Advanced Distribution Automation Research Articles

Development of fault cause estimation method for distribution line

AbstractWe are planning to develop the new Advanced Distribution Automation System (ADAS) equipped with optical communication network and sectionalizer with sensor for more grid reliability and efficiency on maintenance operation. The new system is featured with the function of fault cause or damaged part estimation. The new sectionalizer captures the waveform of electrical line surge originated by fault and the system analyzes the waveform for this function. This paper mainly introduces the system configuration of ADAS and an early stage examination of fault cause estimation technology.

Development of Fault Cause Estimation Method for Distribution Line

We are planning to develop the new Advanced Distribution Automation System (ADAS) equipped with optical communication network and sectionalizer with sensor for more grid reliability and efficiency on maintenance operation. The new system is featured with the function of fault cause or damaged part estimation. The new sectionalizer captures the waveform of electrical line surge originated by fault and the system analyzes the waveform for this function. This paper mainly introduces the system configuration of ADAS and an early stage examination of fault cause estimation technology.

Navigating Challenges for the Electric Control Center of the Future

Electric utilities have been undergoing unprecedented change in the past decade and have responded in part by investing in modernizing the electrical grid. This includes investing in advanced distribution automation and controls, distributed energy resources (DERs), and embracing new operational technologies to derive value from these investments. Utilities are embarking on new technologies and applications, digitizing workflow business assets and processes to support remote office and field work while continuing to provide safe and reliable delivery of power to customers.

Architecture Deployment for Application of Advanced Distribution Automation Functionalities in Smart Grids

Architecture Deployment for Application of Advanced Distribution Automation Functionalities in Smart Grids

Optimal allocation of protection and control devices in smart distribution systems: Models, methods, and future research

The fundamental goal of the distribution system operator (DSO) is to serve its customers with reliable and low-cost electricity. Failures in power distribution systems are responsible for 80% of customer service interruptions. The emergence of smart distribution system (SDS) with advanced distribution automation (DA) and communication infrastructure offers a great opportunity to improve reliability, through the automation of fault location, isolation, and service restoration (FLISR) process. DA includes the installation of protection and control devices (PCD). The use of PCD makes fault management more efficient, reduces average outage duration per customer in case of faults, reduces costs due to unsupplied energy, and improves distribution system reliability. Although the use of PCD remarkably enhances distribution system reliability, it is neither economical nor affordable to install them in all potential locations. To obtain the optimal allocation of PCD (OAPCD), an optimisation problem has to be formulated and solved. Several models and methods have been suggested for the OAPCD in SDSs. Herein, an overview of the state-of-the-art models and methods applied to the OAPCD in SDSs are introduced, identifying the contributions of reviewed works, identifying advantages and disadvantages, classifying and analysing current and future research directions in this area.

The Role of Advanced Distribution Automation in Smart Grid

The Role of Advanced Distribution Automation in Smart Grid

A Systemic Approach for Assessment of Advanced Distribution Automation Functionalities

The lack of information regarding the systemic behavior of new software and hardware before introducing them for controlling and operating power networks consists of a major challenge for power distribution utilities towards a smart grid implementation. In this context, this paper describes an innovative and cost-effective test platform for advanced distribution automation (ADA) functionalities. The platform integrates a steady-state power system simulator, intelligent electronic devices, smart meters, communication infrastructure, and typical operation systems, using a cyber-physical system approach. The development of such platform originated a novel smart grid emulator, aiming at the execution of systemic tests and validation of ADA functionalities in a controlled environment, allowing systemic analysis rarely found in hardware-in-the-loop (HIL) testbeds. Through such an approach, it is possible to predict and solve typical issues that would be typically noticed only in field implementation. The study case presents tests of a specific algorithm for downed conductor location, considering the environment that the power distribution utility would have through the deployment of a smart grid infrastructure. The paper also discusses the robustness of the event-driven synchronization as an interface technique for HIL and software-in-the-loop environment, which is responsible for integrating operation systems, field equipment, and the power system simulator.

Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

In this era of advanced distribution automation technologies, demand response is becoming an important tool for electricity network management. The available flexible loads can efficiently help in alleviating the network constraints and achieving demand-supply balance. Therefore, this forms the rationale behind this paper, which aims to implement a multi-agent system framework in order to achieve flexible price-based demand response. A genetic algorithm-based multi-objective optimization technique is applied to determine the optimal locations and the amount of required demand reduction in order to keep the network within statutory limits. The methodology is based on probabilistic estimation of the granularity of total available flexible demand from shiftable home appliances in each low-voltage feeder. Moreover, an optimal decision making for the start time of appliances upon receiving a real-time price signal is proposed. This is accomplished by considering the willingness to participate as well as price demand elasticity of the different clusters of customers. To fully demonstrate the feasibility and effectiveness of the proposed framework, a modified IEEE 69 bus distribution network comprising 1824 low voltage residential customers has been implemented and analyzed.

Underground and overhead monitoring systems for MV distribution networks

The focus on enhancing the reliability and efficiency of the power grid has led to the implementation of the Smart Grid concept. This concept is based on the deployment of automation, namely advanced distribution automation (ADA) applications, and control technologies relying on the availability of parameters such as voltage, current, temperature etc. acquired from certain nodes of the grid. For a long period of time, the monitoring of the overhead distribution network has known to have a continuous evolution and the line-type stand-alone intelligent sensors, commercially available at this time, are the proof of that. While monitoring such parameters may be typically available in overhead distribution locations, it is not the same in underground distribution locations. Measuring in utility vaults or pad mounted cabinets is not as critical as in cable chambers/manholes, due to the accessibility provided by equipment such as transformers, switches etc. Recently, new developments in sensor, intelligent electronic devices and communication technologies have opened the door to attractive alternatives for monitoring the underground distribution network in general and in cable chambers/manholes in particular. An example of such a monitoring system is presented in this study.

Methods for Harmonic Analysis and Reporting in Future Grid Applications

The rollout of advanced metering infrastructure, advanced distribution automation schemes, and integration of generation into distribution networks, along with a raising of awareness of power quality (PQ), means that there is an increase in the availability of power system monitoring data. In particular, the data for harmonics, whether it is voltage or current harmonics, is now available from a large number of sites and from a diverse range of PQ instruments. The traditional analysis and reporting of power quality examines harmonic orders to the 50th. This means that the harmonic data available for analysis are significantly larger than, for example, steady-state voltage variations where only a few parameters are examined (e.g., the voltage on each phase). Higher frequency components, sometimes called high-frequency harmonics, in the 10–250 kHz range arising primarily due to power-electronic interfaced generation are also becoming significant. Given the vast amount of harmonic data that will be captured through grid instrumentation, a significant challenge lies in developing methods of analysis and reporting that reduces the data to a form that is easily understood and clearly identifies issues but does not omit important details. This paper introduces a number of novel methods of analysis and reporting which can be used to reduce vast amounts of harmonic data for individual harmonic orders down to a small number of indices or graphical representations which can be used to describe harmonic behavior at an individual site as well as at many sites across an electricity network. The methods presented can be used to rank site performance in order for mitigation strategies. The application of each method described is investigated using real-world data.

Reliability Improvement of Power Distribution Systems using Advanced Distribution Automation

Towards the complete vision of smarter distribution grid, advanced distribution automation system (ADAS) is one of the major players in this area. In this scope, this paper introduces a generic strategy for cost-effective implementation and evaluation of ADAS. Along with the same line, fault location, isolation and service restoration (FLISR) is one of the most beneficial and desirable applications of ADAS for self-healing and reliability improvement. Therefore, a local-centralized-based FLISR (LC-FLISR) architecture is implemented on a real, urban, underground medium voltage distribution network. For the investigated network, the complete procedure and structure of the LC-FLISR are presented. Finally, the level of reliability improvement and customers’ satisfaction enhancement are evaluated. The results are presented in the form of a comparative study between the proposed automated and non-automated distribution networks. The results show that the automated network with proposed ADAS has a considerable benefit through a significant reduction in reliability indices. In addition, it has remarkable benefits observed from increasing customers’ satisfaction and reducing penalties from industry regulators.

Neural Network-Based Model Design for Short-Term Load Forecast in Distribution Systems

Accurate forecasts of electrical substations are mandatory for the efficiency of the Advanced Distribution Automation functions in distribution systems. The paper describes the design of a class of machine-learning models, namely neural networks, for the load forecasts of medium-voltage/low-voltage substations. We focus on the methodology of neural network model design in order to obtain a model that has the best achievable predictive ability given the available data. Variable selection and model selection are applied to electrical load forecasts to ensure an optimal generalization capacity of the neural network model. Real measurements collected in French distribution systems are used to validate our study. The results show that the neural network-based models outperform the time series models and that the design methodology guarantees the best generalization ability of the neural network model for the load forecasting purpose based on the same data.

Implementation of an educational real-time platform for relaying automation on smart grids

The increasing research work on power networks has produced important challenges on distribution systems. These multiple advances bring an inevitable need to reshape and modernize teaching methodologies in order to understand the different issues of the smart grid complexity. This paper presents the design and implementation of an interactive platform to assess Advanced Distribution Automation (ADA) with applications and solutions focused on relaying solutions for educational purposes on smart grid. The proposed architecture integrates hardware/software tools to emulate the distribution system's behavior and recreate selected signals. Different features are presented and validated from a basic case study, where the students are able to comprehend the main concepts of relaying devices. The operational functionality of the platform offers the required flexibility to link theory with practice, which is suitable to enhance the learning process and encourage the class innovation. The user can incorporate protective algorithms and automation solutions under a real-time environment with hardware-in-the-loop techniques, such as adaptive protections and reconfiguration methods to optimize the grid. The impact of this platform in educational courses and the development of undergraduate thesis is assessed over the last 5 years in the faculty, and ABET guidelines are included in the evaluation of five Program Educational Objectives (PEOs) to measure the influence on students. Further potential applications are also discussed.

Coordination of PV Inverters to Mitigate Voltage Violation for Load Transfer Between Distribution Feeders with High Penetration of PV Installation

This paper presents the dispatch of reactive power compensation and real power curtailment of photovoltaic (PV) systems to prevent the overvoltage violation when load transfer between distribution feeders is executed. The voltage sensitivity factors of reactive power injection at all PV buses are derived according to the configuration of the distribution network. The advanced distribution automation system issues the control command to each PV inverter for adjustment of PV power generation, according to the sensitivity coefficients and PV installation capacity, so that the ancillary service of voltage support can be provided by all PV systems in a fairer manner. The practical Taiwan Power Company (Taipower) distribution feeders are selected for computer simulation, to verify the effectiveness of the proposed control method to mitigate the voltage violation problem for the operation of load transfer between distribution feeders with high penetration of PV installation.

Adaptive Relay Setting for Distribution Systems Considering Operation Scenarios of Wind Generators

This paper presents a method for an adaptive relay setting for distribution systems with wind generators (WGs). The advanced distribution automation system (ADAS) is applied to monitor the operational status of WGs and line switches. For the change of operational status of WGs or network reconfiguration of distribution systems because of the operation of line switches, the function of the adaptive relay setting is activated by the ADAS control master station. Short-circuit analysis is performed to solve the magnitude and direction of fault-current flows. The protective relay settings are then accordingly revised and loaded to the protective relays along the feeder to achieve the adaptive fault protection. Sample distribution feeders with open- and closed-loop configurations are used to demonstrate the adaptive relay setting for distribution systems with various operational scenarios of WGs. It is concluded that the fault currents contributed by WGs must be included in the design of the tap/level settings of protective relays by the ADAS to achieve good protection of smart distribution systems.

Analysis on Guarantee Strategies of Reliability for Hengqin Power System

In this paper, reliability guarantee strategies for Hengqin were proposed based on reliability affecting factor system and Hengqin needs of high reliability power system and smart grid, and the reliability enhancing degree of these strategies were assessed. Firstly, the indices of reliability were analyzed, and the reliability affecting factor system was built up. Then, combined with the development need of Hengqin power system, four specific reliability guarantee strategies-network structure construction, advanced distribution automation, intelligent operation and maintenance center and the end-line monitoring system-were proposed and the reliability effects were quantitatively assessed. Finally, the reliability effect of the strategies was compared with the reliability goal of Hengqin power system, and the adequacy and completeness of the strategies were verified.

Genetic algorithm optimization methodology for PWM Inverters of Intelligent universal transformer for the advanced distribution automation of future

Genetic algorithm optimization methodology for PWM Inverters of Intelligent universal transformer for the advanced distribution automation of future

Genetic algorithm optimization methodology for PWM Inverters of Intelligent universal transformer for the advanced distribution automation of future

This paper intends to optimize the control fashion of PWM inverters of Intelligent Universal Transformer (IUT) using Genetic Algorithm (GA). IUT is the state of art proposed as an electrical key point of Advanced Distribution Automation (ADA) technology. It comprises the power electronic construction and high frequency transformer. ADA will be raised for tomorrow's distribution system to perform the exchanging platform for both data and information which will be fully monitored and automatically controlled. IUT is introduced as intelligent electronic devices in lieu of traditional transformer with the controllable architecture that enhances the reliability and system performances and leading to the various services and user benefits like desirable output voltage, level and frequency, DC voltage options and sag correction. In case of oil elimination benefit it also yield to size and weight reduction. In this approach current and voltage source controllers based on GA optimization are developed for controlling the firing angle of switching pattern of PWM inverters which are recommended for voltage level and frequency control of IUT. The GA smart optimization fashion with the proposed three levels IUT topology emphasizes on the very smooth control and voltage regulation in both input and output inverters of IUT. GA improves the system characteristics under load and input disturbances with regulating the voltage and harmonic elimination.

Developing Adaptive Neuro-Fuzzy Inference System for Controlling the Intelligent Universal Transformers in ADA

This approach is carry out for developing the Adaptive Neuro-Fuzzy Inference System (ANFIS) for controlling the forthcoming Intelligent Universal Transformer (IUT) in regard of voltages and current control in both input and output stages which is optimized by particle swarm optimization. Current or voltages errors and their time derivative have been considered as the inputs of Nero Fuzzy controller for elaborating the firing angles of converters in IUT basic construction. ANFIS constructed from a fuzzy inference system (FIS) in which the membership function parameters are tuned according to the back propagation algorithm or in conjunction to the least squares method. A neural network maps inputs through input membership functions and associated parameters, and output membership functions and associated parameters to outputs which interprets the input-output map. The associated parameters of membership functions change through the learning algorithm by a gradient vector modeling the input output data in case of given parameters. Optimization method will be investigated to adjust the parameters according to error reduction computed by sum of the squared variation from actual outputs to the desired ones. Advanced Distribution Automation (ADA) is the state of art introducing for tomorrows distribution automation with the new invention in management and control. ADA is equipping by the Intelligent Equipment Devices (IED) in which IUT is a key point introducing as an intelligent transformer subjecting for tomorrows distribution automation in the near future. The proposed ANFIS is a control scheme develop for controlling the IUT by bringing the major advantages like harmonic Filtering, voltage regulation, automatic sag correction, energy storage, 48V DC option, three phase outputs in term of one phase input, reliable divers power as 240V 400HZ for communication utilization and two other 240V 60 HZ outputs, dynamic system monitoring and robustness in major disturbances occurred in terms of input and load variation.

Intelligent Universal Transformers Online Adaptive Control via Artificial Neural Network

Adaptive control is a novel methodology introducing for dynamic identification and control of nonlinear system in case of unknown parameters and absence of precise mathematical model. The Artificial Neural Networks (ANNs) suggest the parallel algorithm in resolving paradigms and result on a robust control fashion in which learning algorithm resembling to the biological brain. Back propagation algorithm is proposed for updating the ANN weighting factors through the on line learning procedure. This research is carry out to investigate the ANN trained algorithm to elaborate the switching angle signals for controlling the Intelligent Universal transformer (IUT) in input and output stages. IUT motive the Advanced Distribution Automation (ADA) with the new invention in automation, management and control. ANN online adaptive scheme is developed for controlling the input current and output voltages of IUT with the major benefits and service option advantages, comprising from a voltage regulation in real time operation, capability on providing three phase power outputs in case of one phase input, energy storage capability,48V DC output option, harmonic Filtering, reliable divers power 240V AC 400HZ for communication usage together with two 240 V AC 60 HZ outputs, automatic sag correction, dynamic system monitoring and system robustness in term of input and load disturbances.