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ABSTRACT Reverse power flow from a photovoltaic (PV) power generation system to distribution system is limited below a certain limit value. The behavior of a power conditioning system (PCS) for large capacity PV power generation system when the output power approached the output power limit value was experimentally estimated. Under the condition, the PCS became uncontrollable. It was pointed out that this phenomenon was caused by the maximum power point tracking (MPPT) control of the PCS. Furthermore, some methods to avoid the uncontrollable condition of PCS were shown. [ABSTRACT FROM AUTHOR]

In this paper, a method for determining line drop compensator (LDC) parameters for step voltage regulators and on‐load tap changers is proposed to avoid voltage violations in distribution systems with voltage fluctuations due to photovoltaic (PV) generation and electric vehicle (EV) charging. Distribution system operators need to effectively solve voltage problems caused by the widespread installation of distributed energy resources with the existing voltage regulators to construct an efficient and rational infrastructure. Our focus was on improving the method for determining the LDC parameters for the existing voltage regulators based on LDC control. A mechanism to dynamically change the LDC parameters depending on the situations in the distribution system was developed by using a mixture of experts, one of the machine learning techniques, and real‐time voltage and power flow information from information technology switches. The power flow calculations were performed using a distribution system model constructed based on the topology, loads, and generation characteristics of an actual distribution system in the Hokuriku region. The effectiveness of the proposed method was evaluated in terms of its improved effect on PV and EV hosting capacity, as well as the impact on the frequency of tap operations of voltage regulators. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

A hybrid approach is proposed for optimizing distribution systems (DSs) by integrating clean energy sources, specifically photovoltaic (PV) and wind power (WT). The proposed technique combines the mud ring algorithm (MRA) and quantum neural network (QNN), referred to as the MRA‐QNN technique. The primary objective is to minimize power loss and enhance voltage stability. The MRA method generates the control signal of the converter, while the QNN method predicts the control signal based on the MRA output. The effectiveness of the approach is revealed through simulations on standard IEEE 33 bus and 69 bus systems. Implementation in MATLAB shows superior performance compared to existing methods, with lower power loss values. There has been a sustained rise in the system voltage profile (In the WT and PV situations, 0.950. and 93 p.u), as well as a considerable reduction in the active power (AP) losses (to 132.39 kW with PV and 81.23 kW with WT from 362.86 kW). With PV, the entire yearly economic loss is lowered from $158932.68 to just $57996.939, and with WT, it is decreased to $56805.479. With three PVs, the yearly economic loss and active power losses are decreased to 30419.871 $ and 69.449, and 4.27 kW and 1875.930 $, respectively. [ABSTRACT FROM AUTHOR]

This article proposes an optimal placement and sizing of photovoltaic (PV) power systems based distributed generation (DG) in radial electrical distribution networks considering the capability of PV inverters to regulate the voltage by optimal injecting and absorbing reactive power at the point of common coupling (PCC) using honey badger algorithm (HBA), as a recent and efficient optimization algorithm to solve the complicated optimal allocation. Several objective functions are achieved for distribution system performance enhancement: minimizing the power loss and the voltage deviation index (VDI) and maximizing the voltage stability index (VSI). Based on historical data and probabilistic models, seasonal hourly solar irradiance, ambient temperature, and load variation curves have been modeled, which simultaneously consider the light, normal, and heavy load demand. The essential components of distribution power systems have been characterized. To investigate the validity of the proposed approach, IEEE 33 and IEEE 69 BUS radial distribution test systems have been considered for power flow (PF) analyses, where Newton's Raphson method has been applied to solve the PF issue. The simulation results of different numerical scenarios have shown the effectiveness and validity of the newly proposed method to solve the optimal allocation problem considering optimal volt‐var regulation control of PV inverters compared to several valid and robust optimization algorithms. [ABSTRACT FROM AUTHOR]

The paper proposes a new stochastic multiobjective technoeconomic model for integrating photovoltaic (PV) and wind energy resources in electricity price (EP)‐driven distribution systems. The primary goal of this paper is to determine the optimal location and capacity for renewable energy‐based distributed generation, specifically PV and wind resources, while considering weather and system uncertainties. These uncertainties include stochastic variations in PV illumination intensity, wind speed, EP, and load fluctuations. To address these uncertainties, the paper employs scenario modeling techniques named as Latin hypercube sampling with Cholesky decomposition. This technique generates multiple correlated scenarios that represent uncertain variables. Subsequently, a scenario reduction technique is applied to identify the scenario with the highest probability. Later, a mathematical model is developed to minimize an objective function that encompasses various factors like system losses, node voltage deviations, the cost of purchasing power from the grid; and simultaneously maximize the total annual energy savings. The objective is to find optimal solutions that strike a balance between different objectives. To obtain an efficient optimum solution, this paper employs an effective meta‐heuristic technique named as JAYA algorithm. The results obtained by the JAYA algorithm are juxtaposed with those obtained using particle swarm optimization and genetic algorithm techniques. The proposed method is evaluated using Institute of Electrical and Electronics Engineers (IEEE) 33‐node and IEEE 69‐node test feeders to validate its feasibility and effectiveness. However, the effectiveness of the proposed method is not limited to any size of test systems. [ABSTRACT FROM AUTHOR]

With increasing interest in using stannous chloride without filtration to achieve hexavalent chromium maximum contaminant level compliance in California, there is new urgency to quantify its effects on water quality and risks to public health manifested in distribution and premise plumbing systems. Accordingly, a 12‐week groundwater pilot study was completed using ubiquitous premise plumbing materials under flowing (to waste) and stagnating conditions of hexavalent chromium‐containing groundwater following stannous chloride addition without filtration. Results quantified the accumulation and release of chromium and tin, with total chromium concentrations exceeding regulatory or acceptable levels under stagnating conditions. Sediment with elevated chromium, tin, arsenic, and manganese concentrations was also observed. Given these observations would likely occur and worsen over time in distribution systems that cumulatively serve large populations, the use of stannous chloride without filtration represents an unacceptable risk to public health compared to other, more well‐established, best available technologies. [ABSTRACT FROM AUTHOR]

Answering the right questions on pipeline condition assessment in light of system‐specific priorities helps utilities make cost‐effective decisions about infrastructure renewal. [ABSTRACT FROM AUTHOR]

US Environmental Protection Agency (EPA) requires public water systems (PWSs) that disinfect to maintain a detectable disinfectant residual throughout the distribution system (DS) to protect consumers against risks from microbial pathogens. The EPA is tasked with proposing revisions to the Microbial, Disinfectant, and Disinfection Byproduct rules by July 2025. Potential revisions could include a numeric minimum disinfectant residual level in place of the "detectable" requirement. Twenty‐three states have defined a required DS numeric minimum disinfectant residual level. Only three such states, Louisiana, Colorado, and Pennsylvania, have made recent changes and have sufficient data available to assess implications. These states were used as case studies to assess the impact this regulatory change had on disinfectant residual levels and microbial and disinfection byproduct (DBP) occurrence in PWS DSs. Results included increases in disinfectant residual levels, decreases in total coliform positive occurrences and violations, and temporary increases in DBP occurrence and violations. [ABSTRACT FROM AUTHOR]

This paper examines the impact of different voltage unbalance definitions on voltage control in unbalanced distribution systems. Traditional voltage regulation methods for unbalanced systems rely on a single voltage unbalance definition with inconsistent adoptions. In such a situation, voltage control performance can vary between definitions, and improper choice leads to control failures. In this study, we perform numerical analysis and simulations to investigate the impact of different definitions. In the numerical analysis, two definitions quantifying negative and zero sequence components are used as reference definitions, and the theoretical error range of the remaining definitions is identified. The results are further verified by the simulations on the IEEE 123 node test system with phase‐by‐phase controlled three‐phase step voltage regulators and smart photovoltaic inverters. The control of the devices is optimized to minimize or limit a specific definition. The results show that the values of each definition at the same voltage condition can differ significantly, and inappropriate definitions may lead to significant uncertainty in the voltage control. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Water utilities must help protect public health by making sure water distribution systems are effectively treated to guard against dangerous levels of Legionella pneumophila. [ABSTRACT FROM AUTHOR]

Unbalanced operation of distribution networks, as a crucial but inevitable aspect of power quality, brings about economic and technical issues. The increase in active power loss is more concerning due to the economic and technical implications. Economic sustainability of liberalized distribution networks is hugely tied to the availability of transparent and effective approaches to determine the stakeholders of this sort of phenomenon. This is done by awarding/penalizing them accordingly. Studies in the literature have not considered the incremental losses that unbalanced operations cause to distribution systems. Here, a mathematical approach based on vector analysis in the symmetrical components space is introduced. This approach quantifies the contribution of each unbalanced load to unbalanced operation and increased power losses. This technique discriminates between the mutual effects of different unbalanced loads on the power losses of the entire network. By means of the proposed approach, the best candidate unbalanced load(s)/location(s) to perform the corrective balancing actions and their ranking are precisely specified. Vector representation of the developed method simplifies its understanding, utilization, and expansion. For validation, the proposed method is applied to the IEEE 37‐bus test distribution network under various scenarios. The results confirm the sound results and practical merits of the developed method. [ABSTRACT FROM AUTHOR]

The article discusses the importance of maintaining water quality in buildings and the role that water utilities can play in this process. While utilities are not responsible for water quality within buildings, they can implement measures such as secondary disinfection and corrosion control strategies to help building owners and operators maintain water quality. The article also highlights the efforts of the American Water Works Association's Premise Plumbing Committee (PPC) in synthesizing industry knowledge and providing guidance on topics such as controlling microbial growth and managing lead and copper in building plumbing systems. The PPC is also working towards creating a training and certification program for building water system (BWS) operators to ensure adequate management of BWSs and the control of microbial pathogens and other contaminants. [Extracted from the article]

This paper proposes a control method for step voltage regulators (SVRs) to avoid voltage violations in distribution systems with unbalanced voltages due to photovoltaic (PV) generation and electric vehicle (EV) charging. Distribution system operators must effectively address voltage problems resulting from the widespread installation of distributed energy resources under the optimizing the utilization of existing voltage regulators to establish an efficient and rational infrastructure. Therefore, this study focused on advancements in voltage control using SVR based on line‐drop compensator (LDC) control, which is widely used in actual operations. We propose a method that utilizes voltage data from information technology switches to detect and address voltage unbalances in the control section, allowing for the sequential adjustment of the monitoring target in LDC control to maintain appropriate voltage limits under unbalanced conditions. We conducted power flow calculations using a distribution system model that represents an actual distribution system in the Hokuriku area. The effectiveness of the proposed method was evaluated in terms of its impact on PV and EV hosting capacity, as well as the frequency of tap operations. © 2023 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes leaky least mean fourth (LLMF) algorithm for the control of five‐level series connected H‐bridge multilevel inverter (5L SCHB‐MLI). The SCHB multilevel inverter is a popular configuration due to its wide application for high‐power and medium‐voltage applications. The complete system comprising the grid, load, and compensator is modeled in MATLAB/SIMULINK. Prototype hardware is also developed in the laboratory for experimental validation. The 5L SCHB inverter is connected in a single‐phase power distribution system and controlled as a compensator. The voltage across both DC links of the H‐bridges is regulated to almost equal value by the proposed control algorithm. The closed loop system is designed to mitigate total harmonic distortion (THD) in the source current and improve the power quality of the proposed system. The system is analyzed under the steady state and dynamic state, and the results are also verified on the hardware prototype developed in the laboratory. The proposed algorithm is also compared with conventional least means square (LMS) algorithm and notch filter algorithm on several parameters. The paper discusses a detailed simulation and hardware analysis on the control of five‐level MLI topology. [ABSTRACT FROM AUTHOR]

Single‐phase loads and photovoltaic generation cause three‐phase imbalance in distribution systems, and prospective growth of normal chargers of electric vehicles may even increase the imbalance. The analysis of such unbalanced systems requires the three‐phase power‐flow calculation. Since existing methods require the admittance matrices of three‐phase transformers, they must be derived for all possible winding connection patterns in advance to its computer‐code implementation. This paper proposes a three‐phase power‐flow calculation method which formulates circuit equations using the modified nodal analysis, making it possible to automatically handle any winding connection. The power‐flow constraints are then embedded into the circuit equations using a fixed‐point iteration. Newton‐Raphson, backward/forward sweep and fixed‐point iteration methods are the existing three categories of solution methods. Newton‐Raphson methods may show convergence problems due to the high R/X ratios of distribution lines. Backward/forward sweep methods cannot be used, because loops are temporarily formed in a distribution system during circuit switching. These justify the use of a fixed‐point iteration. In this paper, the proposed method is validated by practical examples. [ABSTRACT FROM AUTHOR]

In recent years, distributed structures have been developed in distribution networks as a result of privatization as well as integration of independently operated distributed energy resources (DERs) into the grid. In this context, effective management techniques seem to be necessary to enable decentralized operation of systems that have been consisted of multiple agents. Accordingly, novel management schemes should be applied in such systems to enable the distributed reactive power management, which would finally improve voltage profile in the network. As a result, this paper develops a distributed algorithm for reactive power management in multi‐agent distribution systems with the aim of improving the voltage profile of the grid. Correspondingly, in the proposed framework, several cost functions are developed to model the effects of reactive power management on the system from the distribution system operator (DSO) as well as agents' perspectives. Consequently, the proposed reactive power management algorithm would result in voltage profile improvement, while each agent of the system merely strives to maximize its own profits. Accordingly, the proposed scheme ensures the privacy of independent agents. Finally, the proposed scheme is applied on the modified IEEE‐37‐bus test system to investigate its effectiveness on Peer‐to‐Peer (P2P) reactive power management in multi‐agent systems. [ABSTRACT FROM AUTHOR]

The service restoration to sound sections within a short period as much as possible, performed after the permanent fault occurs in a distribution system, is significant for maintaining power supply reliability. This paper proposes an efficient method to find service restoration procedures based on fault searching and the optimal work scheduling of crews, considering the power supply priorities of loads and the probability of occurrence of faults. The proposed method is composed of two‐stage problems to reduce the outage sections efficiently: (i) the problem to find a series of searching procedures for unknown fault locations in the first stage and (ii) the optimization problem of work schedules of crews in the second stage. In the first stage, the order of operation of switches opened for searching for the fault direction is determined, constituting the searching tree. After that, the proposed optimization method can efficiently solve the work scheduling problem by formulating it as a mixed‐integer linear programming problem in the second stage. The computational experiments using a large‐scale distribution system model with many remote and manual switches show that the proposed method can provide efficient service restoration procedures within a reasonable computational time. [ABSTRACT FROM AUTHOR]

This manuscript proposes a hybrid technique for the optimum location of micro‐phasor measurement units (μ‐PMUs) in the distribution system (DS).The proposed hybrid approach is the wrapper of dwarf mongoose optimizer (DMO) and pelican optimization algorithm (POA). The updating behavior of DMO is improved by the POA; therefore, it is called DMO‐POA approach. The main aim of the proposed approach is to avoid discontinuity of supply and minimizes the count of PMDs to reduce cost and attain the maximal count of measurement‐redundancy that is limited to full‐system observability for IEEE bus‐system in zero injection nodes (ZINs) and tie‐switches. The proposed approach considered the optimum count of μ‐PMUs is needed for the thorough distribution system economy, observability, and the reliability measure. The proposed approach considers the distribution of PMUs in the reconfiguration of smart‐distribution‐grids, ZINs and communication system requirements. Here, the objective‐function is aiming at minimizing the costs of reliability and capital. The proposed method uses the infrastructure of communication cost to simultaneously co‐optimize the system switching strategy and find the optimal sites for PMUs. The performance of the proposed technique is tested in different test‐systems, like IEEE‐14 bus, 13, 34, 37, and 123 buses and the performance is executed by comparing it with the existing approaches. Furthermore, the proposed system is effectual to find an optimal solution with less computation and decreases the complexity of the algorithm. [ABSTRACT FROM AUTHOR]

Single phase‐earth faults are the most frequent faults likely to occur but hard to identify in distribution system, especially in a neutral un‐effectively grounded system. To address this issue, this paper innovatively proposes a typical distribution system structure, in which it only introduces one three‐phase isolated power transformer (PT)‐based subnetwork division mode that can effectively limit the zero‐sequence current flow from other sound lines. Second, following the qualitative discussions about the effect of the proposed structures on power supply reliability and probability of bushfires caused by high impedance earth faults (HIEFs), a novel detecting judgement criterion merely using vector‐based variation via pre‐fault and post‐fault zero‐sequence voltage is mathematically formulated. In general, the proposed structure takes into account the the fault current suppression while manifesting fault feature at the same time, and in contrast with current detecting methods, vectorized form can present a wider exploring space and a higher identifying sensitivity, especially in detecting HIEFs. Numerical simulations and field tests validate the effectiveness and adaptability of the proposed detecting approach towards single phase‐earth fault identification field. [ABSTRACT FROM AUTHOR]

Summary: Achieving uninterrupted water supply to the consumer node is considered to be the significant aspect for urban water distribution system (WDS). Under circumstances such as sensor failures or large sampling interval, the intermittent vital data are ignored, which lead to the missing data problem. In this work, an enhanced version of Kalman filter (KF) is proposed termed to be customized KF (CKF). The proposed CKF is equipped to handle the state‐ and input‐dependent noises, which are amplified based on the input and states in WDS. These noises corrupt the measured response from the WDS added to the conventional sensor and model uncertainties. In this case, a real‐world‐existing WDS is considered to test the credibility of the proposed algorithm. This reduces the complexity of the computation and the sampling rate of the measured head level, and the flows are considered to be random. The study indicates that the proposed CKF performs better in estimating the missing data voids with the noise‐corrupted measurements. To have the continuous monitoring accessible in remote sections, the vital parameters are monitored through Internet of Things (IoT) in android platform. The estimated data from the MATLAB and the sensor data of the consumer demands are monitored through user‐defined android application. This technique provides the advantage of monitoring the WDS in flyby condition and also even in the presence of any sensor failures, which also helps to localize the fault location. [ABSTRACT FROM AUTHOR]

As the load on distribution networks grows, system operators and planners are constantly challenged with the issue of voltage regulation or enhancing the quality of supply to customers at the load end of lengthy distribution lines. This paper presents the optimum determination of series capacitor units in a distribution system to maximize energy‐saving and enhance voltage levels. Interestingly, series capacitors can enhance the capability of transmission lines, reduce line losses, enhance the performance of buses with large induction motor loads and reduce voltage flicker. At the same time, the limitations of series compensation are taken into consideration while calculating its optimum values. To achieve the planning objective and optimal load flow objective, two strategies: The Improved Grey Wolf Optimization method (I‐GWO) and Tabu Search (TS), are hybridized to get the benefit of their advantages. The I‐GWO has a movement strategy called dimension learning‐based hunting for enhancing the balance between global and local search and maintaining diversity. The proposed (I‐GWO‐TS) algorithm can solve mixed‐integer programming to achieve the planning and the optimal load flow objectives. The proposed method can be applied to a real Egyptian distribution system that is heavily loaded, with poor voltage regulation, and also has high‐power losses. The obtained results demonstrate the capability of the proposed approach to determine optimal series capacitors' location and sizing for maximization of energy saving. Further, the proposed method improves the network performance regarding the voltage profile and power losses, although the limitations of including series compensation were considered in the distribution system. [ABSTRACT FROM AUTHOR]

In recent years, the aggregation business has gained a lot of attention in Japan. Aggregators will make contracts with customers with photovoltaic (PV) power systems and battery energy storage systems (BESSs) including electric vehicles (EVs) to participate in electricity markets. Aggregators might have to pay electricity supply‐demand imbalance charges when generated and consumed energies contracted at the day‐ahead supply‐demand market are different from those at the current day operation due to distribution network constraints such as voltage and power flow limitations. Therefore, the information on network constraints is very important for aggregators to determine their day‐ahead schedules. In this paper, we evaluated the relationship between aggregator supply‐demand schedules and the distribution system operation. It was assumed that the reverse power flow limitations due to network constraints are notified to the aggregators by distribution system operator (DSO). Two cases of the aggregators' schedules of PV systems and stationary BESSs were compared in the simulations. In addition, aggregator strategies for making adequate schedules were evaluated. [ABSTRACT FROM AUTHOR]

The enforcement of a feed‐in tariff (FIT) program in Japan has increased the number of installations of photovoltaic generation systems in its residential sector. After the end of an FIT program, the surplus electricity of an individual prosumer is purchased by the utility company at a reduced price, which may have an economic impact on the prosumer. To avoid this adverse effect, peer‐to‐peer (P2P) electricity transactions among prosumers based on blockchain and smart contract technologies as well as introduction of residence‐use stationary storage batteries are generating significant interest. In this study, the potential economic merit of P2P transactions and residential storage battery introduction are evaluated using a total optimization approach. For realizing a more practical perspective, this study also investigates the economic merit based on a partial optimization approach, in which an individual prosumer pursues its own profit. Furthermore, in this study, the grid‐side merit of P2P electricity transactions among prosumers is examined. Comparison of the merits determined by the total and partial optimization approaches shows that the realization of P2P transactions could provide a notable economic merit to the participants and reduce both the required facility capacity and power flow variation. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Owing to the large number of power distribution equipment, the supply voltage is managed independently in 6.6‐kV medium‐voltage (MV) and 100‐V low‐voltage (LV) systems in Japanese distribution systems. Both systems have their respective independent allowable voltage range. We have studied the optimum allowable voltage range for MV and LV systems in order to reduce the equipment cost. In this study, we analyze the relationship between the maximum voltage drop and system configuration in an LV systems from the viewpoint of investment costs. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

With increase in the number of photovoltaic system installations, the prospect of voltage deviation from the acceptable range in a distribution system is increasing. Voltage distribution can be controlled using step voltage regulators (SVRs) and static var compensators (SVCs); however, for their coordination, it is necessary to stringently adjust the set value for each distribution line. In this study, a method of applying model predictive control to the coordination between an SVR and an SVC is investigated. In this paper, we first describe the proposed method and subsequently present the results of the performance comparison of the proposed and conventional methods to validate the effectiveness of the proposed method. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Although the installation of photovoltaic (PV) in distribution systems can contribute to the decarbonization of electricity generation, the PV output fluctuates depending on weather conditions, which in turn complicates power flow and destabilizes the voltage levels in distribution systems. Conventionally, step voltage regulators (SVRs) have been used to maintain voltage profiles within allowable ranges, however, the conventional control strategy might not be enough to successfully mitigate high speed voltage fluctuation caused by PVs. In this study, we focused on the time‐limit characteristic of tap operation in a system with two SVRs located, respectively, upstream near the distribution substation and downstream from the substation. Three methods for the cooperative control of two SVRs using moving average filters were proposed. The effectiveness of the proposed methods was validated through numerical simulation based on a model of a rural distribution system with a PV plant integrated at the end feeder. The performance of the proposed methods was compared with each other using evaluation indices such as the amount of voltage deviation and number of tap operations, and it was shown that the method with band‐pass filter for differential control had the best objective function. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This manuscript proposes an Internet of Things (IoT) platform for energy management (EM) in multi‐microgrid (MMG) system to enhance the power quality with hybrid method. The proposed method is the consolidation of opposition based crow search optimizer (OCSO) and radial basis functional neural network (RBFNN), hence it called RBFNOCS technique. The main aim of this manuscript is to optimally managing the power and resources of distribution system (DS) by constantly track the data from IoT‐based communication framework. In the proposed work, every devices of home is interfaced with data acquisition module (DAM) that is IoT object along unique IP address resultant in large mesh wireless network. Here, the IoT‐based communication framework is used for facilitating the development of a demand response (DR) energy management system (EMS) for distribution system. The transmitted data is processed by RBFNOCS technique. By utilizing the RBFNOCS method, the active with reactive power processing for optimal capacity unbalance compensation smart VSIs share the obtainable neutral current (NC). Likewise, the DS IoT framework enhances these networks flexibility and gives feasible use of obtainable resources. Moreover, the RBFNOCS method is responsible for satisfying the total supply with energy demand. The proposed model is activated in MATLAB/Simulink site and the performance is compared with existing models, namely improved artificial bee colony, squirrel search algorithm and gravitational search algorithm based artificial neural network (SOGSNN), GOAPSNN, fruit fly optimization, and FORDF technique. When compared with the existing methods, the efficiency of the RBFNOCS method is 93.4501%. [ABSTRACT FROM AUTHOR]

In this manuscript, an energy management system (EMS) is proposed to the distribution system (DS) using Internet of Things (IoT) framework with a hybrid system. The proposed hybrid method is the combination of the Seagull Optimization Algorithm (SOA) and Owl Search Algorithm (OSA), hence it is called SO2SA technique. The principle objective of the SO2SA technique is to optimize managing distribution system power and resources through continuous monitoring of the data from a communication framework based on IoT. In SO2SA technique, every home device is connected to the module of data acquisition, which indicates an IoT object along with a unique IP address as a result of huge mesh wireless network devices. The sending data are processed through SO2SA technique. Similarly, the IoT architecture of the distribution system enhances the flexibility of these networks and gives optimal utilization of obtainable resources. In addition, the SO2SA technique is responsible for meeting the overall power and supply requirements. The proposed method is implemented in MATLAB/Simulink site and the efficiency is likened to the other different methods. In 50 trail numbers, the RMSE, MAPE, and MBE range of SO2SA technique represents 5.63, 0.90, and 1.035. Thus, the proposed technique is highly competent over all the existing approaches. [ABSTRACT FROM AUTHOR]

In recent years, several renewable energy power sources, such as photovoltaics (PVs) and wind power generation, have been introduced. Although the introduced PVs are undergoing improvements in the distribution system, they still encounter several challenges. One of these challenges is an increase in supply and demand fluctuations. Accordingly, the authors are currently researching a microgrid that eliminates the power flow between the distribution and sub‐transmission systems by using a battery energy‐storage system. In this paper, we propose a method for determining the restriction of power flow by solving optimization problems. Furthermore, a sensitivity analysis was performed in this study on the effects of parameters, such as the capacity of PV, load, and required capacity of a battery energy‐storage system, on the power‐flow restriction caused by the optimization problem. Finally, we discuss the results obtained from studying the conditions that enable the reduction in the required capacity of the battery energy‐storage system. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

According to the increase of the amount of renewable energy, voltage control of the distribution system is becoming more important. Thus, we propose a voltage control method of power conditioning systems (PCSs) in the customers serving as virtual power plant (VPP) with the step voltage regulator (SVR). The proposed method is verified by the simulation and experimental results. As a result, it is clarified that PCSs are able to control voltage moderately and cooperatewith SVR under several voltage fluctuation conditions. [ABSTRACT FROM AUTHOR]

Recently, power system reliability has been challenged due to the increment of electrical demand. When an outage occurs, locating the outage may take a long time because of the distribution system's radial structure and the presence of various elements. To decrease the outage detection time, this study proposes to classify the equipment‐related outage causes to diagnose the faulty equipment at the time of outage occurrence. To this end, available historical outage, load and weather data sets are integrated, and various features are defined. Then, binary classifiers are developed to classify each equipment's failures against others'. To enhance classifiers' performance, this study also proposes to use cost function and ensemble models. The results of applying proposed classifiers show the accuracy of the proposed method and improvements in outcomes. [ABSTRACT FROM AUTHOR]

In this study, a privacy‐based demand response (DR) trading scheme among end‐users and DR aggregators (DRAs) is proposed within the retail market framework and by distribution platform optimiser. This scheme aims to obtain the optimum DR volume to be exchanged while considering both DRAs' and customers' preferences. A bi‐level programming model is formulated in a day‐ahead market within retail markets. In the upper‐level problem, the total operation cost of the distribution system is minimised. The production volatility of renewable energy resources is also taken into account in this level through stochastic two‐stage programming and Monte–Carlo simulation method. In the lower‐level problem, the electricity bill for customers is minimised for customers. The income from DR selling is maximised based on DR prices through secure communication of household energy management systems and DRA. To solve this convex and continuous bi‐level problem, it is converted to an equivalent single‐level problem by adding primal and dual constraints of lower level as well as its strong duality condition to the upper‐level problem. The results demonstrate the effectiveness of different DR prices and different number of DRAs on hourly DR volume, hourly DR cost and power exchange between the studied network and the upstream network. [ABSTRACT FROM AUTHOR]

This study presents a grid‐integrated solar photovoltaic system (SPVS). The objective of the work is to explore the scope of cascaded H‐bridge multilevel inverter (CHBMLI) in the high infiltration of photovoltaic (PV) in the distribution system. A five‐level CHBMLI is implemented with a balanced power‐sharing and equal switch stress mode, which increases the system power rating with longer life. The power conversion efficiency is elevated by reduced switching frequency, compared to two‐level inverters. The damped second‐order generalised integral (DSOGI) control‐based grid synchronisation is used to critically damp system oscillations and overshoots at dynamic operating conditions. Hence, safer service of lower rating power electronic switches at high power operation is ensured. It also has better bandpass filtering at the nominal grid frequency. A single‐input multiple‐output single‐ended primary inductance converter realises the isolated DC sources for the CHBMLI. It extracts maximum power from the PV array by using centralised incremental conductance algorithm. The SPVS also considers the nonlinear unbalanced loads at the bus of common coupling and provide shunt active filter functionality. A minimum number of voltage and current sensors are used in the configuration. An extensive analysis is carried out to validate the theoretical claims. [ABSTRACT FROM AUTHOR]

The design of future distribution systems involves the application of flexible technologies such as renewable‐based distributed generations (DGs), battery energy storage systems (BESSs), demand response for controllable load management and distribution network reconfiguration for achieving assets optimisation and for improving the efficiency of the distribution systems. The renewable‐based DGs are the source of uncertainty that can be overcome by the proper modelling of renewable resources and application of energy storage devices. However, the coordination of these flexible technologies is essential to avoid counterproductive results and to extract maximum possible benefits from these technologies. This work, therefore, aims to study the coordinated impact of controllable load with renewable‐based DGs, BESSs and network reconfiguration for improving the performance of distribution systems. The coordination of these technologies is a very complex optimisation problem due to various constraints associated with charging and discharging of BESSs, complex nature of controllable load management and feeder current limits of distribution network. In this study, an improved water evaporation optimisation algorithm is developed to solve this multi‐constraint complex optimisation problem to minimise the network loss and voltage profile improvement for distribution system. The results show that this coordinated operational problem significantly improves the performance of distribution systems. [ABSTRACT FROM AUTHOR]

It is well‐known that the presence of non‐linear loads in the distribution system can impair the power quality. The problem becomes worse in microgrids and power electronic‐based power systems as the increasing penetration of single‐phase distributed generation may result in a more unbalanced grid voltage. Shunt active power filters (SAPFs) are used for improving the power quality and compensating for the unbalance grid voltage. This study presents a modification of the classical control structure based on the finite control set model predictive control (FCS‐MPC). The proposed control structure can retain all the advantages of FCS‐MPC, while improving the input current quality. Furthermore, a computationally efficient cost function based on only a single objective is introduced, and its effect on reducing the current ripple is demonstrated. The presented solution provides a fast response to the transients as well as compensates for the unbalanced grid voltage conditions. A straightforward single loop controller is compared to the conventional way of realising the active power filters, which is based on space vector pulse width modulation. The simulation results have been obtained from MATLAB/SIMULINK environment, while the obtained experimental results, utilising a 15 kVA power converter, highlight the effective performance of the proposed control scheme and verifies the introduced MPC‐based method as a viable control solution for SAPFs. [ABSTRACT FROM AUTHOR]

Owing to the important role of the power system in modern societies, its resilience against natural disasters has become a top priority for power system operators and planners. Moreover, in recent years, due to the increasing number and severity of weather-related events, several operational solutions have been proposed to increase the resilience of power systems. For instance, in the distribution part of power systems, dynamic micro-grid (MG) formation can enhance resilience by means of distributed energy resources (DERs) when the main grid is unavailable. Following this concept, the capabilities of electric vehicles (EVs) such as vehicle-to-grid make it possible to use the energy stored inside them to restore critical loads. Therefore, the aggregation of EVs in the distribution system can be seen as a DER from the system operator viewpoint, and operators can benefit from this limited energy resource in MG formation. This study uses two types of EV aggregation for this purpose, i.e. a public parking lot and a residential parking. To improve system performance when using these resources, two steps should be taken: (i) employing a master–slave control technique in each MG and (ii) using a demand-side management programme. [ABSTRACT FROM AUTHOR]

Power electronicconverters have attracted significant attention in renewable energy generation and distribution systems. However, some crucial techniques, such as power quality and stability enhancement of converters, still need to be further improved. In this study, an improved reduced‐order generalised integrator (ROGI), which can achieve decoupling, is proposed. It can reduce the α ‐axis and β ‐axis current coupling and improve the dynamic response performance, maintaining the advantage of the conventional ROGI (e.g. less computational burden). Besides, delay compensation is added to the proposed decoupled ROGI, which improves the stability of the current loop and can be effectively applied for the current/voltage harmonic suppression in the distributed system. Also, the procedures of parameter tuning and optimal delay compensation angle computation are given. Finally, the harmonic current compensation of the three‐phase grid‐connected converter is taken as an example for simulation analysis, and the experimental results verify the reasonability and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Assessment and enhancement of transmission network capability have been one of the prime interests of power system monitoring, operation and control. Conventionally, the issue of available transfer capability (ATC) assessment has been tackled considering the transmission and distribution networks as segregated entities because they had little or no influence on each other's performance owing to the unidirectional flow of power from the transmission to distribution networks. Now, with increasing interest in smart transmission and distribution in amalgamation with a paradigm shift in sources of generation from centralised to decentralised even at distribution levels mandating the analysis of power grid while inculcating both the hierarchies simultaneously. In this study, a platform for quasi‐static operation of power transmission and distribution networks, employing a multi‐agent based system has been developed. The developed multi‐agent systembased system has been utilised for assessment of ATC considering active distribution network (ADN) whereby Modified IEEE 24 bus system at transmission and Modified IEEE 123 node system at distribution level has been considered as a test system. It has been observed that the presence of ADN considerably affects the ATC of the system. [ABSTRACT FROM AUTHOR]

Matrix is one of the convenient means for depicting/illustrating a graph on the computer. In this study, the notion graph‐theory in conjunction with matrix algebraic operations has been adopted for solving the load‐flow problem of three‐phase distribution systems (radial and meshed). Five significant matrices, path impedance (PI), loads beyond branch (LB), path drop (PD), slack bus to other buses drop (SBOBD), load flow matrix (LFM), and straight‐forward matrix operations have been utilised to attain the load‐flow solutions. The aforementioned matrices reveal the system's topology and pertinent information about the operating characteristics of the distribution system during LF studies. This algorithm is formulated entirely on various matrices formulation and computations, even at the stage of upgrading the voltage at every individual bus. Owing to the aforementioned reasons, this LF methodology is computationally efficient for large‐sized distribution systems. Moreover, the distributed generations (DGs) modelled as PQ and PV buses are incorporated into the proposed load‐flow algorithm. A generalised breakpoint matrix has been derived to compute the mesh breakpoint and PV breakpoint injections simultaneously. The effectiveness of the proposed methodology has been tested on several standard distribution systems. The test outcome shows the viability and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

In this work, the development of sign regressor least mean mixed norm (SRLMMN) control technique for a distribution static compensator (D‐STATCOM) is presented. This control technique extracts fundamental weight components from the non‐sinusoidal load currents and generates reference grid currents. D‐STATCOM is developed for harmonics eradication, reactive power injection and load balancing and its performance is investigated in several operating modes. The performance of SRLMMN control is compared with recursive least square (RLS) and variable step least mean square (VSLMS) control techniques in terms of convergence, steady‐state error, harmonics elimination, sample time and computation complexity. The major advantages of SRLMMN control technique, are fast convergence, less steady‐state error, low total harmonic distortion (THD) and offers less computation complexity when compared with RLS and VSLMS. A laboratory‐scale prototype of compensator is realised using a voltage source converter with the controller implemented in the dSPACE‐MicroLabBox. Both MATLAB simulation and experimental results are included to demonstrate the performance of shunt compensator under steady‐state and dynamic loadings. The developed SRLMMN control technique mitigates power quality problems and effectively suppresses THD observed in the grid current with reference to IEEE Standard 519–2014. [ABSTRACT FROM AUTHOR]

The proliferation of distributed generation and the electrification of heat and transport pose significant challenges to distribution system operators (DSOs) and transmission system operators (TSOs). These challenges include the choice between network upgrades or operating increasingly constrained networks, with a reliance on the flexibility of distributed energy resources (DERs). This study presents a novel market‐based coordination scheme, which allows both the DSO and TSO to access DER flexibility, while respecting distribution system limits. The DSO's objective in this work is to minimise the cost incurred by DSO adjustments to DERs, required to ensure stable distribution network operation. The methodology presented has the advantages of being compatible with existing TSO balancing market operation, and scalable enough to include multiple DSO markets coordinating with the TSO. The approach is demonstrated on a section of Great Britain distribution network, using high DER growth scenario data for the year 2030. The case studies demonstrate the proposed DSO market mechanism to maintain thermal and voltage limits during periods of peak demand and DER output. The DSO is given priority in using DERs to solve distribution network constraints, however, significant flexibility remains for the TSO even during periods of peak demand and maximum export. [ABSTRACT FROM AUTHOR]

The many well‐established advantages of distributed generation (DG) make their usage in active distribution networks prevalent. However, uncontrolled operation of DG units can negatively interfere with the performance of other equipment, such as tap‐changers, in addition to resulting in sub‐optimal usage of their potential. Thus, adequate scheduling/control of DG units is critical for operators of the distribution system to avoid those adverse effects. A linearised model of a multi‐objective method for coordinating the operation of photovoltaics, battery storage systems, and tap‐changers is proposed. Three objective functions are defined for simultaneously enhancing voltage profile, minimising power losses, and reducing peak load power. The formulated multi‐objective problem is solved by means of the epsilon‐constraint technique. A novel decision‐making methodology is offered to find the Pareto optimality and select the preferred solution. To assess to proposed model's performance, it is tested using 33‐bus IEEE test system. Consequently, tap‐changers suffer lessened stress, the batteries state‐of‐charge is kept within adequate limits, and the DG units operation is at higher efficiency. The obtained results verify the effectiveness of this approach. [ABSTRACT FROM AUTHOR]

This study proposes a stochastic optimisation programming for scheduling a microgrid (MG) considering multiple energy devices and the uncertain nature of renewable energy resources and parking lot‐based electric vehicles (EVs). Both thermal and electrical features of the multi‐energy system are modelled by considering combined heat and power generation, thermal energy storage, and auxiliary boilers. Also, price‐based and incentive‐based demand response (DR) programs are modelled in the proposed multi‐energy MG to manage a commercial complex including hospital, supermarket, strip mall, hotel and offices. Moreover, a linearised AC power flow is utilised to model the distribution system, including EVs. The feasibility of the proposed model is studied on a system based on real data of a commercial complex, and the integration of DR and EVs with multiple energy devices in an MG is investigated. The numerical studies show the high impact of EVs on the operation of the multi‐energy MGs. [ABSTRACT FROM AUTHOR]

Energy loss minimization, voltage profile improvement, and increasing reliability of the power system are the prominent advantages of distributed generation (DG) unit's integration in distribution systems. Therefore, optimal placement and sizing of DG become a critical issue. This article proposes a recently developed adaptive particle swarm optimization (PSO) algorithm known as phasor particle swarm optimization (PPSO) to solve the problem of optimal placement and sizing of DG units in radial distribution networks. The PPSO algorithm is based on modeling the particle control parameters with a phase angle (θ) transforming standard PSO into a self‐adaptive and parametric independent metaheuristic optimization algorithm. The main objective is to minimize the energy loss in the network considering various technical constraints and load variations. In particular, the proposed approach is implemented on a practical radial distribution feeder located at the Haripur area in Pakistan taking into account the hourly actual load values. Comparison of the devised PPSO algorithm with other techniques in the literature was done via an IEEE 33 bus test system. The results obtained by the proposed PPSO algorithm show that it enables a significant reduction in power loss for all the analyzed cases, and outperforms many of other solution techniques applied for the same problem. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Optimisation of cost and load flattening for a distribution network is attempted in this work. The objective function is described in terms of energy cost, CO2 emissions, real power losses, and load flattening. The solution is envisaged in terms of hourly scheduling of distributed generations (DGs), distributed battery energy storage systems (D‐BESSs), and plug‐in hybrid electric vehicles (PHEVs). An investigation in the reformulation of the cost of energy is carried out to eliminate the solutions involving excessive charging and discharging of BESSs/D‐BESSs and PHEVs. It is demonstrated that simultaneous optimisation of cost, CO2 emissions, real power losses, and load flattening cannot be effectively solved as a weighted sum objective function. An ε‐constraint method is applied to obtain the optimal scheduling to achieve cost optimisation, load flattening, and minimisation of CO2 emissions from the utility point of view. A case of decentralised multi‐agent optimisation problem is also formulated and compared. It is observed that the combination of the scheduling of DGs, BESSs/D‐BESSs, grid‐to‐vehicle/vehicle‐to‐grid can successfully be used to significantly reduce the system peak demand along with system cost, losses and CO2 emissions. [ABSTRACT FROM AUTHOR]

This paper proposes a market model for the purpose of optimisation of clustered but sparse microgrids (MGs). The MGs are connected with the market by distribution networks for the sake of energy balance and to overcome emergency situations. The developed market structure enables the integration of virtual power plants (VPPs) in energy requirement of MGs. The MGs, internal service providers (ISPs), VPPs and distribution network operator (DNO) are present as distinct entities with individual objective of minimum operational cost. Each MG is assumed to be present with a commitment to service its own loads prior to export. Thus an optimisation problem is formulated with the core objective of minimum cost of operation, reduced network loss and least DNO charges. The formulated problem is solved by using heuristic optimization technique of Genetic Algorithm. Case studies are carried out on a distribution system with multiple MGs, ISP and VPPs which illustrates the effectiveness of the proposed market optimisation strategy. The key objective of the proposed market model is to coordinate the operation of MGs with the requirements of the market with the help of the DNO, without decreasing the economic efficiency for the MGs nor the distribution network. [ABSTRACT FROM AUTHOR]

The present study proposes a corrective method of electric system overload provided that the wind farm is integrated into the distribution system, taking into account the congestion cost. The authors attempted to mitigate the overload and to monitor flow over transmission lines. Unified power flow controller device was the first suggestion utilised to solve this problem, then due to its extremely fast training and the excellent generalisation performance, extreme learning machine algorithm is employed. The fundamental point is the transmission line alleviation. In addition, other targets are realised: the load shedding avoidance, minimisation of losses and congestion cost. This study is also designed to utilise PowerWorld Simulator and MATLAB software to demonstrate methods for relieving transmission overloads. The accuracy of the proposed approach has been tested for Algerian (Adrar) 22‐bus system. Obtained results showed an improvement in power system behaviour. Simulation results are exposed, discussed and compared at the end of this study. [ABSTRACT FROM AUTHOR]

The adoption of environmentally friendly electric vehicles (EVs) is increasing over the years due to the increased awareness of energy and environmental challenges. However, the current growth is slow because of lack of proper charging infrastructures. This study proposes a multi‐objective synergistic planning model of an EV charging station considering the interaction between the distribution system and transportation networks as the fast charging of EVs affects the operation of both networks. The developed model minimises the power losses and voltage deviation of the distribution system and maximises the EV flow served by the fast charging station (FCS) simultaneously taking into account permissible waiting time and service radius of FCS. Multi‐objective grey wolf optimiser (MOGWO) algorithm is used to obtain the non‐dominated solutions and fuzzy satisfaction‐based decision‐making method is employed to reach final planning scheme. The effectiveness of the proposed model is investigated on the IEEE 123‐bus distribution system coupled with a 25‐node transportation network. The influence of different objectives, service radius and waiting time on the planning of FCS is also explored. Results reveal that the developed method can provide rational siting and sizing of FCS and it is also found that proper service radius and waiting time provide more convenience to the customer. [ABSTRACT FROM AUTHOR]

This article introduces a new method for optimizing the placement of a multiple of D‐Statcoms for voltage sag mitigation in distribution systems. The D‐Statcom's placement is optimally selected not only for improving system voltage sag caused by a single fault event but also for all possible fault events in the system of interest. Therefore, D‐Statcom's placement is optimized in a problem of optimization where the objective function is to minimize the system voltage sag index—SARFIx. D‐Statcom's effectiveness for voltage sag mitigation is modeled based on the method of Thevenin's superimposition for the problem of short‐circuit calculation in distribution systems. This article considers the case of using a multiple of D‐Statcoms with a proposed voltage compensating principle that can be practical for large‐size distribution systems. This article uses the IEEE 33‐buses distribution feeder as the test system for voltage sag simulation and influential parameters to the outcomes of the problem of optimization are considered and discussed. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [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]