Energy Storage Systems for Energy Management of Renewables in Distributed Generation Systems

Distributed generation (DG) systems are the key for implementation of micro/smart grids of today, and energy storages are becoming an integral part of such systems. Advancement in technology now ensures power storage and delivery from few seconds to days/months. But an effective management of the distributed energy resources and its storage systems is essential to ensure efficient operation and long service life. This chapter presents the issues faced in integrating renewables in DG and the growing necessity of energy storages. Types of energy storage systems (ESSs) and their applications have also been detailed. A brief literature study on energy management of ESSs in distributed microgrids has also been included. This is followed by a simple case study to illustrate the need and effect of management of ESSs in distributed systems

A Reduced Switch Asymmetric Multilevel Inverter Topology Using Unipolar Pulse Width Modulation Strategies for Photovoltaic Application

A new design of multilevel inverter configuration is proposed for reducing the component count and improving the quality of waveform in a photovoltaic system. The proposed configuration operates at the binary asymmetric condition for generating the large amount output voltage level with small amount harmonic distortion. Unipolar trapezoidal reference with triangular carriers is used for generating the desired switching pulses to generate the required output voltage level. The proposed configuration requires eight unipolar switches for generating the 31-level output voltage level with total harmonic distortion of 3.18% without using any filters. The value of %total harmonic distortion (THD) satisfies the IEEE 519 harmonic standard. Separate DC sources of proposed configuration are replaced by the array of photovoltaic panels for testing the configuration with the renewable energy source. The proposed configuration is tested with an experimental setup for proving the operation of it. Selected simulation and experimental results are shown for the verification of proposed configuration ability

A New Three-Phase Multi-Level Asymmetrical Inverter With Optimum Hardware Components

In this article, a novel three-phase asymmetrical multilevel inverter is presented. The proposed inverter is designed with an optimal hardware components to generate three-phase nineteen output voltage levels. The proposed inverter exhibits various advantages like a suitable output voltage waveform with improved power quality, lower total harmonic distortion (THD), and more moderate complexity, reduction in cost, reduced power losses, and improved efficiency. A comparison of the proposed topology in terms of several parameters with existing methods illustrates its merits and features. The proposed inverter tested with steady-state and dynamic load disturbances. Various experimental results are included in this article to validate the performance of the proposed inverter during various extremities. In addition, a detailed comparison is tabulated between simulation and experimental results graphically. The proposed inverter has been stable even during load disturbance conditions. The simulation and feasibility model are verified using a prototype model

Identification of Water Hammering for Centrifugal Pump Drive Systems

Water hammering is a significant problem in pumping systems. It damages the pipelines of the pump drastically and needs to identify with an intelligent method. Various conventional methods such as the method of characteristics and wave attenuation methods are available to identify water hammering problems, and the predictive control method is one of the finest and time-saving methods that can identify the anomalies in the system at an early stage such that the device can be saved from total damage and reduce energy loss. In this research, a machine learning (ML) algorithm has used for a predictive control method for the identification of water hammering problems in a pumping system with the help of simulations and experimental-based works. A linear regression algorithm has been used in this work to predict water hammering problems. The efficiency of the algorithm is almost 90% compared to other ML algorithms. Through a Vib Sensor app-based device at different pressures and flow rates, the velocity of the pumping system, a fluctuation between healthy and faulty conditions, and acceleration value at different times have been collected for experimental analysis. A fault created to analyze a water hammering problem in a pumping system by the sudden closing and opening of the valve. When the valve suddenly closed, the kinetic energy in the system changed to elastic resilience, which created a series of positive and negative wave vibrations in the pipe. The present work concentrates on the water hammering problem of centrifugal pumping AC drive systems. The problem is mainly a pressure surge that occurs in the fluid, due to sudden or forced stops of valves or changes in the direction and momentum of the fluid. Various experimental results based on ML tool and fast Fourier transformation (FFT) analysis are obtained with a Vib Sensor testbed set-up to prove that linear regression analysis is the less time-consuming algorithm for fault detection, irrespective of data size

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration

The global concern with power quality is increasing due to the penetration of renewable energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power quality (PQ) disturbances are found to be more predominant with RE penetration due to the variable outputs and interfacing converters. There is a need to recognize and mitigate PQ disturbances to supply clean power to the consumer. This article presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration. The broad perspective of this review paper is to provide various concepts utilized for extraction of the features to detect and classify the PQ disturbances even in the noisy environment. More than 220 research publications have been critically reviewed, classified and listed for quick reference of the engineers, scientists and academicians working in the power quality area

Photovoltaic-STATCOM with Low Voltage Ride through Strategy and Power Quality Enhancement in a Grid Integrated Wind-PV System

The traditional configurations of power systems are changing due to the greater penetration of renewable energy sources (solar and wind), resulting in reliability issues. At present, the most severe power quality problems in distribution systems are current harmonics, reactive power demands, and the islanding of renewables caused by severe voltage variations (voltage sag and swell). Current harmonics and voltage sag strongly affect the performance of renewable-based power systems. Various conventional methods (passive filters, capacitor bank, and UPS) are not able to mitigate harmonics and voltage sag completely. Based on several studies, custom power devices can mitigate harmonics completely and slightly mitigate voltage sags with reactive power supplies. To ensure the generating units remain grid-connected during voltage sags and to improve system operation during abnormal conditions, efficient and reliable utilization of PV solar farm inverter as STATCOMs is needed. This paper elaborates the dynamic performance of a VSC-based PV-STATCOM for power quality enhancement in a grid integrated system and low voltage ride through (LVRT) capability. LVRT requirements suggest that the injection of real and reactive power supports grid voltage during abnormal grid conditions. The proposed strategy was demonstrated with MATLAB simulations

A Fuzzy Logic-Based Emulated Inertia Control to a Supercapacitor System to Improve Inertia in a Low Inertia Grid with Renewables

The contribution of power generation from converter-dominated renewable energy sources (RES) has increased enormously. Consequently, the system inertia is decreasing, and it impacts the frequency of the system. With large-scale integration of power electronic inverter-based power generation from RES, inertia from energy storage devices would be unavoidable in future power grids. In this paper, the inertia emulator is formed with a supercapacitor (IE–SC) to improve inertia in a low inertia grid. To emulate the inertia in a low inertia grid, this paper proposes a fuzzy logic controller-based emulated inertia controller (FL-EIC) for an inverter attached to IE–SC. The proposed fuzzy logic controller estimates the inertial power required based on the frequency deviation and rate of change of frequency (ROCOF). The output of the fuzzy controller adds to the conventional emulated inertia control (EIC) technique to alter the load angle for the power electronic inverter of IE–SC. Specifically, the proposed FL-EIC achieves inertia emulation by proportionally linking the time derivative of the grid frequency and frequency deviation to active power references of IE–SC. A comparison of the conventional EIC and FL-EIC is carried out to prove the effectiveness of the proposed FL-EIC. Furthermore, real-time simulations with the help of the OPAL-RT real-time simulator (OP 5700) are presented to validate the advantage of the FL-EIC

A Fuzzy Logic-Based Emulated Inertia Control to a Supercapacitor System to Improve Inertia in a Low Inertia Grid with Renewables

The contribution of power generation from converter-dominated renewable energy sources (RES) has increased enormously. Consequently, the system inertia is decreasing, and it impacts the frequency of the system. With large-scale integration of power electronic inverter-based power generation from RES, inertia from energy storage devices would be unavoidable in future power grids. In this paper, the inertia emulator is formed with a supercapacitor (IE–SC) to improve inertia in a low inertia grid. To emulate the inertia in a low inertia grid, this paper proposes a fuzzy logic controller-based emulated inertia controller (FL-EIC) for an inverter attached to IE–SC. The proposed fuzzy logic controller estimates the inertial power required based on the frequency deviation and rate of change of frequency (ROCOF). The output of the fuzzy controller adds to the conventional emulated inertia control (EIC) technique to alter the load angle for the power electronic inverter of IE–SC. Specifically, the proposed FL-EIC achieves inertia emulation by proportionally linking the time derivative of the grid frequency and frequency deviation to active power references of IE–SC. A comparison of the conventional EIC and FL-EIC is carried out to prove the effectiveness of the proposed FL-EIC. Furthermore, real-time simulations with the help of the OPAL-RT real-time simulator (OP 5700) are presented to validate the advantage of the FL-EIC

Intelligence-Based Battery Management and Economic Analysis of an Optimized Dual-Vanadium Redox Battery (VRB) for a Wind-PV Hybrid System

This paper proposes an intelligent battery management system (BMS) implementing two large Vanadium Redox Battery (VRB) flow batteries in a master-slave mode to provide grid-level energy storage for a wind-solar hybrid power system. The proposed BMS is formulated to effectively meet a predetermined power dispatch formulated based on forecasted wind and solar data while incorporating features like peak shaving and ramp rate limiting. It is compared to a single battery module operated system to showcase the advantages of the proposed intelligent dual battery module in terms of appreciable reduction in battery size and costs while exhibiting improved lifecycle performance. The battery size is optimized based on heuristic optimization algorithms and modelled in Matlab/Simulink environment. An intelligent fuzzy-based BMS is used to control the dual VRB model to ensure optimized power sharing between batteries. The simulations were carried out and an in-depth economic analysis conducted to analyze the costs and other financial metrics of the hybrid project. Results proved the advantages of the dual battery with the proposed BMS and fortify that the introduction of time-based tariffs and other incentives will further make investments in VRB highly attractive for renewable applications