Distribution Network System Research Articles

Principal component analysis in long term assessment of total viable plate count of municipal water distribution network system in healthcare facility

The microbial quality of water is a critical safety aspect that should not be overlooked, especially when considering human consumption in the facilities for healthcare and the treatment of health compromised populations. The present work aimed to study a municipal network for city water within a healthcare facility microbiologically. The implementation of multivariate analysis was conducted over collected data to decipher trends of the microbiological count of samples from different points-of-use. The statistical study involved an Eigenvalue determination, score graph, loading plot study and outlier diagram. Data showed clustering tendency with aberrant values could be observed. The first component appeared to be associated with bioburden density in the water. While the other component showed a link to the relative locations of the distribution points in the facility and the length of the water lines from the source feeding city water to a great extent. The two components explained more than 55% of the variations in data. A property that highlighted a strong agreement between the order of points-of-use in the loading plot with that of ratio factor which was obtained from the Total Viable Count over the hypothetical distance of sampling port from the reference feeding entrance. Thus, there was evidence of variation in the microbial quality affected by the biological stability of the water distribution system that needed attention and an improvement plan for better control of microbial content in city water to prevent possible excursions in the future. The study showed a valuable perspective approach for the quantitative examination of the microbiological stability of the municipal water distribution network system.

Analysis of IEEE 33, 34 and 69 Bus Systems using Gauss Seidel

Abstract: Optimum power flow studies to minimize either the power distribution losses or the cost of power drawn from the substation, without affecting on the voltage regulation. This paper discusses the concept of Gauss Seidel method to be used with load flow analysis control for stability of large power systems. Voltage Stability has become an important issue of power system stability. This paper work concentrates on simple and efficient load flow analysis of radial distribution system for finding voltage magnitudes and also the voltage profile. This load flow study of radial distribution system network is of prime importance for effective planning of load transfers. Power companies are interested in finding the most efficient configuration for minimization of real power losses and load balancing among distribution feeders to save energy and enhance the overall performance of the distribution system. This test has been performed on the 33, 34 and 69 bus systems with the use of MATLAB software

KAJIAN TEKNIS PENYEDIAAN AIR BERSIH DI DESA OEBOLA LUAR KECAMATAN FATULEU KABUPATEN KUPANG

The availability of clean water in the Oebola village community has not yet been available due to several obstacles, such as the distance of the water source from the residential area has not yet received the service of a clean water distribution system network that makes it easier for the community to obtain clean water to meet their daily needs. This study aims to determine the pattern of clean water consumption, the potential of water sources, the rate of clean water usage in 2020-2030, and strategies to meet the needs of clean water. The research method used in this research is descriptive method. The results of the analysis show that the current use of clean water is 43 liters/person/day less than the standard 60 liters/person/day, there is an adjustment to the limited water use in daily use such as bathing and washing habits. The potential available water sources from the Oetulu spring with a minimum discharge of 1.27 liters/second is smaller than the demand in 2020, which is 2.89 liters/second and in 2030 it is 4.39 liters/second. The strategy to fulfill clean water needs in Oebola Luar village is to provide clean water distribution system network services that make it easier for the community to obtain clean water.

Evolution of Novel Process for Smart Inverter for High Penetration of Rooftop Solar Energy in Power Utility With Secondary Distribution Network – A Review

With the critical change of Rooftop Solar Photovoltaic Energy System (RSPES) between the two different Renewable Energy Systems, the real problems, impacts and a few working qualities of the housetop sunlight based PVs with Low Power Utility Network Distribution System (DS) are currently to be examined and explored throught out the worldwide. The most vital target of review looks into about the load flow in LV Networks and searches a way for implementing high penetration PV network. The study papers discuss the implementation of the Smart Inverter-coordinated secondary distribution system with the proximity of distribution generation (DG) units. This paper reviews based on the methods which are utilized to tackle the issues and improvement of performance in the rooftop solar photovoltaic energy system in the period between 2014 to 2017.

Designing a two-stage transactive energy system for future distribution networks in the presence of prosumers’ P2P transactions

Electric distribution systems are becoming bidirectional and active due to rise of distributed energy resources, electric vehicles and prosumers. In this environment, a transactive energy system is required to not only coordinate the network with respect to the technical constraints, but also model P2P transactions between end-users, taking into account their data privacy and scalability issues. Therefore, a new two-stage transactive energy system is developed to balance the distribution network considering the behavior of different participants. At stage one, the role of orchestrator is modeled to manage the distribution network and its constraints by purchasing energy from up-stream grid, defining dynamic distribution locational marginal prices (DLMPs) or tapping on its storages. At stage two, prosumers make distributed decisions to use grid-sourced/self-generated energy or participate in P2P transactions based on the received DLMPs from stage one and their preferences. This two stage mechanism is solved through an iterative process until stopping criteria are met. The results indicate reduction in total import cost and energy from grid, compared to when no P2P transaction is considered. It is also shown that the proposed model converges to the optimal solution in proper time when the number of participants is increased.

Coordinated Control Strategy of Electricity-Heat-Gas Integrated Energy System Considering Renewable Energy Uncertainty and Multi-Agent Mixed Game

The Integrated Energy System (IES) can promote social energy transformation and low-carbon development, which is also an effective means to make contributions to energy structure optimization, energy consumption reduction, and new energy consumption. However, the IES has the characteristics of complex energy flow, and strong uncertainty with multi-agents. Therefore, traditional mathematical optimization models are difficult to comprehensively and accurately reflect the interest needs of different entities in the integrated energy microgrid. Aiming at this problem, a two-level collaborative control strategy model of “electricity-heat-gas” IES based on multi-agent deep reinforcement learning is proposed in this paper. The upper layer of this model is a multi-agent hybrid game decision-making model based on the Multi-Agent Deep Deterministic Policy Gradient algorithm (MADDPG), and the lower layer contains the power and gas flow calculation model. The lower model provides the upper model with the energy flow data of the IES and the upper layer rewards the decision-making behavior of the agent based on the energy flow data provided by the lower layer. Effectively solving the high-dimensional nonlinear optimization problem existing in the complex coupling network, this method can improve the convergence and training speed of the model. In this paper, the IEEE 33-node distribution network and 20-node gas network coupling system are provided to verify the model. The simulation results show that the proposed collaborative control strategy method can provide effective decision-making for electric-agent and gas-agent and realize the efficient and economic operation of the integrated energy system.

Optimal Allocation of Plug-in Electric Vehicle Parking Lots for Maximum Serviceability and Profit in the coupled distribution and transportation networks

Optimal planning and management of electric vehicle parking lots (EVPLs) can be an effective approach for improving the operation of both the distribution system and traffic networks. However, the limited land areas of cities can be an obstacle for constructing a large number of parking lots (PLs). This paper proposed a model for optimal siting and sizing of EVPLs as well as their charging schedule to maximize the total profit of their owners, while maximum parking demand of plug-in electric vehicles (PEVs) can be satisfied. In the proposed model, the purpose of trips, number of PEVs, plus their arrival and departure time in different urban areas are considered. Distribution network constraints are also taken into account using linearized load flow equations. The proposed model is implemented in a 37-bus distribution system coupled with a 25-node transportation network which includes four different areas in terms of PEV travel type. The simulation results show the effectiveness of the proposed model to cover the parking demand of PEVs with a limited number of PLs.

Optimal PV Placement to Reduce Power Loss and Improve Voltage in Distribution Network System Using K-means Clustering Method

Placing the PV in the right location will maintain the utility voltage, but if the placement of PV in the wrong location will cause the stability of the system to be affected. In this study, optimization of PV placement uses the K-means Clustering method. This method will group each node in the system from the point of view of operating characteristics LSF (loss sensitivity factor) and dV (voltage deviation). The results of grouping each bus with the K-means Clustering method will be the basis for determining the location of PV placement in the IEEE 37 and 69 bus distribution systems. In this method, grouping results are used based on the size of the proximity and have the same characteristics with each other. In determining the optimal location for PV placement, the addition of PV will reduce power losses and improve voltage. Optimal PV location placement in the IEEE 37 bus distribution system is placed on 3 buses with a power capacity of 60% where the value of power losses drops to 176.2 kW and the voltage profile is the best but there are some buses that are still under voltage and overvoltage. Meanwhile, the most optimal PV location for the IEEE 69 bus distribution system is placed on a 6 bus with a power capacity of 60% where the value of power losses drops to 149.5 kW and the voltage profile of each bus is in normal condition..

Evaluation of Priority Control District Metered Area for Water Distribution Networks Using Water Quality-Related Big Data

Partitioning methodologies such as district metered areas (DMAs) are being applied to the stable maintenance of water distribution network systems in normal conditions such as daily operation and abnormal conditions such as water quality and leakage accidents. However, management and evaluation through the use of existing DMAs generally only have the primary goal of stable water quantity and pressure management. Therefore, the methodology can be limited to achieving the direct effects of water quality parameters such as decreased water age, proper management of residual chlorine, and decreased water quality complaints. This study uses a methodology for determining and prioritizing water quality-oriented Priority Control District Metered Areas (PCDMAs) for stable water quality management to respond to the recent large-scale rusty (red) water crisis in Korea. First, 4 evaluation criteria and 11 evaluation indicators were derived using various water quality-related structured data (water quality measurement data, pipeline data, etc.) and unstructured data (water quality complaints, etc.) based on the Geographic Information System (GIS). A comprehensive prioritization assessment was carried out with multi-criteria decision-making methods based on the analytic hierarchy process. As a result, particular indicators of complaint of water quality and the existence of vulnerable facilities (hospitals, school, etc.) were analyzed as the top five priorities, and it was shown that to be important criteria in determining water quality-oriented PCMDAs. Finally, the proposed methodology was applied to the B metropolitan city of the Republic of Korea, and the evaluation results of all the districts were derived and analyzed. The study shows that the data-based water distribution network PCDMAs selection methodology can be used as a decision-making tool to improve the accuracy and reliability of the operation and management (O&M) of the water distribution operator’s water distribution network. In future research, it will be necessary to evaluate PDDMA with detailed data related to the pipe deterioration (buried environment, the condition of internal/external of the pipe, etc.), which had a significant threshold due to data limitations. And it would be possible to make a real-time evaluation of PCDMA with the real-time water quality test data.

Line Loss Interval Algorithm for Distribution Network with DG Based on Linear Optimization under Abnormal or Missing Measurement Data

Data collection is more difficult in distribution network than transmission networks since the structure of distribution networks is more complex. As a result, data could be partly abnormal or missing, which cannot completely describe the operation status of distribution network. In addition, access of distributed generation (DG) to distribution network further aggravates the variability of power flow in distribution network. The traditional deterministic line loss calculation method has some limitations in accurately estimating the line loss of distribution network with DG. A line loss interval calculation method based on power flow calculation and linear optimization is proposed, considering abnormal data collection and distribution network power flow variability. The linear optimization model is established according to sensitivity of line loss to the injected power and sensitivity of transmission power of first branch to the injected power. Introducing the scheduling information into the optimization model, a reliable line loss fluctuation interval can be obtained which actual line loss locates. The effectiveness of the proposed algorithm is verified in IEEE 33-bus distribution network system.

Allocation and Sizing of Photovoltaic Systems to Reduce Power Losses and Economic Aspects using a new PSO approach

In this paper is proposed a new method for optimal allocation and sizing of Photovoltaics (PVs) systems in power distribution network to reduce losses in feeders and minimize the economic aspects of the PVs implementation. The proposed technique, called Modified Particle Swarm Optimization with Dynamic Momentum (MPSO-DM) is proposed so that can be applied in distribution system, that requires a high number of decision variables in the optimization process. This becomes necessary because the classical Particle Swarm Optimization (PSO), in general, presents a performance drop in the exploration of the search space when applied to these situations. The proposed method was tested in a real distribution network of the Federal University of Paraiba (79 buses), which results show a improvement in performance, yielding better solutions when compared to the traditional Modified Particle Swarm Optimization (MPSO) method and MPSO with linear decrement inertia weight.

Optimal Battery Sizing for Frequency Regulation and Energy Arbitrage

This paper proposes an optimization methodology for sizing and operating battery energy storage systems (BESS) in distribution networks. A BESS optimal operation for both frequency regulation and energy arbitrage, constrained by battery state-of-charge (SoC) requirements, is considered in the proposed optimization algorithm. We use utility historical data as input in a case study on a real-world distribution circuit. The results indicate that a BESS generally brings high profits by participating in the frequency regulation market and should be sized to its highest allowable power capacity rather than its energy capacity.

Kendali Sistem Tegangan Baterai Peralatan 20 kV PT PLN Bontang

The protection system is essential in the 20 kV distribution network system. The 20 kV equipment control system is supplied from 2 sources: PT (Potential Transformer) and DC voltage supply (Battery). If the protection relay and mechanics do not get a DC voltage supply, it will have an impact on the equipment not being able to trip when there is a disturbance in the network. There is no DC voltage supply due to battery failure or damage. For this reason, it is necessary to operate the tool manually, which results in the normalization process taking longer because it takes time and long distances, so the duration of outages is even greater. In this study, a monitoring system for the battery of the equipment will be made where previously observations were made about the need for this tool. The method used by the tool uses the blynk application as a receiver of direct voltage and temperature measurement reports that are connected to the gsm module. As a microcontroller processes, Arduino Nano commands from intelligent phones, generating a measurement report from the battery. GSM SIM 900 module as a data receiver and sender in the system. This tool is easy to apply to the system because it does not require a sufficient additional voltage source from the battery. The results of this study become a solution for companies to improve their 20 kV. distribution network system.

A resilience-oriented planning of energy hub by considering demand response program and energy storage systems

Energy hub systems meet the needs of customers in different forms of energy by coordinated operation of different infrastructures, thereby improving system flexibility, reducing losses and reducing operating costs. Due to the increase in the construction of energy hub systems in distribution networks, the issue of optimal design of energy hubs has attracted much attention. Therefore, this study presents a comprehensive model for hub design, in which the technical, economic and security criteria of the hub are fully considered. In the proposed model, the design problem is solved by considering all the operating constraints and seasonal variations of different loads and solar radiation are also taken into account. Uncertainties of electrical, heating and cooling loads as well as the output power of photovoltaic (PV) panels have been considered and in order to model these uncertainties, Monte Carlo simulation approach has been utilized. Besides, in order to improve the resilience of the hub in case of emergency conditions, uncertainties related to the outage of the equipment have been considered in the design problem. The design problem is modeled as a mixed-integer linear programming (MILP) optimization problem and the simulation results indicate that considering the uncertainties of equipment outages along with the load and radiation, despite a 26.51% increase in investment cost, leads to a significant improvement in hub resilience under emergency conditions. Also, the results demonstrate that the implementation of the demand response (DR) program has reduced the demand for power during peak hours, thereby reducing the installed capacity of the combined heat and power (CHP) unit.

E-Library Management System

Internet and Distributed Network System created scope for research in the area of information systems and its related fields. Digital Library, one of the most recent developments in Library and Information Science, helps its user to seek information through a web browser. Digital Library is an organized assortment of information, with its supported services and a place where the information is kept in digital format and can be retrieved over a network. For the last decade, researchers are focusing on the users of Digital Library to develop a more efficient and effective system to provide quality service to users. This paper aims to provide literature on Digital Library for its users that may be helpful for future research. The paper discusses the users-centric approach in the context of Digital Library. Researchers are working on system up-gradation by using wireless technology to connect with end-users directly with libraries. Further, other areas such as user Perception, Attitude, Adoption, and Satisfaction with the digital library are also discussed. Keywords — Digital Library, Users centric approach, Users satisfaction strategic planning Users perception; Digital library literature.

Optimal allocation of energy storage systems, wind turbines and photovoltaic systems in distribution network considering flicker mitigation

Renewable energies have introduced themselves as efficient resources for power production but their integration into power grid makes some challenges during operation. One of these challenges is the negative impact of wind turbines (WTs) on power quality. Flicker produced by WTs is one of the most important parameters which significantly affects power quality of distribution networks. In this paper, to mitigate flicker produced by WTs, distribution network planning problem is solved by considering power quality issue. For this aim, in the objective function, in addition to power losses and energy storage system (ESS) cost, flicker emission and voltage deviation are also minimized. Due to the complexity of the planning problem, crow search algorithm with differential operator (CSAd) is proposed to optimally site and size WTs and ESSs. In CSAd, new solutions are generated by using the information of high-quality solutions. To investigate the impact of various factors on the network performance, the planning problem is solved at different scenarios: (1) Siting and sizing ESSs, (2) Siting ESSs, WTs and PVs as well as sizing ESSs and (3) Siting ESSs, WTs and PVs as well as sizing ESSs and WTs. Simulation results show that optimal siting and sizing of ESSs and WTs can considerably improve the distribution network parameters in terms of power losses and flicker emission. Moreover, the proposed approach produces more accurate and robust results than the other studied methods.

Research on Short-Term Low-Voltage Distribution Network Line Loss Prediction Based on Kmeans-LightGBM

Due to the lack of data quality in real production environment, the traditional line loss calculation method cannot be applied, thus through the investigation of various information systems’ operation in power supply enterprises, a short-term low-voltage distribution network line loss prediction algorithm based on Kmeans-LightGBM is proposed. Operating data quality evaluation system of low-voltage distribution network was set up based on Hadoop platform, the feature dimensions were expanded by feature engineering, then those with no multicollinearity and high correlation with the line loss were selected, data normalization was again performed, Kmeans clustering algorithm was used to cluster the area and then, LightGBM algorithm was used to predict the classes within the area of line loss. Finally, the line loss of the numerical inverse normalization was found and validated with Beijing Power Grid of a low-voltage distribution network. By comparison, the model’s prediction accuracy is found to be higher than BPNN, FOA-SVR and traditional LightGBM.

Multistage Expansion Planning of Active Distribution System Network

Introduction: This paper presents an approach for multistage expansion planning of the active distribution system network problems by considering multiple strategies based on system investment cost, including renewable energy sources based on distributed generation units, operational cost, and reliability. Objective: The developed framework model fulfills the prospects related to techno-economical and reliable multistage expansion planning of active distribution system network for the sustainable development of electric power system. Methods: The mathematical model of the multi-objective function has been developed with the investment decision variables to compute the investment cost. The reliability of the active distribution system network is evaluated in non-supplied energy costs under contingency conditions with and without DGs. Result: The result validates the constraints associated with planning, investment decisions, power quality, and reliability of the system. Conclusion: This study also demonstrates the improvement in per unit (p.u.) voltage of bus nodes for each period of network expansion with DGs over the planning horizon. The proposed method is tested and validated on a 54-bus, 11 kV long-term active distribution network.

Line Loss Prediction of Distribution Network Based on BP Neural Network

Distribution network line loss calculation refers to the calculation of the electrical energy loss, which is generated by all components in a distribution network system in a given period of time. Distribution network, as the end of the power network, is directly connected with users; there are many equipment on the network; the system has impedance, electric energy in the process of conversion, transmission and distribution with a lot of loss, so the calculation of distribution network line loss has very important economic significance. In addition, with the development of power network construction, the rationality of distribution network topology design and the comparison of practical effects of various measures need the guidance of line loss calculation. Line loss and line loss rate is one of the main criteria to reflect the operation of distribution system. Reducing line loss of distribution system is very important for the effective use of power and economic operation of distribution system. In order to better find the effective reduction method and lay the foundation for the scientific establishment of linear contraction targets. This study uses a line loss calculation method based on BP neural network. The method uses the super matching property of the network to map the complex nonlinear relationship between the line loss and the characteristic variables and stores the evolution of the line loss changes with the changes of the structural and operational variables of the distribution line. On the basis of analyzing the theoretical methods, management methods, and various loss reduction measures of power loss calculation, this study also analyzes the status quo and existing problems of line loss analysis and calculation and collects data from line loss calculation and theoretical line loss calculation methods. This study discusses in detail the method and idea of the application of the improved neural network in the estimation of distribution network line loss, and it is used to predict the line loss in a certain area, and the prediction result is good.

Multi-stage resilience scheduling of electricity-gas integrated energy system with multi-level decentralized reserve

Extreme events pose threats to secure and consistent supply of electricity-gas integrated energy system (EGIES), and adequate resilience is essential for improving risk defense abilities. Considering the constraints of power distribution network (PDN) and natural gas system (NGS), a multi-stage strategy integrating multi-level decentralized reserve is proposed for resilience enhancement in EGIES. Storages of multi-area community integrated energy systems (CIESs) serve as the secondary reserve while the primary reserve, i.e., independent electric power/natural gas system, fails to meet reserve requirements. Furthermore, the thermal storage of building air on the consumption side is taken as the tertiary reserve, so as to obtain a better emergency response effect. The scheduling framework consists of reserve calculation, economic scheduling, and fault restoration. On the basis of multi-area reserve calculation, day-ahead economic scheduling is conducted, maintaining adequate reserve with consideration of decentralized reserve constraints; thus, high-priority demands can be recovered in case of supply disruptions. In addition, the flexible topology of PDN is utilized to facilitate the restored loads by optimal islanding partition. Via conic relaxation conversion, the original nonconvex model is tracked into a unified mixed-integer second-order cone programming (MISOCP) formulation, which can be effectively and accurately solved. Finally, numerical study on a modified IEEE 33-bus test system and a modified 7-node gas system connecting multiple community integrated energy systems shows the effectiveness of the proposed resilience strategy.