Showing papers in "International Journal of Emerging Electric Power Systems in 2020"

Optimal Sizing and Placement of Capacitor Banks and Distributed Generation in Distribution Systems Using Spring Search Algorithm

Abstract: Abstract Integration of capacitor banks (CBs) and distributed generation units (DGs) in distribution systems aims to elevate the system performance. Optimal sizing and placement of CBs and DGs using Spring Search Algorithm (SSA) is proposed. The SSA aims to attain economic, technical, and environmental advantages. Various objective functions: total emissions produced by generation sources, voltage deviation, total electrical energy cost, and power losses are evaluated. SSA simulates Hawk’s Law among weights and springs. In SSA, agents are weights connected to each other by springs. Performance of the proposed method is evaluated on the IEEE 33-bus system. The results indicate superiority of SSA compared with other optimization algorithms.

Wireless Power Transfer Topologies used for Static and Dynamic Charging of EV Battery: A Review

Abstract: Abstract Electric vehicles (EV) are found to be a good alternative for the conventional internal combustion (IC) engine vehicles in transportation sector due to its various advantages. Now-a-days, wireless charging of EV battery is preferred among the various methods used for charging EV battery. In this paper, extensive review is carried out on various methods used for wireless charging of an EV battery. Different techniques used for transferring power in wireless mode to charge the EV battery are static EV charging technique and dynamic EV charging technique. Static wireless EV battery charging technique adopts inductive and capacitive method for transferring power whereas, dynamic wireless EV battery charging technique adopts only inductive method for transferring power. These techniques are discussed thoroughly in this paper and broad review is carried out with a focus on the compensation circuit topologies, types of core for magnetic coupled inductors, different converters and controllers used for wireless power transfer (WPT) system. Also, design aspects of an static wireless EV battery charging system along with its equivalent circuit analysis is presented in this paper. Challenges and future development in wireless charging of EV battery is also explained in this paper.

Design of Load Frequency Control for a Microgrid Using D-partition Method

Abstract: Abstract This paper proposes a load frequency control (LFC) scheme for the distributed generation (DG) system of the microgrid (μ-grid) using the D-partition method (DPM). μ-grid is formed with a combination of renewable and non-renewable sources to supply distribution system loads of smaller capacity. In this research paper, μ-grid comprising of a combination of a wind turbine generator (WTG) and Diesel Generator (DG) are taken for investigation of LFC. For the effective control of real power generation of μ-grid, Proportional-integral (PI) controllers are implemented for WTG and DG system so that the frequency deviation is minimized. The PI controller parameters found by using DPM are compared with the conventional Ziegler-Nichols method (ZNM). The main contribution of this work is to provide a single step /simplistic computing method for calculating the PI controller parameters of a dynamic system such as the microgrid system comprising of the renewable energy sources without any further requirements of retuning. Simulation results demonstrate the robustness of the DPM, which is superior in damping frequency oscillations of μ-grid.

Efficient Energy Delivery System of the CHP-PV Based Microgrids with the Economic Feasibility Study

Abstract: Abstract A comprehensive theoretical investigation validated by the measurement is necessary to assess the impact of a microgrid on the electric distribution system. Some key parameters worth investigating are- enhancing economy, reliability, quality, and resiliency of a microgrid. Considering this necessity, a study of energy delivery system in a microgrid and its financial feasibility to integrate into the energy infrastructure has been presented in this paper. A campus microgrid with energy-efficient combined heat and power (CHP) natural gas-fired microturbine and photovoltaic generation has been used as a testbed to evaluate the efficiency of the power delivery. With distributed control and communication capability, this microgrid can be considered as a building block of smart grid that facilitates the inclusion of renewable and energy-efficient distributed generation. Simulation work has been performed to study the economic feasibility to integrate such microgrid into the energy grid. Several cases of remote microgrid operation have been studied to compare the best possible solution.

MPPT Control of PMSG Based Small-Scale Wind Energy Conversion System Connected to DC-Bus

Abstract: Abstract While the use of renewable energy systems in electric power generation is increasing more and more, wind energy conversion systems (WECS) receive considerable attention among these. Thanks to the ability of power generation in all wind speed range by controlling the rotor speed, Variable Speed WECSs are more preferred than fixed speed WECSs. When considering small-scale applications in variable speed WECS, Permanent Magnet Synchronous Generator (PMSG) based WECS structures are focus of the interest due to their advantages such as high efficiency and low maintenance costs. The generator must be operated at an optimum speed to obtain maximum power from the WECS. Moreover, different Maximum Power Point Tracking (MPPT) methods can be used to control and determine optimal operating speed. In this paper, WECS configuration consists of PMSG, uncontrolled rectifier, DC link capacitor, DC-DC boost converter and DC-Bus. Capturing the maximum power from WECS and supplying the DC-Bus is performed via tip speed ratio and PI control (TSR-PI) based MPPT method. Moreover, two wind speed profiles having constant and instant changes are created to test the performance of the proposed method. For comparison purposes, perturbation & observation (P&O) based MPPT method is also carried out in here. According to obtained results from this study performed in Matlab/Simulink environment, it is verified that TSR-PI based MPPT method ensures higher power and efficiency for these wind speed profiles by means of a more successful generator speed tracking.

Optimal total harmonic distortion minimization in multilevel inverter using improved whale optimization algorithm

Abstract: Abstract This paper presents the solution to mitigate the total harmonic distortion (THD) in multilevel inverters (MLIs) using novel improved whale optimization algorithm (IWOA). The IWOA falls under the category of swarm-based nature inspired optimization algorithms. It uses a novel diffusion process using a random walk technique and utilizes an additional ranking system to estimate the optimum solution to minimize THD. Moreover, THD minimization is further accomplished through nine various meta-heuristic algorithms for investigation and comparative analysis. The selected algorithms along with the proposed IWOA are rigorously tested on single phase 5 and 7 level cascaded H-Bridge MLIs for various performance parameters such as consistency, computational efficiency and speed of convergence. It is found that the proposed algorithm outperforms the nine algorithms and is efficient for THD minimization for modulation index (MI) in the range of 0–1. The results are analyzed and reported after thorough verification using MATLAB simulation. Highlights It presents a novel switching technique through improved whale optimization algorithm (IWOA) to optimize the switching angles of a single phase 5 and 7 level multilevel inverters (MLIs) in order to minimize the total harmonic distortion (THD). IWOA incorporates a novel diffusion process and two new position updating techniques The proposed IWOA provides better computational efficiency, improved consistency and faster convergence compared to the older whale optimization algorithm (WOA) with minimal tuning of the algorithm’s parameters. The proposed IWOA is compared alongside various meta-heuristics like genetic algorithm (GA), particle swarm optimization (PSO), grey wolf optimizer (GWO), krill herd (KH), artificial electric field algorithm (AEFA), sun flower optimizer (SFO), galactic swarm optimization (GSO), fruit fly optimization algorithm (FOA) and whale optimization algorithm (WOA) for optimal THD minimization.

Stochastic electrical energy management of industrial Virtual Power Plant considering time-based and incentive-based Demand Response programs option in contingency condition

Abstract: Abstract Nowadays, the sustainable energy management of industrial environments is of great importance because of their heavy loads and behaviors. In this paper, the Virtual Power Plant (VPP) idea is commented as a collected generation to be an appropriate approach for these networks handling. Here, Technical Industrial VPP (TIVPP) is characterized as a dispatching unit contains demands and generations situated in an industrial network. A complete structure is proposed here for possible conditions for different VPPs cooperation in the power market. This structure carries out a day-ahead and intra-day generation planning by choosing the best Demand Response (DR) programs considering wind power and market prices as the uncertain parameters. A risk management study is likewise taken into account in the proposed stages for contingency conditions. So, some component changes, like, regular demand changes and single-line outage are prepared in the framework to authorize the suggested concept in the contingency situation. To determine the adequacy and productivity of the proposed strategy, the IEEE-RTS modified framework is examined to test the technique and to evaluate some reassuring perspectives too. By the proposed methodology, the delectability of DR projects is uncovered in industrial networks and the improvement level of load shedding and the lower cost will be achieved.

Smart branch and droop controller based power quality improvement in microgrids

Abstract: Abstract This paper presents two unique smart branch controller for compensating several power quality disturbances. The first proposed intelligent branch controller comprises a series transformer with its indirectly controlled impedance by secondary voltage injection. Further, the smart controller is made adaptive and flexible. It is installed at the point of common coupling (PCC), where PCC voltage & load current can be locally acquired without the presence of a communication channel, which then tracks its references as pure sinusoidal waveforms. Therefore without any filter requirement, harmonic elimination is done by the smart branch controller. The proposed smart controller can be applied in microgrids (MGs) for multi-objective optimization of power quality (PQ). For proper elimination of harmonics and to enhance the quality of power supply, the smart branch is optimized by a droop controller, which delivers power to a constant current source and eliminates harmonics by providing an appropriate quantity of harmonic voltage to the inverter voltage. The total harmonic distortion (THD) becomes 23.06% for the voltage and 6.24% for the current with droop controller, whereas, with an only smart branch into the power network, the THD becomes 26.47% for the voltage and 12.30% for the current. The simulation result concludes that the discussed optimized smart branch-based droop controller reduces drastically THD. Also, a separate study has been performed on the improvement of PQ by second proposed smart controller called as Photovoltaic Distribution Static Compensator (PV-DSTATCOM) grid-tied system using an adaptive reweighted zero attracting (RZA) control algorithm with perturbation and by applying maximum power point tracking technique (MPPT) for a three-phase system. The converter with PV array along with an active filter feature known as PV-DSTATCOM is required to convert the DC voltage into AC and for the improvement of the PQ by limiting harmonic distortions. It is concluded from the simulation results that the use of the RZA strategy presents an excellent steady state and transient response. The proposed PV grid-tied system is capable of working round the clock for both constant and variable irradiation and linear loads. The system is termed as smart as it can perform both modes automatically sensing the PV power and is capable of multi-directional power flow. The proposed method performs dual functions of improving PQ by working as DSTATCOM and also transfers power to the load and the grid obtained from PV array.

A simplified method for fault detection and identification of mismatch modules and strings in a grid-tied solar photovoltaic system

Abstract: The foremost problem facing by the photovoltaic (PV) system is to identify the faults and partial shade conditions. Further, the power loss can be avoided by knowing the number of faulty modules and strings. Hence, to attend these problems, a new method is proposed to differentiate the faults and partially shaded conditions along with the number of mismatch modules and strings for a dynamic change in irradiation. The proposed method has developed in two main steps based on a simple observation from the Current versus Voltage (I-V) characteristic curve of PV array at Line-Line (LL) fault. First, the type of fault is detected using defined variables, which are continuously updated from PV array voltage, current, and irradiation. Second, it gives the number of mismatch modules (or short-circuited bypass diodes) and mismatch strings (or open-circuited blocking diodes) by comparing with the theoretical predictions from the I-V characteristic curve of PV array. The proposed algorithm has been validated both on experimentation using small scale grid-connected PV array developed in the laboratory as well as MATLAB/Simulink simulations. Further, the comparative assessment with existing methods is presented with various performance indices to show the effectiveness of the proposed algorithm.

Development of thermal model for estimation of core temperature of batteries

Abstract: Core temperature (Tc) estimation plays an important in role in establishing an effective thermal management system of a battery. In the present work, Tc of a lead acid (Pb) battery was estimated using a Kalman filter, based on a thermal model of the battery using convection resistances and capacitances. The governing equations based on measured surface temperature (Ts) and ambient temperature (Tamb) were derived. Since Tc cannot be measured directly, estimation technique was used to predict the same using measured Ts and Tamb. Five test cases for which the profiles of Tc versus time were available were analyzed. It was found that the errors in the predictions varied from 0.25 °C to 3.5 °C., depending on the nature of Tc profiles, with minimum errors when Tc has slow variations with time.

A new method to generate daily load scenario of electric vehicle charging station considering time correlation

Abstract: Abstract Due to the influence of random factors such as travel behavior of car owners and traffic condition, the electric vehicle (EV) charging station load has strong randomness. Establishing an appropriate probability model to describe the stochastic of EV charging station load is of great significance to the safe operation analysis of distribution network. Therefore, this paper proposes the probability modeling and the scenario generation method for EV charging station load based on historical data. Firstly, the load of each period is regarded as a random variable, and the probability distribution model of each random variable is obtained by fitting historical data. Secondly, according to the analysis of load correlation, 96 periods of a day are divided into several sets of adjacent periods. Considering the correlation between different period loads in each set of adjacent periods, the Pair-copula method and the D-Vine structure is used to obtain the joint distribution model in each set of adjacent period loads is obtained. Thirdly, according to the joint distributionmodel, all sets of adjacent periods of a day and the corresponding load scenarios are obtained, and the daily load curve considering time correlation are generated. Finally, referring to the actual historical load curve data, the effectiveness of the proposed method in this paper is verified by comparing with the daily load curve, which is generated based on the independent distribution model of each period load without considering time correlation.

A novel approach of closeness centrality measure for voltage stability analysis in an electric power grid

Abstract: Abstract Modern power systems are increasingly becoming more complex and thus become vulnerable to voltage collapse due to constant increase in load demand and introduction of new operation enhancement technologies. In this study, an approach which is based on network structural properties of a power system is proposed for the identification of critical nodes that are liable to voltage instability. The proposed Network Structurally Based Closeness Centrality (NSBCC) is formulated based on the admittance matrix between the interconnection of load to load nodes in a power system. The vertex (node) that has the highest value of NSBCC is taken as the critical node of the system. To demonstrate the significance of the concept formulated, the comparative analysis of the proposed NSBCC with the conventional techniques such as Electrical Closeness Centrality (ECC), Closeness Voltage Centrality (CVC) and Modal Analysis is performed. The effectiveness of all the approaches presented is tested on both IEEE 30 bus and the Southern Indian 10-bus power systems. Results of simulation obtained show that the proposed NSBCC could serve as valuable tool for rapid real time voltage stability assessment in a power system.

Evaluating critical characteristics of vegetable oil as a biodegradable insulating oil for transformer

Abstract: Abstract In transformer, fuel based mineral oil is used as insulation and coolant over many years. The ecological issue related with the current liquid insulation system is the throwing away of used oil samples after drawn out service. The paper investigates the critical properties of biodegradable oil such as olive and palm oil according to international standards. After that, a small laboratory setup of 1 kVA transformer was designed for the load test with insulating fluids with olive oil and palm oil were tested. Likewise, an attempt has been made for the technical feasibility of mixing proportion was also investigated. Then, the experimental results were compared with mineral oil. Experimental analysis shows that vegetable oil’s electrical and fire resistance properties are better than the conventionally present used mineral oil. Yet, the viscosity of vegetable oil is much higher than mineral oil. Added to that, vegetable oils are exhibiting the higher amount of higher molecular fatty acids. From the load test, it is found that transformer with nature ester palm oil has a higher efficiency that of olive oil, but it is found lower efficiency than mineral oil.

Improved Insulation Durability to Improve Transformer Aging

Abstract: Abstract In transformers, in addition to the primary and secondary coils, there are several other important components and accessories in which the insulating material is one of the most critical components of a transformer. Sufficient insulation between different active parts are necessary for safe operation. Adequate insulation, it is not only necessary to insulate the coils from each other, or from the core and tank, but also guarantees the safety of the transformer against accidental surges, but with the growth in size and complexity of power stations, transformer is facing insulation problems. The evaluation of the transformer overload capacities certainly leads to complex variables that affect the operating life of the power and distribution transformer. In this study, the long-life calculation is performed on the basis of two experiments, which are related to the insulation degradation of the mineral oil and cellulose paper such as by adding different types of nano-particles to the mineral oil to enhance the strength of oil, and by changing the loads under different operating conditions to control the deteriorating rate of the insulation to prevent the life of the transformer. The insulation breakdown strength is improved from 37 kV to 71 kV by mixing the semiconductor nanoparticles such as gadolinium-doped ceria (GDC) and cerium dioxide (CeO2) with mineral oil. Moreover, for cellulose paper, thermal degradation rate is kept below its limit by reducing the temperature when controlling the load.

Daily peak-based short-term demand prediction using backpropagation combined to chi-squared distribution

Abstract: Abstract An efficient and economic scheduling of power plants relies on an accurate demand forecast especially for the short-term due to its tight relation to power markets and trading operations in interconnected power systems. A slight deviation of load prediction from real demand could engender the start-up of a conventional power station which could be either time-consuming or requiring expensive combustible, a deviation that could interfere as well with renewables intermittency and demand response strategies. Hence, load forecasting still a challenging subject because of the various transformations that the energy sector undergoes and that directly impact the demand profile shape. Therefore, conceiving dynamic load demand forecast approaches will permit utilities save money in different vertical structures and regulation schemes. In this paper, we propose a novel approach for short-term demand prediction valid for normal and special days to address the impact of climate changes along with events occurrence on forecast accuracy. This approach is based on the prediction of hourly loads, established on the daily peak load prediction using backpropagation combined to chi-squared method for weighting historical data to enhance the training process. Obtained results from extensive testing on the Moroccan’s power system confirm the strength of the developed approach, that improved the forecast accuracy by a range of 1.1–4% compared to the existing methods.

Electric Vehicle Traffic Pattern Analysis and Prediction in Aggregation Regions/Parking Lot Zones to Support V2G Operation in Smart Grid: A Cyber-Physical System Entity

Abstract: Abstract In this paper mathematical model for traffic pattern analysis, prediction and resource utilization of Electric Vehicles (EV) in aggregator regions/parking lot zones is proposed. The proposed and presented mathematical model for EV traffic pattern/resource utilization in smart city can be used to estimate the amount of power/voltage available/required by EVs in different aggregator regions. Development of multiagent communication (MAC) based framework for aggregator to EV communication is discussed. V2G aggregation in distribution network forms a Physical part and utility side with sensing/communication forms a Cyber part which combinedly constitutes a Cyber-Physical system. Simulations were carried out on IEEE 33/69 bus test systems using MATLAB and MOBILE C was used for MAC. The results obtained were promising in terms of improved voltage profile and reduced power losses.

Influence of Series Compensation Degrees on Secondary Arc Current Characteristics under the Different Series Compensation Mode

Abstract: Abstract The high compensation degree series compensation has a broad development prospects in long distance and large-capacity UHV transmission lines. But it is generating secondary arc current contains low frequency components with high amplitude when the single-phase grounding fault occurs in the series compensated transmission line, which is not conducive to rapid arc extinguishing. To solve this problem, this paper based on the mechanism of generating secondary arc by series compensation transmission lines, and using ATP – EMTP electromagnetic transient program to establish the simulation model of UHV series compensation device. And the suppression effects of small resistance short connection fault series compensation and linkage bypass series compensation measures on secondary arc current and recovery voltage under different series compensation layout mode are studied respectively. The results show that the attenuation speed of the secondary arc current is related to the series compensation arrangement modes and the time when the series compensation device is short connected or bypassed. Series compensation device short connected or bypassed before circuit breaker tripping which can accelerate the arc extinction speed, and the suppression effect is better when the series compensated double platform segmentation layout is distributed on both sides of the line. The results can be used as a reference for the engineering design of UHV with large capacity and long distance and high compensation series compensation transmission lines.

Protection Coordination of Radial Distribution Networks Connected with Distributed Generation Considering Auto-reclosing Schemes by Resistive Superconducting Fault Current Limiters

Abstract: Abstract Radial distribution networks are normally protected against fault currents by fuses and reclosers. This protection is coordinated in a way that reclosers clear temporary faults before the melting of fuses and fuses melt to clear permanent faults. Distribution networks, which are recently connected with distributed generations (DGs), incur a variety of issues that are certainly worthy of closer considerations. One of these issues is the operation of protection devices. Recloser-fuse coordination may be lost when DGs are integrated with distribution networks due to the effect of current flowing from DGs during fault period and the breaking of the radiality nature of these networks. The impact of DGs on recloser-fuse coordination depends on penetration level, location, and type of DG. Recloser-fuse coordination of radial distribution networks connected with DGs can be kept by connecting resistive superconducting fault current limiter (R-SFCL) in series with the DG to limit the fault current contribution of DG during the fault period. However, when considering the auto-reclosing scheme of the recloser, recloser-fuse coordination may be lost even if R-SFCL is connected. This paper shows the effectiveness of R-SFCL to restore recloser-fuse coordination without considering auto-reclosing scheme. It also proposes solution methods based on three different configurations of R-SFCL to maintain recloser-fuse coordination when auto-reclosing scheme is considered. Simulation results illustrate the effectiveness of the proposed configurations of R-SFCL to keep recloser-fuse coordination. All simulations are performed using MATLAB/Simulink package.

Machine learning roles in advancing the power network stability due to deployments of renewable energies and electric vehicles

Abstract: Abstract Renewable energy sources are widely installed across countries. In recent years, the capacity of the installed renewable network supports large percentage of the required electrical loads. The relying on renewable energy sources to support the required electrical loads could have a catastrophic impact on the network stability under sudden change in weather conditions. Also, the recent deployment of fast charging stations for electric vehicles adds additional load burden on the electrical work. The fast charging stations require large amount of power for short period. This major increase in power load with the presence of renewable energy generation, increases the risk of power failure/outage due to overload scenarios. To mitigate the issue, the paper introduces the machine learning roles to ensure network stability and reliability always maintained. The paper contains valuable information on the data collection devises within the power network, how these data can be used to ensure system stability. The paper introduces the architect for the machine learning algorithm to monitor and manage the installed renewable energy sources and fast charging stations for optimum power grid network stability. Case study is included.

Research on Power Generation Control of Asynchronous Machine as Main Generator

Abstract: Abstract High-power asynchronous machine can be used as the main generator of diesel locomotive and marine power system. The standalone power system of asynchronous generator based on four-quadrant converter is proposed. The magnetic field energy required by the machine must meet the minimum requirements for power generation, and the balance between power generation and load power must be ensured. Therefore, the initial voltage and capacitance of the DC-link capacitor are first analyzed and calculated. After that, the simple and easy slip prediction control is designed, that is, the given electric frequency takes into account the influence of the slip ratio. A power generation system is designed with an asynchronous machine as the main generator to achieve a DC voltage of 750 V, with an output power of up to 520 kW. Simulate the system for different operating conditions. The stable DC voltage is maintained under full load at different speeds. When suddenly unloading or loading 50 %, it can restore stable DC voltage in 10 ms time. In the case of stepless speed regulation and stepped speed regulation of diesel engine, the generator can still generate a stable DC voltage with loads of different power levels. The simulation results show that the power generation system has good load capacity and good dynamic performance.

Study on the insulation characteristics of environmentally friendly CF3I/N2/CO2 mixed gas

Abstract: Abstract SF6 gas is a kind of gas medium widely used in the insulation of power equipment. However, due to the greenhouse effect of SF6, new environmentally friendly gas that can instead of SF6 has been the goal for researchers. CF3I gas is one of the most promising alternative gases for SF6. In this paper, two-term Boltzmann equations of CF3I/N2/CO2 ternary gas mixture at 0.1 MPa and 300 K are calculated to obtain an electron energy distribution function (EEDF), an electron drift velocity Ve, a critical fold breakdown field strength (E/N)cr of the ternary mixed gas, and the synergy effect coefficient is used to analyze the synergy effect between the mixed gases. The calculation results show that the CF3I/N2/CO2 ternary mixture has a synergistic effect, and the 50% CF3I/40% N2/10% CO2 ratio scheme makes the mixed gas most likely to replace SF6 from the physicochemical properties. Comparing the calculated data of this paper with the data of other works of literature, the validity of the calculation method and calculation data in this paper is verified, which provides theoretical support for the research of SF6 alternative gas.

Assessment method of comprehensive energy saving potential of distribution network considering source-load power uncertainty

Abstract: Abstract The comprehensive energy-saving potential evaluation method of the energy-saving schemes of a distribution network considering the power uncertainty of source and load is studied in this paper. The K-means clustering method is firstly employed to extract typical scenarios of distribution network, and the forward-push back method is used to calculate the power flow in typical scenarios, then energy-saving reconstruction schemes are formulated according to the power flow calculation results. A comprehensive energy saving potential evaluation index system that consists the improvement rate of network loss, line loss rate, transformer loss rate, annual electricity saving cost, annual equipment investment cost, annual maintenance cost and voltage quality improvement rate is built, and the comprehensive evaluation method based on DEMATEL-ANP-TOPSIS mixed decision model is used to evaluate the comprehensive energy-saving potential of the energy-saving reconstruction schemes regarding the index system. Finally, the optimal reconstruction scheme is selected based on the evaluation results of energy saving potential in multiple scenarios. The effectiveness of the proposed method is verified by an example in IEEE-33 node distribution network.

Mitigation of power quality issues using UPQC

Abstract: Abstract Power quality has become major concern these days due to application of power electronic devices. Conventional equipment like passive filter, segregate series and shunt filters and synchronous condenser etc. have become inadequate to mitigate different power quality problems. Since, power quality mainly concerned with voltage quality and the current quality in the system. For voltage quality, series compensator is used and for current quality, shunt compensator is used. Further, when these two power quality problems are mitigated simultaneously, the device, which is used, called unified power quality conditioner (UPQC), in power distribution system. In this paper voltage related power quality problems such as (voltage sag, voltage swell, voltage and current distortion) are discussed and UPQC controller is simulated to mitigate these problems. There are different control techniques available for UPQC. Here one of them i.e., unit vector template generation (UVTG) is used to simulate UPQC controller. The considered system efficiently regulated the DC link voltage using properly tuned PI parameters. The proposed work is also validated using experimental results.

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

Abstract: Abstract The optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

Ultra mega power plant disturbance related oscillation detection in Indian grid using PMU data

Abstract: Abstract The power system oscillations in the grid are an issue of concern to the system operator. They may transform a stable system into an unstable system when the system is operating on the edge and contingency occurs. The oscillations developed in the system may grow and spread across the power grid if no timely, corrective action is taken to mitigate them. The paper presents the ultra-mega power plant generation complex related blackout analysis. The case study presented in this paper demonstrates the utilization of synchrophasor data to have a better realization about the grid disturbance. It covers some of the important dynamic simulation studies considered representative of various scenarios during this. The paper illustrates utilization of Prony analysis using multiple signals and Fast Fourier Transform methods in conjunction with frequency data obtained in real-time from PMUs installed in the western regional grid of India to determine the frequency of oscillations, its magnitude, and related damping during this disturbance. The focus of this study involves the application of these techniques to gain insight into the oscillatory behavior of the system during this disturbance associated with ultra-mega power plant having generation capacity greater than or equal to 4000 MW from the western part of Indian grid. Based on this, distinct categorization of oscillations into “local mode” and “inter-area mode” of oscillations was done for enhanced understanding about the type of oscillations getting excited during this disturbance.

A model for calculating losses in transformer related to orders and harmonic amplitude under analysis of joule effect, eddy current and hysteresis

Abstract: Abstract The electrical transformer is one of the most used equipment in electrical power systems. The non-linear electrical loads are increasing, mainly in the electrical distribution system, and the electrical power transformer is inserted in this scenario, supplying these loads. Consequently, the increasing non-linear loads affect the electrical transformers and their factors directly, like in the dependency between temperature and harmonic increase. Therefore, to study the influence of harmonics in the transformer’s temperature, one should understand how it will behave with these changes in the electrical power system. For this reason, in this article, numeric simulations and tests were performed to predict the transformer temperature behavior. The proposal is a numeric technique for coupling two equations, thermal and electromagnetic, of an electrical transformer, considering heat sources regarding joule, eddy current, and hysteresis effect. To evaluate the numeric simulation and understanding the electrical transformer behavior in real-life, tests with specific harmonic orders (3rd, 5th, and 7th) and their combinations and a test with less than 10% total harmonic distortion, according to IEEE 519 standard were performed. It is verified that the electrical transformer temperature rises with the increase in harmonic amplitude and its orders. Results show that the industry must be aware of the effects of the increasing non-linear loads when designing the next generation of transformers concerning their durability and lifetime.

Assessment of the potential of multifarious demand response programs in reducing transformer loss of life

Abstract: Abstract Transformer may enter the ageing cycle sooner if it is loaded more than the rated value for longer periods of time in its life cycle. This paper exploits demand response as a way to improve transformer life by reducing the hottest spot temperature (HST) which is caused due to better load profile. The aim of the paper is to investigate the impact of various types of price-based and incentive-based demand response programs (DRPs) on the transformer life and other attributes like energy consumption, peak to average ratio, etc. Entropy method is used to determine the weights of multi-attributes in a multi-attribute decision-making (MADM) model formed by the various attributes and the multifarious demand response programs. Using these weights, the various DRPs are ranked using Program Ranking Index to assist the utility in deciding which DRP is to be employed. IEEE transformer model is used to calculate the transformer ageing for two cases with and without demand response programs. The simulation results validate the effectiveness of demand response in mitigating transformer loss of life. Furthermore, the economic and technical benefits of employing demand response are quantified.

Detection of coherent groups using measured signals, in an inter-area mode, for creating controlled islands to protect the power system from blackout

Abstract: Abstract Controlled islanding is an effective way of preventing the system from catastrophic blackouts. This is generally solved either as a constrained combinatorial optimization problem or a slow coherency based linearized approach. The combinatorial explosion of the solution space of an extensive power network increases the complexity of solving, while the linearized slow coherency approach cannot track the varying coherent generator groups with a change in system operating conditions. Offline coherent studies are utilized in wide area measurement system (WAMS) data-based approaches to determine islanding boundaries. So, the present study proposes a novel coherency based controlled islanding technique that clusters generators and load buses simultaneously from the measured signals, ensuring generator coherency. Therefore, identification of inter-area modes from bus voltage angle signals is necessary to determine coherent bus groups. So, Zolotarev polynomial based filter bank (ZPBFB) is adopted in the present work to determine inter-area modes. The dimensional reduction techniques are used to cluster the coherent buses. The bus clusters thus obtained with the proposed method are compared with bus clusters determined from small signal stability analysis. The proposed method is demonstrated on IEEE 39-bus, 68-bus and 118-bus test systems and compared with graph spectra based controlled islanding.

Power quality (PQ) analysis in a power feeder that supply different social class consumers

Abstract: Abstract The aim of the present work is to evaluate the power quality (PQ) required in individual customers in low voltage (LV), along an electrical circuit of 13.8 kV, in a distribution network standardized in urban area and with diversity of energy consumption profiles. Energy, including comprehended parts of the region with downside against financial rates. The data is useful in this sales environment of a Brazilian distribution company. These data were developed by the data mediation systems for a communication interface that enable to identify and evaluate PQ disturbance. The results of the surveys is compared with limits reported in Module 8 of the National Electric Energy Distribution Procedures (PRODIST), according to Brazilian Regulation Agency (ANEEL), that is, the pre-definition of rules, standards, parameters, and procedures about the quality of electric power supplied and the quality of the service provided. The PRODIST Procedure has a major analysis focused in the voltage supplied. The data sensors are based on studies of Duration Relative of Predary Stress (DRP) and Duration Relative of Transgression for Critical Stress (DRC). In this paper the results are presented and the challenged to supply this area with diversity of consumer profiles is commented.

Analysis and detection of electric field distribution characteristics of degraded insulators

Abstract: Abstract After long-term operation, the electrical performance of UHV transmission line insulator string decreases and zero-value insulators are prone to occur. The existence of zero-value insulators leads to the flashover of insulator strings, which causes large-scale power outages in serious cases. In order to improve the power quality and detect the zero-value insulators of transmission lines more timely and efficiently, the influence of zero-value insulators on the electric field distribution of insulator strings is simulated and calculated by finite element method. At the same time, taking the grounding current of insulator string as the cut-in point, the principal component analysis method is used to screen the effective characteristic quantities, and then as the input of artificial neural network, and the fault area of insulator string is determined by the neural network. The simulation results show that the recognition accuracy of artificial neural network based on insulator string grounding current is high, and it has certain engineering application value.