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In this paper, a study is conducted to solve voltage problems that may occur, when large-scale Distributed Generations (DGs) and Electric Vehicles (EVs) are connected to the distribution system, through coordinated control between DGs and EVs. Using the Graph Search Method (GSM), the voltage problem was solved through the reactive power control of EVs and DGs in the near area where the voltage problem occurred. As a result, it was possible to obtain a result with high robustness against the change of the topology and reduction of the total loss of distribution system. In addition, when the voltage problem cannot be solved by only reactive power control, the active power control was performed for EVs and DGs included in a specific divided system of the conventional distribution system using the GSM to maintain the voltage within the normal range. Finally, to verify the performance of the proposed method, the whole algorithm was implemented by linking the Open Source Distribution System Simulator (OpenDSS), and the MATLAB.

This paper proposes a new solution for the classification of short-circuits in medium-voltage distribution grids. The solution requires the measurements of the phase voltages at the time of the short-circuit and the voltage amplitudes of the short-circuit wave resulting from the fault. The values of the voltage before the short-circuit are used to calculate the expected values of the short-circuit wave amplitudes for the different types of short circuits. These calculations are based on an analysis of the charge flow between the capacitances of the power line due to the disturbance. The short-time matrix pencil method was used to detect the incoming short-circuit waves. Tests of the algorithm were carried out on the IEEE 34-bus Feeder model, taking into account the influence of voltage sensors on the measured signal values. The classification algorithm uses only non-zero components due to their relatively low attenuation. Despite that, it achieves high performance in the classification of single- and two-phase short-circuits.

The widespread deployment of electric buses (EBs) offers substantial flexibility resources to support the service restoration and enhance the resilience of distribution system (DS). Therefore, this paper presents a comprehensive and collaborative service restoration strategy for resilient DS, considering the support of EBs. First, the restoration flexibility model for EBs is derived, which quantifies the restoration capability of EBs by dividing effective EB clusters. This model is integrated into the DS restoration process. Then, a two-step collaborative restoration method of DS is proposed with the aim of minimizing the load curtailment cost. The first step addresses the restoration planning problem to determine the dispatch decisions for EB clusters. Based on above planning solutions, the second step focuses on the real-time restoration problem of DS, obtaining optimal restoration results through coordinating EB clusters and other local resources. In this stage, the impact of natural disasters on the EB cluster dispatch in transportation system is considered, and a rolling optimization method is employed to deal with uncertainties from renewables, load, and EB cluster dispatch time. Finally, numerical simulations are conducted using the modified IEEE 33-bus distribution test system and a 29-node transportation system to verify the effectiveness of the proposed restoration method.

The data integration of high voltage (HV) and medium voltage (MV) distribution power grids is a development trend in future energy management systems. This integration brings about challenges such as handling large-scale networks and bad data, which can impact the speed and accuracy of state estimation. To address these issues, a forward/backward sweep (FBS) robust state estimation algorithm (FB-SE) is proposed, particularly suitable for simple loop and radial distribution systems. The algorithm consists of two stages: 1) Bad Data Pre-processing (BDP); and 2) Branch Power Flow State Estimation; Both stages follow the FBS strategy. The preprocessing of bad data only involves one FBS calculation, aiming to identify and rectify obvious bad data; The branch power flow state estimation introduces the weights of state estimation and uses a classification normalized residual index function to achieve weight allocation. The state estimation algorithm proposed in this paper avoids solving Jacobian matrices and linear equations. It can also handle simple ring networks by opening the loop and performing power compensation. The simulation results based on IEEE examples show that this algorithm has advantages in computation speed, robustness, and convergence.

Detecting High Impedance Faults (HIFs) in Distribution Systems (DSs) still requires effective solutions. HIFs can cause damage, such as shock hazards and bushfires. However, conventional protection cannot identify HIFs due to their low fault current, and most existing solutions neglect the multiple operating scenarios of the DSs. Thus, this paper proposes a new self-adaptive approach for HIF detection, considering the conductor fall period in a system with distributed generation, a condition usually overlooked in existing studies. The algorithm is based only on the fundamental component and third harmonic extracted from the neutral current using the Stockwell Transform. The approach was thoroughly evaluated, considering several scenarios, such as changes in the system loading, background noise, events that can cause false detection, and variations in the distributed generator power output. The tests considered HIFs signals from real field measurements and generated by a simulation model. The results showed that the algorithm is promising, with high detection rates for all the evaluated scenarios, which included over 400,000 HIF and 6,000 non-HIF cases. Additionally, a comparison proved the superiority of the proposed approach over existing methodologies.

• Coordinated control between DGs and EVs addresses voltage problems in distribution systems. • Graph Search Method (GSM) optimizes reactive power control to resolve local voltage issues. • The proposed method enhances robustness to topology changes and reduces system losses. • Active power control is applied when reactive power alone cannot solve voltage problems. • OpenDSS and MATLAB integration verifies the performance of the proposed voltage control method. In this paper, a study is conducted to solve voltage problems that may occur, when large-scale Distributed Generations (DGs) and Electric Vehicles (EVs) are connected to the distribution system, through coordinated control between DGs and EVs. Using the Graph Search Method (GSM), the voltage problem was solved through the reactive power control of EVs and DGs in the near area where the voltage problem occurred. As a result, it was possible to obtain a result with high robustness against the change of the topology and reduction of the total loss of distribution system. In addition, when the voltage problem cannot be solved by only reactive power control, the active power control was performed for EVs and DGs included in a specific divided system of the conventional distribution system using the GSM to maintain the voltage within the normal range. Finally, to verify the performance of the proposed method, the whole algorithm was implemented by linking the Open Source Distribution System Simulator (OpenDSS), and the MATLAB. [ABSTRACT FROM AUTHOR]

• A restoration flexibility quantification method is developed for EB clusters. • A two-step collaborative restoration strategy for the resilient DS is proposed. • Uncertainties associated with the EB cluster dispatch time and renewables power outputs are well addressed by using rolling optimization method. The widespread deployment of electric buses (EBs) offers substantial flexibility resources to support the service restoration and enhance the resilience of distribution system (DS). Therefore, this paper presents a comprehensive and collaborative service restoration strategy for resilient DS, considering the support of EBs. First, the restoration flexibility model for EBs is derived, which quantifies the restoration capability of EBs by dividing effective EB clusters. This model is integrated into the DS restoration process. Then, a two-step collaborative restoration method of DS is proposed with the aim of minimizing the load curtailment cost. The first step addresses the restoration planning problem to determine the dispatch decisions for EB clusters. Based on above planning solutions, the second step focuses on the real-time restoration problem of DS, obtaining optimal restoration results through coordinating EB clusters and other local resources. In this stage, the impact of natural disasters on the EB cluster dispatch in transportation system is considered, and a rolling optimization method is employed to deal with uncertainties from renewables, load, and EB cluster dispatch time. Finally, numerical simulations are conducted using the modified IEEE 33-bus distribution test system and a 29-node transportation system to verify the effectiveness of the proposed restoration method. [ABSTRACT FROM AUTHOR]

• Type of fault can be classified using non-zero travelling wave modal components. • Fault classification method based on voltage wavefront amplitude was developed. • Easy method of calculating the amplitude of fault travelling wave was developed. This paper proposes a new solution for the classification of short-circuits in medium-voltage distribution grids. The solution requires the measurements of the phase voltages at the time of the short-circuit and the voltage amplitudes of the short-circuit wave resulting from the fault. The values of the voltage before the short-circuit are used to calculate the expected values of the short-circuit wave amplitudes for the different types of short circuits. These calculations are based on an analysis of the charge flow between the capacitances of the power line due to the disturbance. The short-time matrix pencil method was used to detect the incoming short-circuit waves. Tests of the algorithm were carried out on the IEEE 34-bus Feeder model, taking into account the influence of voltage sensors on the measured signal values. The classification algorithm uses only non-zero components due to their relatively low attenuation. Despite that, it achieves high performance in the classification of single- and two-phase short-circuits. [ABSTRACT FROM AUTHOR]

• A bad data preprocessing strategy before state estimation. • A branch power flow state estimation algorithm only needs simple circuit calculation. • The algorithm can be applied to simple loop distribution systems. • Comparative results over the WLS and BE-SE based estimators. The data integration of high voltage (HV) and medium voltage (MV) distribution power grids is a development trend in future energy management systems. This integration brings about challenges such as handling large-scale networks and bad data, which can impact the speed and accuracy of state estimation. To address these issues, a forward/backward sweep (FBS) robust state estimation algorithm (FB-SE) is proposed, particularly suitable for simple loop and radial distribution systems. The algorithm consists of two stages: 1) Bad Data Pre-processing (BDP); and 2) Branch Power Flow State Estimation; Both stages follow the FBS strategy. The preprocessing of bad data only involves one FBS calculation, aiming to identify and rectify obvious bad data; The branch power flow state estimation introduces the weights of state estimation and uses a classification normalized residual index function to achieve weight allocation. The state estimation algorithm proposed in this paper avoids solving Jacobian matrices and linear equations. It can also handle simple ring networks by opening the loop and performing power compensation. The simulation results based on IEEE examples show that this algorithm has advantages in computation speed, robustness, and convergence. [ABSTRACT FROM AUTHOR]

Detecting High Impedance Faults (HIFs) in Distribution Systems (DSs) still requires effective solutions. HIFs can cause damage, such as shock hazards and bushfires. However, conventional protection cannot identify HIFs due to their low fault current, and most existing solutions neglect the multiple operating scenarios of the DSs. Thus, this paper proposes a new self-adaptive approach for HIF detection, considering the conductor fall period in a system with distributed generation, a condition usually overlooked in existing studies. The algorithm is based only on the fundamental component and third harmonic extracted from the neutral current using the Stockwell Transform. The approach was thoroughly evaluated, considering several scenarios, such as changes in the system loading, background noise, events that can cause false detection, and variations in the distributed generator power output. The tests considered HIFs signals from real field measurements and generated by a simulation model. The results showed that the algorithm is promising, with high detection rates for all the evaluated scenarios, which included over 400,000 HIF and 6,000 non-HIF cases. Additionally, a comparison proved the superiority of the proposed approach over existing methodologies. • The substation transformer neutral current is the only measurement needed. • The method is easily replicable and uses only two metrics. • The method's adaptive thresholds enable using it in different system conditions. • The method did not falsely detect the tested short and long-lasting transients. • The technique was tested in wider scenarios than existing methods in the literature. [ABSTRACT FROM AUTHOR]

• The optimal and efficient EV charging control is modeled as a partially-observable constrained Markov decision process and solved by RL. • One of the critical drawbacks of applying reinforcement learning (RL) in power and energy systems—security risk—is overcomed. • The limitations of classical safe RL methods are theoretically analyzed and how the proposed framework overcomes these limitations are quantitively discussed. • The proposed approach is validated by comparing its performance with those of five state-of-the-art benchmark methods. The optimal and secure electric vehicles charging control can be formulated as a large-scale partially-observable constrained Markov decision process (PO-CMDP) problem with high levels of security risks and uncertainties. Such a problem is very difficult to be handled by optimization-theory-based methods. Data-driven methods, especially reinforcement learning (RL), are suitable for handling uncertainties but are poor in ensuring safety, which is unacceptable in power systems. Motivated by the fact that humans could be supervised by an expert when learning a new skill involving risk, this paper proposes a safe RL framework that embeds rule-based local and global shields in the loop of RL for supervising the actions of agents. The proposed framework not only strictly guarantees local and global security in the training and execution phases, but also helps the agent to find a more near-optimal policy. The effectiveness and efficiency are demonstrated by comparison with multiple baseline methods in the IEEE-33 node system. [ABSTRACT FROM AUTHOR]

• An original control strategy for mitigating neutral currents using smart loads. • A simple and low complexity, model-based, dual-loop control design. • Systematic and intuitive synthesis of control gains solving LMI constraints. • Effective mitigation of neutral currents under both linear and nonlinear loads. This article presents a strategy for minimizing neutral current in distribution microgrids using electric spring-based smart loads. A dual loop control scheme is proposed – the outer loop generates reference voltages for the individual electric spring in each phase using a simple voltage division concept that results in zero neutral current, while in the inner loop, the output voltage and current of the electric spring are controlled using repetitive controllers. The control system features a simple structure and systematic design and is minimally reliant on exact knowledge of parameters, making it robust in the presence of uncertainties. The electric spring in each phase is controlled independently and identical to the other phases without requiring any axis transformation. Detailed design of the proposed solution is presented and its performance is tested by simulating it on a benchmark low-voltage distribution microgrid to show its effectiveness and validity. [ABSTRACT FROM AUTHOR]

• Judgment theorems of security boundary are proposed for the first time. • The proposed theorems are verified by mathematical proofs and observations. • Applications based on the proposed judgment theorems are given. Security boundary characterizes the operations range of a distribution system satisfying N-1 security, and this paper proposes three judgment theorems for it. Firstly, the relevant concepts of the security boundary are introduced. The security boundary represents the set of all the critical secure operating points in the state space of a distribution system. Based on the degree of criticality, it can be classified into two types, i.e., strict and non-strict boundaries. Secondly, the load relationships between interconnected feeders are defined, and based on this, three judgment theorems are proposed. Thirdly, the proposed theorems are rigorously proven. Finally, an IEEE RBTS test system is used to verify the proposed theorems and demonstrate their applications. The proposed theorems enable convenient judgment of whether an operating point is a security boundary point and its type. This work reveals the load distribution characteristics of security boundary points, providing fundamental contributions to security boundary theory. [ABSTRACT FROM AUTHOR]

• The presented algorithm is applied to fulfill the network identification objectives. • Quantitative and qualitative analysis is performed to verify the efficacy of the work. • The algorithm is validated on the benchmark IEEE 13-bus and 34-bus distribution systems. • In contrast to state-of-the-art frameworks, the presented work provides better performances under various dynamic scenarios. The network parameters of the distribution system play a very important role for the network operator in performing a timely and satisfactory operation. Therefore, they require to be updated on a time-to-time basis otherwise it may lead to non-optimal operation of the distribution system. To deal with this issue, the reformulation strategy and the fast iterative shrinkage-thresholding approach (FISTA) algorithm are designed herein to accomplish the network identification objectives using distribution phasor measurement units (D-PMUs) measurements. The presented algorithm has capabilities to determine the manifold tasks such as the identification of structure of the distribution system, variation in network configuration, branch parameters (e.g., conductance and susceptance), and changes in branch parameters. Simulation is performed with the help of the synchronized dataset to validate the efficacy of the presented algorithm on the manifold benchmarked testbeds such as IEEE 34-bus and IEEE 13-bus systems. Additionally, the FISTA algorithm demonstrates excellent performance even with the presence of a certain level of Gaussian noise in the D-PMU measurements. To illustrate the efficacy of the presented work over the state-of-art methods, the comparative analysis is carried out on the benchmarked test cases. [ABSTRACT FROM AUTHOR]

[Display omitted] • A physics-informed fast voltage control method of distribution network is proposed. • It develops a novel deep reinforcement learning algorithm with graph knowledge. • The proposed algorithm uses multiple agents with continuous action space. With the recent rapid uptake of photovoltaic (PV) resources, the overvoltage condition during low load periods or intermittent renewable generation is one of the most critical challenges for electricity distribution networks. Traditional model-based local or centralized control methods that rely on proper system parameters are difficult to mitigate rapid changes in power systems. Utilizing model-free/data-driven multiagent deep reinforcement learning (MADRL) has been recognized as an effective solution to active voltage control. However, existing MADRL-based control approaches trained solely on data are agnostic to the underlying real-world physics principles. Therefore, this paper aims to incorporate physical knowledge of regional distribution networks into MADRL's decision-making. The main contributions of this paper are summarized as follows. First, a novel physics-informed MADRL -based distributed voltage control method is proposed, which is still under a centralized training and distributed execution framework and only requires local measurements. Second, graph neural networks are employed to help MADRL agents learn graph knowledge (node features and topological information). Further, transformer is introduced to extract discriminative representations and ensure agents' cooperative control. Third, we adopt a physics-guided architecture of neural networks in the actor network to stabilize the training process and improve sample efficiency. Finally, simulation results based upon modified IEEE 33-bus and 141-bus networks validate the proposed method's effectiveness, robustness and computation efficiency. [ABSTRACT FROM AUTHOR]

• Design of static state estimation technique for Hybrid AC/DC microgrids that considers the unique operating characteristics under Islanded operating mode. • Modifications to the Jacobian of Weighted Least Squares (WLS) method for islanded hybrid AC/DC microgrids. • The importance of the Interlinking Converter in Islanded Hybrid AC/DC microgrids was established in terms of critical measurements in State Estimation (SE). • Validation of the WLS SE method on a large Islanded Hybrid AC/DC microgrid (906-AC and 118-DC) along with 12-bus and 71-bus Islanded Hybrid AC/DC Microgrids. In this work, a static state estimation (SSE) approach for the hybrid AC/DC microgrid (MG)s operating in islanded mode is studied. In the islanded mode, the Interlinking Converter (IC) is critical for maintaining equal or normalized power between the AC and DC parts of the Microgrid (MG). Since the power exchange between AC and DC parts of the MG is determined from AC MG frequency and DC bus voltage, these also need to be considered as system variables along with bus voltages. Hence, in the proposed approach, the Weighted Least Squares (WLS) method is used to estimate the steady-state frequency (ω), along with AC bus voltages (magnitude and phase) of AC MG and DC bus voltages of DC MG simultaneously. Further, to incorporate frequency and droop equation of IC measurement, the Jacobian matrix of WLS is revised. The developed WLS-based Static SE is tested on two test systems: i) 12 bus system (6 bus AC and 6 bus DC) and ii) 71 bus system (38 bus AC and 33 bus DC). Moreover, the impact of accuracy classes of measurements is studied on a large Hybrid AC/DC MG (906 nodes AC MG and 118 node DC MG). All the SE results have been validated by comparing the obtained results with the corresponding true values (calculated from load ow analysis). [ABSTRACT FROM AUTHOR]

• Methodology to evaluate zero-sequence impedance for three-limb core is proposed. • Evaluation method for fault current with three-limb core transformer is proposed. • KEPCO model with Yg/Yg and Yg/Δ are presented for evaluation on faulted feeder. • Fault at neighborhood feeder is examined with variations: DER capacity and distance. • Remarkable impact of three-limb core type on reverse fault current is demonstrated. As many DERs with solid grounding are connected to the distribution system, unwanted reverse fault current is generated during a single-line-to-ground fault. Therefore, it often causes protection problems such as protection blinding and sympathetic tripping. To ensure reliable protection coordination between protective devices, fault current should be calculated accurately. Although three-limb core transformers are utilized for DERs for economic and spatial reasons, the conventional method that assumes five-limb core transformers for DERs is still used to calculate fault current. The zero-sequence impedance of a three-limb core transformer is often unknown. For this, a methodology for evaluating the zero-sequence impedance according to the core-type of transformer is presented with IEC 60076-8 standard. Then, a methodology for evaluating fault current is proposed considering the impact of DERs, loads, and transformer core types. The proposed methodologies are used for a comprehensive analysis of fault current discrepancies according to the core-type of transformers. The results indicate that significant discrepancies exist in fault current evaluated with five- and three-limb core transformers. Therefore, to accurately calculate the fault current, utility engineers should use the proper zero-sequence impedance of three-limb core transformers instead of five-limb core transformers. [ABSTRACT FROM AUTHOR]

• Propose a dual-cascade secure fault protection method for EDS employing THD-based detection and Sequence-based location algorithm. • Propose a robust THD-based fault detection algorithm for EDS, capable of handling symmetrical and unsymmetrical faults, regardless of pre-existing grid harmonics. • Develop a Communication-less sequence components-based fault location algorithm to locate the faults, especially in case of grid-reconfiguration. • Demonstrate the algorithms practicality on IEEE-9 buses ring system using MATLAB/Simulink and experimental results, emphasizing its significance. In this paper, a protection method with two cascaded algorithms is proposed to face fault events in Electrical Distribution Systems (EDSs). The first algorithm uses the Total Harmonic Distortion (THD), the estimates of the amplitude voltages, and the zero-sequence component of the grid voltages for defining an adaptive algorithm that provides a secure detection and identification process for the faults in the grid network. The second algorithm uses the behavior of the positive and negative-sequence components of the grid voltages during the fault events to locate and isolate the faults. Its main merit is that it doesn't need to employ communication lines for transmitting trip signals between the protective devices (PDs) of the system. A Second Order Generalized Integrator (SOGI) is used for obtaining the estimated variables and sequence components, which allows fast detection with a low computational burden. The harmonic content existing prior to the fault is taken into consideration for not affecting the detection of the fault. The performance of the protection method's is evaluated experimentally and by using simulations in MATLAB/Simulink and employing the IEEE 9-bus standard ring system. The proposed method shows the capability for detecting, identifying, and isolating different fault types with different DG penetrations and fault resistances in different locations of the proposed network and even when the grid configuration is changed. The method is robust to the possible harmonic distortion of the network. [ABSTRACT FROM AUTHOR]

• An analytical model is proposed to characterize the automatic tripping process of switches under multiple faults caused by extreme disasters, based on network flow theory. • A DS prevention and rapid restoration method is established considering the sequential actions of multiple types of switches. • The proposed method enables DS operators to fully consider the impacts of automatic switch tripping and the coupling of DS topology before and after events when developing strategies for extreme disasters. With the increasing frequency and intensity of extreme disasters, enhancing distribution system (DS) resilience has been an urgent need for smart grid. Among various resilience enhancement measures, network reconfiguration is the most commonly used one. Multiple switches are involved in distribution network reconfiguration, e.g., circuit breakers (CBs), fuses (FUs), remote-controlled switches (RCSs), and manual switches (MSs). According to the characteristics of various switches, it is vital to establish an analytical switch action model for generating feasible and effective DS resilience enhancement strategies. In this paper, an analytical model is developed to characterize the automatic tripping process of switches under multiple faults caused by extreme disasters. A novel DS resilience enhancement method is further proposed, which considers the sequential actions of multiple types of switches to enhance the prevention and rapid restoration capability of DSs against extreme disasters. Before the strike of a disaster, the topology of DS is reconfigured based on RCSs, MSs, and CBs to improve the survivability of loads. The automatic tripping process of CBs and FUs is simulated when faults occur. After the disaster, the DS is reconfigured based on RCSs and CBs after events to isolate faults and restore critical loads. The proposed method is formulated as a mixed-integer linear programming (MILP) problem, which can be efficiently solved using commercial solvers. Case studies conducted on the modified IEEE 123-bus test systems demonstrate the effectiveness of the proposed method for DS resilience enhancement. [ABSTRACT FROM AUTHOR]

• A robust repair crew dispatch method towards the uncertainty of switches is proposed. • A tri-level MILP model is formulated to determine the scheduling applicable to all possible scenarios. • A customized NC&CG algorithm is employed to effectively solve the tri-level model. After natural disasters' strike, the remote-controlled switch plays a key role in network reconfiguration to restore the critical load. However, the status of these switches is hardly acquired in case of cyber malfunctions. This paper proposes a robust repair crew dispatch approach for distribution systems considering the uncertainty of remote-controlled switches. The proposed approach is formulated as a tri-level robust optimization model to obtain the repair crew dispatch strategy applicable to possible fault scenarios. The system operator determines the repair crew dispatch scheme at the first level. At the second level, the real-time status of switches under different combinations of faults and repair processes is modeled and the worst fault scenario is calculated. Based on the real-time status of switches, the operator utilizes distributed generators and network reconfiguration to restore loads. A nested column-and–constraint generation (NC&CG) algorithm is customized for the proposed robust model to achieve the optimal solution. Simulation results on the IEEE-33 node distribution test system and the IEEE 123-node system show the proposed approach can effectively reduce the maximum system loss and the NC&CG algorithm can significantly reduce the computing time. [ABSTRACT FROM AUTHOR]

Pursuing resilience enhancement, we propose a hierarchical decision-making framework for proactive consumers and the supplying utility interacting through an electricity distribution system. Such decision framework enables identifying solutions that are optimal for both the leading partner, the electric utility, and the other agents, proactive consumers and non-proactive consumers, that react to the decisions of the leading agent. Resilience improvement interventions include installing batteries and undergrounding distribution lines. The proposed technique can be helpful to distribution system planners, who can use it to optimally coordinate the resilience enhancement investments by the electric utility and proactive consumers. We analyze cases pertaining to realistic distribution systems. • Resilience enhancement using batteries and undergrounding feeders. • Hierarchical optimization including the electric utility and proactive consumers. • Enhancement outcomes depend significantly on cost and available options. • Hybrid solutions involving both the utility and proactive consumers are common. [ABSTRACT FROM AUTHOR]

• A novel method for estimation of interharmonic content using MODWPT and KEMD. • HIF detection using interharmonic content in the current waveforms. • A standard HIF model simulation in SIMULINK. • Algorithm is tested on an extensive dataset obtained from simulation. Despite extensive research, high impedance fault (HIF) detection remains challenging because it is always associated with low magnitude, nonlinear, asymmetric and random fault currents. This paper presents a new technique for arcing high impedance ground fault detection in distribution feeders through analysis of interharmonic content of the current signal. The origin of interharmonics is related to the random variation of the electric arc associated with HIF. For effective separation of interharmonic components, a novel method using maximum overlap discrete wavelet packet transform (MODWPT) and a newly developed special knot based empirical mode decomposition (EMD) is presented. The results indicate that the proposed scheme can reliably detect HIFs with a reasonable detection speed and at the same time achieve high security against no-fault cases. [ABSTRACT FROM AUTHOR]

Highlights • Updating pseudo data considering the impact of spatial-temporal correlation. • Studying the impact of load aggregation and PV penetration on spatial-temporal correlation. • Developing a non-iterative computationally efficient DSSE algorithm. • Proposing a time series state estimation framework suitable for unbalanced LV distribution networks. Abstract The increasing complexity of distribution networks calls for advancement in distribution system state estimation (DSSE) to monitor the operating conditions more accurately. A sufficient number of measurement devices is imperative for a reliable and accurate state estimation. The limitation on the measurement devices is generally tackled with using the so-called pseudo measured data. However, the errors in pseudo data by current techniques are quite high leading to a poor DSSE. As customer loads in distribution networks show high cross-correlation in various locations and over successive time steps, it is plausible that deploying the spatial-temporal dependencies can improve the pseudo data accuracy and estimation. Although the role of spatial dependencies in DSSE has been addressed in the literature, one can hardly find an efficient DSSE framework capable of incorporating temporal dependencies present in customer loads. Consequently, to obtain a more efficient and accurate state estimation, we propose a new non-iterative DSSE framework to involve spatial-temporal dependencies together. The spatial-temporal dependencies are modeled by conditional multivariate complex Gaussian distributions and are studied for both static and real-time state estimations, where information at preceding time steps are employed to increase the accuracy of DSSE. The efficiency of the proposed approach is verified based on the quality and accuracy of the indices, standard deviation and computational time. The method applied to a combination of residential and industrial customer loads in three different balanced medium voltage (MV), and one unbalanced low voltage (LV) distribution case studies for evaluations. [ABSTRACT FROM AUTHOR]

Highlights • This paper presents the specific technical aspects associated with CVR and VAr management for an urban distribution system operation. • The focus is explicitly on VAr management during CVR, since it has not been addressed in the literature in greater detail. • In summary, it can be seen that there are possibilities for both positive and negative effects under each simulated stand-alone Volt/VAr control method. • It is revealed that a carefully designed Volt/VAr control strategy is required for successful implementation of CVR under high penetration of solar-PV. Abstract Modern distribution systems are mainly characterized by the behavior of non-linear consumer loads and their stochasticity, intermittency of renewable energy resources; and recurrent operation of Volt/VAr control devices. Conservation voltage reduction (CVR) has been adopted by most of the distribution utilities around the world as a viable technique for peak load shaving and long-term energy savings. Due to the diversified and inherent characteristics associated with the modern distribution systems with high levels of solar-PV penetration, achieving significant voltage reduction, high power factor, minimum number of tap changer operations and low power losses could be challenging. This paper has addressed the issue of VAr management in urban distribution systems while implementing CVR in the presence of highly intermittent solar-PV. Three conventional Volt/VAr control strategies were used to identify the specific technical aspects associated with CVR and VAr management in distribution systems in the presence of high solar-PV penetration. A case study on an urban distribution system with high penetration of solar-PV has been conducted in this paper. It is revealed that a carefully designed Volt/VAr control strategy is required for successful implementation of CVR under high penetration of solar-PV. [ABSTRACT FROM AUTHOR]

• A two-stage outage management strategy is proposed for resilience enhancement. • The preventive stage determines MPS locations under fault uncertainty. • The post-disaster stage coordinates the dispatch of emergency mobile resources. • The dynamic microgrid formation accelerates the load restoration. Repair crews (RCs) and mobile power sources (MPSs) are emergency mobile resources (EMRs) for distribution system repair and restoration. In this paper, an outage management strategy (OMS) is proposed to improve the distribution system resilience against extreme weather events in both preventive and post-disaster stages. In the preventive stage, considering the uncertainty of fault location, the resource allocation problem is formulated as a two-stage stochastic programming to minimize the expected load shedding cost shortly after the disaster. The post-disaster stage is a cooperative dispatch of EMRs, accompanied by dynamic microgrid formation. With the progress of line repair, the MPSs are dispatched to different locations to support microgrids. The optimal repair sequence of faulted lines and scheduling of MPSs are determined in a multi-timeslot dispatch model. The proposed algorithm is validated by IEEE 123-bus test system and a 118-bus real-world system. The simulation results demonstrate that OMS can efficiently restore critical loads via an optimal utilization of mobile resources. [ABSTRACT FROM AUTHOR]

• Employs the typical hardware structure of μPMUs. • The islanding condition is determined locally at each DG bus by a simple detection procedure increases the grid resiliency in case of communication links interruptions. • No need to change or recalculate the threshold values with the change of the grid topology. • It is applicable in networks with inverter based and synchronous based DGs. • Discriminates islanding phenomena from other perturbations within 0.1 or 0.12 s with zero NDZ. This paper focuses on the use of micro-phasor measurement units (μPMUs) for the prompt detection of unplanned islanding conditions. The investigated method is based on the monitoring of voltage and current phasors at distributed generation (DG) buses equipped by μPMUs. The difference between two consecutive phasors (voltage phasors and current phasors) are monitored until a perturbation occurs. When a perturbation is detected, the first phasor, called pre-disturbance phasor, is kept fixed and the second one, called post-disturbance phasor, is continuously updated with each new sample arrival. The differences between the pre-disturbance and post-disturbance phasors are calculated and summed up for a predefined time window. When this exceeds a predefined threshold, the island condition of the related bus is detected. The presented procedure can distinguish the islanding condition from other perturbations, such as motor starting, faults, and capacitor switching. The performance of the proposed procedure, as well as its sensitivity to the system conditions and predefined values, are analyzed considering a 7-bus distribution system and the IEEE 33-bus test system, both with synchronous generators and inverter-based DGs. [ABSTRACT FROM AUTHOR]

In recent years, scientists have extensively focused on renewable energy resources such as wind power and solar units to reduce the consumption of fossil fuels as the main source of environmental pollutions. One of the main challenges for the production of wind and solar energies is that they often involve uncertainties due to the stochastic natures of wind speeds and solar radiation. Therefore, the existing uncertainties in the resources of wind and solar units must be considered in the planning procedure of distribution systems for having a reliable performance. To consider uncertainties in the output power of renewable energy resources, a new formulation is proposed to determine the optimal location and sizing of solar and wind units in the distribution system. To achieve this, Particle Swarm Optimization (PSO) algorithm as a robust technique is employed to find the best location and sizing of wind, solar and fuel cell units in the distribution system. The main objective of the present work is to minimize the Total Harmonic Distortion (THD), the total power losses, the total cost of DG units (including investments, replacement, operation and maintenance costs) and greenhouse gas emissions. Different types of loads such as linear and non-linear loads as well as load growth are also considered in the distribution system. To demonstrate the effectiveness of the proposed algorithm, 31-bus test system is considered as the case study. Our findings show that the use of renewable energy resources significantly reduces the greenhouse gas emissions in the mentioned system. Furthermore, the simulation results reveal that DG units must be added at some years to keep the voltage within its allowable limits. [ABSTRACT FROM AUTHOR]

In distribution networks, the lack of measurement data is usually thought to be an inevitable bottleneck of conventional grid operation and planning. Recently, the availability of smart meters in the distribution network has provided an opportunity to improve the network observability. In medium-voltage (MV) distribution networks, there is an increasing demand to use aggregated smart meter data for the state estimation, instead of adopting pseudo-measurements with a low level of accuracy. However, the performance of an estimator requires good knowledge of the available measurements, in terms of both expected values and associated uncertainties. Therefore, this paper intends to firstly pave a new way of utilizing smart meter data gathered from the low-voltage (LV) feeders in a concrete and reliable manner. For the purpose of state estimation in MV distribution networks, smart meter data is to be processed through three steps: phase identification, data aggregation and uncertainty evaluation. The feasibility of the proposed method is verified on the IEEE European LV Test Feeder with a set of real-world smart meter data. Afterwards, the influence of the aggregated smart meter data on the three-phase state estimation are investigated on the modified IEEE 13-node test system and IEEE 34-node test system. Simulation results show that the effect of aggregated smart meter data on the accuracy of state estimators is dependent on both the accuracy level of the aggregated data and the measurement configuration in the network. Furthermore, the use of aggregated smart meter data is shown to be able to provide improved state estimation. [ABSTRACT FROM AUTHOR]

Most distribution systems are operated in an unbalanced state; hence, neutral currents can be generated by unbalanced currents in three-phase four-wire distribution systems. This paper proposes a novel adaptive reclosing scheme that uses the neutral current in a distribution system with a battery energy storage system (BESS). The BESS, which operates as an uninterruptible power supply, is connected to the load side. In the proposed scheme, there are two circuit breakers (CBs) at the source and load sides. The wavelet transform of neutral current is performed using symlets 5 mother wavelet at level 2. The summation of the absolute values of level 2 detail coefficients is calculated, and the absolute value of the differentiation of this summation is proposed as a new index for detecting fault clearance. The CB at the source side is reclosed after detecting fault clearance using ADSum. Then, the CB at the load side is reclosed after the completion of a synchronism check. To verify the proposed scheme, the BESS is modeled using the ATP-ElectroMagnetic Transients Program. In addition, various simulations are conducted according to fault types and fault clearance times. Simulation results show that successful adaptive reclosing is possible in the distribution system with the BESS. [ABSTRACT FROM AUTHOR]

With the increasing penetration of distributed generations (DGs) in distribution systems, new challenges are introduced into voltage control of distribution systems, such as the frequent switching operations of traditional voltage control devices, resulted from rapid voltage fluctuations, and coordination between traditional voltage control devices and fast controllers such as inverters in DGs. In order to solve the challenges above, an event-trigger based two-stage architecture is presented, taking the characteristics of inverters and conventional devices, such as on-load tap-changers (OLTCs) and shunt capacitor banks (CBs), into account. An event-trigger mechanism is designed to make a fast response to large voltage deviations and reduce unnecessary switching operations of traditional devices, compared with periodic methods. The integration of inverter-based voltage control, in the proposed two-stage architecture, can provide a fast and continuous response to voltage deviation. Moreover, as reactive capacities in DGs, determined by inverters, are reserved in global voltage optimization, it can further reduce the switching operations of traditional devices in the following voltage control process. Simulations in a IEEE 33-bus distribution system show that the proposed architecture can ensure a higher voltage quality and reduce the number of switching operations of OLTCs and CBs by the event-trigger mechanism, the integration of inverter-based local voltage control, and the inverter’s reserved reactive power capacity in global voltage optimization. [ABSTRACT FROM AUTHOR]

This paper compares traditional local voltage control strategy with coordinated, optimization-based ones in low voltage (LV) distribution systems with photovoltaics and battery energy storage systems. Optimization-based strategies are formulated within a model predictive control (MPC) framework. Three strategies based on MPC are proposed and implemented, namely, centralized, decentralized and distributed MPC. The formulated strategies for voltage control are compared in a case study using a modified CIGRÉ European 3-area low-voltage network. Results indicate that decentralized MPC gives a better voltage profile in the network when compared to local voltage control strategy, since the latter inherently fails to maintain voltages of buses in the network not connected to photovoltaics or battery storage system within limits. Centralized MPC strategy is able to provide the optimal voltage profile across the network but utilizes 13 % higher reactive power from the control devices to achieve this when compared to decentralized MPC. The latter performs well as long as the reactive power reserves within an area is sufficient but faces drawbacks similar to that of local voltage control strategy when the reactive reserves are completely exhausted. Distributed MPC utilizes 1.3 % higher amount of reactive power reserves compared to centralized MPC in order to provide a network voltage profile similar to that of the latter while also yielding architectural advantages of decentralized MPC. [ABSTRACT FROM AUTHOR]

• Communicative protection schemes pose economic and security issues. • Existing communicative-less schemes focus on microgrid protection. • No comms-less schemes on overcurrent protection for self-healing systems. • Fault location estimates and relay load flows to predict relay settings. • Relay setting group selected locally by artificial neural network. Network reconfiguration has allowed supply restoration to disrupted areas after fault events. However, changes in network topology can alter the direction and magnitude of fault currents and jeopardize the coordination of overcurrent relays. Adaptive protection schemes using system-wide communications have been developed to solve this issue by performing dynamic relay recalibration. Unfortunately, system-wide communications are also associated with huge economic costs, data integrity issues, and limitations of infrastructures. Moreover, in less developed communities, such schemes are less applicable. Although various communication-less schemes have been proposed, they mainly focused on adapting overcurrent relay protection for different distributed generation penetrations and microgrid islanding statuses. Currently, no communications-less adaptive protection method has been proposed to address the miscoordination of protection relays caused by network reconfiguration for supply restoration. Thus, this paper presents a communication-less adaptive protection scheme to maintain relay coordination in a reconfigurable distribution network that performs supply restoration. The scheme deploys microcontroller units to predict the correct relay settings by monitoring load flows through the relays. The scheme is demonstrated on the IEEE 33-bus and 69-bus test distribution systems using two different relay placement strategies, non-directional and directional relays. The proposed scheme achieved up to 10.8 times lower disruptions than the existing system in N-1–1 contingency scenarios. Overall, the scheme provides a simple and low-cost alternative to improve the effectiveness of power system protection in a reconfigurable network. © 2017 Elsevier Inc. All rights reserved. [ABSTRACT FROM AUTHOR]

• Propose a three-stage resilient enhancement approach under hurricanes. • Coordinate MEGs with fault isolation and the forced cut-off of wind power. • Establish the step function of wind power cut-off. • Introduce auxiliary variables indicating faulted, energized, and outage zones. • Establish a stochastic model solved by the modified progressive hedging algorithm. Mobile emergency generators (MEGs) have been widely used to enhance the resilience of distribution systems. However, the traditional two-stage MEG dispatch strategies focus on only the prepositioning and reallocation before and after hurricanes, neglecting the resilient operation during hurricanes. Therefore, this paper proposes a novel three-stage MEG dispatch model to enhance the resilience of distribution systems. To improve the survivability of distribution systems during hurricanes, the fault isolation operations by remote-controlled switches (RCSs) and forced cut-off of wind power are coordinated with MEG dispatch, which is prepositioned as a preparedness measure before hurricanes. Based on the realization of fault scenarios during hurricanes, MEG reallocation and fault isolation by manual switches (MSs) are conducted to boost the restoration of the distribution system after hurricanes. Considering the uncertainties of wind power cut-off and line faults, the proposed method is incorporated into a stochastic dispatch model, which takes the conditional value-at-risk (CVaR) as an objective function to improve robustness in extreme cases. In addition, the computational burden with multiple scenarios is reduced by the modified progressive hedging algorithm (PHA). Finally, the proposed method is validated on a modified IEEE 33-bus distribution system. Simulation results show that the survivability and restoration of the distribution system can be enhanced by the proposed approach. [ABSTRACT FROM AUTHOR]

This paper proposes a new adaptive reclosing technique that considers the battery energy storage system (BESS) in a distribution system. The proposed technique focuses on operation of the BESS as an uninterruptible power supply (UPS). The algorithm detects the fault clearance using second-order differences of total harmonic distortion (THD) (SODT) of the current supplied by the BESS and allows the BESS to keep feeding to the healthy phase. A synchronism check is adopted between the utility and the BESS to minimize the transients at the moment of reclosing. To verify the proposed algorithm, the whole system and algorithm were modeled using ATP-EMTP. Various simulations are performed by varying the fault clearance time, fault types, fault resistances, and fault locations. The simulation results show that the BESS can be operated as a UPS and provide an improved reclosing scheme. [ABSTRACT FROM AUTHOR]

This paper presents the implementation of a Solid State Transformer (SST) model in OpenDSS. The goal is to develop a SST model that could be useful for assessing the impact that the replacement of the conventional iron-and-copper transformer with the SST can have on the distribution system performance. Test distribution systems of different characteristics and size have been simulated during different time periods. The simulations have been carried out assuming voltage-dependent loads and considering that power flow through either the HV/MV substation transformer or any of the MV/LV distribution transformers can be bidirectional. Simulation results prove that a positive impact should be expected on voltages at both MV and LV levels, but the efficiency of current SST designs should be improved. [ABSTRACT FROM AUTHOR]

The presence of power electronic-based wind turbines and photovoltaic systems in distribution networks has provided distribution companies an opportunity to implement voltage control through using the reactive power of these systems. In this paper, a decentralized method based on fuzzy logic is proposed to control the reactive power of distributed generations (DGs) regarding the technical constraints. The fuzzy system is optimized by gradient descent algorithm (GDA) and then implemented on various DG technologies including a photovoltaic (PV) system, permanent magnet synchronous generator (PMSG) wind turbine and also a doubly fed induction generator (DFIG) wind turbine. The system under study is tied to a real distribution network. Having simulated the system, the paper shows that the fuzzy system can appropriately determine the desired reactive power that should be produced by each DG based on the voltage variation of the bus at which the DG is connected. Furthermore, a centralized voltage control is also applied to the same network to verify the performance of the method proposed. The verification indicates that the method is capable of finding the near-optimal solution. A scenario in which an unwanted conflict appears in the DGs’ function is defined in detail and then a strategy is presented to resolve the situation. In addition to this, the coordination between the stator of the wind turbines and grid side converter (GSC) is examined. To investigate the robustness of the proposed method in different distribution networks, simulation results are also presented for IEEE 33-bus distribution test system. The numerical results show that the fuzzy system can effectively control the voltage of the DG connection bus. [ABSTRACT FROM AUTHOR]

The fault current contribution of inverter based DGs (IBDGs) may affect the operation of protective devices present in the system. Hence, it is necessary to consider the presence of IBDGs in short-circuit analysis of distribution system. A short-circuit analysis approach for unbalanced distribution system with IBDG, incorporating different voltage dependent control modes, is proposed in this paper. Comparison of the results obtained by the proposed method with those obtained by the time domain simulation studies carried out using PSCAD/EMTDC software, shows the accuracy of the proposed technique. [ABSTRACT FROM AUTHOR]

This paper aims at adopting the Particle Swarm Optimization (PSO) technique to find the near-optimal solutions for the capacitor allocation problem in distribution systems for the modified IEEE 16-bus distribution system connected to wind energy generation based on a cost function. The proper allocation and the optimized number of capacitors have led to adequate power losses reduction and voltage profile enhancement. Because of the wind power generation variations due to the nature of wind speed intermittency and the lack of reactive power compensation, the problem under study have been presented involving a nonlinear fitness function. In order to solve it, the corresponding mathematical tools have to be used. The formulated fitness cost function has consisted of four terms: cost of real power loss, capacitor installation cost, voltage constraint penalty, and capacitor constraint penalty. PSO technique has been used to obtain the near-optimum solution to the proposed problem. Simulation results demonstrate the efficiency of the proposed fitness cost function when applied to the system under study. Furthermore, the application of PSO to the modified IEEE 16-bus system has shown better results in terms of power losses cost and voltage profile enhancement compared to Genetic Algorithm (GA). In order to verify the successful adaptation of PSO toward attaining adequate near-optimal capacitor allocations in distribution systems, this metaheuristic technique has been employed to the large-scale IEEE 30-bus system. The proposed PSO technique has provided adequate results while modifying the objective function and constraints to include the power factor and transmission line capacities for normal and contingency (N-1) operating conditions. [ABSTRACT FROM AUTHOR]

With the participation of distributed energy resources (DERs) in inertia emulation, voltage control and primary frequency response, distinct angle and voltage dynamics are introduced in a conventional distribution network. These additional low-frequency dynamics emanating from a pre-dominantly resistive distribution network influence the mode properties of system oscillations uniquely. For better control and partitioning of active distribution network during emergency conditions coherent participation of DERs in local and inter-area modes need to be evaluated. In this work, fundamental factors affecting the bus coherency of distribution system are analyzed. It introduces a concept of coherency duality between pre-dominantly resistive and inductive distribution networks along with unique effect of source and control interactions by DERs. The work discovers pre-dominance of voltage based coherency criteria for active power flow control/islanding in resistive sub-networks and angle based criteria for inductive sub-networks, due to the reverse relation between state and power variables. Dynamic coherency changes inflicted by DER variabilities like different control and source interactions, increased penetration level, change in the spatial distribution of DERs, and dynamic loading are presented in the work. The proposition is tested for modified IEEE-39 bus systems with 33 bus 132/33/11/0.4 kV and 2182 bus 20/0.4 kV distribution networks in DigSILENT/PowerFactory. • In this work, the fundamental factors affecting the angle and voltage coherency criteria of active distribution system are defined for predominantly inductive and resistive networks which results duality in coherency. • The importance of coherency based network control and partitioning in active distribution network two scenarios are considered in the work. In first scenario, voltage coherency based emergency control of distribution system and in second scenario, cases are discussed. • On increasing the virtual inertia injections in a predominantly resistive network, few oscillatory modes tend to shift towards right half of s-plane, thus hampering small signal stability. • On increasing the penetration of DGUs in a predominantly resistive network, new low damping modes are generated hampering oscillatory stability. [ABSTRACT FROM AUTHOR]

• A prediction model for rainfall-caused outages in the distribution system. • The rainfall waterlogging model to quantify the ponding evolution in the distribution system. • The data processing framework integrating spatiotemporal data. • Multi-target random forest is proposed to predict the ground and overhead equipment. Improving the prediction accuracy of weather-related outages in the distribution system is crucial for disaster prevention and mitigation. Due to the vulnerability of the distribution system in rainfall, we propose a multi-target prediction model of the rainfall-caused outages of the distribution system based on the fusion of spatiotemporal attributes. In this article, the ground subdivision model based on element reconstruction is firstly proposed to establish a spatial grid. Then the rainfall waterlogging model considering seepage, drainage and confluence is established to provide a targeted reference for distribution system outage prediction. Then the multi-target random forest based on superposition features is proposed to deal with the meteorological data, geographic environment data, power grid data and waterlogging data. The model outputs the rainfall outage probability and visualization results of ground and overhead equipment branded with time and space labels. Finally, the model is tested on the instance data and compared with other models. [ABSTRACT FROM AUTHOR]

The present work presents an approach for optimal reconfiguration of electrical distribution systems (EDS) to minimize energy losses considering uncertainties in the load demand and in the wind based distributed generation (DG). The optimization algorithm applied to solve the reconfiguration problem is based on the bio-inspired metaheuristic Artificial Immune Systems (AIS). An interval power flow model is used to obtain an interval energy loss from the representation of the uncertainties. The interval loss is used to guide the AIS algorithm through the search space. Network and operational constraints as the radiality and connectivity of the network as well as different load levels are considered. Well-known test systems are used to assess the impact of the uncertainties representation in the reconfiguration problem. [ABSTRACT FROM AUTHOR]

This paper presents a new method to construct the low-order equivalent model for distribution system, which is very essential in large power system simulations. The distribution system connected to a substation is seen from the transmission power system as a nonlinear input–output system. In order to cope with the computation complexity, nonlinear model reduction technique based on covariance matrix is employed to obtain a new low-order dynamic system, which can closely represent the dynamic characteristics of the detailed system. The absence of drastic simplifications, direct consideration of the distribution network and the proper preservation of the input–output behavior of the detailed distribution system allow the equivalent model to attain good accuracy. Simulations and analysis are carried out on WSCC system to verify the validity of the proposed method. The simulation results show that this new method could attain high accuracy of simulation of distribution system under various operating conditions, thus improving the precision of power system stability analysis. [ABSTRACT FROM AUTHOR]

This paper proposes a socially acceptable framework for the realization of efficient voltage management by cooperation among consumers in electric distribution systems where the frequent voltage variation problem is caused by large amounts of photovoltaic (PV) generation systems. In the proposed framework, the profit maximization problem of the coalition under the constraints to suppress the voltage variations caused by PVs is formulated as a linear programming problem, and the payoff allocation among consumers is provided using a solution concept from cooperative game theory called the core. The proposed method efficiently computes the payoff allocation in the nonempty core to accomplish the cooperative voltage management system. Unlike most related works, this paper employs cooperative game theory to explicitly address incentives for cooperation with the consumers. Although the computation for finding an allocation in the core generally requires a significant amount of time, this paper demonstrates that the allocation can be efficiently calculated by using the dual optimal solution of a formulated linear programming problem. The proposed method is validated by computational experiments on a large-scale distribution system model in which consumers with demand resources (including PVs and controllable loads) are connected. • The proposed method provides an allocation of the payoff belonging to the core. • Under the proposed framework, the cooperative actions by all consumers are stable. • The proposed core allocation requires a low computational burden. [ABSTRACT FROM AUTHOR]

Reconfiguration is an important way to increase the power distribution systems efficiency. The problem of reconfiguration is a complicated combinatorial optimization problem with discrete decision variables. To solve such problem, a powerful optimization technique is required. This paper presents a discrete Teaching–Learning-Based Optimization (DTLBO) algorithm for solving the distribution system reconfiguration (DSR) problem. The objectives are power loss minimization and voltage profile improvement in presence of distributed generation (DG). The proposed method is applied to 33-bus and 69-bus test systems and a part of the distribution network of Ahvaz, a city in the south of Iran. A comparison between the proposed algorithm and other existing methods shows the effectiveness and capability of the proposed method to reach the global optimum and rapid convergence to the optimal solution. [ABSTRACT FROM AUTHOR]

This paper presents a new and comprehensive Objective Function (OF) for capacitor placement in distribution networks. In this study, distribution network management’s viewpoint toward identifying comprehensive OF to maximize the benefit of a distribution company is considered. In addition to considering active power loss cost and capacitor cost, two other important terms, i.e. cost of buying reactive power and voltage drop penalty for maximizing the benefit of distribution companies are considered in the OF. All actual conditions including time varying nature of load, annual load growth, time varying price of active and reactive power, and switchable and fixed capacitor are taken into account based on the reality. The profit derived from the proposed OF is compared with two other common OFs, and it is shown that the benefit achieved from the proposed OF is more than the two other OFs. The proposed OF is validated and tested on radial distribution systems with differing topologies and varying sizes and complexities. [ABSTRACT FROM AUTHOR]

This paper presents an algorithm for deciding preferences in maintenance activities for feeder sections of distribution systems. A component importance measure, known as diagnostic importance factor (DIF), has been used for this purpose. A methodology has been developed to compute a newly framed weighted cumulative diagnostic importance factor (WCDIF) for each feeder section which represents quantitatively relative significance for prioritization of maintenance activities. The developed methodology includes the effect of distributed generations (DG) and loads. It has been implemented on two sample distribution systems and ranking lists of feeder sections for maintenance activities have been obtained. [ABSTRACT FROM AUTHOR]

Distributed generation has been playing a vital role in dealing with issues related to distribution systems. This paper presents an approach which provides the distribution system operator with a set of solutions for DG placement to optimize reliability and total cost of power consumed by the distribution system. Optimal location of a Distributed Generator is evaluated based on the performance indices derived for reliability index and total cost of power consumed by the system. The proposed approach is applied to a 15-bus radial distribution system and a 18-bus radial distribution system and the results are analyzed. [ABSTRACT FROM AUTHOR]