Performance Of Distribution Network Research Articles

Energy storage systems with distributed generation in power network reconfiguration using improved artificial bee colony algorithm

Recently, the Distributed Generation (DG) structure has become an important aspect of daily planning and has achieved a variety of functions while maximizing the functionality of utilities. It should balance the energy equilibrium of the system components and the production limit. Uncertainties arise during the operation of the DG, represented by generator power, load requirements and fluctuations in electricity prices. The reactive power problem is the major concern associated with the DG system. This paper analyzes both DG and an energy storage system along with their optimal performance using a specific algorithm. For optimal analysis of DG and ESS, an Improved Artificial Bee Colony Algorithm (IABC) is proposed. The IABC evaluates the performance of distribution network. It takes DG and ESS into account for analyzing optimal design problems, the main goal of which is to minimize their reactive power dispersion functions. In addition, there are barriers to reducing the DG’s operating costs. The proposed method is implemented on the MATLAB platform and tested using the IEEE 33-bus system. To confirm the effectiveness of the proposed method, it will be compared with the existing methods such as artificial bee colony (ABC) and levy-based method, respectively.

A review on condition assessment technologies for power distribution network infrastructure

Reliable performance of the electricity distribution networks is critical to avoid outages and disruptions which may lead to substantial economic losses. Some of the important components of the electricity distribution networks include overhead cables, utility poles, cross-arms, substations, and transformers. These components are subjected to deterioration with aging and pose risks of failure creating safety concerns, specially under extreme weather conditions. Efficient maintenance and the use of accurate condition assessment techniques to monitor the integrity of the aforementioned components are key factors to be considered in managing the electricity distribution assets. This article presents a review of different condition assessment techniques employed for monitoring the electricity distribution infrastructure. The conventional inspection techniques and advancements in non-destructive testing methods are discussed outlining the relative advantages and disadvantages. Other than the normal failures of distribution infrastructure due to component ageing, unexpected and less frequent extreme weather events can have significant impacts on the resilience of the electrical power infrastructure. Thus, the effects of extreme weather conditions on the reliability of the electricity distribution networks and the failure rates of assets are reviewed in this study. Further, the maintenance and decision-making approaches implemented in the power distribution networks are also discussed.

Designing a bi-level flexibility market for transmission system congestion management considering distribution system performance improvement

One of the main challenges of Transmission System Operators (TSO) is the management of unexpected congestions due to sudden increases in demand levels or equipment failure. They can rely on demand-side flexibility resources to deal with these difficulties in this situation. The fact that these resources are often located in the distribution network necessitates coordination between TSOs and Distribution System Operators (DSOs). The purpose of this study is to present a market-based framework for transmission system congestion management through demand-side flexibility resources considering distribution network loss reduction. The proposed framework consists of two levels. At the first level, the TSO clears the flexibility market, and the only participants in this market are DSOs. The second level consists of local markets implemented in each distribution network and settled by DSOs. Prosumers can sell their proposed flexibility services in these markets. DSOs amend the prosumers’ bid prices for distribution network performance optimization and then submit them to the first level flexibility market. To evaluate the performance of the bi-level flexibility market, the proposed structure has been implemented on the IEEE 9-Bus transmission system. The system consists of two distribution networks that provide the flexibility required by TSO. Based on two constraints, the loading state of the distribution network (Technical) and the convenience of prosumers (Behavioral), three scenarios have been considered. According to simulation results, ignoring both technical and behavioral constraints will result in lower costs for the TSO.

Influencing Factors on Power Losses in Electric Distribution Network

Line losses reduction greatly affects the performance of the electric distribution network. This paper aims to identify the influencing factors causing power losses in that network. Newton-Raphson method is used for the loss assessment and the Sensitivity analysis by approach One-Factor-At-A-Time (OAT) for the influencing factors identification. Simulation with the meshed IEEE-30 bus test system is carried out under MATLAB environment. Among the 14 parameters investigated of each line, the result shows that the consumed reactive powers by loads, the bus voltages and the linear parameters are the most influencing on the power losses in several lines. Thus, in order to optimize these losses, the solution consists of the reactive power compensation by using capacitor banks; then the placement of appropriate components in the network according to the corresponding loads; and finally, the injection of other energy sources into the bus which recorded high level losses by using the hybrid system for instance.

Improvement of Distribution Network Performance by Optimally Allocating EV Charging Station

With zero emissions to the environment, electric vehicles (EVs) are the most environmentally friendly mode of transportation. The placement of EV charging stations (EVCS) in the Radial Distribution Network (RDN) is necessary to satisfy the demand of charging in various places while minimizing power loss on the power system networks. In the distribution system, distributed generation (DG) not only reduces power loss but also enhances power quality. To fully utilize the benefits of DG, it is necessary to find the optimal location and size in the distribution system. In this work, the ideal installation of EVCS has been consistently demonstrated in the IEEE 33 bus distribution network. In order to provide widespread charging facilities, the RDN has been split into three regions, and it has been established that each area has one charging station placed. The main purpose is to minimize the Active Power Loss and Voltage Deviation Index (VDI) to maintain a healthy power system network. Adding DG to the appropriate EV Station is obtained through optimization. This problem has been formulated as a problem of optimization for finding the best location to install EVCS in the IEEE 33 bus RDN by using the Symbiotic Organisms Search (SOS) algorithm. The obtained results have been validated and compared using the Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA).

Comparative Evaluation of Network Reconfiguration and Capacitor Allocation in Radial Distribution Network Performance Improvement

Comparative Evaluation of Network Reconfiguration and Capacitor Allocation in Radial Distribution Network Performance Improvement

A MIQP Approach Based on Demand Response in Distribution Networks to Improve the Multi-Objective Function in the Presence of Renewable Energy Resources and Batteries to the Subway Systems

The increasing expansion of devices such as electric vehicle charging stations, renewable energy resources, and electric subways, will cause an imbalance between load and production in the distribution network, which will lead to an increase in power losses, a decrease or increase in voltage and ultimately impose more costs on the independent system operator (ISO). In this paper, we have presented a mixed integer quadratic programming (MIQP) optimization model to improve the distribution network performance in the presence of these devices. The proposed model is a mixed integer model including demand side management modeling, energy storage system, battery to subway (B2S) system, optimal control of on-load tap changer (OLTC), step voltage regulator (SVR), fossil generation resources, renewable energy and capacitors, and shunt reactors. The considered multi-objective function is a scenario-based stochastic model, which accurately models the uncertainties in renewable energy resources. Paying attention to the nature of the proposed model will guarantee globally optimal solutions. The proposed model runs on the standard network of 33 buses, and the simulation results guarantee the optimal and accurate performance of the proposed model. The simulation results demonstrate that the outage of three distributed generation units from the network causes an average increase of 55% in energy losses, and the outage of three renewable units leads to an increase in emissions of about 40%. Another point received from the results illustrated that with the implementation of the proposed model under any load level of the network, as well as the outage of fossil and renewable distributed generation (DG) resources, no load shedding will occur in the network during the 24 hours. Finally, due to the short execution run time, the proposed model can be used for real and online grids.

Evaluation of current and future water demand scenario and hydraulic performance of water distribution systems, a case study for Addis Kidam Town, Ethiopia

The hydraulic performance and future water demand of water distribution networks are major factors affecting the efficiency of water distribution systems throughout the world. Currently, Addis Kidam Town in Ethiopia is facing many water supply challenges. Their existing water distribution system is inadequate experiencing significant water loss, pressure, and flow velocity. All becoming worse with forecast population increases. The main objective of this study was to evaluate the hydraulic performance of the water distribution network considering both the existing water demand, together with forecast future water demand. The study was undertaken in Addis Kidam Town in Ethiopia using static analysis and WaterGEMS V8i software. The data were collected using experiment tests, field observation, focus group discussions, and interviews. Sampling sizes of pipes and junctions of distribution networks were used to evaluate velocity and pressure changes of 12% and 15%, respectively, from high and low-pressure zones. The results of this study indicated that the existing distribution network was designed to supply a population of 8,906; however, the current population was 25,854. The existing system can accordingly not meet current demand. The current system was only supplying 19.5 l/c/d to each family and was only able to supply 45.2% of households. All compounded because water loss of the distribution network was 37.9%. Simulation of existing distribution network at junctions and pipes has both 26.6% and 4.3%, and 2.4% and 29.9% lower pressures and velocities during peak and minimum hourly demand, respectively. Model performance values of RMSE, MAE, R2, and NSE of distribution networks were 0.65, 0.40, 0.96, and 0.82 and 0.56, 0.38, 0.98, and 0.78 during the calibration and validation of pressure, flow, and tank level, respectively. The research recommends a two-phase strategic water distribution system response beginning by upgrading and expanding the water distribution network, to first achieve a supply of 30 l/c/d by 2032, and then lifting this to the 30–80 l/c/d range before 2042. The proposed water management upgrading approach is expected to establish a good water supply for all residential communities of the town facing comparable challenges. In general, this study’s findings showed that the existing water supply system could not meet the present demand, let alone meet future growth demand. The existing modeling highlighted that significant increases in supply are possible by targeting system improvements, together with the need to find additional supply to meet both present and future water demand.

Application of Three-Phase Power Flow Analysis to the Nigerian Distribution Networks

Single-phase power flow analysis is used to study most distribution networks in Nigeria. The use of single-phase-power flow analysis assumes that the network is balanced and that the conductor phases act identically. However, Nigerian distribution networks are highly imbalanced because of untransposed lines, irregularly distributed loads in conductor phases, mismatched conductor sizes, and spacing. Consequently, single-phase modeling of the networks fails to reflect actual network behavior, resulting in an incorrect power flow solution. This research presents the three-phase modeling of radial distribution networks for a three-phase-power flow study of Nigerian distribution networks. Olusanya's 54-bus and Ajinde's 62-bus distribution networks in Nigeria were evaluated, both of which were very imbalanced. Without making any assumptions about the network components, these two distribution networks were properly modeled. Each network's three-phase power flow study was carried out in the MATLAB environment. The power flow solutions for each network demonstrated unevenness in the voltage profile for each network phase, as well as inequality in the real and reactive power losses in each phase, indicating that the deployed three-phase-power flow analysis properly mirrored the underlying network characteristics. Therefore, applying three-phase power flow analysis to distribution networks is critical for proper assessment of distribution network performance.

An Optimization Method of Active Distribution Network Considering Time Variations in Load and Renewable Distributed Generation

Network optimization is one of an effective ways to enhance the performance of an active distribution network (ADN). Aiming to improve the operation and power quality of the ADN considering time variations in load and renewable distributed generation (RDG) power, a multi-time period optimization model and its dynamic solution method are proposed. Considering the real time load demand and power generation variation of RDG versus input parameters like wind speed and solar irradiance, the time variation models of load and RDG power output are developed. The minimum power loss and maximum absorption of RDG power are served as the optimization indexes to construct the dynamic muti-time period optimization model. A hybrid particle swarm optimization (HPSO) algorithm is presented based on integer coding and random coding technique, which can find the most satisfactory solutions for the proposed dynamic model. Considering the time variation of load and RDG power of ADN, the optimal network structure and RDG allocation scheme at any time interval are determined by analyzing the obtained solutions. Additionally, two ADNs with time variation in load and RDG are tested to verify the effectiveness and superiority of the proposed dynamic optimization model and HPSO algorithm. The simulation results show that the proposed method can improve the operation performance and RDG optimal utilization of the ADNs through muti-time period dynamic optimization.

The Role of Distributed Generation on The Performance of Electrical Radial Distribution Network

Purpose: This article provides available information on the role of distributed generation (DG) in the performance of a power distribution network. 
 Design/methodology/approach: The study reviewed articles about available methods for reducing technical losses in electrical distribution networks. The second step involved studying various researchers' views on renewable energy in some developing countries for introducing DG into a distribution network. The influence of DG on the economic performance of a distribution network. Finally, the study scouted for available information on the implementation of a demand response (DR) program on the performance of a distribution network in the presence of DG.
 Findings: Available information reveals that the reliability of DG for reducing the technical losses in a distribution network is higher than relying on alternating current controllers. There are indications of renewable energies in developing countries for introducing DG into a distribution network. According to the articles reviewed, the approach for the optimal location of DG did not include the combination of the voltage stability index and power loss reduction index. It is also worth considering using the power system analysis toolbox (PSAT) for DG sitting. The economic influence of DG on a distribution network's performance has not been evaluated based on the technical loss, generation cost, emission cost and reliability. It is also worth considering the benefits of demand response programs in the presence of DG.
 Research limitation: The review concentrated mainly on DG's influence in reducing technical loss. Articles relating to the effect of DG on other distribution network technical issues such as voltage stability, harmonics etc. also require attention
 Practical implications: Distribution network performance is essential for the operation of electrical gadgets. Therefore, improved distribution network performance will result in the economic development of a country.
 Originality/Value: This paper provides the platform that stimulates interest in using DG to improve the distribution network performance.

Improvement of distribution networks performance using renewable energy sources based hybrid optimization techniques

A very critical and integral part of the power system is the distribution networks. The final component of the power system, including transmission systems or consumers, is the distribution system (DS). This leads to the highest energy loss that happens. So improving the performance of distribution networks is required not only to provide the reliability of power supply but also to achieve the most economic cost. By optimizing the power flow and simultaneously minimizing the total emission cost and generation cost and taking into account the power losses, these objectives can be achieved. In recent years, heuristic methods are widely employed for solving such complex problems, and The main modern optimization techniques are genetic algorithm(GA). The most important issue in Evolutionary Algorithms is exploration vs. exploitation. Maybe GA is restricted for exploration features, what causes slow convergence and poor robustness Therefore, using the hybridization strategy, the main reason behind this is that such a hybrid approach is expected to create swape between the exploration and exploitation. This work presents performance improvement of a radial distribution networks using a new hybrid optimization technique of Genetic Algorithms (GA) with Equilibrium optimizer (EO) algorithm called Hybrid Genetic Algorithm Equilibrium optimizer (GAEO). It is used for optimum location and size of Renewable Energy Sources (wind energy, photovoltaic, fuel cell) on distribution systems. DG source locations and capacity have strongly influenced the improvement of the distribution network performance by reducing the entire system's power loss, enhancing the voltage profile, reducing fuel costs and emissions of contaminants.

A Critical Analysis of Modeling Aspects of D-STATCOMs for Optimal Reactive Power Compensation in Power Distribution Networks

Distribution static compensators (D-STATCOMs) can enhance the technical performance of the power distribution network by providing rapid and continuous reactive power support to the connected bus. Accurate modeling and efficient utilization of D-STATCOMs can maximize their utility. In this regard, this article offers a novel current-injection-based D-STATCOM model under the power control mode of operation for the reactive power compensation of the power distribution network. The versatility of the proposed D-STATCOM model is demonstrated by combining it with two of the most established distribution load flow techniques, viz., the forward–backward sweep load flow and the BIBC–BCBV-matrix-based direct load flow. Further, the allocation of the proposed D-STATCOM model is carried out under a multiobjective mathematical formulation consisting of various technical and economic indices such as the active power loss reduction index, voltage variation minimization index, voltage stability improvement index and annual expenditure index. A novel parameter-free metaheuristic algorithm, namely a student-psychology-based optimization algorithm, is proposed to determine the optimal assignment of the different number of D-STATCOM units under the multiobjective framework. The proposed allocation scheme is implemented on a standard 33-bus test system and on a practical 51-bus rural distribution feeder. The obtained results demonstrate that the proposed D-STATCOM model can be efficiently integrated into the distribution load flow algorithms. The student-psychology-based optimization algorithm is found to be robust and efficient in solving the optimal allocation of D-STATCOMs as it yields minimum power loss compared to other established approaches for 33-bus PDNs. Further, the economic analysis carried out in this work can guide network operators in deciding on the number of D-STATCOMs to be augmented depending on the investment costs and the resulting savings.

A review of battery energy storage systems for ancillary services in distribution grids: Current status, challenges and future directions

Battery Energy Storage Systems (BESS) are essential for increasing distribution network performance. Appropriate location, size, and operation of BESS can improve overall network performance. The appropriately scaled and installed BESS helps meet peak energy demand, improve the advantages of integrating renewable and distributed energy sources, improve power quality control, and lower the cost of expanding or re-configuring the distribution networks. This paper investigates the feasibility of BESS for providing short-term and long-term ancillary services in power distribution grids by reviewing the developments and limitations in the last decade (2010–2022). The short-term ancillary services are reviewed for voltage support, frequency regulation, and black start. The long-term ancillary services are reviewed for peak shaving, congestion relief, and power smoothing. Reviewing short-term ancillary services provides renewable energy operators and researchers with a vast range of recent BESS-based methodologies for fast response services to distribution grids. Long-term ancillary services will provide the distributed network system operators and researchers with current BESS-based bulk-energy methods to improve network reliability and power quality and maximize revenue from renewable energy generation. The review presents a list of energy storage policies and BESS projects worldwide with a cost-benefit analysis. The challenges for deploying BESS in distribution grids recommended solutions for the implementation challenges, and future research directions are also presented.

Performance Enhancement of Radial Power Distribution Networks Using Network Reconfiguration and Optimal Planning of Solar Photovoltaic-Based Distributed Generation and Shunt Capacitors

In this work, an efficient hybrid optimization approach entitled harmony search and particle artificial bee colony algorithm is proposed to deal with the distribution network reconfiguration and solar photovoltaic-based distributed generation and shunt capacitor deployment in power distribution networks to improve the operating performance of power distribution networks. The proposed hybrid algorithm combines the exploration and exploitation capability of both algorithms to achieve optimal results. The optimization problem is formalized which includes distributed generation and shunt capacitor locations, open/close state of switches as discrete decision variables, and the optimum operating point of compensation devices as continuous variables. An efficient spanning tree approach is utilized to track the optimal topology of the network. The validity of the proposed hybrid algorithm in handling the optimal planning problem of the distribution network is assured through eight different operating scenarios at three discrete load levels. The efficiency of the proposed performance enhancement approaches was validated using 69 node and 118 node distribution networks. The obtained results are compared against similar techniques presented in the literature.

The Impact of Collaborative Communication on the Physical Distribution Service Quality of Soft Drinks: A Case Study of Beverage Manufacturing Companies in Greece

This research aimed to use the collaborative communication aspects of information sharing, incentive alignment, and decision synchronization to explain physical distribution service quality in the soft drink demand chain. The research was prompted by a desire to learn more about a topic that has received little attention in Greece while also contributing information about the variables that influence the performance of soft drink distribution networks. Manufacturers in Greece provided the data. The aspects of collaborative communication were significant determinants of the physical distribution service quality. Physical distribution service quality was shown to be significantly predicted by incentive alignment and information sharing, but not by decision synchronization. This research shows that collaborative communication aspects such as information sharing, decision synchronization, and incentive alignment enhance physical distribution service quality in soft drink demand chains. The research used a primary sample of 200 study participants from different drink manufacturing plants around Greece. In our research, we focused on vertical cooperation between manufacturers and distributors and its effect on physical distribution service quality. This is a relatively unexplored topic in the developing world. According to the scholars cited in the literature review, information exchange, incentive alignment, and decision synchronization improve physical distribution service quality in demand chains.

A novel artificial hummingbird algorithm for integrating renewable based biomass distributed generators in radial distribution systems

Improving the performance of the electric distribution network is essential to meet the needs of the customer and guarantee the service continuity. Installing generators with small sizes known as distributed generators (DGs) can contribute to enhance the network operation by mitigating the network loss and improving the voltage profile. Integrating these generators in inappropriate places can cause serious consequences to the network operation. Therefore, this paper proposes a novel metaheuristic approach of artificial hummingbirdalgorithm (AHA) to identify the best locations and sizes of biomass-based DGs in radial distribution network. The proposed approach has enriched exploration and exploitation phases that enhancing its search capability and avoiding stuck in local optima. The network active power loss and the voltage deviation are selected as the targets to be minimized. Moreover, a new version of AHA is programmed to solve multi-objective problem with the purpose of mitigating both targets. The analysis is conducted on three radial distribution networks of IEEE 33-bus, IEEE 69-bus, and IEEE 119-bus. Three scenarios are implemented in each network, the first one is minimizing the active power loss, the second one is mitigating the voltage deviation, and the last one is multi-objective problem. Also, biomass-based DGs with unity, fixed, and optimal power factors are analyzed. Excessive comparison to fractal search algorithm, particle swarm optimizer, genetic algorithm, the whale optimization algorithm, sperm swarm optimization, tunicate swarm algorithm, pathfinder algorithm, seagull optimization algorithm, and sine cosine algorithm, multi-objective water cycle algorithm, multi-objective grey wolf optimizer, and multi-objective sparrow search algorithm is conducted. Moreover, statistical tests of Wilcoxon, Friedman, ANOVA, and Kruskal Wallis are performed to assess the performance of the proposed approach. The gotten results confirmed the preference and competence of the proposed approach in integrating the biomass-based DGs in radial distribution networks.

Electrical distribution grid of Kirkuk City: A case study of load flow and short circuit valuation using ETAP

The load flow study and short circuit analysis can be considered as the backbone of the electrical power network. This study based on real data collected from 12 substations, each substation contains many feeders provide the electricity network of Kirkuk city (a city in Iraq located at the north of Baghdad). The methodology of this article depended on using the Electrical Transient Analyzer Program (ETAP) software in assessing the performance of Iraqi electrical distribution network (Kirkuk city as a model) by starting modeling and simulation in order to assess the reliability through testing the load flow, and short circuit test. A complete study of load flow assessment of an actual Kirkuk city power distribution network with actual load values is presented (data have been taken from the Directorate of Electricity Distribution of Kirkuk city). The results of modeling the whole city and the detailed reports of this study can give us a comprehensive assessment with the presence of actual loads values, including total demand, PF, transmission line parameters, and the weakness points of the electrical grid.

Optimal integration of battery energy-storage system with high penetration of renewable energy in radial distribution network

Abstract Considering the intermittent nature of renewable energy, a storage system to reserve power in off-peak hours and then to supply it during peak hours is necessary. However, if these storage devices in a network are not placed in an appropriate manner, the advantages can never be achieved. In this study, the allocation and sizing strategies of a battery energy-storage system (BESS) in an optimal way are proposed to improve the performance of the radial distribution networks. The test network adopted is a standard IEEE 33 bus network that is integrated with solar power. Simulations are carried out in DIgSILENT PowerFactory for the distribution network model and the process of optimization is done through MATLAB®. The optimization algorithm adopted is the genetic algorithm. The system is studied for 24 hours with a step size of 15 minutes, employing a time-sweep analysis of dynamic load. It is studied under three different scenarios and the results are compared. The results illustrate a considerable reduction in power losses in the case of the optimized BESS. The total losses before the optimization process are 16 365.57 kW. The total losses after the employment of the proposed solution are 10 246.5 kW, which means that the losses are reduced by ≤62%.

Distribution networks performance improvement by sectorisation and operating pressures reduction – case study: babadag town

Abstract The cumulated effects of climate changes and accelerated urban development, amplified by insufficient funding and/or capacity to implement proactive methods and strategies for monitoring and optimization of water supply systems negatively impact the operation and overall efficiency of these systems, generating considerable problems regarding public comfort and safety and also service costs. Out of all problems, the most tangible issues for the final user are the ones related to the distribution network – the closest system component. In order to address these problems, an integrated analysis of the conditions of each urban area is required, accounting for actual water demand, pressure requirements, network configuration, power consumption and development forecasts. This article presents the set of measures proposed for optimisation of the distribution network of Babadag Town from Romania, consisting of changes intended to improve the hydraulic capacity of the network and also on reducing the water loss based on water balance evaluation and hydraulic modelling of existing and proposed network configurations.