Utility Grid Research Articles

Comprehensive review on control schemes and stability investigation of hybrid AC-DC microgrid

The utility grid integration of distributed generation units is seen as one of the most accomplished through the use of microgrid. Control methods and stability analyses in the microgrid are continuously being investigated in the field of hybrid microgrid. The most reviewed control method is hierarchical control, consisting of primary, secondary, and tertiary layers. This paper reviews multiple schemes of primary control for current or voltage regulation, secondary control for voltage or current error correction, power-sharing in microgrid, and tertiary control for power flow and energy management in a hybrid microgrid system. Additionally, this study examines the benefits and drawbacks of several control architectures that function as distributed, centralized, and decentralized controls. The principle of operation and effectiveness of each microgrid architecture control method have been discussed. Specific control factors are investigated in this paper, including mode transition and coordinated control between numerous interlinking converter and energy storage systems. System stability is the main concern of microgrid for system engineer thorough knowledge of control strategies is the upmost requirement. Thus, this paper highlights control strategies, rotor angle, voltage and frequency instability in power systems, and methods for improving stability in microgrid are also reviewed.

Solar Off-Grid Electric Vehicle Charging Station

Abstract: Nowadays, there is a great development in electric vehicle production and utilization. It has no pollution, high efficiency, low noise, and low maintenance. However, the charging stations, required to charge the electric vehicle batteries, impose high energy demand on the utility grid. One way to overcome the stress on the grid is the utilization of renewable energy sources such as photovoltaic energy. The utilization of standalone charging stations represents good support to the utility grid. Nevertheless, the electrical design of these systems has different techniques and is sometimes complex. This paper introduces a new simple analysis and design of a standalone charging station powered by photovoltaic energy. Simple closed-form design equations are derived, for all the system components. Case-study design calculations are presented for the proposed charging station. Other important features of an off-grid solar EV charging station might include the use of smart charging technology to optimize charging speed and efficiency, as well as the ability to monitor and control the system remotely. Safety features such as overcharge protection and grounding would also be important considerations. We can visualize the expected results using a Cayenne Software, we can also control the street lighting by Internet of Things. The results show that the charging process of the electric vehicle battery is precisely steady for all the PV insolation disturbances. In addition, the charging/discharging of the energy storage battery responds perfectly to store and compensate for PV energy variations.

English

Recently, Micro Grids (MGs) have become extremely popular due to their advantages of effective power conversion and high transmission efficiency. The MG and Nonlinear Loads (NL) are being incorporated into the electricity network. MGs are connected by Voltage Source Converters (VSCs), and NL infuses harmonics into the utility grid using power devices. However, the emergence of stability problems in the MG is caused by the nonlinear characteristics of Renewable Energy Sources (RESs), the rising use of power electronic devices and unexpected variations in load. This paper aims to suggest a microgrid that employs RESs comprising wind and Photovoltaic (PV) systems. This method is established to distribute stable power to loads without any interruptions. A Doubly Fed Induction Generator (DFIG) is deployed as a wind system. To stabilize the PV input voltage, the Boost converter is implemented. Furthermore, intended for enhancing the microgrid's performance, a constant output without distortion is attained from the converter with the deployment of a Whale Optimized Proportional Integral (WO-PI) controller. The 3Φ inverter is utilized to sustain the DC link voltage, and it combines PV, wind, and battery output at a single point and feeds it to the grid. The results are implemented using the MATLAB platform, and simulation outcomes show that the suggested control technique is effective with a THD of 2.33% and reduced overshoot issues.

Realistic μPMU Data Generation for Different Real-Time Events in an Unbalanced Distribution Network

Monitoring, protection, and control processes are becoming more complex as distributed energy resources (DERs) penetrate distribution networks (DNs). This is due to the inherent nature of power DNs and the bi-directional flow of current from various sources to the loads. To improve the system’s situational awareness, the grid dynamics of the entire DER integration processes must be carefully monitored using synchronized high-resolution real-time measurement data from physical devices installed in the DN. μPMUs have been introduced into the DN to help with this. In comparison to traditional measurement devices, μPMUs can measure voltage, current, and their phasors, in addition to frequency and rate of frequency change (ROCOF). In this study, an approach to generating realistic event data for a real utility DN utilizing strategically installed μPMUs is proposed. The method employs an IEEE 34 test feeder with 12 μPMUs installed in strategic locations to generate real-time events-based realistic μPMU data for various situational awareness applications in an unbalanced DN. The node voltages and line currents were used to analyze the various no-fault and fault events. The author generated the data as part of his PhD research project, utilizing his real-time utility grid operation experience to be used for various situational awareness and fault location studies in a real unbalanced DN. The DN was modeled in DIgSILENT PowerFactory (DP) software. The generated realistic μPMU data can be utilized for developing data-driven algorithms for different event-detection, classification and section-identification research works.

Decarbonizing Telecommunication Sector: Techno-Economic Assessment and Optimization of PV Integration in Base Transceiver Stations in Telecom Sector Spreading across Various Geographically Regions

Renewable energy is considered to be sustainable solution to the energy crisis and climate change. The transition to renewable energy needs to be considered on a sectoral basis and one such sector that can potentially decarbonized with renewable energy is the telecommunication sector. Several base transceiver stations (BTS) in remote regions have unstable electric supply systems. Diesel generators (DG) are a common solution to energy problems on such telecommunication sites. However, they have high fuel costs on the global market and contribute to high carbon emissions. Hybrid renewable energy systems may provide a stable power output by integrating multiple energy sources, essential for supplying a dependable and uninterrupted power supply in the context of the telecom sector, notably base transceiver stations (BTS). Deploying such a system might also help BTS, which relies mainly on diesel generators with battery storage backup, reduce operational costs and environmental problems. This study presents the framework for large-scale photovoltaic system penetration based on techno-economic analysis (based on actual on ground data with least assumptions) in base transceiver stations (BTS) encapsulating telecom sector spread across various geographical regions. The proposed framework includes a mathematical model complemented with system design in HOMER software tool. The techno-economic aspects of the study were spread across 2, 12 and 263 sites, along with comparison analysis of photovoltaic system installation with and without energy storage devices, respectively. The sites included both on-grid and off-grid sites, which were exposed to high levels of power outages and subjected to reliance on costly and environmentally hazardous diesel generators. Optimization results showed that the photovoltaic system with a diesel generator and battery storage system provide a promising solution to the energy problem, with an average decrease in LCOE of 29%, DG hour’s reduction by 82% with 92% reduction in carbon emission and a reduction in NPC of 34% due to the high availability of solar. The techno-economic analysis indicated that optimized photovoltaic system and storage results in both on–off grid BTS sites with better options, amid low cost of energy and free accessibility of solar. Moreover, the results spread across geographical regions aiming at a reliable and environmentally friendly option that reduces load on utility grid across on-grid BTS sites and substantial overall reduction in diesel usage.

Fault Detection and Classification to Design a Protection Scheme for Utility Grid with High Penetration of Wind and Solar Energy

This paper designed a protection scheme for utility grid with high share of renewable energy (RE) generated from wind energy and solar energy plants. This is based on extraction of features from the current using Stockwell transform (ST), Hilbert transform (HT), and alienation coefficient. A Stockwell index (SI) is designed by extracting current features using ST, a Hilbert index (HI) is designed by extracting current features using HT, and an alienation index (AI) is designed by extracting current features using an alienation coefficient. A fault index (FI) is formulated by multiplying the SI, HI, AI, and WF (weight factor). This FI is implemented for fault detection. Fault classification is achieved considering number of fault phases and ground fault index (GFI). This GFI is designed by processing zero sequence currents applying ST. GFI effectively identifies the ground involved during event of a fault. A designed protection scheme is effective to identify faults in the scenario of high RE share and during various cases of study which includes the variations of fault impedance, different fault occurrence angles (FOA), fault incident at different nodes, and noisy condition. This protection scheme effectively discriminates the fault events from the operational events such as feeder operation, load, and capacitor switching. Performance of hybrid protection method formulated in this paper is better relative to alienation coefficient-based protection scheme (ACPS) reported in literature. The ACPS has maximum error and mean error of fault detection equal to 9.54% and 5.99%, respectively, which is relatively high compared to the respective values for the proposed method which are 1.89% and 0.978%, respectively. ACPS is effective for detecting the fault events in noise level of 30 dB SNR (signal-to-noise ratio) whereas the proposed method effectively identifies the faults in the high noise scenario of 20 dB SNR.

A novel dynamic pricing model for a microgrid of prosumers with photovoltaic systems

Due to the growing demand for electricity and the increasing number of consumers who can produce energy (prosumers) using photovoltaic systems today, energy generated by prosumers can be utilized in the microgrid instead of selling it to the main utility grid. Pricing is one of the most important mechanisms for motivating prosumers to interact with each other in the microgrid. Many works have proposed different pricing models that mostly focus on optimizing prosumers’ behavior and energy usage costs. However, most of the proposed models require constant involvement of the end-user to adjust energy consumption profiles, which is not always possible in a real-world scenario. In this paper, a novel pricing model is presented with the aim of maximizing the utilization of energy generated in the microgrid and reducing the import of energy from the utility grid, whereas ensuring more beneficial prices for energy within the microgrid compared with the utility grid. Mathematical models based on the supply and demand ratio and prosumers’ absolute deviation from the predicted energy usage profiles are developed to determine the internal equilibrium price and the amount of energy each prosumer can buy and sell by interacting with the microgrid. To cover the energy transfer losses in the microgrid, a dynamic loss allocation mechanism is proposed. The proposed pricing model is validated using real energy usage profiles from 100 prosumers. The results show that the total energy usage cost can be decreased, whereas the amount of unused energy that is shared outside the microgrid is minimized.

Protection Challenges on Integration of Distributed Sources to Power system network: A Review

— Electricity generation has to be increased to meet various type of future load demand like LED lightning, Electrical 
 Vehicles, mobiles, communication network, non linear load etc. Automation is essential requirement now a days in each sector. 
 To provide automation at residential, commercial and industrial sectors electrical energy is required. To meet energy 
 requirement of various sector utility grid is integrated with DG Sources, which mainly include renewable energy sources like 
 solar, wind and other environment friendly sources either in large scale or small scale depends on the location and availability. 
 This type of technology leads power system to era of smart grid. Smart grid technology provides features like digitization, two 
 way communication, distributed generation, adaptive islanding, self monitoring and self mitigating, fully controllable compare to 
 conventional Grid. Though smart grid technology is advantageous but due to integration of distributed generation at 
 transmission and distribution system will increase protection challenges in the power network. This paper gives an insight of 
 different protection issues which occur at transmission, distribution and Micro grid network. The paper also focuses on the 
 techniques and solution of the various protection challenges.

An unprecedented control of 3‐phase grid tied solar photovoltaic‐hydrogen/bromine‐supercapacitor composite storage microgrid for pulse power load regulation under nonideal grid conditions

AbstractPhotovoltaic (PV) power penetration into the distribution grid has increased. PV power fluctuations, abrupt load changes, nonlinear loading, growing usage of portable electronic devices, electric cars low average power and comparatively high pulse power needs, and other factors translate into severe grid instability. As a result, in these circumstances, power exchange between PV and the utility grid becomes a difficult task. Therefore, this article proposes a hydrogen/bromine (H2/Br2) redox flow battery and supercapacitor composite energy storage for a three phase grid tied PV system with multifunctional active power filter support to ensure grid codes. Further, the system is equipped with an unprecedented control technique that encompasses: an adaptive frequency tuned complex coefficient filter‐phase locked loop that provides grid frequency and phase angle information under adverse grid conditions, a modified sparrow search algorithm tuned tilt integral derivative with filter plus double integral controllers are employed to regulate the control errors under various system dynamic and disturbance conditions, fractional order incremental conductance maximum power point tracking is incorporated to efficiently track the PV peak power irrespective of atmospheric variations, a holistic fast‐acting power based energy management control employed for efficient regulation of load power and smooth out the PV power variation, and PV feedforward control dynamics to enhances system dynamics by reducing oscillations under various atmospheric conditions. The aim is to attain a smooth power transition with the grid at the unit power factor under normal and nonideal grid conditions. With reactive power injection, the control also maintains the voltage profile. During all these operations, no trade‐off occurs with the system power quality. Matlab simulations and the real time simulation test bench results under unfavorable grid circumstances demonstrate the effectiveness of the proposed method, and system harmonics are well within bounds in all the scenarios undertaken.

Artificial neural network assisted robust droop control of autonomous microgrid

AbstractElectric grid is vulnerable to power imbalance and inertia is the grid's response to overcome such disturbance. Augmentation of power electronic converter based renewable energy technologies like Photovoltaic Generators (PVG) and batteries in utility grid significantly reduces inertia. Inertia degradation is indicated by sharp Rate of Change of Frequency (ROCOF) events due to any grid component failure or imbalance. Fixed gain feedback Proportional Integral Derivative (PID) control is insufficient to deal with varying ROCOF events. This work proposes Sliding Mode (SM) robust droop control scheme assisted by Artificial Neural Network (ANN) algorithm for an islanded PVG integrated microgrid. Droop response is governed by swing equation that uses PVG Maximum Power Point (MPP) forecasted by ANN. ANN forecast is compared with optimized Gaussian process regression algorithm based on mean squared error and speed of training as key performance indicator. The algorithms are trained and validated based on climate dataset of Islamabad, Pakistan. SM control performance is compared with various PID gain settings and qualified as the most suitable against variable source, load and ROCOF scenarios. Finally, significance of accurate MPP forecast for droop control is established by comparing the ANN and deterministic forecaster assisted droop response in a microgrid case study.

An Extensive Review and Analysis of Islanding Detection Techniques in DG Systems Connected to Power Grids

Nowadays, the integration of distributed generators with the main utility grid is highly increasing due to the benefits which can be obtained, such as increasing the system efficiency and reliability. Apart from that, many technical and safety issues appear in the system due to this integration. One of these issues is the islanding condition, which has to be detected effectively and quickly before having any detrimental effects on the protection, stability, and security of the system. This study provides a detailed overview of several islanding detection approaches, which are divided into traditional methods, including local and remote methods, and modern methods, including methods based on signal processing and computational intelligence. Moreover, a comparison between each method based on various criteria, such as non-detected zone, quality factor, response time, implementation cost, degrading power quality, reliability, suitability for the type of distributed generators, suitability for multi-distributed generators system, and sensitivity to cyber-attacks, is carried out. Therefore, this review will offer a solid background in order to help researchers interested in this field distinguish between islanding detection methods and their relative advantages and disadvantages, as well as to be able to choose the most suitable islanding detection method among the others to be implemented in the network.

Low voltage ride through control strategy for grid-tied solar photovoltaic inverter

Abstract This paper presents a low voltage ride through (LVRT) control strategy using an active power oscillations based reference current generation approach for grid tied solar photo voltaic (SPV) system under line-to-ground (LG) and double line-to-ground (LLG) faults. Proposed control strategy minimizes the harmonics injected into the grid, as well as oscillations in injected reactive power and DC-link voltage. Further this control strategy provides a dynamic control of active and reactive powers, the flow of sinusoidal currents into the grid, and avoids the disconnection between the utility grid and SPV system during faults. A proportional resonant (PR) current controller is developed in a stationary reference frame to achieve the power quality by fulfilling the grid codes. Simulation and experimental results are presented to highlight the merits of the proposed control scheme.

An improved DC link voltage control with double frequency second‐order generalized integrator for enhanced power quality of grid‐interfaced DFIG system

SummaryIn this study, an optimal double frequency second order generalized integrator (DFSOGI) based grid side converter control (GSC) is used for monitoring active power injection from the DFIG wind energy system as well as improving power quality at utility grid terminals. The reference DC voltage is adapted to variations in voltage at the point of common coupling (PCC) that reduces the burden on the converter switches and switching losses. In addition, an intelligent control technique based on white shark optimization algorithm (WSO) is endorsed, where an objective problem is formulated to obtain the desired parameters of the controller. Finally, time‐domain simulations are conducted in MATLAB environment that demonstrate the validity of the implemented control over various operating conditions. To affirm the adequacy of the proposed control strategy, the response of DC link voltage obtained through optimal tuning is compared to the conventional one. The proposed WSO tuning outperforms traditional manual tuning pertaining to enhancing the overall performance of the DFIG system. The designed WSO gains exhibit better steady‐state and transient performance including settling time, steady‐state error, and peak of over amplitude and harmonic distortion. The grid currents' total harmonic distortion (THD) is within 5% that meets specified IEEE‐519 standard.

Analysis of an Urban Grid with High Photovoltaic and e-Mobility Penetration

This study analyses the expected utilization of an urban distribution grid under high penetration of photovoltaic and e-mobility with charging infrastructure on a residential level. The grid utilization and the corresponding power flow are evaluated, while varying the control strategies and photovoltaic installed capacity in different scenarios. Four scenarios are used to analyze the impact of e-mobility. The individual mobility demand is modelled based on the largest German studies on mobility “Mobilität in Deutschland”, which is carried out every 5 years. To estimate the ramp-up of photovoltaic generation, a potential analysis of the roof surfaces in the supply area is carried out via an evaluation of an open solar potential study. The photovoltaic feed-in time series is derived individually for each installed system in a resolution of 15 min. The residential consumption is estimated using historical smart meter data, which are collected in London between 2012 and 2014. For a realistic charging demand, each residential household decides daily on the state of charge if their vehicle requires to be charged. The resulting charging time series depends on the underlying behavior scenario. Market prices and mobility demand are therefore used as scenario input parameters for a utility function based on the current state of charge to model individual behavior. The aggregated electricity demand is the starting point of the power flow calculation. The evaluation is carried out for an urban region with approximately 3100 residents. The analysis shows that increased penetration of photovoltaics combined with a flexible and adaptive charging strategy can maximize PV usage and reduce the need for congestion-related intervention by the grid operator by reducing the amount of kWh charged from the grid by 30% which reduces the average price of a charged kWh by 35% to 14 ct/kWh from 21.8 ct/kWh without PV optimization. The resulting grid congestions are managed by implementing an intelligent price or control signal. The analysis took place using data from a real German grid with 10 subgrids. The entire software can be adapted for the analysis of different distribution grids and is publicly available as an open-source software library on GitHub.

An adaptive vector control method for inverter‐based stand‐alone microgrids considering voltage reduction and load shedding schemes

AbstractThe droop mechanism is widely utilized in a stand‐alone microgrid (MG) to regulate power‐sharing among distributed generators (DG). However, over the years, the droop phenomena are continually modified to lessen the deviation in voltage and frequency parameters caused due to classical droop. This study suggests computing the droop coefficient for voltage–current (V–I) droop to take into account for proportional power distribution among DGs. In grid utility networks, the conservation voltage reduction (CVR) strategy is widely used to curtail the use of energy. Hence, this paper investigates the CVR's performance for stand‐alone MG by performing the adaptive vector control scheme in the two‐phase d–q reference frame. In addition to it, the paper is intended to develop a coordinated control strategy for stand‐alone MG involving classical P–f droop and self‐sustained V–I droop employed to perform the function of CVR during peak demand and overloading conditions. Further, a load‐shedding control approach is also considered to cut out some segments of load during overloading conditions to operate the MG in the stable zone. The validation of the proposed strategy is conducted on MATLAB/Simulink software.

Power Efficient Mini Inverter

Inverters are extensively used in both residential and commercial settings to serve as a backup power source in the event of a power outage from the utility grids. In the case of a power outage, an inverter powers the electric equipment. As the name suggests, an inverter converts AC to DC to charge the battery before inverting DC to AC to power the electronic devices. So here is a power efficient converter that is compact in size and can provide an output voltage of 220v-230/150w. This energy-efficient mini inverter can be used to power items such as WiFi networks, mobile charges, lights, and so on. Key Words: Transformer, Inverter, AC Load etc.

Optimal Configuration Planning of Multi-Energy Systems using Optimization-based Deep Learning Technique

There has been discovered that the freestanding hybrid renewable resource, which combines energy sources like solar, wind, etc., is an efficient substitute for supplying electricity to isolated places that are not connected to utility grids. The appropriate supply of electricity is subject to several restrictions, including variations in peak load, power outage supply, and other factors like swings. This study suggests an effective strategy for managing and sizing hybrid renewable energy resources to get around the drawbacks. First, the prediction of weather and loading demand is carried out using Bi-Directional Gated Recurrent Unit (Bi-GRU) network, in which past data are utilized to predict the uncertainties in load. This is done to assist the right sizing of resources for that purpose, a Long Short-Term Memory (LSTM) is used. Furthermore, the Search and Rescue Optimization Algorithm (SRO) employed for optimizing the parameter of power management. Utilizing MATLAB R2020a, the proposed model is tested by simulating it and comparing its performance to that of other models using metrics like variation rate, battery energy, Loss of Power Supply Probability (LPSP), forecasting error, net present cost, and cost of energy.

LVRT and Reactive Power/Voltage Support of Utility-Scale PV Power Plants during Disturbance Conditions

This paper proposes a control technique for a large-scale grid-connected photovoltaic (PV) plant that maintains the connection of an inverter to the grid voltage under different types of faults, while injecting a reactive power to accommodate the required grid connection. This control strategy is suggested to improve the low-voltage ride-through (LVRT) capability of grid-connected PV power generation plants. A 20 MW solar PV power plant is modeled and simulated using Matlab/Simulink. The power plant is composed of 10 parallel groups of arrays with a power rating of 2 MWp. The solar PV arrays are connected to a medium-voltage side-rated 22 KV to the utility grid. A dynamic analysis of the grid-connected large-scale solar PV power plant is introduced. This analysis is accomplished in order to determine the impact of three-phase short-circuits at the point of common-coupling (PCC), where the solar PV power station is connected to ensure a practical voltage level by injecting active and reactive power. The reactive power support allows for faster restoration of voltage values at the PCC. When subjected to transient disturbances, the stability of the studied system relies on both the type of the disturbance and the initial operating situation. The disturbance may be either small, resulting from electrical load changes, or large, such as from a transmission line short-circuit (fault) and significant generator loss.

Techno-economic appraisal of electric vehicle charging stations integrated with on-grid photovoltaics on existing fuel stations: A multicity study framework

The affordable transportation industry has been severely compromised in 2022 as a consequence of the unexpected surge in the price of fossil fuels. By 2050, the transportation industry is forecasted to expand twice, leading to a variety of issues, such as fossil fuel depletion and environmental emissions. As a result, worldwide trend toward electrifying transport, with energy production originating from both traditional and carbon-free sources. Therefore, consumers of electric vehicles require convenient access to the services of charging stations around the country. This research investigates existing fuel station rooftops for the deployment of the grid-connected photovoltaic (GCPV) system electric vehicle charging stations (EVCS), design, and performance analysis of Pakistan's cities. A mathematical model of the GCPV EVCS under consideration has been described. Three cities in Pakistan: Multan, Lahore, and Islamabad-EVCS powered by photovoltaics and the utility grid have been designed and their comparison of the techno-economic performance indicators have been done through System Advisor Model (SAM) software. To comprehend the impact of uncertainty on the functionality of the GCPV EVCS, sensitivity analyses were conducted at all three designated cities in Pakistan. With this strategy, Pakistan will be able to reduce its greenhouse gas emissions to the level required by the Paris Agreement.

Intelligent algorithm-based efficient planning of electric vehicle charging station: A case study of metropolitan city of India

Electric vehicles are gaining popularity and going to become the mainstream mode of transportation in urban and rural areas not only in India but globally in the next few years. In the adoption of electric vehicles, there are certain issues like proper charging infrastructure, charging time etc. and out of these the sizing and siting of the charging station particularly in urban areas where the cost of land and location plays an important role. Thus, it is important that the charging station location should be easily accessible for the electric vehicle users and cost effective as well. This paper presents an intelligent algorithm based efficient planning of electric vehicle charging station considering geographical information and road network. The cost function has considered such as investment cost, charging station electrification cost, electric vehicle energy loss cost and travel time cost. An intelligent algorithm-based approach is employed to solve the planning problem of electric vehicle charging stations. Further, the impact on reliability of the grid is also evaluated by determining the charging cost loss on each considered location. The result shows that the applied method provides better optimized solutions which are beneficial for electric vehicles users, charging station operator and utility grid.