Existing Power System Network Research Articles

FRT capability improvement of a wind power system using support vector regression and deep neural network models

ABSTRACT The increasing energy demand and environmental conditions have led many countries to favor renewable energy,such as wind and solar,over conventional power plants. As per the Central Electricity Authority (CEA), India’s wind power capacity has grown substantially, reaching 45,154 MW in 2023, from 22,465 MW in 2013. However, integrating wind generators to an existing power system network can reduce transient stability during faults. To prevent wind turbine disconnection during faults, Indian grid code authorities mandate Fault Ride Through (FRT) or Low Voltage Ride Through (LVRT) capability for wind turbines. This paper proposes Dynamic Voltage Restorer (DVR) for enhancing the FRT capability of a constant speed wind turbine. Analysis and simulation are done on a fixed speed wind turbine employing Squirrel Cage Induction Generator (SCIG) under balanced and unbalanced voltage sags. Performance of DVR with two Artificial Intelligence-based controllers, Support Vector Machines(SVM) Regression Model Based Supervised Machine Learning algorithm, and Deep Neural Network (DNN) controller, is analysed and compared. The SVM Regression algorithm, achieves 100% voltage sag compensation under unbalanced voltage sags, reduces torque pulsations to 25% and maintains rotor speed at rated values, enabling the turbine to remain connected to the grid. Additionally it reduces Total Harmonic Distortion to 2%.

Fault Analysis of Microgrid With Grid-Connected and Islanded mode Using IoT-Wavelet Approach

Now a days microgrid is one of the most widely used method in power network to reduce system losses as well as improve the reliability in the field of electrical systems. Integration of power projects typically involves adding new distributed energy sources with and without compensating devices to an existing power system network. It is essential to design new protection scheme due to changes in the topology and dynamic behavior of the system. Now fast fault detection algorithmic approaches are necessary to integrate different types of generating sources and loads under smart environment. The protection scheme must provide physical monitoring as well as parametrical with the help of new technologies. Internet-of-things(IoT) is one of the source to monitor electrical systems under various environmental conditions of the system. Wavelet (WT) basically investigates the fault transient signals of different frequency and divides the waveform into different approximate and detailed coefficient values, which provides the important knowledge about the classification and location of fault. The detection of faulty-line and the location of fault by implementation wavelet detailed coefficients of Bior1.5 mother wavelet. This proposed method provides fault analysis of IoT based protection of microgrid with Grid-connected and Islanded Mode Using Wavelet Approach under various types of faults.

An auto-tuned droop coefficient-based controller for microgrid system to enhance grid resilience during blackouts

This paper presents a reliable auto-tuned droop coefficient-based controller (ATDC) for a microgrid (MG) system for enhancing grid resilience during blackouts. Existing power system networks experience blackouts due to inevitable failures such as overloading on lines, failure of a protection system, and imbalance in the power lines. The consequences of blackouts can be resolved by adapting to the concept of resilient MGs with high dynamic stability for power restoration. However, impedance parameters of power lines will change during blackouts, this eventually affects system's performance. Therefore, synchronization of MG sources to the utility grid and providing power supply to the critical loads during power system blackouts are the key factors to be resolved by maintaining system within permissible limits. The proposed ATDC-based controller adapts to changes in system parameters and auto-tunes the droop coefficients to provide proper control coordination between the each of distributed generator (DG) in MG. The proposed ATDC-based controller is designed in silico, and its effectiveness is tested under various conditions of MG operations. Results are compared with conventional and improved droop controller strategies. The test results demonstrate that the proposed controller maintains grid supply frequency within IEEE-1547 standards while ensuring appropriate power-sharing between load and MG sources.

Optimum generation scheduling incorporating wind energy using HHO–IGWO algorithm

Recently, renewable energy participation is gaining importance in the existing power system. However, the large penetration of these renewable energy sources into the existing power system network may cause an imbalance in supply and demand response. Unit commitment is the decision-making process in which generating units are turned ON and OFF at the hourly interval as per the load demand under certain constraints to provide economic scheduling. Thus, an advanced intelligent approach is needed to cope with this combined unit commitment problem with a large penetration of intermittent sources. This paper offers the solution to optimal scheduling by implementing the hybrid Harris Hawks optimizer algorithm (HHO–IGWO). Standard IEEE systems with 10-, 19-, 20-, and 40 units are simulated. Further, to test the feasibility and effectiveness of the proposed method, a comparative analysis for a 10-, 20-, and 40-unit system has also been performed with penetration. The comparative analysis reveals that proposed is more efficient in tackling unit commitment problem in the presence of wind as renewable energy source.

Optimal Location and Sizing of Conglomerate DG- FACTS using an Artificial Neural Network and Heuristic Probability Distribution Methodology for Modern Power System Operations

In existing power system networks, the positioning and sizing of multi-DG is critical at the optimum locations for effective energy management. Initially optimal power flow is assessed using the NR method (without DG) in which performance parameters such as real power loss, accuracy, selectivity and MSE are obtained, but in an undesirable manner. To meet load demand; multi-DGs are placed and their optimal locations are assessed by the proposed heuristic probability distribution methodology and an ANN because existing techniques provides poor performance parameters for selecting the location and sizing of DGs. The optimal positions of multi-DGs are estimated in terms of performance parameters including real power loss of transmission network, accuracy, selectivity and MSE, while the performance parameters obtained with the ANN are better than the heuristic pdf. Then, the sizing of multi-DGs is evaluated in relation to active and reactive power. It is found that that sizes of multi-DGs are smaller with ANN than with heuristic pdf. It is preferable to connect the buses having lowest real power losses with the smallest multi-DGs. The performance analysis is tested in the standard IEEE 9- bus and IEEE 57- bus systems on Simulink. To improve the distortion level in real and reactive power, multi-FACTS namely TCSC, TSC and STATCOM are used. The switching of TCSC and TSC is done by SPWM while STATCOM switching is controlled with ANFIS. The locations of multi-FACTS devices are chosen for buses having larger distortion and the sizing of multi-FACTS devices is also optimally decided. The application of multi-FACTS devices helps to improve power quality and fulfill load demand with minimal size in order to make the system economical.

Assessment and Integration of Renewable Energy Resources Installations with Reactive Power Compensator in Indian Utility Power System Network

Renewable energy (RE) resource assessment is essential for planners and investors to increase its penetration capacity, and improve social and economic security. Integration of renewable power generations (RPGs) and reactive power compensators (RPCs) offer potential benefits to the existing power system network by providing a prospect for voltage control, reduction in power losses, sustainability, and reliability improvement. There are proven outcomes with these RPGs and RPCs placement in distribution systems. This work proposes a candidature location and sizing of RPGs and RPCs optimally in the Indian utility transmission power system network. The foremost purpose of this integrated operation at multiple nodes is to increase the performance of the power system concerning power loss and voltage deviation reductions, and voltage stability improvement. The loss sensitivity factor (LSF) based particle swarm optimization (PSO) technique is adapted for finding the candidature locations and sizing the RPGs and RPCs under five different configurations. Simulation outcomes display the proposed methodology can lead to extensive performance enhancement in the power system towards the sustainable development of electric energy transactions. Further, renewable resource assessment is carried out to find the viability of the candidature locations. The potential of wind and solar energy resources is assessed widely and suitable tools are used to evaluate the power extraction through RE at these selected locations. The results show that the candidature locations have great potential to evacuate the energy, which can effectively improve the existing power system technically and economically. Additionally, it is attested that the RPGs can also be utilized for power system enhancement.

Energy storage optimization for global adjustment charge reduction in Ontario

Abstract Incorporation of energy storage (ES) with existing power system networks for economic and technical purposes, is on the rise. ES systems are employed for enhancing the operation of power systems through offering several ancillary services; such as frequency and voltage regulation, and operation reserve. Further, ES are used for money-making intent such as energy arbitrage (EA) and lessening utility energy charges such as demand charges. In this paper, a novel algorithm is proposed to reduce the utility charges of global adjustment (GA) for a large customer in the Canadian province, Ontario. The proposed algorithm optimizes the size of the battery storage system (BSS) and its schedules. In the developed algorithm, BSS is optimally deployed to minimize the charges associated with GA and demand charges (DC) for class-A customers in Ontario jurisdiction. Furthermore, BSS is employed for secondary profit-gaining missions such as behind-meter energy arbitrage (EA), demand response (DR). The developed algorithm is tested using real data of a class-A customers in Ontario. Obtained results show the economic feasibility employing BSS for bill reduction using the proposed method. Further, detailed sensitivity studies on several parameters of the developed method are presented showing the performance and potential of the algorithm for making profits.

Integrated Power Flow Analysis with Large-scale Solar Photovoltaic Power Systems Employing N-R Method

Abstract A method is proposed to modify the conventional load flow programme to accommodate large-scale Solar PhotoVoltaics (SPV) power plant with series power specifications. The programme facilitates easy handling of any number of SPV systems with standard control strategies such as pf-control and voltage-control, considering solar inverter’s power constraints. In this method, the non-linear equations related to SPV systems, located at multiple locations, are solved with the main load flow equations in an integrated fashion, considerably reducing the implementation task. This task is achieved by augmenting the inverter buses to the existing power system network in such a way that the changes required in the conventional programme are minimal. To show the effectiveness of the proposed method, it is compared with the alternate-iteration method popularly followed in the literature. The workability of the proposed method has been demonstrated by using a Single Machine Infinite Bus (SMIB) system and the IEEE14-bus power system with SPV systems. Various test cases pertaining to meteorological variables and control strategies are also presented.

Impact of PV Distributed Generation on Loop Distribution Network

The rapid spreading of the Photovoltaic (PV) Systems as Distributed Generation (DG) in medium and low voltage networks created many effects and changes on the existing power system networks. In this work, two methods have been used and applied to determine the optimal allocation and sizing of the PV to be installed as DGs (ranging from 250 kW up to 3 MW). The first one is to determine the location according to the maximal power losses reduction over the feeder. The second one is by using the Harmony Search Algorithm which is claimed to be a powerful technique for optimal allocation of PV systems. The results of the two techniques were compared and found to be nearly closed. Furthermore, investigation on the effects on the feeder in terms of voltage levels, power factor readings, and short circuit current levels has been done. All calculations and simulations are conducted by using the MATLAB Simulation Program. Some field calculations and observations have been expended in order to substantiate the research findings and validation.

Impact of TCPS, SMES and DFIG on Load Frequency Control of Nonlinear Power System Using Differential Evolution Algorithm

In recent times, wind power is increasingly being integrated in the existing power system network for well-known reasons, but due to unpredictable variations in wind speed, the load frequency control (LFC) of such power systems becomes a difficult task. This paper addresses the problem of LFC of a multi-source hydrothermal nonlinear power system having wind power penetration. Differential evolution (DE) algorithm has been used to optimally tune the proportional, integral and derivative controller used for LFC in the power system subjected to fluctuations of wind power and load. The reheat and generation rate constraints nonlinearities have been considered appropriately for both areas. Besides, the impact of thyristor-controlled phase shifter (TCPS) and superconducting magnetic energy storage (SMES) on the LFC performance has been analyzed with the parameters of TCPS and SMES being tuned using DE algorithm. The system has been investigated for various operating conditions including the weak grid condition to establish the effectiveness of the proposed approach for wide variations in system conditions. The performance is analyzed and discussed in respect of frequency and tie-line power deviations, peak overshoot, settling time, and value of performance index. Further, robustness of the system is investigated by varying the system parameters from − 50 to + 50% in steps of 25% and step load disturbance from 1 to 20% in steps of 5%. Modeling and simulations are carried out using MATLAB/Simulink® to demonstrate the effectiveness of the DE algorithm.

Quasi‐oppositional harmony search algorithm based optimal dynamic load frequency control of a hybrid tidal–diesel power generation system

In recent years, high penetration of distributed generations based on wind energy, solar energy and so on in the existing power system network has been noticed. However, due to their stochastic behaviour, operations under autonomous mode as well as in grid-connected mode are not an easy task. This has forced the power utilities to re-define frequency regulation criteria to enhance the overall system stability and reliability. In line with the same, dynamic performance analysis of load frequency control (LFC) of an autonomous hybrid power system model (HPSM) consisting of tidal power plant (TPP) and diesel power plant is explored in this study. A concept of deloaded TPP is adopted in the studied HPSM to utilise the available reserve power for the frequency support. Apart from this, the studied model also incorporates frequency regulation through inertia and damping control and supplementary control strategies. These control strategies are realised through conventional controllers whose gain values are optimised using quasi-oppositional harmony search algorithm (QOHSA) for the optimal dynamic performance of LFC. The efficacy of the proposed QOHSA is corroborated by comparing the results with those yielded by few other existing state-of-the-art algorithms.

LUT Assisted Adaptive Overcurrent Protection of Reconfigurable Microgrids

Microgrids are the key solution to handle the growing technical, environmental and economical concerns of existing power system networks. The purpose of this paper is to develop an intelligent and adaptive overcurrent protection system for a microgrid. This system is capable of monitoring, protecting and controlling the microgrid. A look up table is created and maintained at the central protection system of the microgrid, which has details of normal and faulted current in all feeders for various topologies of the microgrid system. It has the optimized values for time dial setting and operating time of relays for faults at a specific location in the reconfigured system, which is generated using Dual Simplex algorithm. Hence the Central Protection System aids in providing suitable overcurrent relay coordination to the microgrid, which may incur reduced network disconnection. The hardware prototype of the Central Protection System is realized, tested and validated on a balanced 21-bus microgrid system.

Lyapunov Exponent-Based Online Voltage Stability Assessment Using PMU Data

In nowadays profit-making-power market, especially with deregulation, the existing power system network is operating at its maximum permissible limits. In such stressful conditions, even a small disturbance may lead to system collapse because of voltage or frequency stability issues. In addition, with the increase in nonlinear loads and reactive power demand, voltage stability (VS) has recently gained more attention. However, the traditional stability assessment tools may not be capable to forecast VS problems sufficiently in advance. In view of this, the present paper addresses a novel methodology based on Lyapunov Exponent (LE) to forecast the VS of the system using the time stamped series voltage data received from the Phasor Measurement Unit (PMU). Because of the geographical wide spread nature of network and the unpredictable disturbances at any location, the stability assessment in post-disturbed condition is computationally challenging, especially in case of online control. In contrast with the traditional VS methods, the proposed method tracks only the LE to predict voltage stability and hence finds efficient alternatives to the online surveillance of the voltage stability of wide area network (WAN) having PMU data. This paper develops the LE theory for calculating the Voltage Stability Index (VSI) and its effectiveness is verified by applying it to New England 39 Bus system.

Grid connection to CPP in a deregulated electricity market: A case study related to fault current levels

Cost of power is one of the major driving factors for profit margins in any industry. Deregulation of electricity market enhances this opportunity for industry consumers to settle for minimum prices for the same usage of electricity. This leads to restructuring of existing power system networks. Addition of infinite power sources such as grid, demands for a thorough check of design limits of the available switchgear. Thus, short circuit current levels become a deciding factor in importing additional power with existing switchgear. In a Captive Power Plant (CPP), the maximum fault current levels are studied with respect to single phase to ground fault (Line to ground – LG) and three phase short circuit fault. Methods of grounding determine whether LG fault current can exceed the three phase fault current. This becomes necessary as the estimated maximum current is used for deciding the rated short circuit breaking capacity of switchgear. LG fault currents are computed and compared with three phase fault currents at different system voltage levels for a particular CPP where power import from grid is considered. An attempt is made to study the variation of Coefficient of grounding with system grounding resistance for a particular voltage level which is resistively grounded.

An innovative finite state automata based approach for fault direction estimation in transmission lines

Abstract In this work finite state automata or finite state machine based directional protection scheme is proposed for transmission lines. Phase angle of positive sequence current is used as input to finite state automata based fault direction estimation module. Finite state automata is used as fault pattern recognizer which estimates the direction of fault. The output of the proposed FSM based scheme will be ‘−1’ for reverse section faults and ‘1’ for fault in primary section faults. The performance of the proposed technique is evaluated using data simulated for variation of fault type, fault inception angle, fault location, power flow angle, reverse power flow and fault resistance. Accuracy of the method is found to be 100% from all 11,500 fault cases. Proposed technique does not use voltage unlike conventional directional relaying schemes due to which there is no issue regarding close-in fault detection. The reach setting of the proposed method is up to 99.9% of line length which has advantage over conventional relaying schemes which have reach up to 80–85% of line. Although proposed method is a pattern recognition based technique, it does require an extra training module unlike artificial neural network to estimate the direction correctly. The proposed technique is effective because it do not require any training and the computation complexity is very less as compared to training based algorithms. Proposed method is also tested in an existing power system network of India, which shows accurate result in estimating fault direction.

Analyzing the Impacts of Wind Generation on Distribution System Performance

Increasing wind power generation affects performance of existing power system in terms of power losses, voltage regulation and short circuit levels. Jhimpir wind generation having 49.5 MW capacity is connected to 132kV network of Hyderabd Electric Supply Company (HESCO) to meet its energy demand. Distribution network of HESCO is modelled and simulated using Power system Simulator – Siemens Network Calculator (PSS SINCAL) as simulation platform. Simulation results are compared to observe impacts of wind integration to existing power system network. Simulation results indicate reduction of power losses from 15.26 to 14.79MW as a result of wind integration to existing HESCO network. Reduction in power losses is mainly caused by changed current flows in lines. Reduction in current also reduce line drops resulting in improved bus voltages. Short circuit level is slightly increased for all buses due to network modification. Increase in short circuit level is highest near the wind generation as Zorlu grid shows 13.02% increase. 66kV network shows small increase in short circuit level due to its long distance from wind generation facility. Use of real network data for this research work identifies possible protection issues alongwith the reduction in power losses and voltage drop. Each system network has separate network parameters and will have different response to any network change. Hence a simulation analysis is important to ensure maximum benefits from renewable energy sources and their integration with existing power system network

Flower Pollination Algorithm Based Optimal Placement of Solar DGs in Distribution System

Rapid exhaustion of fossil fuels, concern about environmental issues, enforces renewable distributed generations (RDGs) in the existing power system network. Appropriate allocation of these sources in the distribution network needs proper planning. In this paper an efficacious method for optimal placement of solar DGs is presented. Proper probabilistic models are used for modelling the solar irradiance, and determine the exact output power from the photo voltaic (PV) array. Different seasons are considered for the analysis. The main objectives are power loss reduction, voltage profile enhancement. First the best locations for placement of PV arrays are identified using voltage stability factor (VSF) method. Flower pollination algorithm, a new meta heuristic technique is used for determining the optimal number of PV arrays placed at these identified locations. The proposed methodology is tested on IEEE 33 and 69 bus systems and compared with other methods for validation.

Optimal Power Flow considering intermittent Wind Power using Particle Swarm optimization

Inclusion of renewable generation in the existing network is necessary due to the increase in raw material cost for generating electricity and growing demand. Optimal power flow incorporating wind generation is solved using Particle swarm optimization (PSO) in this paper. Weibull distribution function is used for modelling the intermittent nature of wind farm and then it is incorporated in the existing power system network. A direct cost function of the wind power purchased is presented in the paper. Cases without and with wind power are solved using PSO due to its ability in solving the non linear problems. The analysis is carried out on IEEE 30 bus test system and the obtained results are compared with the few existing methods. From the results it can be inferred that this method provides enhanced results.

Transient stability enhancement of a grid‐connected wind farm using an adaptive neuro‐fuzzy controlled‐flywheel energy storage system

With the rapid growth of the wind energy systems in the past years and their interconnection with the existing power system networks, it has become very significant to analyse and enhance the transient stability of the wind energy conversion systems connected to the grid. This study investigates the transient stability enhancement of a grid-connected wind farm using doubly-fed induction machine-based flywheel energy storage system. A cascaded adaptive neuro-fuzzy controller (ANFC) is introduced to control the insulated gate bipolar transistor switches-based frequency converter to enhance the transient stability of the grid-connected wind farm. The performance of the proposed control strategy is analysed under a severe symmetrical fault condition on both a single-machine infinite bus model and the IEEE-39 bus New England test system. The transient performance of the system is investigated by comparing the results of the system using the proposed ANFCs with that of the black-box optimisation technique-based proportional–integral controllers. The validity of the system is verified by the simulation results which are carried out using PSCAD/EMTDC environment.

Suppression of Fault Currents on DG Using Various Fault Current Limiters in Distribution Network

Protection of Distributed Generation (DG) is a challenging task in entire electrical family. DG plays a vital role in advanced power systems engineering. The connection of DG to the distribution network has numerous advantages. Even though it has a advantages, while connecting the DG with existing power system network, the fault current level in many places have often exceeded which causes the abnormal conditions in the entire power system network. In order to reduce the fault current level, various Fault Current Limiters (FCL) are proposed. In this paper hybrid Fault Current Limiter (HFCL) and its applications are proposed to minimize the effect of the DG on the distribution protection system in a radial system during a fault. The simulated results are analysed and compared with a Solid State Fault Current Limiter (SSFCL) and Superconducting Fault Current Limiter (SFCL) using MATLAB simulation. The effectiveness of proposed fault current limiters are determined and examined in the test system.