises the load restoration such that the network remains radial. Also, it uses a meta‐heuristic algorithm to arrive at an optimal solution. Moreover, the optimal solution is validated using GE Multilin, model‐750/760 overcurrent relay in ETAP (industrial simulation software). The efficacy of the proposed method is examined on 33‐bus and a practical 14‐bus distribution system. [ABSTRACT FROM AUTHOR]

Network integration studies try to assess the impact of future developments, such as the increase of Renewable Energy Sources or the introduction of Smart Grid Technologies, on large‐scale network areas. Goals can be to support strategic alignment in the regulatory framework or to adapt the network planning principles of Distribution System Operators. This study outlines an approach for the automated distribution system planning that can calculate network reconfiguration, reinforcement and extension plans in a fully automated fashion. This allows the estimation of the expected cost in massive probabilistic simulations of large numbers of real networks and constitutes a core component of a framework for large‐scale network integration studies. Exemplary case study results are presented that were performed in cooperation with different major distribution system operators. The case studies cover the estimation of expected network reinforcement costs, technical and economical assessment of smart grid technologies and structural network optimisation. [ABSTRACT FROM AUTHOR]

Reconfiguration and smart control of remote‐controlled sectionalising switches in distribution networks are considered as the major solutions for loss mitigation, interruption time reduction and reliability improvement after events. That is because these automation tools bring about changes in the topology of the network, isolate the faulted regions, operate distributed generators for local load satisfaction and restore the un‐faulted regions as rapidly as possible. Thus, a new solution methodology for solving the simultaneous optimal wind turbines (WTs)/switches placement as well as network reconfiguration is developed to enhance the distribution network's efficiency and reliability. Power losses, voltage deviation index, switch cost and reliability cost based on expected customer interruption cost are considered as the objective functions. The approach profits from a new multi‐objective algorithm based on modified artificial bee colony for providing the best compromise solution. The presented framework is shown to provide superior results when applied to the IEEE 69‐node test feeder. Finally, different scenarios based on feeder reconfiguration, switch placement and WT placement problems are constructed and presented in Section 5. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: Functional magnetic resonance imaging (fMRI) has become very important for noninvasively characterizing BOLD signal fluctuations, which reflect the changes in neuronal firings in the brain. Unlike the activation detection strategy utilized with fMRI, which only emphasizes the synchronicity between the functional nodes (activated regions) and the task design, brain connectivity and network theory are able to decipher the interactive structure across the entire brain. However, little is known about whether and how the activated/less‐activated interactions are associated with the functional changes that occur when the brain changes from the resting state to a task state. What are the key networks that play important roles in the brain state changes? Methods: We used the fMRI data from the Human Connectome Project S500 release to examine the changes of network efficiency, interaction strength, and fractional modularity contributions of both the local and global networks, when the subjects change from the resting state to seven different task states. Results: We found that, from the resting state to each of seven task states, both the activated and less‐activated regions had significantly changed to be in line with, and comparably contributed to, a global network reconfiguration. We also found that three networks, the default mode network, frontoparietal network, and salience network, dominated the flexible reconfiguration of the brain. Conclusions: This study shows quantitatively that contributions from both activated and less‐activated regions enable the global functional network to respond when the brain switches from the resting state to a task state and suggests the necessity of considering large‐scale networks (rather than only activated regions) when investigating brain functions in imaging cognitive neuroscience. [ABSTRACT FROM AUTHOR]

The availability of smart grid technology makes it more feasible to use optimal reconfiguration and Volt/VAr control strategies for minimising electricity losses in distribution systems. This study presents a two‐stage heuristic method to calculate the optimal impact of network reconfiguration and switching of already‐installed capacitors over electrical distribution losses. The two‐stage method searches first for a set of reduced feasible reconfigurations with less losses via a binary particle swarm optimisation and an optimal power flow algorithm, and then performs a Volt/VAr control for each feasible reconfiguration by switching capacitors, until reaching negligible changes in losses. Numerical examples and a test case considering a practical distribution network of the Taiwan Power Company demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this study, a multi objective method for optimal network reconfiguration as well as reactive power dispatches of distributed generations (DGs) has been proposed to improve the network performances by using non‐dominated sorting particle swarm optimisation. The various network performances in terms of multi objective function include minimisation of system power loss, voltage deviation and energy wastage from solar and wind generation system. The effectiveness of the proposed method has been tested on the IEEE 33‐bus radial distribution system for different combinations of network reconfiguration and reactive power output of DGs or its varying power factor. The obtained results also compared and indicated that better network performances achieved with both network reconfiguration and power factor optimisation over other cases. In addition, this strategy also results in lesser energy wastage from distributed renewable generation over without network reconfiguration option; hence, this approach is also suitable for saving and utilising maximum capacity of available renewable sources. [ABSTRACT FROM AUTHOR]

This paper presents an efficient way of solving the distribution system reconfiguration (DSR) problem in electrical power systems with consideration of different types of distributed generators (DGs). The objective of a DSR is to minimize the system power loss while satisfying the system constraints and keeping the topology of the system radial. In this paper, a new DSR algorithm based on a modified particle swarm optimization (PSO) is proposed to incorporate DGs with the constant voltage control mode. The proposed method is very efficient because it avoids an extra iteration loop for computing the reactive power at PV buses in order to keep the voltage at a specified magnitude. Furthermore, if the reactive power requirement is not met in between the extreme limits, the proposed algorithm strictly searches for the best possible tie switch combination to simultaneously reduce the power loss and ensure that the DGs operate in PV mode within acceptable reactive power limit. The proposed algorithm also integrates hourly DSR with optimal DG active power scheduling considering the DG type, generation limit constraints, and the allowable DG penetration level. The validity and the effectiveness of the proposed method has been tested using standard IEEE 33-bus and 69-bus distribution networks with various case studies. Test results show that the proposed method is robust and delivers a minimal average power loss compared with different methods, and it efficiently models DGs in DSR, demonstrating that the presence of DGs can further reduce the system loss. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

This study analyse the impact of different distributed generation (DG) operating modes towards the system performance when network reconfiguration, DG generation and tap changer setting are simultaneously configure to optimal value. The main consideration in the optimal configuration process is to minimise daily power losses. For the purpose of optimisation, imperialist competitive algorithm is applied. Analysis is conducted based on safety margin of total DGs penetration, photovoltaic generation based on daily irradiance and daily load profile. The analysis of different DG mode of operations is conducted using IEEE 33 having five tie‐switches and one on‐load tap changer. [ABSTRACT FROM AUTHOR]

This study proposes a new particle swarm optimisation algorithm for combined problem of capacitor placement and network reconfiguration simultaneously in the presence of non‐linear loads. Here, the minimising cost of real power losses and capacitor installation and also improving the power quality criteria have been pursued as the goals of an optimisation problem. In the proposed method, to achieve better control on the algorithm's exploration and exploitation capabilities, particles velocity will be dependent upon both particle's fitness and time. Perturbation module is adopted to perform perturbation on some particles and provide extra diversity to jump out from local optima and avoid premature convergence. The proposed model is implemented on two typical networks including 33‐bus IEEE standard well‐known test system and a 77‐bus radial distribution network of Sirjan, Iran. Through showing numerical results, the performance of the presented method will be discussed in comparison to previously proposed ones. The numeric comparison also indicates that simultaneously capacitor placement and network reconfiguration lead to far better results than they are considered non‐simultaneously. Furthermore, in regard to harmonic distortion, as a term of a multi‐objective function, it also improves the power quality of the network during the reconfiguration and capacitor placement procedures. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive optimisation model that combines reactive power (VAR) optimisation and network reconfiguration to minimise power losses and eliminate voltage violations. In this model, the reactive power of distributed generators (DGs), VAR compensators, the position of tap‐changer and the states of branches are formulated as continuous and discrete decision variables. The original non‐convex three‐phase optimisation model was converted to a mixed‐integer second‐order cone programming model using the second‐order cone relaxation, big‐M method and piecewise linearisation. The results of numerical tests showed that the proposed model can achieve significant additional gains in network loss reduction and voltage violation mitigation. This developed method can be used as a basic analysis tool for active distribution networks operation schedule or planning. [ABSTRACT FROM AUTHOR]

Simultaneous expansion of the electrical and thermal energies collected with conventional expansion options is scrutinised. A robust, bio‐inspired evolutionary optimisation method is proposed, to handle the complex expansion planning of a system consisting of both electrical and thermal forms of energy. Rewiring, network reconfiguration, installation of new lines and also new electrical and thermal generation units are considered as the traditional alternatives in expansion planning. To solve the problem, overall generation requirements of a network are assigned along the planning horizon. The allocation problem is formulated as a mixed‐integer non‐linear programming problem that minimises the overall system cost owing to generation capacity among the grid nodes and the newly added or upgraded lines. The performance of the original shuffled frog leaping (SFL) optimisation algorithm is advanced to overcome the complexity of the proposed expansion planning problem. Two modification steps were added to the original SFL technique to enable the proposed modified SFL algorithm to extricate from local minima. The two modification phases pledge a fast convergence rate by achieving a rapid adaptive algorithm, besides a better diversification which is the key to extricate from local minima. The efficacy and robustness of the proposed methodology are verified by applying the method to two modified standard test systems. [ABSTRACT FROM AUTHOR]

Network reconfiguration has been involved in energy loss reduction by considering the time‐varying nature of loads. Nowadays, with the integration of intermittent micro‐sources (MSs) to the power grid, optimal configuration should be determined corresponding to the variations in loads and generations. In this study, optimum reconfiguration instants are achieved based on the switching operations and energy losses costs. Moreover, the sequence of selecting loops for reconfiguration is optimised in conjunction with the time intervals by a joint optimisation algorithm. Furthermore, a simple branch exchange method of reconfiguration is modified in the presence of MSs. Discrete genetic algorithm (DGA) is employed to optimise the reconfiguration instants as well as the sequence of selecting loops. By applying the proposed method, the total operating cost of the network is reduced significantly, compared to optimum fixed configuration and hourly reconfiguration policies. The proposed algorithm is evaluated on a real‐life 77‐bus distribution system with two interconnected MSs. [ABSTRACT FROM AUTHOR]

In this study, algorithms for directional relays using only current measurements are presented. Developed for radial distribution networks, these algorithms will determine fault direction based on ratios between variations of sequence currents during and before faults: ΔI2/ΔI0 ratio for line‐to‐ground faults and the ΔI2/ΔI1 ratio for line‐to‐line faults. The ratios are used as input of a support vector machine classifier, which was trained beforehand thanks to simulation tools. The classifier classifies ratios into two categories, according to the fault location: upstream or downstream towards the relay. Test results from simulations show good performances of the algorithms in most cases, with the presence of different distributed generation technologies. Moreover, impact of certain factors on algorithms, such as measurement errors, high‐impedance faults or network reconfiguration, is studied. Finally, the implementation of algorithms is also discussed. [ABSTRACT FROM AUTHOR]

Similar to other cities worldwide, the increasing amounts of short-circuit current in Bangkok (Thailand) and the vicinity areas are becoming higher than the interrupting capacity (IC) of circuit breakers. To cope with the problem, the Electricity Generating Authority of Thailand (EGAT) has come up with the solutions of network reconfiguration, e.g. bus splitting and transmission line disconnecting. These solutions help reduce effectively the amounts of short-circuit currents by increasing the equivalent system impedance. However, bus splitting and transmission line disconnecting tend to decrease the system reliability. One of the alternative approaches, the installation of high-voltage direct current (HVDC) can help reduce the amounts of short-circuit currents, while the system reliability is maintained. Therefore, this paper mainly presents the reliability evaluation method of the systems with HVDC installation, which requires AC/DC power flow calculation. To avoid system constraint violation, generation redispatch, load shedding, and DC power flow control are executed. The Monte Carlo simulation is used to repeatedly evaluate the system reliability until convergence. The proposed method is tested in (i) the IEEE Reliability Test System 79 (RTS79) to confirm the correctness of reliability evaluation and (ii) the system of EGAT Bangkok including its vicinity areas to show the readiness for real implementation. Comparison of reliability indices among all solutions of short-circuit current reduction is presented and discussed. The results show that the proposed method is effective and the HVDC installation can increase the system reliability, depending on its installation location and capacity. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In the future, a large number of distributed generators are expected to be connected to the distribution system. However, with the connected capacity of distributed generation (DG) increasing, the problems of short-circuit capacity (SCC) over the interrupting capacity of the circuit breaker (CB) and power loss increases due to reverse power flow from DG are inevitable. In this paper, a reconfiguration methodology based on an optimal algorithm is applied to the distribution system with DG to minimize power loss, taking into account the SCC. Moreover, in order to further reduce the loss, the daily load variation is also considered and the optimal model decided by calculations. Finally, to illustrate its application, the methodology is applied to a case study of a 33-bus system with decentralized DG units. The results show that this method is obviously able to reduce power loss and make the network operate in the optimal mode with normal load variation, at the same time decreasing the SCC within the interrupting maximum of the faulty CB. Moreover, the whole voltage profile is also improved. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In the present electrical engineering curriculum, power distribution engineering is one of the core courses offered to the students with power systems specialization. Since the distribution systems are mostly radial, the topics related to radial distribution system (RDS) are emphasized in this course. In RDS, network reconfiguration is frequently performed for optimizing system performance. Before the reconfiguration operation is physically performed, it is necessary to have computer-aided performance assessment of the reconfigured RDS from load flow analysis. For students' education, it is necessary that the students should familiarize themselves with computer simulation of RDS reconfiguration followed by load flow analysis. The purpose of this paper is to clearly and illustratively explain the various underlying sub-processes involved in the simulation experiment of RDS reconfiguration. The pseudo-codes in the form of flowcharts and complete C-language program codes for RDS reconfiguration are also included. © 2007 Wiley Periodicals, Inc. Comput Appl Eng Educ 14: 260–276, 2007; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20103 [ABSTRACT FROM AUTHOR]

Summary: To meet the demands of communication‐intensive workloads in the cloud, virtual machines (VMs) should utilize low overhead network communication paradigms. In general, such paradigms enable VMs to directly communicate with the hardware by means of a passthrough technology like Single‐Root I/O Virtualization (SR‐IOV). However, when passthrough‐based virtualization is coupled with lossless interconnection networks, live migrations introduce scalability challenges due to the substantial network reconfiguration overhead. With these challenges in mind, we proposed a virtual switch (vSwitch) SR‐IOV architecture for InfiniBand in our previous work titled "Towards the InfiniBand SR‐IOV vSwitch Architecture". In this paper, we first suggest solutions to rectify the space‐domain scalability issues that are present in vSwitch‐enabled subnets as a result of the VMs using dedicated layer‐two addresses. Then, we discuss routing strategies for virtualized environments using vSwitches and present a routing algorithm for Fat‐Trees. We also present a reconfiguration method that minimizes imposed reconfiguration overhead on Fat‐Trees. We perform an extensive evaluation of our prototype algorithms, and as vSwitch‐enabled hardware does not yet exist, we deduce from empirical observations by emulating vSwitches with existing hardware, as well as large‐scale simulations. Our results show significant reduction in the reconfiguration times as route recalculations can be eliminated, and for certain scenarios, the number of reconfiguration subnet management packets sent to switches is reduced from several hundred thousand down to a single one without degrading the routing quality. [ABSTRACT FROM AUTHOR]

Nowadays, due to the increasing electrical demand, optimal operation of distribution network has taken much attention. To reach this goal, 1 of the useful methods is the implementation of custom power devices. This paper tries to investigate the unified power quality conditioner (UPQC) placement and sizing along with distribution network reconfiguration for the reactive power compensation in the radial distribution system. This approach finds the optimal sizing and location of UPQC and the optimal changing of the switches status between feeders. Real power loss reduction is the chief function of this work. The proposed method is applied on the 69‐bus radial distribution test system. To check the feasibility and effectiveness of the proposed methodology, various scenarios of reconfiguration and UPQC placement are taken into account at different load conditions. Results show that the network reconfiguration with the placement of UPQC provides lower energy losses compared with other methods. [ABSTRACT FROM AUTHOR]