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However, curtailment compensation costs eventually surpass upgrade costs, making network upgrades a practical option once the HC level reaches 118%, 106%, and 97% for rural, suburban, and urban regions, respectively. Keywords: distribution networks; renewable energy sources EN distribution networks renewable energy sources 3763 3764 2 09/05/23 20230901 NES 230901 Decarbonization policy leads to an increasing trend of integration of renewable energy sources (RESs) in distribution grids. [Extracted from the article]

Increasing the penetration level of distributed generation (DG) units requires overcoming the technical challenges associated with their integration into the distribution systems, especially protection problems. Change in the current profile of the distribution system due to the presence of DG units disrupts the operation of the conventional fuse saving coordination (FSC) scheme. The first objective of this paper is to provide an overview of the state‐of‐the‐art of FSC schemes in distribution systems with distributed generators that has not been systematically presented yet. In addition to comparing the features of reliability, cost, speed, implementation, calculation burden, and requirements, the impact of presence of distributed generations on the performance of the conventional FSC scheme is investigated in details. The second objective of this paper is to propose an FSC restoration scheme for minimizing the challenges of previous works. Using a quasi‐voltage current term, the proposed scheme modifies the adjustable time coefficient of the recloser in two ways of pro and plus. The former scheme provides an approximate FSC with a simple setting while the latter scheme provides complete coordination at the expense of a more complex setting. No need for voltage measurement makes its implementation practical in available distribution systems. The effective performance of the proposed FSC scheme is verified through extensive simulation studies in the ETAP environment. [ABSTRACT FROM AUTHOR]

A power line carrier (PLC) communication characteristics‐based method is proposed for single‐phase‐to‐ground fault location in neutral isolated medium voltage meshed distribution networks in this paper. The carrier signals with a time‐varying frequency and constant amplitude are processed by a set of PLC transmitters and receivers, whose placement is optimized by regarding the power network as an undirected graph. Two signal encoding and decoding algorithms for the PLC terminals are proposed to avoid using expensive timing systems between the terminals. The fault location technique is implemented by comparing the cosine similarity of amplitude attenuation and phase offset between the fault and a feature library. The node corresponding to the maximum cosine similarity of the characteristics between the present fault and the library is selected as the location of the current fault. Only one set of low‐cost PLC communication terminals and the widely available power lines are needed in the fault location system, making this approach highly practical. Numerical simulations using MATLAB/Simulink have been performed to verify the technique's feasibility. The results show that the method can accurately locate faults in neutral isolated medium voltage meshed distribution networks. Besides, the presented approach achieves a high level of accuracy in estimating transition resistance values. [ABSTRACT FROM AUTHOR]

With the increasing integration of distributed energy resources (DERs) into distribution systems, the optimization of system operation has become complex, facing challenges such as inadequate consideration of market participants' benefits, poor computational efficiency, and data privacy concerns. This paper introduces the concept of a virtual power plant (VPP) as a solution for energy integration and management. To strike a balance between operational safety and the interests of market participants, a dual‐layer model is proposed. This model considers the benefits of both Distribution System Operators (DSO) and VPP, while also enhancing the consideration of distribution network constraints. The DSO considers AC optimal power flow and utilizes penalty functions to ensure network security in case of violations. To enhance computational efficiency and privacy, the paper presents the parameter‐sharing twin delayed deep deterministic policy gradient approach. This approach allows multiple intelligent agents to share a neural network model, effectively reducing the computational load. During the training process, only essential data is exchanged among the agents, ensuring the privacy of sensitive information. The effectiveness of the proposed model and the algorithm is validated through a case study on an IEEE 33‐node system. [ABSTRACT FROM AUTHOR]

This paper emphasizes the integration of wind and photovoltaic (PV) generation with battery energy storage systems (BESS) in distribution networks (DNs) to enhance grid sustainability, reliability, and flexibility. A novel multi‐objective optimization framework is introduced in this study to minimize energy supply costs, emissions, and energy losses while improving voltage deviation (VD) and voltage stability index (VSI). The proposed framework comprising normal boundary intersection (NBI) and decomposition‐based evolutionary algorithms (DBEA) determines the optimal siting and sizing of renewable‐based distributed resources, considering load demand variations and the intermittency of wind and solar outputs. The comparative analysis establishes that the proposed strategy performs better than many contemporary algorithms, specifically when all the objective functions are optimized simultaneously. The validation of the proposed framework was carried out on the standard IEEE‐33 bus test network, which demonstrates significant percentage savings in energy supply costs (49.6%), emission rate (62.2%), and energy loss (92.3%), along with enormous improvements in VSI (91.9%) and VD (99.8953%). The obtained results categorically underline the efficiency, reliability, and robustness of the proposed approach when employed on any complex distribution network comprising multiple renewable energy sources and battery storage systems. [ABSTRACT FROM AUTHOR]

Earth faults is a challenging fault type to locate in resonant grounded networks due to their naturally low fault current, and the problem increases with an increased fault impedance. This paper describes the detailed implementation and laboratory testing of a method for detection, location and clearing of earth faults with very small fault currents. The method consists of two indicators used in the fault detection stage, where their simultaneous operation ensures selective fault detection and faulty feeder selection. One of these indicators also enables continuous fault indication throughout a sectionalizing process. The laboratory tests demonstrate that both indicators function as intended, and it is the current sensors which ultimately limit the attainable sensitivity. Faults up to 15 kΩ were detected successfully in the laboratory network based on phase current measurements, while the sectionalizing indicator showed much higher sensitivity and functioned as intended in a 50 kΩ fault. Measurements from one field test in a 22 kV network corroborate the laboratory results and demonstrate the expected earth fault indicator response. [ABSTRACT FROM AUTHOR]

There exist problems of hard coordination and threshold setting as well as low sensitivity in overcurrent relay due to the bidirectional and small fault current when distributed generators are integrated into the distribution network. This paper introduces ferrite rings (FRs) to act as boundaries of distribution feeders, and a peak time of voltage traveling wave‐based protection is proposed. The characteristics of FRs are analyzed and their feasibility as line boundary is validated. The fault characteristics of internal and external faults are analyzed when FRs are installed at both ends of the protected feeder. The results show that the peak time of the voltage travelling wave of the internal fault is far smaller than that of the external faults. According to the difference, the fault detection method and the protection scheme are proposed. Simulations in PSCAD and experiment validate that the proposed protection principle can reliably distinguish between internal and external faults. Besides, the proposed protection scheme has higher sensitivity compared to ROCOV‐based protection. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the fault current contributions of small‐scale single‐phase photovoltaic inverters under grid‐connected operation and their potential impact on the protection of distribution systems. To conduct this analysis, an autotransformer‐based voltage dip generator is proposed as a means to test the photovoltaic inverters' contribution to short‐circuit currents. Laboratory tests are then performed to obtain the short‐circuit current contribution of eight single‐phase photovoltaic inverters. Using the short‐circuit current data obtained, a behaviour model is developed and simulated on Matlab‐Simulink. The model is then applied to a real distribution system and case studies are conducted to simulate the potential impacts on the protection system. Results indicate that while the massive penetration of small‐scale single‐phase photovoltaic inverters can alter the protection system's operating time, the impacts are not significant. Only in very specific scenarios, such as events related to high impedance faults, some impact can be observed. In these situations, the presence of photovoltaic inverters further complicates the already difficult task of identifying high impedance faults through conventional overcurrent protections. This study provides valuable insights into the integration of photovoltaic inverters into distribution systems, and can aid in the development of effective protection measures for future grid designs. [ABSTRACT FROM AUTHOR]

The upcoming network investment decisions and regulatory framework adopted by distribution system operators (DSOs) are most likely to be impacted by the integration of fluctuating distributed generation. The economical hosting capacity (HC) improvement method is investigated in this paper as a trade‐off between curtailment and upgrade using a Monte Carlo simulation procedure. The associated costs of both methods are vital indicators for network operators that are trying to maximize the HC and minimize cost. In addition, the breakeven point where curtailment and upgrade costs intersect is the decisive point at which network upgrade becomes sensible as marginal curtailment cost exceeds upgrade cost. A shift in global climate conditions can impact the photovoltaic (PV) levels that motivate network operators to investigate PV penetration, especially in colder climate regions. Thus, the primary objective of this paper is to investigate the shift of the breakeven point to guide DSOs to either adopt PV curtailment as a temporary measure or grid upgrade as a risk aversion strategy considering Finnish climate and load patterns. The real‐time load and PV generation data are utilized for the simulations to consider the dynamic performance indication of three Finnish distribution networks. Curtailment remains a low‐cost option to obtain a percentage HC rise of 13%, 7%, and 8% for rural, suburban, and urban regions, respectively, beyond which curtailment compensation cost surpasses upgrade cost. In essence, PV curtailment serves as an immediate and least‐cost solution to relieve network violations and defer network investment until the HC level (118%, 106%, 97%) making the upgrade a practical option afterwards. [ABSTRACT FROM AUTHOR]

Leveraging distributed resources to enhance distribution network (DN) resilience is an effective measure in response to natural disasters. However, the willingness and economy of distributed resources are typically ignored. To address this issue, this paper proposes an emergent trading framework that uses parking lots (PLs) as resources to provide power support to critical loads (CLs) in a blackout due to typhoons. In this trading framework, an evolutionary Stackelberg game‐based trading model is established to consider maximizing all stakeholders' economic benefits, considering possible resources isolation under typical fault scenarios caused by typhoons, and a benefit allocation mechanism is proposed for all stakeholders to motivate all stakeholders to participate in the trading. This framework allows that critical loads could reduce their load loss, parking lots could receive adequate compensation to stimulate them to participate in the trading, and distribution utility could ensure its economic benefits. Furthermore, an iterative evolutionary‐Stackelberg solution set‐up is applied to obtain the equilibria of the proposed framework. Simulation results on the modified IEEE 69‐bus test system and IEEE 123‐bus test system reveal the validity of the proposed method. [ABSTRACT FROM AUTHOR]

The ongoing electrification of road transportation sector, which is expected to continue to strongly increase over the next years, will result in the connection of a significant number of electric vehicle (EV) chargers in LV and MV distribution networks, particularly in residential applications with on‐board ("slow") EV chargers. In order to evaluate loading limits of existing distribution networks for the maximum number of EV chargers that can be safely connected (commonly denoted as a network EV "hosting capacity", HC), this paper introduces a general approach to determine one commonly used network design parameter (after‐diversity maximum demand, ADMD) and one new parameter (maximum daily energy demand, MDED), which are both obtained from the load profiles of maximum per‐hour demands for uncontrolled residential EV charging. The presented approach uses actual EV charging data from the UK as the inputs in Monte Carlo simulations to generate daily EV charging profiles for arbitrary numbers of EVs, enabling to identify related ADMD, MDED and per‐hour maximum demand values, as well as their seasonal variations. The assessed ADMD, MDED and hourly maximum EV charging demands for uncontrolled EV charging are then combined with available UK residential daily load profiles before the EVs are connected ("pre‐EV demands"), where their combined coincidental and noncoincidental maximum demands are evaluated against the static thermal rating (STR) and dynamic thermal rating (DTR) loading limits of network components (transformers and overhead lines), taking into account relevant weather/ambient conditions. This is denoted as a network HC for uncontrolled EV charging. Finally, evaluating the resulting per‐hour maximum demand values against the STR and DTR loading limits and MDED values allows to select one particular scheduling method for controlled EV charging, which gives the absolute maximum number of EVs that can be safely connected in the considered network, that is, maximum network HC for fully controlled EV charging. The presented approach is illustrated on the example of the IEEE 33‐bus test network (modelled using typical UK network components), for the pre‐EV residential demands taken from the recordings at a UK MV substation, and for ambient data taken from a UK Met Office weather station. Obtained results allow to evaluate the range of network EV HC values for uncontrolled and controlled EV charging, that is, lower and upper HC limits, which can be correlated with the commonly used allocations of the firm and non‐firm network HC, respectively. [ABSTRACT FROM AUTHOR]

The occurrence of natural disasters has led to an alarming increase in power interruptions, with severe impacts. Compounding this problem is the uncertain nature of data, which presents significant challenges in enhancing the resiliency of power distribution systems following such events. To tackle these issues, this paper introduces a robust optimization approach for improving the resiliency of power distribution systems. The approach encompasses crew teams for switching actions as part of the restoration process, along with demand response programs and mobile generators (MGs). By simultaneously leveraging these elements and considering the uncertainty associated with electrical load and electrical price, the resiliency of the system is enhanced. The objective function is tri‐level, comprising minimum, maximum, and minimum functions. At the first level, the approach minimizes the cost of commitment of combined heat and power plants (CHPs) by taking into account the location of MGs and the reconfiguration structure in power distribution systems. The second level aims to identify the worst‐case scenario for the uncertainty variables. Finally, the third level focuses on minimizing the total operation cost under the worst‐case scenario using demand response programs. The proposed algorithm is implemented on an IEEE 33‐bus test distribution system, with four different cases investigated. [ABSTRACT FROM AUTHOR]

This paper proposes three‐phase steady‐state models for distributed generators (DGs) with different negative control strategies. An augmented rectangular load flow method is used for three‐phase distribution systems. For two types of DGs with power electronic devices: photovoltaic power generators and doubly fed induction generators, the nodal voltage equations and output power equations are derived. Moreover, under unbalanced conditions, the strategies for mitigating the effects caused by negative sequence components are formulated as functions of the nodal voltage and the injected current. Furthermore, the models are incorporated into an augmented rectangular load flow method with nodal voltage and injected current as state variables in three‐phase systems. Case studies are conducted to verify the correctness and accuracy of the proposed models by comparing the results obtained from MATLAB and PSCAD. [ABSTRACT FROM AUTHOR]

Considering the importance of the renewable energy sector in the distribution systems, energy operation, and management which are connected to the distribution network (DN) in the form of multiple microgrids (MMGs) is crucial in reducing cost and pollution. Hence, this paper aims to propose optimal energy management for MMGs in the DN. Different objective functions have been taken into account in this optimization, including network cost, pollution reduction, and distribution network power losses. To design the multi‐objective optimization problem, a fuzzy method has been adopted for simultaneous multi‐objective calculations. Furthermore, the effect of the placement of distributed generations (DGs) and microgrids (MGs) is considered to reduce the distribution network power losses. Information gap decision theory (IGDT) has formulated uncertainties about renewable sources and consumers. To solve this optimization problem, a new method of the modified Harris Hawk optimization (MHHO) algorithm has been implemented, compared with the original HHO and genetic algorithm (GA). Finally, the proposed method has been analysed under the IEEE 33‐bus distribution network for a 24‐hour time horizon, including three MGs considering different renewable energy sources (RESs). The simulation results have demonstrated the high performance of the allocated network with the MHHO algorithm compared to the other scenarios. [ABSTRACT FROM AUTHOR]

Distributed energy resources (DERs) provide flexible load restoration strategies, which can effectively enhance the resilience of active distribution systems (ADSs). Whereas, the widespread DERs in ADSs complicates the supply‐demand relationship and make the system resilience difficult to access. Therefore, this paper proposes a simulation‐based resilience assessment algorithm of ADSs considering the microgrid formation based on grid‐edge DERs. Microgrid formation is used to depict the resilience gain of grid‐edge DERs on ADSs. Specifically, a resilience assessment framework for ADSs is firstly proposed, where the uncertainty of component state and supply‐demand is modelled based on probability statistics. Then the mixed integer linear programming is used to search for optimal load restoration strategies with microgrid formation. On this basis, a set of resilience indices are defined to quantitatively analyse the resilience of ADSs, and a resilience assessment algorithm with uncertainty scenario generation is proposed to obtain these indices. Furthermore, extensive numerical results based on a modified IEEE 123‐bus feeder validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The efficient, reliable, and resilient supply of electricity has become essential for social and economic well‐being of the modern society. However, more frequent occurrence of extreme weather events has exposed inequity in the planning and operation practices of power distribution systems, evidenced in higher vulnerability and longer power interruptions for some parts of the grid as compared to others. This paper proposes an equity‐aware power distribution system restoration model in an effort to ensure a more equitable yet resilient power distribution operation after outages. To this end, the proposed equity‐aware distribution system restoration model balances the efficiency of the restoration operation and the equitable allocation of distributed energy resources among affected customers after an outage, while prioritizing the critical infrastructure (e.g. hospitals). The results demonstrate the effectiveness of the proposed framework to ensure a more equitable restoration process as measured by the proposed fairness and restoration performance indices. [ABSTRACT FROM AUTHOR]

With the increasing rate of population in big cities around the world, the tendency to build new buildings in the suburb of main cities or to build large apartments in the main cities has been highlighted. In this regard, building residential complexes has seen a dramatic increase in these areas as it makes it possible to build a large number of residential units within a reasonable space. Although these complexes have brought numerous benefits, they are some challenges regarding their construction processes. One main concern associated with these complexes is how to optimally install energy components such as transformers, combined heat and power (CHP) units, boilers etc., in the shared area of apartments in the residential complex. To address this issue, this paper models the energy system of a residential complex as an energy hub and proposes a novel framework to obtain the optimal planning of such an energy hub. In order to address the conflicting desires of the residential complex's builders and the future residents of the residential units, a multi‐objective (MO) optimization problem has been considered in the proposed method that simultaneously optimizes the investment costs, operation costs, and the reliability of energy supply. In this regard, a Multi‐objective Particle Swarm Optimization (MOPSO) algorithm combined with classical linear programming (LP) optimization method has been proposed to solve the MO optimization problem. In order to demonstrate the effectiveness of the proposed method, a case study including a residential complex with 300 residential units is considered, and the proposed method is implemented in this case study. The numerical results show that the proposed framework can appropriately optimize investment costs, operation costs, and the reliability index simultaneously, and the obtained Pareto frontier gives the investors the freedom to opt for any point from this surface. [ABSTRACT FROM AUTHOR]

This paper extends the study of a zero‐sequence impedance‐based fault location method (FLM) designed for medium voltage (MV) distribution feeders whose principle has been presented in a previous work Bach et al. This method is able to locate any type of earth fault with any type of neutral grounding inside a convex set of nodes forming the solution area. The total length of the lines inside this area is statistically computable a priori and depends only on the number and location of additional voltage measurements deployed on some remote end secondary substations. To be efficiently applied to the most challenging rural feeders presenting a lot of ramifications, simulations have shown a need for synchronized measurements, such as the ones obtained using phasor measurement units. Besides, this paper addresses the coupling potential of this method with more traditional ones such as Takagi‐based FLMs to enhance the performances of both, solving the multiple estimation problem while potentially locating the fault within one node. Finally, an extensive sensitivity analysis has been carried out, showing a good robustness with respect to impedance estimation errors or fault impedance values while showing the need for synchronization, especially on some remote measurement locations. [ABSTRACT FROM AUTHOR]

In the case of a single‐phase grounding fault in the distribution network, the transient zero‐sequence current (TZSC) tends to be non‐linear and non‐stationary. The faulty line selection is relatively difficult. The distributed power access further brings many difficulties to faulty line selection. This work proposes a novel method of faulty line selection using spatial image generation and deep learning. At first, the optimal smooth denoising model can be used to smooth the zero‐sequence current for each line, reducing the external environment electromagnetic interference. Then, the treated zero‐sequence current is mapped into the colorful floral hoop image by using symmetrized Hilbert transform pattern (SHTP). The SHTP transforms the one‐dimensional time domain signal into the two‐dimensional space domain image, enhancing invisible information and obtaining more abundant feature information. Finally, the deep features of the SHTP floral hoop image are extracted by means of deep learning method. In order to improve the faulty line selection universality, a mixed sample library containing three different topologies is established, including the 10 kV radial distribution network, IEEE‐13 node model, IEEE‐34 node model and StarSim platform. The comparisons show that the proposed method has a more noticeable visualization effect on fault features, higher classification precision rate, and better anti‐noise performance. [ABSTRACT FROM AUTHOR]

This paper presents a multi‐objective restoration scheme for improving the resilience of integrated electricity and natural gas distribution systems against extreme weather events. The coupling constraints of electricity and gas networks are tackled properly using a linearized optimal power flow (OPF). Distributed generators, power‐to‐gas facility, rescheduling of generation/storage units, and microgrid formation are employed as operational resources/measures for restoring the integrated energy system after the event landfall. An adaptable directed multi‐commodity flow‐based microgrid formation is utilized, that is, the network configuration is dynamically changed in accordance with time‐variant load priority weights. The proposed method was successfully examined on an integrated electricity and natural gas distribution system comprised of the modified IEEE 33‐bus distribution network and a 14‐node natural gas distribution network. Numerical results showed that using microgrid formation increased the supplied critical load of integrated electricity and natural gas distribution system by about 16%. Moreover, due to making benefit of the power‐to‐gas unit, the supplied critical load increased by about 12.3%. respectively. While utilizing energy storage systems along with the power‐to‐gas unit facilitated the exchange of energy between the power distribution network and natural gas distribution network regarding time‐variant load priority weights, the supplied critical load increased by about 13%. [ABSTRACT FROM AUTHOR]

Microgrids are a new concept resulting from decentralized power sources, which have changed energy utility grid topography. As this promising field is penetrated, control must be streamlined immediately. This paper analyses key control mechanisms in energy utility networks, including centralized, decentralized, and distributed setups. The focus is on the auxiliary category as the various benefits and drawbacks of each approach is investigated. Information interchange architectures that enable multiple control techniques in the auxiliary control domain are examined using distributed energy networks. The research emphasizes the necessity of auxiliary control in ensuring reliable and effective utility infrastructure operation but notes the lack of a comprehensive scholarly reference. Additionally, the study explores key concerns in utility grids' auxiliary control mechanisms, emphasizing information‐sharing system limits. The goal is to demonstrate the importance of auxiliary control and evaluate its challenges, such as latency, which require new solutions for a seamless transition to a sustainable energy future through rigorous academic assessment. At the auxiliary level, complex, decentralized regulatory mechanisms are recommended to handle transmission channel bandwidth and operational overhead in energy utility networks. These innovative measures have the potential to transform the fundamental structure of our energy landscape, heralding in unprecedented efficiency and sustainability. [ABSTRACT FROM AUTHOR]

Nowadays, due to network expansions, system operators are dealing with natural events including system failures. Evaluating the system readiness to maintain the network interconnections during severe faults are known as an important challenge of today's distribution networks. To do this, this paper presents an online non‐model‐based scheme of evaluating the system resiliency and supplying critical loads within severe natural conditions. In this case, by developing system resiliency as multi‐metric decision making problem and proposing the Choquet integral and graph theoretic methodology, the system resiliency is evaluated. The proposed resiliency scheme is an online non‐model‐based approach can be used for all distribution system configurations with the potential of natural event failures. In this case, by proposing online resiliency criteria based on the system critical loads and branches and developing the proposed criteria on Choquet integral scheme in the form of optimization procedure, the system resiliency is evaluated. The validity of the proposed approach is carried out on two different systems including the IEEE 123‐bus test system and the Consortium for Electric Reliability Technology Solutions (CERTS) microgrid. Simulation results present effectiveness of the proposed scheme to provide proper protective switching strategy and design the system resiliency criteria for future distribution systems. [ABSTRACT FROM AUTHOR]

The structure complexity and the extended geographical area are among the factors that create challenges in accurate fault location and detection in distribution networks. The single‐phase to ground (SPG) faults are considered as most frequent reasons for distribution network interruption, which can threaten the network's reliability. Signal processing methods are usually used as common approaches to distinguish and locate faults in distribution networks. This paper proposes a novel scenario to select optimal wavelet packet transform (WPT) coefficients for SPG fault location and a method based on superimposed voltage energy to distinguish the faulty phase according to these coefficients. Furthermore, employing the energies of the superimposed voltages helps to minimize the effects of high resistance faults (HRFs) and load encroachment on the efficiency of the faulty phase detection part. Comparing the obtained results with other scenarios demonstrates the considerable efficiency of the proposed scenario. Finally, with the help of general regression neural networks (GRNN) as machine‐learning tools, a new algorithm is derived for detecting and locating the SPG fault and capacitor bank switching overvoltage (COV). Simulation results are implemented on the IEEE 34‐bus standard distribution network, demonstrating the efficiency and superiority of the suggested method. [ABSTRACT FROM AUTHOR]

An explosion accident in an enclosed cable trench caused by the discharge of 10 kV three‐phase cable joints is discussed. Combined with the disassembly analysis, the fault recording data analysis, and the validation of experiment, the evolution of the cable joint fault is deduced and discussed. The results show that the trigger of the cable joint fault is the creepage discharge at the cross‐linked polyethylene–silicon rubber insulation interface. This results in the partial breakdown and the grounding failure of three‐phase cable joints. Under the long‐term floating potential and current thermal effect, the insulations are gradually ablated and decomposed into a large amount of combustible gas. Finally, the accumulated combustible gas is ignited by the arc caused by a three‐phase short circuit at the moment of the reclosing operation. The analytical method and conclusions proposed in this paper can provide suggestions and guidance to prevent analogous distribution network cable joint fault accidents. [ABSTRACT FROM AUTHOR]

This paper presents the optimal scheduling of active distribution network (ADN) with linear and non‐linear loads in the presence of an integrated unit of electric spring and electric vehicle parking lot (IUEE). The proposed scheme is formulated in the form of three‐objective optimization, which minimizes the expected operating cost of the ADN, voltage deviation function (VDF), and the total harmonic distortion (THD) of the voltage in separate objective functions. Constraints include harmonic power flow (HPA) equations, operation and power quality limits, and operation model of the IUEE. This scheme has uncertainties of load, energy price, and energy demand of EVs, which are modelled here using stochastic programming. Next, the sum of the weighted functions method as a subset of the Pareto optimization technique is adopted to extract the integrated single‐objective problem. Then, Sine‐Cosine Combined Algorithm (SCA) and Gray Wolf Optimization (GWO) are used to achieve an optimal solution. In the end, by examining the numerical results obtained from the implementation of the proposed scheme on a 69‐bus ADN, the capability of the design in enhancing the economic situation, operation, and power quality of the ADN compared to network power flow studies obtained by optimal scheduling of the IUEE is confirmed. [ABSTRACT FROM AUTHOR]

The access of large‐scale distributed generation (DG) easily leads to energy imbalance in distribution network. To deal with this issue, this paper proposes an energy optimal schedule method for distribution network considering the participation of source‐load‐storage aggregation groups (SAGs). Firstly, the system model consisting of distribution network layer and SAGs layer is established, and the schedule objectives and constraints of each layer are also given. Secondly, considering the fluctuation on the load side, a forecasting method based on Adaboost integrated convolutional neural networks and bidirectional long‐short term memory is proposed. Then, the improved sparrow search algorithm (ISSA) is proposed by using the tent map and Levy flight on the original sparrow search algorithm. At the same time, by introducing Pareto dominance relation and adaptive grid algorithm, the multi‐objective sparrow search algorithm (MOSSA) is derived. After that, a two‐layer optimization framework (ISSA–MOSSA) is proposed to solve the studied system. The simulation results verify the accuracy of the proposed load forecasting model, the superiority of ISSA as well as MOSSA, and the effectiveness of ISSA–MOSSA in solving the energy optimal schedule problem of the distribution system with the access of DG. [ABSTRACT FROM AUTHOR]

The Volt/Var optimization (VVO) problem is used for scheduling the voltage regulation and reactive power compensation equipment in distribution networks to minimize power loss and voltage violation. In order to solve the VVO problem for a forthcoming time horizon, it is necessary to predict some parameters such as load demand and renewable energy production. The prediction of these parameters is always accompanied by uncertainty that robust optimization can be used to solve this concern. This paper presents a scenario‐based robust Volt/Var optimization (RVO) method that significantly reduces the number of scenarios required for the worst‐case approach. Solving the VVO problem with the worst‐case scenarios reduces the computational burden and maintains the voltage security of the distribution network against the severe events. The proposed RVO is formulated based on a mixed‐integer second‐order cone programming (MISOCP) model in which Volt/Var control (VVC) equipment is scheduled over a two‐stage strategy. The proposed method is validated using modified 33‐bus and 69‐bus IEEE test systems. The results demonstrate that the proposed RVO method maintains the network's voltage profile within the acceptable range against uncertainties. [ABSTRACT FROM AUTHOR]

Optimal power flow (OPF) plays an important role in the secure and economical operation of the distribution network. This paper proposes a novel generalized linear‐constrained optimal power flow (GLOPF) model for both radial and mesh distribution networks, which iteratively approaches the optimal solution to the original OPF problem. The first‐order Taylor series approximation method is applied to linearize the non‐linear and non‐convex power flow constraints for a given Taylor expansion point (TEP). In addition, the objective function of the GLOPF model is only added with an easy‐compute second‐order penalty on state variables, which is at least positive semi‐definite and guarantees the convexity of the quadratic optimization. Then a TEP‐based iterative (TEP‐I) method is proposed in the GLOPF model to construct a series of linear‐constrained convex quadratic optimizations, which avoids the complex calculation of quasi‐Hessian or Hessian matrices in traditional sequential programming methods. The converged solution to the GLOPF model is proved to satisfy the Karush–Kuhn–Tucker conditions of the original OPF problem. Furthermore, the GLOPF model at first and second iterations can be implemented as the 'cold‐start' and 'warm‐start' LOPF models, respectively. Case studies verify the super‐linear convergence and high accuracy of the proposed GLOPF model. [ABSTRACT FROM AUTHOR]

A transformer‐less unified power flow controller (UPFC) is a power electronic device consisting of series and shunt voltage source converters (VSCs) that are not connected to a common DC bus. It can control power flow in medium voltage (MV) distribution networks without the need for interfacing transformers. Hence there is a significant reduction in size and cost compared to a conventional UPFC. This paper investigates the operating range of a transformer‐less UPFC in an MV distribution network and the required power ratings of the series and shunt converters. The results showed that a transformer‐less UPFC is able to provide active power control using partially rated converters. However, its ability to control reactive power is limited by the current ratings of the converters. The analysis was verified using software simulation and hardware experiment. [ABSTRACT FROM AUTHOR]

Single phase line‐broken (SPLB) fault is one kind of high impedance fault (HIF). When a SPLB fault occurs, there are four scenarios: SPLB fault with neither side conductors grounded (SPLB‐NSCG), with source side conductor grounded only (SPLB‐SSCG), with load side conductor grounded only (SPLB‐LSCG), with both side conductors grounded (SPLB‐BSCG). Traditional HIF detection methods using current or voltage characteristics have low sensitivity to SPLB fault. In this paper, voltage characteristics are analysed firstly in the cases of the first three scenarios of SPLB fault, respectively. Theoretical analysis finds that the voltage at both the sides of the disconnection point is significantly different. A high sensitive SPLB fault detection method based on differential voltage is proposed for radial distribution network with different data synchronization ability. Finally, SPLB fault location methods based on centralized intelligent mode feeder automation (FA) and intelligent distributed mode FA are proposed. Simulations based on PSCAD verify that the proposed SPLB fault detection method is feasible, highly sensitive and immune to the neutral grounded mode, fault scenarios and fault resistance. [ABSTRACT FROM AUTHOR]

The grasshopper heuristic optimisation algorithm (GOA) is one of the newest heuristic techniques. It attempts to imitate locust's behaviour in solving different problems. In this paper, first, optimal location and size of fixed capacitor banks on distribution systems have been obtained using the GOA. Determination of the optimal number of capacitor banks and their optimal locations and sizes represent one of the major challenges facing distribution system operators. Therefore, second, a combined power loss sensitivity and GOA technique has been introduced to obtain the optimal number, location and size of the capacitor banks on distribution systems. Third, a proposed technique for optimal placement of fixed and switched capacitor banks considering daily load variations is introduced. Finally, a new technique of combined rough set theory and GOA is proposed to minimise daily switching of the capacitor banks and minimise daily power losses. Four test systems with different sizes and complexities are considered to evaluate the proposed techniques which are the 33, 69, 85 and 141‐bus systems. To clarify the validation and effectiveness of the proposed solution techniques, the obtained results have been compared with other previously used solving techniques. The obtained results demonstrate the accuracy and effectiveness of the introduced techniques. [ABSTRACT FROM AUTHOR]

High impact–low probability (HILP) incidents, such as hurricanes, usually and gravely damage electric distribution networks. A resilient distribution network must have an ability to recover itself with a fast restoration methodology against the effects of HILP events. Due to improve the electric distribution network resiliency against HILP incidents, this paper suggests a probabilistic–proactive distribution network operation model based upon the chaos theory (P‐PDNOMC(. Here, a resilience index based upon operational cost and load shedding cost is employed to decrease the effects of a hurricane as an HILP incident. P‐PDNOMC is formulated as a framework that consists of a novel hurricane modelling and operation scheduling in normal and emergency conditions with uncertainties considering. It should be noted that a prediction approach based on the chaos theory and the least‐squares support vector machine (LS‐SVM) is also designed to consider the provisional and spatial behaviour of the hurricane. Furthermore, this paper proposes a novel optimization framework for damaged lines determination based upon the P‐PDNOM C (DLsP‐PDNOM C) by considering multi‐zone and multi‐period damaged equipment budget constraints. Here, the load shedding cost is applied to present the efficiency of the proposed model. The numerical results indicate the resiliency enhancement of the electric distribution network in the face of HILP incidents. [ABSTRACT FROM AUTHOR]

In the energy distribution networks, the most important and valuable equipment is oil‐immersed distribution transformers. Besides, due to the key role of these transformers and their multiplicity, their lifetime monitoring is inevitable. The life of a transformer depends on the weakest solid insulation material (i.e. paper insulation). On the other hand, monitoring the transformer insulation status requires accurate information to be available about the oil temperature at every moment. Therefore, it is important to control and predict the oil temperature rise in the transformer. In this study, a new model based on fundamental heat transfer theory is proposed for thermal behaviour prediction of top oil of indoor distribution transformers using the concept of thermal resistance, namely electro‐thermal resistance model (E‐TRM). In E‐TRM, the thermal resistance network is formed by following three‐dimensional heat transfer path and assigning thermal resistance to each path. To evaluate the proposed E‐TRM, the results of this model are verified with experimental results. Moreover, the E‐TRM is used to predict the thermal behaviour of the indoor transformer in the overloading condition. At the end, the transformer loss of life is estimated based on the oil temperature and a normal cyclic overloading strategy is presented for overloading management. [ABSTRACT FROM AUTHOR]

Recently, microgrids (MGs) present a vital role in the transformation of the existing power networks to the smart grids. Connecting MGs to construct the multi-microgrid (MMG) system enhances the robustness of the system against disturbances and upgrades overall network performance. In this paper, the MMG, as a source of self-healing support to the distribution networks, is analysed extensively. In fact, the MMG strengthens the self-healing of the network by participating in the restoration of disturbed loads. In this study, an operational framework is proposed for the self-healing problem in radial interconnected MGs based on two-stage cyber communication network architecture. In the first stage, the local control system (LCS) within each MG, schedules the accessible resources according to the local power consumption target. In the second stage, a number of LCSs are communicated globally to perform self-healing action. The communication of LCSs is accomplished using a consensus algorithm. Nevertheless, when a fault takes place in MG and a line is eliminated, the healthy MGs, due to demand and supply information in the first stage, supply the on-outage loads as far as possible. To validate the effectiveness of the proposed framework, two benchmark distribution networks (the 33-bus and the 119-bus) are employed. [ABSTRACT FROM AUTHOR]

The conventional distribution network is becoming an active grid due to widespread integration of distributed energy resources (DERs). This integration raises great concerns about security of the power system considering the growing interactions between the transmission and active distribution systems. One way to ensure stability of the integrated power system is prediction of critical contingencies which can jeopardize the power system security. Therefore, this paper aims to investigate transient stability contingency ranking in power grids considering the uncertainties raised by DERs of active distribution networks. To this end, probabilistic transient stability prediction framework is provided, in which the probability density function of transient stability condition is calculated based on the normalized stability indicators. The normalized stability indicators are based on the rotor angle and rotor speed. The normalized stability indicators are only utilized in the case of using fault data for prediction. Based on the proposed scheme, the instability of generators is anticipated through the proposed probabilistic transient stability prediction framework. Also, the effects of the probable topology changes on the line overload and also the voltage profile are investigated. Finally, the performance of the proposed method is validated and compared with the time domain simulation under various operating conditions. [ABSTRACT FROM AUTHOR]

Power flow calculations are an essential stage in many planning and control applications for distribution systems.To use these in control applications, however, the calculation time needs to be improved, and this can be done by the use of a trained ANN. This paper presents the considerations for constructing ANNs for DSs, and describes a method for training the system in order to support switching events representing a change in topology. The solutions for three DSs, balanced as well as unbalanced, are presented and the various considerations affecting the most appropriate ANN construction are discussed. The results are compared to the solution from the classical complex Newton‐Raphson and the fixed‐point iterative methods. The solutions have very high precision and good results are found for switched laterals. The computational performance is also compared and an improvement of two orders of magnitude is observed. [ABSTRACT FROM AUTHOR]

With the advent of small‐scale heat and electricity producers in distribution energy systems, the interdependencies between energy carriers have been increased. Moreover, the rapid deployment of micro CHP, electric heat pumps, electricity‐to‐heat appliances etc., calls for new local market frameworks to be employed in distribution energy systems. In response, this paper presents a new energy market framework based on the concept of peer‐to‐peer negotiations to facilitate energy transactions between agents at the distribution level while addressing the interdependencies between different energy carriers. Moreover, linear optimization problems are proposed to investigate the optimal strategies of market participants with various configurations. These optimization problems not only obtain the optimum strategy of agents to participate in the day‐ahead peer‐to‐peer electricity market, the day‐ahead heat market, and gas distribution systems but also obtain their optimal operation scheduling for the entire next day. The numerical results successfully demonstrate the applicability and merits of the proposed market framework. [ABSTRACT FROM AUTHOR]

Electric vehicle (EV) charging will bring new challenges to the coordination of grid and EV load. To facilitate large‐scale EV applications, optimal scheduling of EVs has become essential. However, the power grid has no power to force EV users to charge or give up charging. The actual type and mode of user's charging, may deviate from the expectations of grid. When the number of deviation's EV is sufficient, the power grid schedule will not achieve the expected results. In this context, a multi‐objective scheduling method considering user's charging selection is proposed to determine the optimal EV charging. The novel contributions of this paper lie in the exploitation of the user's preferences and their criterion of charging selection in form of functions based on concepts from economics. Three types of charging preferences for EV users including radical, conservative and balanced are used to influence the charging cost of EVs and load variance of grid. Finally, the ideal scheduling and actual scheduling are used to simulate various scenarios. The extensive results show that by introducing a method considering the influence of EV user's selection, the efficacy of the proposed scheduling can be further improved. [ABSTRACT FROM AUTHOR]

In the literature, many works detail the benefits of Volt‐VAr control to minimise the losses in a distribution system. However, it is also important to understand the impact of it on the life of the other assets in a distribution system. Since, distribution transformers (DTs) are the important assets of a distribution system, the main objective of this paper is to appraise the impact of Volt‐VAr control on the life of DTs. The paper presents a detailed methodology to estimate the loss of life (LoL) of the DTs under various Volt‐VAr control schemes, such as base‐case (without any control), voltage control, and Volt‐VAr control (VVC). The proposed methodology is implemented on modified IEEE 13‐bus and IIT‐Roorkee distribution systems considering the voltage‐dependent load models, seasonal load influences, and harmonics. The simulation results are presented to explore the ability of VVC in reducing the hottest‐spot temperature in the DTs during peak hours. The results reveal that the life of the DT can be extended by a considerable amount by optimally controlling the voltages and reactive power flows in the distribution system. Moreover, it gives a significant reduction in energy losses and improvement in power factor in distribution systems. [ABSTRACT FROM AUTHOR]

Many applications of Distribution Management Systems (DMSs) are based on power flow solutions. Fast and robust power flow methods capable of accommodating systems of general topologies and the most common models of Distributed Energy Resources (DERs) are, therefore, becoming indispensable. In this context, this paper proposes contributions for the symmetrical component‐based three‐phase power flow methods for distribution system analysis. The introduction of symmetrical components in the three‐phase power flow problem allows it to be decomposed into three single‐phase problems, which can be solved iteratively. Such decomposition significantly expedites the power flow solution problem, simplifies implementation complexity, and makes way for parallel computing techniques. The accuracy and validity of the proposed method were tested on distribution test feeders of different sizes and topologies and the results of several case studies were compared with those obtained by the Sequence Newton–Raphson method, and by the OpenDSS. Contributions of the paper include: (i) A new formulation of the Sequence‐Decoupling Compensation method in terms of real‐valued matrices; (ii) a novel modelling for PV buses; (iii) a simple procedure to tackle convergence issues related to delta and ungrounded‐wye connected transformers; and (iv) a modelling for wye, closed‐ and open‐delta connected step‐voltage regulators in the sequence frame of reference. [ABSTRACT FROM AUTHOR]

Due to a variety of social and economic reasons, renewable energy resources (RES) have grown exponentially in the recent years. Although, with the inclusion of RES into the electrical grid, multiple predicaments like voltage stability are to be unequivocally foreseen. This paper proposes to use decentralised measurements gathered from the distribution grid. Exemplarily, an adapted Cigré low‐voltage benchmark network is used for simulation on a real‐time simulator (RTS). The voltage and VAR control (VVC) is implemented on a standardised measurement device, in addition to other smart grid functionalities. The VVC algorithm is executed on the measurement devices and uses real‐time analogue signals from the RTS for validating the implemented VVC functionality. The distributed measurements are then communicated to a central controller device using IEC 61850 architecture and the decisions of the VVC algorithm are processed back to the client devices for co‐ordinated VVC control strategies. These include transformer tapping, reactive power control, and network reconfiguration. The results also indicate the advantages of implementing VVC using decentralised measurements against the existing control strategy at the transformer with no decentralised measurements. [ABSTRACT FROM AUTHOR]

Unlike traditional microgrids, Provisional Microgrid (PMG) utilizes only renewable generation and small energy storage units; thus, it does not have an inherent self‐islanding capability and instead, relies on importing power from any coupled microgrid (CMG) for islanding purposes. Therefore, assuring adequate power sharing between interconnected provisional and coupled MGs is crucial for assuring self‐islanding capability and reliable operation. The optimal power that can be transferred between the coupled MG and the PMG is mainly restricted by the size of the interconnecting tie‐line; hence, determining the tie‐line optimal size becomes a crucial task that must be tackled. Furthermore, the amount of power transferred is significantly influenced by the flexibility level of each microgrid. Since battery storage systems (BSS) is the main source of flexibility in PMGs, it becomes also vital to obtain the optimal size of the BSS for planning islanded PMG system. This paper presents an optimization model to jointly determine the optimal size of the BSS in each MG and the tie‐line size to assure optimal power sharing and minimum system cost (tie‐line investment cost, BSS investment cost, and interconnected system's operation cost). Numerical results demonstrate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

The integration of information and communication technologies in power networks enables greater flexibility through Smart Grids and increased network adequacy and reliability. Information and communication technology's functionality and design diversity within the cyber‐physical power system should be explicitly defined to quantify the risk of information and communication technology failures. The purpose of this paper is to quantify the cyber‐physical reliability risk introduced by the information and communication technology deployed for dynamic line rating implementations, which are usually installed in adverse environments and have a higher failure risk than indoor information and communication technology installations. This cyber‐physical reliability study employs a modified sequential Monte Carlo approach with a Markov state space to capture the dynamic line rating‐information and communication technology functionality. The method integrates the additional dynamic line rating states within the overhead line operating states, which allows quantifying the risk of dynamic line rating failures against the risk of traditional probabilistic line rating uprating practices. Results from IEEE 24‐bus and 14‐bus network reliability studies indicate that dynamic line rating‐information and communication technology failures (a) increase generation costs in the 24‐bus transmission network with high generation flexibility, while (b) they reduce the reliability of the 14‐bus network with small generation diversity and multiple load points. Such results can provide insightful recommendations on the quality of dynamic line rating‐information and communication technology infrastructure and inform utility's investment planning processes and maintenance practices. [ABSTRACT FROM AUTHOR]

This paper investigates the planning and operational processes of modern distribution networks hosting distributed energy resources (DERs). While in the past the two aspects have been distinct, a methodology is proposed in this paper to co‐optimise the two phases by considering the operational flexibility offered by DERs already in the planning phase. By employing AC optimal power flow (OPF) to analyse the worst‐case scenarios for the load and distributed generator injection, the optimal set‐points for the DERs are determined such that the network's security is ensured. From these results, the optimised individual characteristic curves are then extracted for each DER which are used in the operational phase for the local control of the devices. The optimised controls use only local measurements to address system‐wide issues and emulate the OPF solution without any communication. Finally, the proposed methodology is tested on the Cigre LV benchmark grid confirming that it is successful in mitigating with acceptable violations over‐ and under‐voltage problems, as well as congestion issues. Its performance is compared against the OPF‐based approach and currently employed local control schemes. [ABSTRACT FROM AUTHOR]

This paper is intended to give an effective coordination method between high penetration of plug in electric vehicles (PEVs) and optimal operation management (OOM) of distribution network problem. An effective fuzzy logic controller (FLC) is proposed which focuses on coordinated smart charge/discharge control of high penetration of PEVs with OOM in an iterative optimization process. In each iteration, the proposed FLC receives the voltage of the connection node of the PEVs, the remaining time to the peak load and the available energy of the PEVs while appropriately specifies the amount of absorbed or injected active power of the PEVs. This coordination leads to the minimization of the electric network losses, voltage flattening and reducing the produced pollutant. A modified version of Sine‐Cosine Algorithm (MSCA) is used to minimize the objective functions while the problem constraints are satisfied. An appropriate 33‐bus distribution network with 1000 PEVs in 100 groups is considered in order to show the authenticity and efficiency of this work. The results show that the proposed FLC‐based coordination procedure could effectively adjust the exchange power of the PEVs with the OOM decision variables in an acceptable time duration. [ABSTRACT FROM AUTHOR]

The electric spring (ES) is a reactive compensator which is series with a noncritical load. This paper utilizes the ES in the distribution networks and examines the underlying performance operationally and economically. A virtual generator model for the electric spring is proposed to ease the study of power systems. An algorithm based on the backward/forward sweep method is proposed for solving the optimal power flow. Then, with a 24‐hour real price and load data of ISO‐NE market, the performance of ES is evaluated operationally and economically in two distribution systems. The ESs may exchange reactive power between each other and this raises active and reactive power losses. To cope this problem, the feeders' voltages of the middle load demand are set as the reference voltages of ESs in each feeder so, each ES has a different reference voltage to cease the ES power exchanges. In this work, indexes such as voltage profile, active power loss, reactive power loss, power factor, electric bill payment, net present value, internal rate of return and the payback year are measured. The results of case study confirm the ES improves power loss, voltage profile, power factor, and stability while it reduces the operation cost. [ABSTRACT FROM AUTHOR]

With the access of renewable distributed generations and the uncertainty of demand‐side response, the operation states of the active distribution network (ADN) are uncertain. This study proposes a novel optimal strategy taking active management costs of the source–network–load as the goal and considering the site selection and the incentive price for the responsive load to optimise the ADN. To deal with uncertainties, a chance‐constrained optimisation model is established and the Monte Carlo sampling method is used. Then, the uncertain model is settled by the improved backtracking search algorithm, which uses an adaptive mutation scale factor. Finally, the practicability of the proposed strategy and the performance of the algorithm are verified by the modified IEEE 33‐bus distribution system and an actual distribution system in China. [ABSTRACT FROM AUTHOR]

Demand side participation is a fundamental property of modern power distribution networks. Time‐of‐use pricing is a common strategy to persuade customers to shift a part of their consumption to low consumption hours. In flat time‐of‐use pricing, it is not the price that changes over a period, it is the cost of energy. The aim of this paper was to quantify impact of cost elasticity of demand on investment plans over a multi‐stage horizon, where the time‐of‐use pricing was taken into account. On one hand, time‐of‐use pricing was modeled with three load levels as peak, medium‐peak and off‐peak. On the other hand, the tendency of customers to participate in reduction of demand was modeled where it shows rate of response of customers to change in cost of energy and it determines maximum demand response penetration. So, it was examined how time‐of‐use pricing and responsive customers can postpone the investments. Mixed integer linear programming method was utilized to solve the optimal distribution expansion planning problem. Simulations were performed on an 18‐node distribution network. Results revealed effectiveness of the proposed model and showed that consideration of cost elasticity of demand in expansion planning, changes optimal configuration of network and significantly influences total costs. [ABSTRACT FROM AUTHOR]

This study employs a sophisticated bi‐level optimization methodology to model the most efficient operation of microgrids (MGs) within the operational framework of distribution companies (DCs). In this bi‐level optimization problem, the upper level strives to maximize the profits of both MGs owners and DCs, while the lower level is dedicated to ensuring load balance, managing distributed generation, and implementing load curtailment strategies. The coordination of power transmission is facilitated by the DCs. At the upper level of decision‐making, the optimal pricing strategies for power transactions are determined, accounting for various factors such as market prices, demand response programs, and uncertainties in wind speed. Through the utilization of a bi‐level optimization framework, this study comprehensively captures the complex interactions between MGs and DCs, taking into consideration the objectives and constraints of both entities. This approach offers a more precise representation of the decision‐making process in retail electricity markets, thereby providing valuable insights into the optimal operation of MGs within the DCs setting. [ABSTRACT FROM AUTHOR]