ELK Research Centre - Phd Research Centre In Chennai

Latest News

Role of soft computing techniques for classification of power quality parameters and state-of-the-art mitigation techniques in Smart-Micro-Grid: A extensive review by ELKRC

Role of soft computing techniques for classification of power quality parameters and state-of-the-art mitigation techniques in Smart-Micro-Grid: A extensive review by ELKRC

29 Dec 2020

ABSTRACT

The power system at a worldwide level is growing with the help of revolutionary transformation because of the integration of several distributed components such as advanced metering infrastructure, communication infrastructure, and electric vehicle distributed energy sources. The distributed components help to improve the reliability and increase the efficiency of the energy management system and ensure the security of the future power system. The study also discusses how artificial intelligence techniques are applied to provide effective support in the integration of renewable energy sources, integration of energy storage systems, management of the grid and home energy, and security and demand-responsive. It was found that the involvement of the smart grid uses different battery technologies to increase the efficacy of the grid. It includes using lead-acid (L/A) batteries, lithium-ion (Li-ion) batteries, sodium-sulfur (NAS) batteries, and vanadium redox flow batteries (VRB). It was also found that challenges faced in smart grid power quality that create an issue in fault detection and conduction of safety analysis.

Keywords: Power Quality, Art, Mitigation, Micro Grid, Generation Forecasting, Great Health Monitoring, Home Energy Management

 

1. INTRODUCTION

Due to the increasing population at a worldwide level, there is an increase in demand for more facilitates because of which the energy service provider needs to increase their power generation, distribution, and synchronization abilities. High power generation at a global level is dominated by fossil fuel which is the main contributor to carbon dioxide in the atmosphere.

The above figure clearly states that there has been an increase in the global carbon dioxide levels with China emitting 28&, the United States emitting 15% and the rest of the world emits 21%. The countries such as Japan, Germany, Brazil, Saudi Arabia, and Indonesia contribute towards carbon dioxide emission with 4%, 2%, 2%, 1% respectively.

Due to the increasing carbon dioxide emission, it creates a threat in the world related to increasing global warming conditions and poor environmental conditions.  Due to global warming, degrading environmental conditions increasing carbon dioxide emission from the traditional power system, the government needs to focus on increasing renewable electric energy sources (Ord, 2020). For example; contributing green energy sources for power generation and distribution help in declining capital cost and provides a tax benefit to the government (Pilo, Pisano & Soma, 2009). There are several research has been conducted in this field and recommending fluxing in the market. The study also finds out the application of renewable energy sources provide an alternative source that only depends on the fossil fuel for the creation of green energy option for the hazard is gas emission reduction and also focuses on controlling the peak flow graph.

The above figure of peak flow graph of greenhouse gas emission globally in comparison to the energy consumption. It was found that in the year 2014 greenhouse gas emission was the largest with more than 3,400,00 MT CO₂ which reduced to 3,300,00 MT CO₂ in the year 2015. The greenhouse gas emission in the year 2016 was recorded to be low at 3,100,00 MT CO₂ as compared to the energy consumption of 5,150,00,00KWh. Thus, it can be said that the year 2016 recorded less greenhouse gas emission as compared to energy consumption levels. In the year 2017, the global greenhouse gas emission was recorded to be 3,000,00 MT CO₂against energy consumption of 5,000,000,00 kWh. Therefore, to reduce carbon dioxide emission and bring improvements in the environmental conditions along with meeting human need, the focus must be given to the construction of smart grids (Asgher, Babar Rasheed, Al-Sumaiti, Ur-Rahman, Ali, Alzaidi & Alamri, 2018).

To examine the smart grid technologies, it can be said that it helps renewable energy sources integration in the future power system by including several advanced information communication technologies.

 It mainly focuses on connecting with the customer data and transforms the electric power grid with the high iteration of distributed generation in the power system.

Apart from this, the smart energy market also focuses on artificial intelligence techniques that are considered as an easier technique to design good policy incentives and also help the consumer to make decisions about their consumption and generation so that it will help to contribute to the reduction of carbon dioxide emission. Apart from this, there are several challenges for the adoption of Artificial Intelligence (AI) in the electrical power system because it and designing automation technologies for heterogeneous devices so that it is not easy to learn and adapt by the consumption against the pricing signal (Javaid, Hafeez, Iqbal, Alrajeh, Alabed&Guizani, 2018). The energy sector is considered a complex field because it includes several intelligent tools that help to manage the system effectively and make a timely decision. Concerning this, artificial neural network reinforces on the adoption of learning genetic algorithm and multi-agent systems to provide a solution to the problem as per the classification, forecasting, networking, optimization, and controlling strategies (Ramos & Liu, 2011). Due to the lack of information about the advanced automatic controllable resources, several system operations are still performed manually or in a basic level of automation so that the inclusion of artificial intelligence in the great system has had to adapt innovative and new directions to the electrical grid. It depends on the distribution of the smart grid concept with artificial intelligence techniques that mainly focus on the optimization of controllable load by using several techniques that are related to the intelligent and cost result production. Apart from this, the genetic algorithm also helps in the effective management of a standalone microgrid. It optimizes the controllable load by increasing the computing power and helps to access more data storage with the help of techniques. It mainly provides a more efficient and powerful way to handle the limitation that is related to the adoption of the traditional grid system (Edris & D'Andrade, 2017). The current research analyzes how artificial intelligence and market liberalization can potentially help to increase the overall social welfare of the grid. The facts related to the comprehensive review of the state-of-the-art artificial intelligence techniques to support various applications in a distributed smart grid and are also discussed in the research.

2. LITERATURE REVIEW

2.1 Advanced metering in the smart grid

While focusing on the advanced metering in the smart grid, it includes major elements regarding the smart grid. It consists of superior meters or smart meters so much monitor the limit usage, talk, and control by optimizing the power usage, enforce data management systems to keep or technique metering and control data. AMI helps because of financial benefits, improved services, or opportunities because of attention regarding environmental concerns. Advanced meters shall hold bidirectional communication among the purchaser then the power provider, recording of electricity usage, communicating the data to the utility, with capability following measure control disturbances. It consists of an embedded processor because of Power Quality Analyzer (PQA) (Xu, Qian & Hu, 2018). The PQA embedded law core is done regarding the LPC3250 controller which has the ARM processor embedded within it. LPC3250 is NXP Semiconductor’s product. ARM is a design agency that manufactures ARM processors. ARM is a 32 bit embedded processor as has combined features of both Reduced Instruction Set Computer (RISC) and Complex Instruction Set Computer (CISC) architectures and supports around 266MHz. ARM has impure RISC architecture which makes it efficient to be used in the raw processor. The main difference reveals from the RISC architecture is its learning set. It helps a few a couple of cycle instructions involving stack load keep multiple instructions, an inline puncheon shifter for pre-processing, unique conditional execution to improve the overall performance. Digital Signal Processor (DSP) 16x16 pain-fill accumulates instructions for digital signal processing. Thus, ARM is now not an unaccompanied core but an entire array or assembly of designs sharing comparable graph principles than a common instruction set. The testing procedure includes analyzing if the selected sample has deviated from the reference wave path or not.  It includes a quantitative determination of deviation by estimating the magnitude and angle deviation. AD7654 includes both voltage inputs as well as current inputs to determine the 5000 samples in 2.5 microseconds. The other estimating factors such as electric phase current, powers are included to estimate the PQA hardware efficacy (Li, Qiu & Jing, 2018).

The figure describes three PQAs. If the RMS charge of the v is less than 90% of the rated value half a wheel then less than 1 min Swell and Voltage Sag are the instantaneous prices of the actual or much less than 90% of the instant voltage.  The main reason behind it that the length is much less as compared to deemed voltage to keep effective voltage harmonics. It interrupts sequence discovery techniques and standards. The pattern relies on per cycle generated transients, the algorithm of checking every out of the ADC. The testing pattern is deviating beyond deciding the total of which instituted. Both deviations are committed to caring for modern-day or voltage inputs kilo samples of the second. It is obtained in 2.5 microseconds to make some cycles. Thus, more than 5 microseconds rise meters as each segment voltage leading to enhancement of factor or energies.

2.2 Communication interface in the smart microgrid

While focusing on communication interface in the smart microgrid, it includes different technologies such as Digital Subscriber Line (DSL), Power Line Communication (PLC), Optical fiber, ZigBee is IEEE 802.15.4, Wireless Fidelity (Wi-Fi) WiMAX, and others.

Digital Subscriber Line (DSL) includes ten Mbps after ten Gbps statistics dosage on the conventional cellphone line. Asymmetric DSL (ADSL) includes eighth Mbps, ADSL2+ provides 24 Mbps or very-high-bit-rate DSL (VDSL) presents 52 Mbps downstream records dimension over copper wires. Power Line Communication (PLC) is an extensively old wireline communication technology for the SG. However, PLC rear plenty of empiric challenges such as unpredicted propagation functions or electromagnetic interference that hamper the working of transformers and transmission power lines. PLC applied sciences are used to bring improvements in the workings of the transformers transmission. Narrowband PLC (NB-PLC) offers 1 bps to 500 Kbps statistics dosage at 500 kHz frequency while broadband PLC (BB-PLC) provides up according to 200 Mbps data rate at 2 MHz to with 30 MHz frequency (Carralero & Quiambao, 2016).

An optical fiber (OF) guided media conversation is a globally deployed wireline communication infrastructure to strengthen the network for SGs purposes. It includes video visitors and dead low latency at all high speed. It provides the most regarding ten Gbps information dimensions together with an alone wave ranging from 40 Gbps to 1600 Gbps together with wave partition multiplexing (WDM). The optical/electric transducers used between optical verbal exchange is the best choice for SG fit according to spiffy sensing excuse features of the current yet voltage values of electrical power. Wireless communication technologies are usually an excellent suitable fit after pleasure on implementation then much less set up the price so a community following job together with the clever grid. However, wireless indicators may additionally bear greater wastage and thrusting that hampers the working of wireline indicators. It also impacts on over transmission or environmental factors It consequently leads to signals grant-based communication on shorter-range. It has fewer statistics quantity, bandwidth, and much less secure systems to secure confidential information (Batiller, Bugayong, Caisip, Coligado, Padilla & Pedrasa, 2016).

ZigBee is an IEEE 802.15.4 based on wi-fi mesh topology network because of cost-effective, ignoble rule, and well-organized solution wireless communication system. ZigBee has fewer facts dosage within private vicinity networks (PANs) certain as HAN. This wireless science affords numerous services certain namely automation, control, messaging, or far-off rule on client electronics/home/building so nicely namely healthcare, etc. It uses advice sequel measure spectrum (DSSS) according to grant communication in associated gadgets in altogether less power. It provides 250 kbps facts quantity on the 2.4 GHz unlicensed band, forty kbps over 915 MHz puttee, or 20 kbps above 868 MHz licensed bandage by channel. Wireless Fidelity (Wi-Fi) is a very popular or turned wireless partial location network (WLAN) science adopted by using the home services worldwide. When the operations take place in an unlicensed form, it disturbs the functioning of other associated technology applications and their spectrums. Innovations within applied sciences are moving Wi-Fi in the direction of government unfinished then reduced charge communication. Cellular networks are almost suitable wi-fi science of WAN verbal exchange structure because of the transportations of SMs or the Utility companies due to its stable infrastructure. Cellular networks are imparting numerous wider area capabilities in imitation of the SG purposes of a dead low-cost way. Emergent of third-generation (3 G) then LTE wi-fi communication technologies according to the cellular networks grant a good deal higher records charges in NAN yet WAN networks. Typical statistics dosage on Universal Mobile Telecommunications System (UMTS) example over three cellulars is 2.048 Mbps on the scale regarding over after one hundred twenty Kilometers and LTE is 300 Mbps downlink then 75 Mbps uplink above the strip about a hundred kilometers (Kabalci, 2019).

2.3 Electric vehicle in smart microgrid

While focusing on the electric vehicle, it is built-in between government systems and operates along with distinctive targets such as control drawing systems,  grid mechanism (during charging), and ESS of the electric grid to comply with the feeding rule. It scales up the cost initially and later decreases. It is referred to as an automobile with a grid (V2G). The restrained EVs as resources, theirs spatial-location, weak single, and low storage capacity, make unrealizable for the V2G services. In this case, a large number concerning EVs are aggregated in one-of-a-kind approaches depending on the rule schemes or goals following recognize the V2G concept. The quantity concerning the EVs as like a singular controllable distributed energy source execute participate between energy demand because of supporting electric grid between regulation or regulation management (Anastasiadis, Konstantinopoulos, Kondylis & Vokas, 2017).

The figure illustrates the VPP rule implementation among the V2G context. Within the electric grid then electricity needs players, the EV aggregator will operate namely a digital government plant. As depicted in Fig. 3, the clustered EV collection at charging rank presents fame as available SOC/available control in conformity with the charging management law (CMS) that communicates including the aggregator government core (local VPP control). At the VPP government middle, the aggregated battery power can stand despatched by providing ancillary applications whenever requested via the DSO and TSO. The VPP monitoring in the middle is embarked to centralize the power and communication management between energy users such as customers, producers, or grid operators. All these components are known as highly integrated as per the IoT because it is expected to generate a large amount of data that help several applications in the smart grid to execute distributed energy management, generation forecasting, great health monitoring, home energy management, and fault deduction. As a result, the paper mainly focuses and provides a comprehensive review of the state-of-the-art artificial intelligence technique that mainly helps to provide support for the application that is in a distributed smart grid (Jiang, Ning & Ge, 2019).

2.4 State-of-the-Art Artificial Intelligence Techniques for Distributed Smart Grids

 The integration of renewable energy resources (RES) can be executed by considering the prosumer and generation side. The prosumer side includes managing energy flow with the help of bidirectional interactive advancements. It includes the use of solar energy sources that help in reducing long-distance transmission losses and huge investment costs (Espe, Potdar& Chang, 2018).

The use of an advanced power distribution system loop structure in the generation side to eliminate the loss reduction and regulate voltage. It includes the use of an Artificial Intelligence (AI) based genetic algorithm that helps in determining the optimal schedule of units (Zafar, Mahmood, Razzaq, Ali, Naeem & Shehzad, 2018).  

Energy storage systems (ESS) is an essential component of future smart grid as it provides back-up for the renewable energy sources and mitigates the high energy demand on the local grid.  It ensures continuous power supply, improves the efficacy of the distribution grid, and reduces costs (Abujubbeh, Al-Turjman & Fahrioglu, 2019).

Using ESS with RES will help in reducing the consumption of fossil fuels and increasing the utilization of green energy (Farmanbar, Parham, Arild& Rong, 2019).

Deep learning (DL) and support vector regression (SVR) can be used to manage computing resources, customer data, and training algorithms that are included in the demand response and management of the grid (Liu & Hsu, 2018).

The demand and supply prediction enhances the reliability of the generators and helps in deciding smart grids (Sangpetch& Lo, 2002).

Home energy management (HEM) includes using software and hardware program to supervise the production of energy and manage energy consumption inside the home (Kakran&Chanana, 2018).

 The use of AI-based applications and wireless networks like ZigBee, Bluetooth, and WiFi enhance the working of HEM by developing communication between the grids (Gandoman, Ahmadi, Sharaf, Siano, Pou, Hredzak&Agelidis, 2018).

AI-based techniques such as ANN enhance the workings of the smart grid and provide security against cyber attacks. The major issues related to the establishing of the smart grid are related to security, privacy, and reliability issues. It hampers the communication, networking, and performance of the smart grid (Rahbari, Vafaeipour, & Van Den Bossche 2017).

 The smart grids are efficient in reducing the energy consumption levels by the households by developing a network of measuring devices and sensors. The different technology-based equipment such as turbines, sensors, virtual power plant improves the security and reliability of the grid by integrating renewable energy sources (RES) (Saponara, Saletti&Mihet-Popa, 2019).

 

2.4.1 Smart Microgrids

The microgrids are small, compact centralized electrical systems that provide power with low carbon emission and cost. Microgrids act as smart grids that integrate renewable energy with consumer and community participation to produce electricity. A smart microgrid is a modernized electric grid up to expectation utilizes information and communications science in imitation of gather yet employment on information, certain as like facts about the behaviors on suppliers or consumers, between an automated fashion following enhancing the efficiency, reliability, economics, and sustainability concerning the manufacturing or allocation on electricity. Transmission or operations: wide‐area monitoring, control, and protection. The smart grid is the shrewd limit rule which consists of several smart applied sciences kind of renewable, IoT, automation, etc. To construct a smart grid the complete regulation ought to remain modified from the good after the purchaser side also the construction (Hirsch, Parag & Guerrero, 2018).

 

The figure describes the secure critical lightning (unbalance to the secure critical lighting and secure the critical motor. It also includes nonsecure non-critical lighting that is interconnected and establishes control commands and feedback signals. The EMS controller and its functioning are related to battery inventor and power distribution.

Serial No.

Type of source/Load

 

Specification

 

1

Total Network Capacity

100kVA, 400V, 3PH, TT grounding system

2

PV Generator

25Kw

3

Diesel Generator

50kW

4

BESS

25kW, 50kW

5

UPS

15kVA, 400V, 3PH

6

Managed Tools

400kVA, Air conditioner, heater & Standard 16 A Loads, 10kVA

7

Priority unmanaged loads (Single phase)

PH1-N230 V, Lighting 13kVA, PF 0.7 & Loads: 12kVA, PF 0.8, PH 2-N 230 V, Lighting 8kVA, PF 0.55 & Loads: 7kLVA PF 0.6, PH-3-N 230 V, Lighting: 16kVA, PF0.8 & load:3.5kVA, PF 0.67

8

Priority unmanaged loads (Three phase)

400V, 3PH + N:20 kVA, PF 0.85 (Motor Loads)

9

Critical unmanaged loads (Three-phase)

400V, 3PH + N:6.45 kVA, PF 0.85 (Miscellaneous Loads)

Table 1 Microgrid specifications

Microgrids use different battery technologies to increase the efficacy of the grid. It includes using lead-acid (L/A) batteries, lithium-ion (Li-ion) batteries, sodium-sulfur (NAS) batteries, and vanadium redox flow batteries (VRB). Several microgrid projects have been developed by nations such as Morocco, Japan, Canada, Africa, and Venezuela to make effective use of microgrid generated energy (RETD, 2012).

For example, in Venezuela, the solar power plant has been established to make use of solar energy and generate 3500 kWh power annually.

2.4.2 Challenges in smart grid power quality

The major challenge with large-scale integration and orchestration of automated distributed devices to realize a truly smart grid is related to designing AI automated technologies in the electrical power systems (Ali, & Choi, 2020).

As per the above figure, the major issues related to smart grid power quality is with the estimation of the current status of renewable energy as improper estimation creates issues in the future forecasting of resources. The topological configuration of the renewable DG system is another aspect to be considered as it is related to the topology of the DG system. Power quality challenges are found related to monitoring ad quantification along. Therefore, power quality mitigation techniques are to be implemented to classify and strengthen circuit configuration.

Challenge is also faced in developing coordination between the RES penetration and distributed energy. It also includes issues related to rapid management of the system conditions especially related to controllable loads (CLs) and distributed generators (DGs). Hindrances are also caused because of complicated end-to-end control techniques. Moreover, in the absence of AI techniques in the smart grid working, there is an issue in fault detection and conduction of safety analysis (Cetina, Roscoe & Wright, 2017).

2.4.3 Signal Processing technique

The power quality detection and classification schemes that are based on digital signal processing (DSP) and machine learning (ML) are included in the microgrid to enhance its efficacy (Mishra, 2019).

The above figure describes the PQD&C model in which feature extraction is executed with the help of signal processing techniques and ten feature selection and classification processes are carried out. It includes input signals that are based on feature extraction unit application. It is an integral part of the signal processing technique and performs the activities related to the feature selection unit. In the next phase, the classification unit is carried out that is based on the application of an intelligent classifier. As a result, by carrying out the different processes effective decision-making process is executed to extract features (Zamani, Golshan, Alhelou & Hatziargyriou, 2019).

The above figure explains the different feature extraction techniques that are used to extract features from SPTs. It includes a Wavelet Transform based method that represents transients that help in ascertaining sounds within audio and high-frequency components within a two-dimensional image. The Stockwell Transform based method is responsible for improving the time-frequency decision of Short-Time Fourier Transform (STFT). The Gabor Transform based method analyzes specific frequency content material among the photo between particular instructions of a localized location around the point. The Hilbert-Huang Transform based method passes a signal called the intrinsic mode and achieves immediate frequency data. The Kalman Filter based method controls the effect on more than one terminals that are affected by data sensing frequencies (Ucar, Alcin, Dandil & Ata, 2018). The feature selection is performed by using different signal processing techniques (SPTs) such as Fourier Transform (FT), Short-Time Fourier Transform (STFT), S-transform (ST), Hilbert transform (HT), and Kalman filter (KF).

2.4.3.1 Fourier Transform

The Fourier Transform (FT) is day dependent and tells about frequency contents among the sign and does now not incorporate records over then she appears and for or long that exist. It is represented with an equation

Fourier radically change (FT) is aged after the procedure and analyze only stationary signals, but close PQ signals are non-stationary, hence, a technique is developed that focuses on frequency statistics. It must also capture the timing over occurrence regarding the disturbance. Since FT is not an environment-friendly analyzing device for extracting the transient facts about the non-stationary signals. It performs keep both topical and periodic functions (Kita, Miranda, Favela, Bono, Michon, Lin, & Hu, 2018).

2.4.3.2 Short-Time Fourier Transform

Short-Time Fourier Transform (STFT) divides the complete epoch inside within several small/equal – time intervals. It extracts several frames about the signal to lie analyzed including a hole that moves along time (Wang, Zhao, Wu, Xie & Zhang, 2017). Nonstationary indicators characterized with the help of extensive measure of frequency spectrum together with temporary yet under harmonic components are hard to analyze with STFT. For non-stationary signals, the STFT does now not song the signal dynamics suitable appropriate to the boundaries of fixed eyelet cover. It is estimated by using a mathematical expression

2.4.3.3 Discrete Fourier Transform

 DFT is ancient for analysis about frequency content material within consistent state periodic signal then is appropriate because of harmonic analysis. It is a widely separated sign processing algorithm. The Fast Fourier transform (FFT) produces the same result to evaluate the DFT but the sole difference is FFT is a great deal faster. It is estimated by using a mathematical expression (Ponomareva, Ponomarev & Ponomarev, 2018).

2.4.3.4 S-Transform

S-transform (ST) is a hybrid of STFT and wavelet analysis, bridges the gap between them containing the elements over each grudging its characteristic properties. Gaussian makes S-T a strong tool for monitoring characteristic analysis. ST has excessive tolerance and accuracy over-classification (Shafiullah & Abido, 2018).  The disadvantage of the S-transform is the hard computation because each frequency point in the Fourier spectrum wishes to be extended by using the Gaussian aspect for inverse Fourier transform. Therefore, the conduct epoch of s-transform is more. It is estimated by using a mathematical expression

2.4.3.5 Hilbert-Huang Transform

 Hilbert transform (HT) together with Empirical passion Decomposition (EMD). It is a new technique on analyze non-stationary signals. The substantial use concerning EMD is after preparing the signal because of the input on HT (Gururani, Mohanty & Mohanta, 2016). EMD generates a collection of intrinsic anger functions (IMF), that helps in the extraction of energy associated with various personal era scales. It is estimated by using a mathematical expression

2.4.3.6 Kalman Filter

 Kalman filter includes the amplitude for capturing waveform. If there is anybody alternate in the magnitude regarding the fundamental component, the Kalman filter is used to analyze the voltage event. The effects of the Kalman filter depend on the model of the rule then suitable selection over filter parameters. If the filter parameters are not suitable, the rate regarding convergence wish to lie slow or the effects choice diverge (Talebi, Kanna & Mandic, 2016). For example, the use of DFT helps in identifying the computation algorithm and extracting the spectrum at particular frequencies.

As per the above figure, it can be said that different techniques such as autoregressive moving average, likelihood ratio, mutual information ratio, Kalman Filter, and game theory are used to detect and classify schemes that are based on digital signal processing. It also includes other techniques such as image processing, wavelet, Gradient-Based Technique, ICA, PCA, Neural networks, and DFT to ascertain stationary as well as non-stationary signals. For example, the autoregressive moving average is used for the evaluation of a (weak) static stochastic process of phrases that are in joining polynomials because of the autoregression (AR) and shifting average (MA). The likelihood ratio is used to examine the goodness over fit about joining competing statistical data based on the ratio regarding their likelihoods, especially one discovered utilizing maximization on the complete parameter area then every other discipline mutual information ratio is used to enhance the performance of the smart grid by bringing improvements in storage and management of data (Aly, 2020). Kalman Filter supports practical operations by estimating the modern-day regime about the propeller system or issuing up to date instructions. Game theory describes the functioning of the model concerning the behavior of human populations. The image processing includes processing of an image with the help of digital equipment and algorithm. Wavelet has a specific feature that makes it useful in signal processing Gradient-Based Techniques are methods for nonlinear functions that assume simplicity and represent differentiable functions.  ICA, PCA, Neural networks are used for predictive purposes by exercising adaptive control through trained datasets. DFT converts a finite annex into equally-spaced samples such as a same-length supplement and equally-spaced samples about the discrete-time Fourier transform (Karimipour & Leung, 2020).

As per the above figure, the different techniques of signal processing are used to provide cybersecurity, reduce noise in the fault identification, and used as a sensor network. It is also used for DSP energy management, low voltage smart metering, estimation of wide-based noise, fussy based network, and estimation of power quality. It is also used for load management, data privacy in smart meters, load disintegration, and smart metering.

While focusing on several techniques that are included in the single processing technique, it includes several techniques such as autoregressive moving average, likelihood ratio, mutual information, Kalman filter, and game theory that help in providing cybersecurity, and reducing noise for fault detection. For example, the compression technique is useful in storing and managing data that enhances the performance of the smart grid. On the other hand, game theory is responsible for carrying out functionaries related to the home energy management process. A transformerless active filter-based technique is responsible for improving the quality of the workings of the single-phase households (Kurt, Yılmaz & Wang, 2018).

2.4.4 Artificial Intelligence techniques

Artificial Intelligence technique is defined as an important element of power quality disturbance (PQD) that helps in controlling power grid pollution. It includes the use of a kernel SVM (KSVM) classifier for carrying out the classification process and making use of kernel combinations. Moreover, there is a classification of optimized S-transform (OST) and kernel SVM (KSVM) so that the multiple features are identified (Wang & Chen, 2019).

The enhancement in the distributed generation, distribution management, and smart consumption include several AI-based techniques such as Random forest regression, k-nearest neighbor regression, linear regression are used to forecasting the load. It includes correlating the categorical distinctive levels and provides valuable information about whether aspects. However, the major limitation of the technique is that it includes growth factors of the population that drive the load demand. The AI-based techniques such as the Compact decision tree (CTD), fit k-nearest classifier (FitcKnn), linear regression model (LRM), stepwise linear regression model are also used to forecast energy demand. However, the use of techniques is limited as they apply to small buildings. AI-based technique such as ANN is used to classify the load curve patterns of each consumer in the DSM to give financial benefits. It also helps in the detection of energy fraud. However, its use gets restricted as is based on decision variables and creates security issues (Wang, Liu, Ye, Tang, Gou, Huang & Wen, 2019). 

2.5 Power Quality improvement provide Digital Economy by the Smart Grid

Power quality is essential for producers and customers. Power quality controls the traits over the rule supply and implements the deregulation approach at both the consumer level and power provider level. The improvements in the power quality help in reducing the troubles related to monitoring attributes. It includes removing issues related to technical implications of poor power quality. It includes making effective use of different devices such as workstations, PCs, copiers, printers, lighting, and other electronic devices so that there is a reduction in waste of resources. It includes the use of a transformer so that there is a reduction in the copper losses and control over wild movements (Bagdadee, & Zhang, 2019). It could be expressed with the help of expression such as equation 1

 in which ECU = total copper loss Ewl = Eddy's current loss, 50 Hz (full load) ECL = Additional eddy current loss, 50 Hz (full load) ESL = Floating losses of construction parts (full load) 50 Hz IS = Effective current on harmonics (per unit) n IL = effective value of total load current (per unit) IP =The basic component of the load current (per unit) at the frequency 50 Hz HN = harmonic number

2.6 Analysis and Mitigation of Power Quality Issues in Distributed Generation Systems

Poor power quality leads to unnecessary wastage of power and the financial system. It creates a pecuniary liability on the suppliers then consumers. The unstable voltage then frequently often creates a fix with base stations through the transmission line. Evaluation technique concerning power multiplication problem is depicted that creates an issue in the Distributed Generation Systems. There are 5 categories of problems such as voltage unbalance, voltage interruptions, flicker, transients, and harmonic distortion. After identifying the category, characterization of the hassle is made through measuring and gathering data to locate abroad the causes, characteristics, then equipment impacts. The subsequent two steps are related to figuring out the spread about solutions, and evaluation of solutions. The last step is to consider the optimum solution besides whole the chances after achieving the most pecuniary outcome (Basak, Chowdhury,  nee Dey, & Chowdhury, 2012).

Serial number

Mitigating measures

Figure

  •  

STATCOM

Statcom is based on the linked customized power device that corrects and controls modern-day harmonics. It improves the power exorcism and offers filtering, voltage regulation at distribution. It acts as a filter component to establish a shunt-connected voltage source converter (VSC), IGBTS together with PWM (Ramamurthy, Wanniachchi & Enomoto, 2016).

 

 

  •  

UPQC

A UPQC regulated the voltage and preserve them at the goal level. It mitigates the issues such as much negative monitoring factor, assigns tunable currents, and load unbalance. It injects currents among the system in imitation of making the source currents coherent sinusoids in-phase along with the source voltages (Abdalaal, 2020)

 

  •  

UPS

UPS is based on reduced-switch-count mass that monitors the topology, energetic front-end filtering, and seamless transition process. It monitors Grid isolation and suspends feed at some stage to avoid power failure (Estévez de Bén, Alvarez-Diazcomas & Rodríguez-Reséndiz, 2020). 

 

 

 

 

2.6.1 Power quality definition and standards

Power quality is related to standardization, assessment, monitoring, and remission that are borne by manufacturers, customers, utilities, or researchers. Power quality is referred to as maintaining the quality of electric power distribution so that there is a reduction in the loss of power consumption and distribution. Power quality has exceptional meanings beyond special points of view, it could be in the form of solved or share resolutions of the product. If that is considered beside the point of a view about electric devices must have a rule quality. Therefore, it is essential to maintain the standards and regulations so that there is standardization in the power quality distribution (Music, Bosovic, Hasanspahic, Avdakovic&Becirovic, 2012).

2.6.2 Smart microgrids, new tools of smart grid, and challenges in smart grid

Smart microgrids, new tools of smart grid help in advanced forecasting in the form of demand (load) forecasting, electricity price forecasting,  wind, and PV production forecasting. For example, to improve the wind output control degree the use of vague control for power storage provision among wind farms. As a result, issues related to variability, unpredictability, and weather allegiance of renewable power assets are identified that create challenges for integration in the renewable generation as per the predominant grid (Yoldaş, Önen, Muyeen, Vasilakos& Alan, 2017).

2.7 Intelligent tools in smart microgrid

2.7.1 Advanced metering infrastructure (AMI)

AMI enables the application over technologies, such as intelligent meters or other advanced dimension devices, according to enable two-way information technologies by establishing a linkage between IP addresses and smart utilities. Thus, AMI is responsible for making provisions for real-time data transfer at a rate that is low and affordable by the consumers. This desire commends the smart grids a broad thoroughness on functionalities, such as far-flung consumption control, time-based pricing, destruction forecast, fault or outage detection, remote coalition and disconnection on users, theft discovery, and loss measurements, or tremendous money series then debt management. Meeting these goals means the development in imitation of a smarter grid that will have better monitoring upon limit virtue beyond different aspects. Logging and reporting on someone sort of anxiety or outage between all speedy way will improve the power characteristic index in AMI-equipped grids (Ikpehai, Adebisi, & Rabie, 2016). 

2.7.2 Modern monitoring devices

The modern monitoring devices are based on the real-time rule that displays overall performances within a wide area. It includes a resolution parameter following understanding then optimizing the dictation operation. Advanced system focus avoids blackouts then reports the rule logs to predict yet stop probably faults, generate information for after decision-making, prevent wide-area disturbances, or enhance the transmission capability and reliability over the grid. This feature is the beginning of the direction that leads after PQIs. Without intelligent devices, a smart grid is just a grid, but enabling its characteristic pleasure furnishes more efficiency, quickness, and legibility to PQI into smart microgrids (Lai, Lu, Wang, Dehghanian & Tang, 2019).

2.7.3 Information and communication technology

Communication science sheds a necessary function among improving the power characteristic problems on clever microgrids. Previously, devices were trying to become structured about the verbal exchange to reach the expectation level of choices. However, the devices showed some drawbacks such as incertitude, lack of recording, and latency issues. Other researchers suggested using low-bandwidth communication dictation up to expectation used to be not hence efficient. Some lookup holds have been taken in conformity with accomplishing the verbal exchange technology more reliable by way of predicting the lost bits in the conversation links. However, after all, the deficiency of a proper, fast, and high-bandwidth conversation system is a drawback for the PQI devices. With a reliable, fast verbal exchange science the monitoring multiplication of smart microgrid intention improves a lot (Lai, Lu, Li & Tang, 2018).

2.7.4 Smart appliances

Nowadays, just about the domestic appliance producers hold started following include smart chips inner the home appliances to make it viable because of each device to hold a two-way conversation including the grid, mean than the ability in imitation of being controlled from nearly in all places while taking section within demand response program. A class of clever home equipment ought to be smart loads, which could directly impact the smart grid power quality; extra small print respecting the act about it units ought to lie found.

2.7.5 Storage devices

With the growing entry about probabilistic RESs, the usage of storage devices is a fundamental section on the smart microgrids. The appearance of advanced electrical energy tankage technologies has greatly influenced the vision because of the future of this technology. Deployment integrated superior storage device technologies include wonderful capacitors, advanced sodium-sulfur battery technologies, and glide batteries together with compressed air. To build a wide vision of smart grids, it includes pumped hydro and angry storage technologies. Developments in storage technologies intention affect the plug-in hybrid motors (PHEV) science and its influences regarding DSM then peak administration scenarios (Olival, Madureira & Matos, 2017).

2.7.6 Computational intelligence

A vital issue on smart grids is the computational intelligence that has progressed highly in the closing decade, construction it possible according to function advanced rule techniques between real-time then forecasting applications. Deployment of its technological know-how desire significantly affects the power characteristic of smart microgrids considering just about the real-time PQI techniques need high computational capabilities to digitally control the effect of the PQI process.

2.7.7 Advanced monitoring methods

Advanced rule methods may screen or control the control dictation factors or do redact that viable because government electronics to give a well-timed and rapid brawny answer in conformity with anybody event. These strategies additionally contain in decision-making procedures regarding demand pricing, bettering asset management and an extensive place concerning computer-based algorithms, certain as much information collecting, monitoring, yet inspecting to supply innovative solutions beside deterministic and predictive perspectives, upgrades in computational functions to merge power-converting mission with PQI purposes for government electronic-based converters (Olival, Madureira & Matos, 2017).

2.7.7 Active demand-side administration and  demand response

The DSM is a set of activities, which ultimately pleasure conduct to more advantageous reliability, expense management, peak shaving, peak shifting, transmission then technology about virtue reduction or extended voltage quality. Different technologies are worried into DSM, such as power system, RESs, battery storage, smart appliances, computational intelligence, then almost whole the clever grid technologies. Having an extra reliable microgrid so much has a tremendous voltage outline results in the implementation of DSM.

2.7.8 Multiagent technology

Multiagent technological know-how is truly an umbrella term so much encompasses quite a few applied sciences for a common goal; this goal could remain anybody achievement, such as like PQI within smart microgrids. The multiagent rule makes such feasible for different sections in imitation of work to balance and achieve the described goal; that is a kind of hierarchical rule as it makes use of exclusive retailers following operates a task. For example, in imitation of performing a required report scenario; one-of-a-kind agents should remain employed, such as power or dimension agent, computational agent, decision-making agent, and, finally, the agent is accountable to perform the moves concerning the generation of gadgets (Gomes, Spínola, Vale & Corchado, 2019).

2.7.9 Internet of things

The concept of the Internet over Things (IoT) is a very considerable area concerning technological know-how up as it includes almost everything, ranging out of an affected person whosoever has implanted a heart monitor to home equipment together with an integrated base station to join to the internet. Nowadays, half of home appliance organizations incorporate quintessential chipsets that integrate digital appliances It includes an active sharing of DSM units, higher regulation planning, and competitively priced graph of transmission systems. This intention also improves the functionality concerning two-way communication in the grid yet costumers (Al-Turjman & Abujubbeh, 2019).

2.8 Power quality improvement device

PQI gadgets have been delivered and installed whole atop the electrical energy grid. To circulate the PQI devices chronic in smart grids, a comment on beforehand old PQI devices ought to keep introduced. PQI devices may want to lie categorized in 3 foremost generations based totally on their developing epoch addition to a transition condition; a short rationalization about these categories is provided between the accordant sections. As they progress through conventional electric systems, the smart electrified systems are not considered to be sudden but a transition situation. It should apply the function to pass through smart electrical systems’ standards (Ceaki, Seritan, Vatu & Mancasi, 2017). As a summary, before introducing different generations on PQI devices, an obstruction design concerning an array of PQI units is shown in Figure.

2.8.1 First-generation power quality improvement device

the first grid is based on a simple structure and does not involve much cost. It helps in reducing the value concerning the use of high-power APFs, hybrid power filters are a splendid choice that has the abilities on both active and dead limit filters at the identical time. It is also responsible for defining instant applications for hybrid limit filters and increasing the durability of the system (Naderi, Hosseini, Ghassemzadeh, Mohammadi-Ivatloo, Savaghebi, Vasquez & Guerrero, 2020).

2.8.2 The second generation of power quality improvement devices

The second generation is based on the use of power quality instruments so that there is a generation of power at a low cost. It includes the use of PQI devices, such as DVR, static volt-amperes reactive (VAR) compensator (SVC), STATCOM, the automatic voltage regulator (AVR), and UPS so that there is the establishment of more complicated control systems. It will help in reducing power loss and increasing the efficacy of the system (Gandoman,  Ahmadi, Sharaf, Siano, Pou, Hredzak & Agelidis, 2018). 

The third generation of power quality improvement devices is based on pioneered devices such as ES, smart impedance, and MFDGs so that the several power generation tasks are performed fault free. For example, the use of a PQI device known as smart impedance helps in enhancing quality factors, tuned, or displacement control issues (DPF).

 

2.8.3 Smart impedance

Smart impedance can improve voltage rule or durability within sickly structures certain as small microgrids (smart grids) especially when the supply impedance is no longer mean.

While focusing on the smart impedance, it is the device that possesses the features of the second generation as well as third-generation PQI equipment and known as smart impedance. By considering the physical point of view, smart impedance is considered an effective device that is made up of a combination of APF and appropriated control strategy and a capacitor bank. It also includes a coupling transformer that helps in solving the issues related to the tuning process in the case of passive filters. It also helps in enhancing the quality factor by establishing a regulation between the weak systems in the smart grids. As a result, there is an improvement in the voltage regulation and displacement power factor (DPF). The smart impedance is controlled by the proportional resonant (PR) with the help of a shunt active filter. The main reason behind the selection of this technique is that it helps in performing a series of APF and mitigating selected harmonics of interests (Baloi, Pana, & Molnar-Matei, 2011).

2.8.4 Electrical spring

Electrical spring is another major component of the grid that is based on the mechanical dipping standards after regulating the voltage in a distributed way.

ES performs a similar position to the mechanical springs internal the mattresses to prevent subsidence. It is responsible for stimulating mechanical features on ES to recover the voltage dips. It moves the function of a smart load with the power generation plan between the cases of integration into the noncritical electrified appliances. The utility of the distribution of electrical energy through grid intention lead to an increase in the longevity and impartial conduction of the system as compared to the communication system. It includes ES which is capable of compensating active and effective power. 

2.8.5 Multifunctional distributed generations

The pioneering technology to improve the rule exorcism among smart grids is the use of MFDGs to monitor devices virtually locally or globally. These days the progress is mainly related to making a CO2-free world, cheap or tidy strength sources would accelerate the attention following RESs. However, close about it energy sources utilize limit electronic-based converters the following yield the desired AC voltage with the predominant electricity grid, as makes it strength sources a costly electricity generation. To perform the technology more charge effective, other functionalities may want to remain brought following the government electronic-based interfacing converters, certain as rule attribute increase capabilities.

2.8.6 Applied control methods to multifunctional distributed generations to enhance power quality

Applied control methods to multifunctional distributed generations to enhance power quality are also an integral part of the 3rd generation microgrid. It includes MFDGs interfacing monitoring electronic-based converters so that the multifunctional capacity of the grid is generated. It also includes monitoring methods are PR administrator and model-based predictive discipliner (MPC) to control the voltage and current simultaneously (Guerrero, De Vicuna & Uceda, 2007).

2.8.7 The Proportional + Resonant control method

To overcome the harmonic reference tracking issues concerning a PI controller, the PR discipliner used to be developed; the major difference between PI and PR controllers is the parallel resonant loops so hold the duty of monitoring the harmonic references. It has been widely used as a MFDGs or hierarchical microgrid monitoring.

2.8.8 Current-controlled method

The use of the current-controlled method is executed for the creation of the control objective and tracking the current reference.

It includes the use of assessment methods such as harmonic-free output current of MFDG so that there is an estimation of default compensating of CCM It is estimated by using an expression

In which I erf isis knew as the main current for CCM and I ref_f is known as the foundational current reference. Iref_h is known as the harmonic reference to the current CCM. As a result, there is the attainment of expression

It represents the local load harmonic current. It leads to the creation of a whack-a-mole effect that indicates that the creation o harmonies at certain points lead to the compensating effort in the grid. It is represented with the help of expression

In which Hd (s) specifies the harmonic detector. It is used to extract the harmonic components from the local load current. It leads to the creation of harmonic frequencies by using expressions

That is in equivalence to MFDG.

2.8.9 Voltage-controlled method

Although CCM is used in most of the grid-connected MFDGs, VCM is increasingly used because of its stand-alone capabilities. MFDGs conduct power execution over a coincident generator to establish autonomous control on microgrids, for voltage then frequency control, VCM ought to keep applied according to interfacing converters. Another advantage of using VCM is the limit regarding the number of MFDG gadgets the following piece the power between a decentralized way utilizing a stoop controller besides someone wants after a talk in MFDG.

To recompense the PCC voltage harmonics, because of voltage mention a feedforward period should lie old as

MFDG moves the position on little impedance in elect harmonic

frequencies together with equal harmonious impedance regarding up to expectation sweet and up to the expectation it could take in chosen tunable currents.

2.8.10 Hybrid control method

HCM is based on the rule of the voltage and modern-day aspects in which the output Inductance+Capacitance +Inductance Filter (LCL) filter fundamental capacitor voltage is responsible for line current management. The fundamental difference between CCM, VCM, or HCM is that, unlike the two methods, such could control the fundamental factors in a decoupled way, so up to expect such pleasure proclaim incomplete modern characteristics following MFDG interfacing converter controllers (Li & He, 2014).

2.8.11 Model-based predictive control (MPC)

In this section, MPC would stay applied according to a prototype microgrid which includes an MFDG after try the PQI characteristics namely nicely as much multiobjective operation capability concerning the limit method (Rodriguez, Kazmierkowski, Espinoza, Zanchetta, Abu-Rub, Young & Rojas, 2012). The simplest cost function for an MPC discipliner could remain a modern-day notice monitoring such as

The above figure describes the functioning of a simple MPC that makes use of a modulator to generate switching signals concerning a continuous yield about the predictive control. The fundamental competencies include finite number overstating between optimization problems, which desire propulsion to lower aggregate about computational encumbrance or a strong solution because of the limited systems including limited computational abilities. Another ability of FCS-MPC is to convert modulation bottom that minimizes the computational encumbrance. It has a disadvantage regarding moving to switch frequency and FCS-MPC.

2.8.12 Multi-objective model-based predictive control

The predominant distinction of multi-objective model predictive monitoring (MOMPC) and single-objective mannequin predictive control lies among defining the virtue function and the balance factors up to expectation as a substitute on the usage of a simple price characteristic (Savaghebi, Jalilian, Vasquez & Guerrero, 2012). It ascertains  a greater problematic value feature desire stand used, as is as follows

 

Control Method

Advantages

Disadvantages

Application case

PR-CCM

Control Simplicity

Needs HD block

 

Grid-Connected MFDGs

 

PR-VCM

Decentralized power-sharing without communication systems

The problem in IDG comp needs grid slide info, the problem in ILocal comp, needs HD block

Stand-alone MFDGs

PR-HCM

 

No need for HD block, independent Control of IDG and VDG, could replace CCM with HD

Control complexity, slow dynamic response

Grid-Connected ad Stand alone MFDGs

 

MPC

Fast dynamic response

Operation in grid-connected mode only

Active power filters, Grid-connected MFDGs

MOMPC

Fast dynamic response

Operation in grid-connected mode only

Modular active power filters, Parallel grid-connected MFDGs, Modular UPSs

 

Table 2 Comparison of different control methods applied to MFDGs  (Power quality issues of smart microgrids: applied techniques and decision-making analysis