An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles

Modern power system requires advanced and intelligent sensors-based protection such as a Phasor Measurement Unit that can provide faster, accurate, and real-time data acquisition. The aim is to allow accurate action-based performance for analysts in monitoring the transmission lines so that rapid actions can be taken during abnormal circumstances before the blackout occurs. Among different algorithms, this study focuses on modelling the non- recursive phasor estimation method in a power Simulink environment for a standard test system equipped with a developed algorithm to detect the fault zone. The algorithm includes an index for faulty bus classification based on the positive-sequence voltage measurements of the pre-fault and post-fault conditions, where the bus with a maximum differential percentage is identified as a faulted bus. An important differentiation of this work is that the proposed algorithm can coordinate with all phasor measurement units to accurately determine the faulty line using the index of unwrapped dynamic phase angles. Furthermore, the robustness of the indices is analyzed in the presence of sudden load change, measurement noise, and during nonlinear high-impedance faults. The performance of the comprehensive algorithm is investigated on the IEEE 9-bus and 39-bus standard test systems by applying different faults scenarios, considering several factors such as fault inception angles, line-fault resistance, ground-fault resistance. The comparative studies have shown that the proposed indices can play a significant role in segregating the fault and non-fault conditions, as they are needed to supervise the appropriate relays for enhancing the overall security of the power grid

Traffic aware wireless sensor networks MAC protocol for smart grid applications using spiral backoff mechanism

Smart grid is an innovative electrical power delivery networks which integrate distributed renewable energy sources and electric vehicles with the main power grid. Smart grid employs communication network to automate the generation, transmission and distribution and collect metering information from different parts of the grid and the customers to optimize energy distribution and consumption. Moreover, Distribution automation, Demand-Response (DR) and Direct Load Control (DLC) are applied to reduce the consumption of electricity during peak hours. However, it requires a robust, reliable communication network to facilitate real time data exchange between the utility gateway and smart meters of the customer premises. IEEE 802.15.4 standard provides a low cost, low power WSNs solution for smart grid communication networks. The IEEE 802.15.4 standard uses slotted Carrier Sense Multiple Access-Collision Avoidance (CSMA-CA) with binary exponential backoff algorithm (BEB) to avoid collision between the sensor nodes. However, BEB does not consider the s requirement which degrade the smart grid network performance. In this paper, a traffic aware spiral backoff mechanism is proposed to improve the network performance. Simulation results show that proposed spiral backoff algorithm reduces the end-to-end delay and increase packet delivery ratio (PDR) for real time data

Adaptive Algorithm for Optimal Route Configuration in Multi-Hop Wireless Sensor Network

Wireless Sensor Networks (WSNs) are best solutions for numerous aspects of engineering applications such as monitoring, control and surveillance of electrical plant amongst others. Autonomously, sensors will communicate with each other, collaborate, share and forward information in a multi-hop fashion without any centralized controller. To gather relevant data, the route optimization mechanism is used to solve the long routing problem and provide the shortest path amongst communicating nodes. Thus, this shortest path criterion is not suitable for WSN as it may lead to power drainage of several nodes and may cause high signaling and processing costs due to the network reconstruction. This paper proposes an optimal route configuration technique based on an adaptive genetic algorithm in which the architecture of multi-hop wireless sensor network is considered as a distributed computing infrastructure. The obtained results show that the proposed algorithm provides an optimal route configuration with the best performance in terms of evaluating the covered distance, packet loss and time delay

Cost-Effective Design of IoT-Based Smart Household Distribution System

The Internet of Things (IoT) plays an indispensable role in present-day household electricity management. Nevertheless, practical development of cost-effective intelligent condition monitoring, protection, and control techniques for household distribution systems is still a challenging task. This paper is taking one step forward into a practical implementation of such techniques by developing an IoT Smart Household Distribution Board (ISHDB) to monitor and control various household smart appliances. The main function of the developed ISHDB is collecting and storing voltage, current, and power data and presenting them in a user-friendly way. The performance of the developed system is investigated under various residential electrical loads of different energy consumption profiles. In this regard, an Arduino-based working prototype is employed to gather the collected data into the ThingSpeak cloud through a Wi-Fi medium. Blynk mobile application is also implemented to facilitate real-time monitoring by individual consumers. Microprocessor technology is adopted to automate the process, and reduce hardware size and cost. Experimental results show that the developed system can be used effectively for real-time home energy management. It can also be used to detect any abnormal performance of the electrical appliances in real-time through monitoring their individual current and voltage waveforms. A comparison of the developed system and other existing techniques reveals the superiority of the proposed method in terms of the implementation cost and execution time

LM555 timer-based inverter low power pure sinusoidal AC output

The demand of highly efficient and stable DC to AC inverters used in renewable energy systems to convert DC output from green energy sources into purely sinusoidal unwavering AC is on rise, due to low cost energy generation and conversion, less complexity and environmental factors. Later this converter energy can be feed in to grid or utility supply for load sharing purpose also (can be work as Distributed Generation System (DGS)). This paper represents a duty cycle-based configuration of LM555 timer to generate an AC output of 50Hz. Two BJT transistors (NPN and PNP) are used to convert the 12V DC into 12V AC cycle. Also the low pass filter design is tested to transform distorted square wave into pure sinusoidal wave with minimum ripples on no load condition. The results shown are simulation based, showing a proper shape of 220V AC output with very less harmonics surges and noise effect

Single-phase inverter for small voltage supplies for use in distributed measurement systems

This paper presents the simulation details of a single-phase 50Hz inverter that could be used for obtaining small-voltage AC or DC supply source needed for powering small electronic devices that could be employed for distributed measurement in monitoring systems. Energy harvesting from solar presents a source that may prove viable alternative to conventional battery sources. It provides high power density in outdoor applications. This work obtains 220V 50Hz AC using 12V DC supply voltage using appropriately configured switching devices operated by 1KHz to 10KHz sampling frequency. The output is normalized by a low pass filter (LPF) made from 500 micro-H inductance with 10 micro-F capacitance

Monitoring of renewable energy systems by IoT‐aided SCADA system

With the rapid increase of renewable energy generation worldwide, real‐time information has become essential to manage such assets, especially for systems installed offshore and in remote areas. To date, there is no cost‐effective condition monitoring technique that can assess the state of renewable energy sources in real‐time and provide suitable asset management decisions to optimize the utilization of such valuable assets and avoid any full or partial blackout due to unexpected faults. Based on the Internet of Things scheme, this paper represents a new application for the Supervisory Control and Data Acquisition (SCADA) system to monitor a hybrid system comprising photovoltaic, wind, and battery energy storage systems. Electrical parameters such as voltage, current, and power are monitored in real‐time via the ThingSpeak website. Network operators can control components of the hybrid power system remotely by the proposed SCADA system. The SCADA system is interfaced with the Matlab/Simulink software tool through KEPServerEX client. For cost‐effective design, low‐cost electronic components and Arduino Integrated Development Environment ATMega2560 remote terminal unit are employed to develop a hardware prototype for experimental analysis. Simulation and experimental results attest to the feasibility of the proposed system. Compared with other existing techniques, the developed system features advantages in terms of reliability and cost‐effectivenes

Dynamic load modeling for bulk load-using synchrophasors with wide area measurement system for smart grid real-time load monitoring and optimization

Bulk data modeling in a smart grid dynamic network has been performed using an automated load modeling tool (ALMT), an on-load tap changer, and exponential dynamic load modeling. However, studies have observed that a small parameter variation may lead to considerable variations in measuring grid big data. Therefore, this study presents dynamic real-time load modeling, monitoring, and optimization method for the bulk load. The case study was conducted on Sarawak Energy Berhad (SEB), Malaysia. The grid system’s real-time data and load modeling achieved the objectives. Dynamic load model was achieved by using load response in MATLAB Simulink environment. This paper also includes new parameter estimations of the load composition at the selected bus. The simulation results of load models were compared with the recorded data by applying an event of bus tripping time interval. The Least Square Error Method was used to converge the estimated parameter values on load composition and compared with the actual recorded data until optimized load models were achieved. This work is a precious and significant contribution to utility research to identify, monitor, and optimize the most appropriate representation of system loads