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This paper presents a multistrategy fusion particle swarm optimization model for dynamic economic dispatching of renewable energy in distribution networks. The objective is to minimize active network losses and system voltage deviation while considering the integration of distributed energy sources and static reactive power compensators. The algorithm incorporates specific strategies, including a particle position change strategy based on the midpipeline convergence approach, a strategy for generating exploding particles near the optimal particles, and a particle velocity update strategy relying on the global optimal particle position. The inertia weights and particle position update methods of the simplified particle swarm optimization algorithm are also utilized. Simulation experiments are conducted on an IEEE 33 bus radial distribution system, demonstrating the effective optimization of system losses while ensuring system voltage stability. This research contributes to the scientific understanding of renewable energy integration in distribution networks and its economic dispatching. [ABSTRACT FROM AUTHOR]

The increased integration of renewable energies (REs) raised the uncertainties of power systems and has changed the approach to dealing with power system challenges. Hence, the uncertain nature of all the power system variables needs to be considered while dealing with the optimal planning and operation of modern power systems. This paper presents a probabilistic optimal active and reactive power dispatch (POARPD) based on the point estimate method (PEM), considering the uncertainties associated with load variation and wind power generation. In the POARPD, the deterministic optimal active and reactive power dispatch (OARPD) is performed in two stages, which gives a deterministic two-stage OARPD (TSOARPD). The objectives of TSOARPD are the operating cost (OC) minimization in stage 1 and voltage stability (VS) maximization in stage 2, whereas the VS is improved by maximizing the system's reactive power reserve (RPR). In this paper, instead of using multiobjective optimal power flow, this TSOARPD is used to give more importance to VS when the system is substantially loaded. The POARPD problem is solved using PEM for modified IEEE-9 bus and standard IEEE-30 bus test systems by considering the correlation between the loads. The results are compared with Monte Carlo simulation (MCS). While solving POARPD, the voltage-dependent load model is used to account for the real-time voltage dependency of power system loads. This paper discusses the detailed procedure of solving POARPD by considering correlation and the increased nonlinearities by giving more importance to VS when the system is heavily loaded. [ABSTRACT FROM AUTHOR]

Electric power systems constantly encounter disturbances and faults, necessitating fast and precise identification and rectification of these issues. This is crucial for ensuring the stability and reliability of the system. This paper introduces a protection scheme for accelerating the second zone operation of the distance relay during internal faults. The proposed scheme exploits the locus of power with positive power characteristics to effectively distinguish between internal and external faults. This is achieved by detecting the remote circuit breaker operation (RCBO). The locus of power remains predominantly within regions 1 or 2, with occasional transfers between these regions due to internal faults prior to and following the RCBO. Conversely, in the case of external faults, regions 3 or 4 are implicated. This distinct variation in the locus of power is applied to derive the protection algorithm. This is affirmed through sequence network analysis of various faults in the transmission line. The cumulative rate of change in relative reactive power has been employed for single‐phase RCBO detection. The proposed protection logic employs supplementary undervoltage logic to avoid single‐phase operation during two‐phase and three‐phase faults. The simulations are conducted with meticulous consideration of key factors, such as fault type, fault resistance, fault location, fault inception angle, and power source angle. Simulation results demonstrate the effectiveness of the proposed protection scheme. [ABSTRACT FROM AUTHOR]

With the development of new energy, a cost-effective reactive power compensation scheme is essential to the voltage stability of the power system for small-capacity distributed generation. This paper proposes a coordinated control scheme of inverter cluster which is based on the reactive power support capability of the photovoltaic inverter. Moreover, by using power angle vectors, a reactive power distribution algorithm is proposed to solve the poor power quality of the point of common coupling connecting source and load in the distributed generation station. Simulations verify the performance of the algorithm is better than the conventional static capacity distribute algorithm and dynamic residual margin distribute algorithm. Finally, the effectiveness of the reactive power compensation scheme and distribution strategy for improving power quality and regulation ability proposed in this paper is verified by operation experiments in the actual power station. [ABSTRACT FROM AUTHOR]

In order to improve the reactive power optimization effect of the distribution network, this paper combines the multiagent deep reinforcement learning algorithm to analyze the reactive power optimization strategy of the distribution network and constructs an intelligent optimization model. Moreover, the simulation models of power conversion elements, power transmission elements, control elements, and measurement elements in the platform are described, and the program structure and interactive functions are analyzed. In addition, this paper proposes a reactive power optimization method for distribution networks based on data-driven thinking. Finally, by using historical data and an artificial neural network, this paper extracts electrical quantity data such as load power and distributed power output and environmental data such as temperature and wind speed to perform multiagent analysis. The experimental verification shows that the reactive power optimization effect of the distribution network based on multiagent and multiagent deep reinforcement learning proposed in this paper is very good. [ABSTRACT FROM AUTHOR]

The optimization of business management strategy is a research hotspot in the field of resource processing under the market economy environment. Based on the theory of business process orientation, this paper constructs a reactive power optimization method of random matrix for business management and verifies the correctness and effectiveness of the method through an example. The random matrix construction method of enterprise management network and the feature extraction method that can reflect the operating state of the system are optimized, and the conflict problem in the process of enterprise management resource competition is solved. In the process of OpenDSS/Matlab cosimulation, the business management network state data and random matrix index data are processed by means of statistical modeling and feature extraction, and the random Petri net technology is used to construct a continuous time random matrix. The experimental results show that, combined with the verification of the business management network simulation model of the transformed IEEE-37 node, the traditional optimization method takes 96.63 s, while the business process-oriented scene matching method takes 1.32 s, which shows that the business process-oriented method constructed in this paper takes 96.63 s. The business management random matrix has obvious advantages in optimizing the operation speed, which verifies the accuracy, feasibility, and rapidity of the method and effectively improves the performance of the system. [ABSTRACT FROM AUTHOR]

Accurate device parameters play critical roles in calculation and analysis of power distribution network (PDN). However, device parameters are always affected by the operating status and influenced by manual entry; besides, the distribution area of PDN is very wide with many points, which brings more challenges to PDN parameter identification. Most of the proposed algorithms recently assume that the parameters of PDN contribute in a nonlinear probability space and optimize parameters by the power flow model with a loss function. Although these algorithms can achieve satisfying results in PDN analysis, the relationship between the power flow model and loss functions remains unclear. In this paper, the outputs of the power flow model have been analyzed firstly by experimental data, which includes the head and end voltages, as well as active and reactive power on the low-voltage side. It is revealed that the loss functions used by current algorithms are not suitable and reasonable for power flow model in PDN calculation, which constitutes one of the main findings of this work. Subsequently, this work proposes four novel loss functions combined with genetic algorithm (GA) and Markov Chain Monte Carlo (MCMC) to identify PDN parameters. Compared with the published algorithms, our experimental results show that the loss function defined in this paper can achieve better and more stable performance with about two times lower in MAE, RMSE, and RMPE evaluation functions to identify PDN parameters. [ABSTRACT FROM AUTHOR]

This paper presents the challenges of optimal measurement devices placement (MDP) in the distribution system by considering the improvement of accuracy and speed for state estimation (SE) in the presence of distributed generations (DGs). We assumed that active and reactive power measurements (both injection and flow) with voltage magnitude measurements were used to estimate the power system's state. The paper employed phase measurement unit (PMU) and smart meters, which are the two commonly used measuring devices. For numerical evaluation of the system, the power system states are based on the angle and magnitude of voltages at every bus. The issues normally experienced in the optimal measurement devices placement in distribution networks were investigated using the binary dragonfly algorithm (BDA), in this study. As a way forward to proffer solutions to these issues, a fair compromise between accuracy, speed, and the number of measurements (NoMs) was reached, and the proposed solution was tested in two different scenarios applied in the IEEE 33-bus distribution test system. The results illustrate that by increasing the accuracy, NoMs and the cost are going to rise as well. On the other hand, by escalating the speed, NoMs decrease and the accuracy falls dramatically. [ABSTRACT FROM AUTHOR]

Optimal reactive power dispatch (ORPD) is a particular case of the optimal power flow (OPF) which consists in determining the state of an electric power system by optimizing a specific objective function and satisfying a set of some operating constraints. In this paper, the purpose is to solve deterministic and stochastic multi‐objective ORPD (MO‐ORPD) problem under load and renewable energy sources (RES) uncertainties. The uncertainty is modelled using stochastic scenario‐based approach (SSBA). The objectives to be minimized are active power loss and cumulative voltage deviation from their corresponding nominal values. The MO‐ORPD is solved using sum weighed method, and fuzzy satisfying method is used to select the best compromise solution among Pareto front of non‐dominated solutions. In this paper, quantum‐behaved particle swarm optimization differential mutation (QPSODM) algorithm is proposed to solve the ORPD problem. The proposed methodology has been examined and confirmed on the IEEE 14‐bus and the practical Adrar's isolated power system. The performance of the proposed methodology is compared with recent algorithms. Simulation results show that the proposed methodology can solve the MO‐ORPD including RES effectively and can give best and logic results. Furthermore, a sensitivity analysis is carried out to show the performance of the proposed algorithm comparing to own developed algorithms particle swarm optimization (PSO) and quantum PSO (QPSO). [ABSTRACT FROM AUTHOR]

Summary: In the modern world, only conventional energy resources cannot fulfil the growing energy demand. Electricity is a fundamental building block of a technological revolution. Today, most of the electricity demand is met by the burning of fossil fuels but at the cost of adverse environmental impact. In order to bridge the gap between electricity demand and supply, nonconventional and eco‐friendly means of energy generation are considered. Renewable energy systems (RESs) offer an adequate solution to mitigate the challenges originated due to greenhouse gasses (GHG). However, they have an unpredictable power generation with specific site requirements. Grid integration of RESs may lead to new challenges related to power quality, reliability, power system stability, harmonics, subsynchronous oscillations (SSOs), power quality, and reactive power compensation. The integration with energy storage systems (ESSs) can reduce these complexities that arise due to the intermittent nature of RESs. In this paper, a comprehensive review of renewable energy sources has been presented. Application of ESSs in RESs and their development phase has been discussed. Role of ESSs in increasing lifetime, efficiency, and energy density of power system having RESs has been reviewed. Moreover, different techniques to solve the critical issues like low efficiency, harmonics, and inertia reduction in photovoltaic (PV) systems have been presented. Unlike most of the available review papers, this article also investigates the impact of FACTS technology in RESs‐based power system using multitype flexible AC transmission system (FACTS) controllers. Three simulation models have been developed in MATLAB/Simulink. The results show that FACTS devices help to maintain the stability of RESs integrated power system. This review paper is believed to be of potential benefit for researchers from both the industry and academia to develop better understanding of challenges and solution techniques for REs‐based power systems and future research dimensions in this area. [ABSTRACT FROM AUTHOR]

Load forecasting is an integral part of the energy study unit to schedule the generating unit by the load demand. Many studies were conducted on load forecasting based on real power demand; however, very few papers were published on reactive power demand. In this research work, an attempt has been made to predict the requirement of reactive power as a function of demand for real power. Household loads are considered for evaluating the demand for reactive power as a critical load. The attempt has been made based on the data collected from the laboratory experimental setup for one year. The load forecasting requires time series analysis of the data set along with error minimization between predicted values and actual value; therefore, the global flower pollination algorithm along with Holt-Winters' exponential model has been used to predict the reactive power. Autoregressive integrated moving average (ARIMA) and seasonal autoregressive integrated moving average (SARIMA) models have been used as benchmarking models to evaluate the effectiveness of the model under various conditions. Python-developed model has been used to predict the demand for reactive power, and a MATLAB model has been developed to optimize the cost function. A detailed comparative analysis of the proposed model along with some well-established optimized models such as GA, PSO, and FPA has been presented related to evening peak demand for a microgrid architecture in Conclusion. The analysis includes median values of different quantities such as nMBE, nMAE, nRMSE, and RMSE. Normalized MBE, indicating underestimation and overestimation, is negative for ARIMA but 0.42 for HW-GFPA during validation and 0.43 for the testing data set. Normalized RMSE, measuring the variance between actual and forecasted values, is lowest at 0.803 for proposed HW-GFPA during validation and 0.799 for testing. [ABSTRACT FROM AUTHOR]

This paper presents a performance comparison between switching and reduced-order models of grid-following inverters. Different models have been developed to study the inverter's operation using MATLAB and PSIM simulation tools. These models offer a tradeoff between accuracy and computational burden. The switching model fully represents the discontinuities in the inverter due to switching, but such a model demands high computational resources. The inverter representation is simplified using reduced-order models, which is common in the literature. However, the fidelity of these simplified models might not be adequate for some applications. Therefore, it is essential to investigate the performance of such models closely to ensure their suitability depending on the purpose of the analysis. Hence, a comparative study between switching and reduced-order models is presented here by simulating different scenarios and operation conditions. The results have validated the efficacy of the reduced-order model in representing the grid-following inverter's operation in both steady state and response to a step change resulting from active or reactive power variation. Unlike the switching model, the findings illustrate that the reduced-order modeling fails to represent harmonics and losses. After simulating different scenarios, this work highlights the main differences between the switching and reduced-order models to facilitate the choice of the proper modeling method for researchers. [ABSTRACT FROM AUTHOR]

One of the main challenges of a four-switch three-phase rectifier (FSTPR) is a DC imbalance in capacitor voltages. On the other hand, under unbalanced grid voltage conditions, unbalanced three-phase input current and the DC-link voltage affect the performance of the FSTPR. Although many papers focus on designing a controller to balance DC-link capacitor voltage, a few papers are available to cope with the imbalance of DC-link capacitor voltages and input current simultaneously under unbalanced grid voltage. In this paper, first, the operation of the FSTPR under unbalanced grid voltage conditions is investigated. It can be seen that under these conditions, the oscillatory parts of the active and reactive input power, i.e., sin and cos components, are the leading cause of the problems that can severely degrade the FSTPR performance of the controller. Therefore, this paper presents a promising control technique to eliminate the mentioned oscillation components. Aiming at this purpose, the current control loops in the dq axis are divided into two positive and negative sequences, i.e., idq+ and idq−. Simulation results in MATLAB/SimPowerSystem™ show that the proposed controller can reduce the output voltage ripple, the total harmonic distortion, and the unbalancing of input current compared to a conventional controller. Under these conditions, the DC-link capacitor voltages are more balanced, significantly reducing the voltage limiter of the FSTPR. [ABSTRACT FROM AUTHOR]

In this paper, the optimal operation of microgrids (MGs) with thermal blocks, distributed generations (DGs), storage systems, and responsive loads is presented to achieve optimal scheduling of active, reactive, and thermal power of the mentioned elements in the day-ahead (DA) reactive power and energy market environment. The thermal block has a combined heat and power (CHP) system, a boiler, and thermally responsive loads. This scheme minimizes the difference between the total operating costs of the MG and power sources and the total revenue gained from the sale of energy and reactive power of the mentioned elements in the markets located in the MG. It is constrained by the AC power flow equations, network operation constraints, and the operating model of these elements. Furthermore, this scheme is subject to the uncertainties of energy price, load, and renewable power. In this paper, to access the optimal resistant solution against the maximum prediction error associated with the mentioned uncertainties, a robust model based on information gap decision theory (IGDT) is used. Finally, by implementing the proposed scheme on a 119-bus radial MG, the obtained numerical results confirm the ability of the scheme to simultaneously improve the economic and operational situation of the MG. The proposed scheme succeeded in improving energy cost, energy loss, voltage drop, and power factor of the distribution substation by roughly 101%, 44%, 41%, and 16% compared to power flow studies, even in the worst-case scenario caused by uncertainties. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates the hybrid HVDC with cascaded multi‐infeed MMCs' basic control characteristic and designs the coordinates control strategy considering the DC voltage control and commutation failures of the LCC inverters. The complete basic UI curves of the hybrid HVDC are obtained, and the interaction mechanism of each converter is also clarified, which is in master‐slave control mode. Through the obtained basic characteristic, to reduce the commutation failures of the LCC inverter, the coordinated DC voltage control strategy with dynamic limiter is designed to enhance the AC voltage stability. And the coordinated DC voltage control method coped with the dynamic limiters is also designed. Based on the proposed method, the DC voltage can be stable and unbalanced active power can also be distributed reasonably by the DC voltage control strategy, while much more reactive power can simultaneously be released from VSC to support the stable operation of the LCC inverter. Such that the DC side operation and AC side voltage stability of the hybrid HVDC can both be improved. Finally, the simulations verify the theoretical analysis done in the paper. [ABSTRACT FROM AUTHOR]

There is higher harmonics and electromagnetic interference caused by high-power-density switching power supply during high-frequency and normal operations which affects power quality of switching power supply and also impacts the environment. To solve this problem, this paper proposes a dual digital signal processor (DSP) controller suitable for unified power quality regulators and designs high-power-density switching power supply control system for promoting green environment. The overall structure of the system is divided into two parts, the power main circuit and the control circuit. In the main power circuit, the electromagnetic interference (EMI) filter is used to filter the input AC voltage and convert it into a stable DC voltage. A high-frequency inverter is used to invert the DC voltage into a high-frequency AC voltage to achieve harmonic control and reactive power compensation. In the control circuit, dual DSP controller is used to improve real-time detection, control of the output voltage, and current and driver temperature of the high-power-density switching power supply, while high-precision analysis and processing system collect different information and then achieve the power quality control of the switching power supply based on system software to keep this environment green. The experimental results suggest that the harmonic content of the experimental objects controlled by the system is reduced by 16.7% compared with the existing power quality control and the absolute error of the system is less than 0.02 V which improves the de-noising performance. The power generation systems require that the consumption of natural resources and renewable energy solutions can assist in saving the natural resources. [ABSTRACT FROM AUTHOR]

The increasing integration of renewable energy sources into modern electric grids has led to a rise in uncertain factors that must be managed to maintain voltage security during reactive power optimization (RPO). Traditional deterministic RPO methods fail to account for these uncertainties, which can result in power grid security issues such as voltage violations. To address these challenges, this paper proposes a data-driven interval-based reactive power optimization method (IRPOM). The IRPOM represents the uncertainties associated with renewable power generation and load demands as intervals within the RPO problem formulation. The proposed method uses an improved particle swarm optimization algorithm to solve the RPO problem. In each iteration, the uncertain power flow is solved using the optimizing-scenarios method- (OSM-) based interval power flow (IPF) algorithm. This approach calculates the real power losses and checks whether state quantities, including voltage, power flow, and generator output, exceed their limits. Furthermore, a data-driven modeling approach is introduced to reduce the conservativeness of the IRPOM solutions. The effectiveness of the proposed method is demonstrated through detailed computational analysis on a modified IEEE 30-bus system. The results show that the proposed approach ensures economic efficiency while maintaining a low bus voltage threshold crossing probability close to zero. [ABSTRACT FROM AUTHOR]

In this paper, an intelligent integrated approach is proposed to control the reactive power and restore the voltage balance in a three-phase power system using particle swarm optimization (PSO), Gaussian process regression (GPR), and support vector machine (SVM). The PSO algorithm is used in offline mode to determine the optimal set of firing angles for the thyristor-controlled-reactor (TCR) compensator according to the smallest fitness value required for voltage balancing. The optimum firing angles are then used to train the GPR and SVM regression models. The GPR and SVM models are finally used as a real-time controller to retrieve the voltage balance in online mode. A simulation model and experimental setup of the electrical power system are built. The modeled system consists of a 500 km long transmission line. The line is divided into three-pi sections to guarantee a real system response. Several simulation and practical case studies have been conducted to test and validate the capability of the proposed integrated approach in solving the voltage unbalance problem. The results have revealed the supreme ability of the proposed integrated approach to restore the voltage balance quickly (within 20 ms) and for a wide range of voltage unbalance factors (VUFs) (3.90–8.42%). [ABSTRACT FROM AUTHOR]

To supply resident loads far from the grid, a stand-alone wind system with a small-scale wind turbine and battery storage can be used. The traditional configuration of the system has a permanent-magnet synchronous generator (PMSG). Other alternative configurations use doubly fed induction generator (DFIG). The systems with DFIG have variable speed operation with a limited speed range which reduces the captured power from the wind turbine. Also, there is a rotor-side converter (RSC) which carries the reactive power of DFIG, in addition to the slip power. In this paper, an improved system configuration with DFIG is controlled by an advanced control scheme. By this advanced scheme, the speed range is increased such that maximum power operation of wind turbine is obtained for complete range of wind speed, and volt-ampere (VA) requirements of RSC are reduced by the operation at nearly zero-slip power. [ABSTRACT FROM AUTHOR]

The depletion of nonrenewable energy and climate lead to increasingly bad environment. The efficient development of new energy has become an urgent problem to be solved. As a kind of new energy, how to effectively develop and utilize wind energy has aroused widespread concern all over the world. In this paper, a three-phase static a-b-c coordinate system is used for transformation. Taking the variable-speed constant-frequency doubly fed wind power generation system as the control object, the technology of generator power decoupling control is realized. The rotor side and grid side power converters adopt vector control methods based on stator flux orientation and grid voltage orientation, respectively. In this paper, the motion equation, flux equation, voltage equation, and electromagnetic torque equation of the motor are established. Vector-oriented control technology is used to control the generator. The control model of the VSCF doubly fed wind power generation system is established by using the simulation software PSCAD, and the simulation experiment is carried out. The feasibility of the power decoupling control method based on vector control is verified. The change trend of the active power of the power generation system is consistent with that of the wind speed, which shows that the control system has good stability. Using the field-oriented vector control method, the dual PWM controller can independently control the active power and reactive power. This greatly simplifies the nondecoupling control function equation in the expression. The dual PWM controller is well adjusted to minimize the power loss of the wind power generation system. [ABSTRACT FROM AUTHOR]

Summary: During the last years, the electricity networks worldwide have rapidly developed, especially with integrating many types of renewable energy sources (RESs). The optimal operation is an opportunity to increase the penetration level of stochastic RESs into the power grid to maximize energy efficiency. Generally, the optimal power flow (OPF) problem is a highly complex, non‐convex, and non‐linear optimization problem. The complexity of the OPF problem is further increased as stochastic RESs are incorporated into the network. This paper presents an effective solution to the OPF problem for a traditional power generation with stochastic RESs. For solving this problem, chaotic Bonobo optimizer (CBO) is proposed in this paper based on the Chaos Theory to avoid the stuck in the local minimum by applying the original Bonobo optimization (BO). The performance of BO is enhanced using the chaotic maps sequences technique to enhance its global search capability and prevent getting stuck into local solutions. Uncertainty of the output power generated by RESs is forecasted based on probabilistic models. To minimize the total operating cost, the direct, underestimation, and overestimation costs of RESs are considered. Three different objective functions are considered, minimizing total operating cost, emissions, and power losses. Moreover, a carbon tax is incorporated in the objective function problem to minimize carbon emissions. The proposed OPF model and CBO technique are verified on the modified IEEE‐30 and IEEE‐57 bus test systems to confirm the superiority and effectiveness of the proposed CBO to achieve the optimal solution. The simulation results prove the efficiency and robustness of CBO for finding the best solution to the OPF problem with stochastic RESs. [ABSTRACT FROM AUTHOR]

Parallel restoration following blackouts can reduce economic and social losses. This paper aims to develop a parallel restoration method coordinating the partitioning scheme of the blackout system and restoration strategies of subsystems. The susceptible-infected-recovered model, i.e., a virus propagation model of complex networks, is used to decide the parallel restoration strategies online. Firstly, various types of viruses are used to represent different subsystems. The probability vector of virus infection is obtained according to the importance level of each bus. Secondly, an immunization strategy is developed based on the faulted buses in the blackout situation. According to the infection rate and the immunization strategy, the virus propagation direction will be changed based on real-time system conditions. The startup characteristics of units and the charging reactive power of restoration paths are considered as constraints to embed in the virus propagation process. Finally, the partitioning scheme and the restorative actions for subsystems are determined based on the infected results of viruses. The effectiveness of the proposed method is validated by case studies on the IEEE 39-bus and the IEEE 118-bus test systems. [ABSTRACT FROM AUTHOR]

Wind turbines (WTs) are a desirable alternative to traditional nonrenewable power resources as a result of recent environmental concerns. Some of them are fixed speed wind generator (FSWG) and have been integrated to power system by squirrel cage induction generator (SCIG). Induction machine absorbs reactive power during all operating conditions, especially at fault condition may result in severe voltage drop which can lead to generator outage. This outage disconnects a significant amount of active power and consequently leads to frequency instability. In order to prevent induction generator (IG) outages in short circuit failures, this paper investigates thyristor-controlled series capacitor (TCSC) device as a candidate solution. TCSC compensates the IG terminal voltage drop by adjusting transmission line impedance at fault condition. In the proposed method, a metaheuristic technique means that shuffled frog leaping algorithm (SFLA) has been utilized to optimize the TCSC controller gains. The proposed scheme can be applied for both SCIGs and wound rotor induction generators (WRIGs) which is another advantage of this method. Single-machine infinite bus system is considered as case study, and various operating conditions and disturbances have been considered to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Renewable energy sources (RESs) such as solar photovoltaic (PV) systems are increasingly used as distributed generation for replacing the conventional energy. At the same time, energy storage systems like battery (BAT) must be applied for maintaining the balance between fluctuating energy production and load consumption. BAT's state of charge (SOC) should be maintained within their design limits unaffected by RES intermittency and/or load power variations. This necessitates advanced power control and management methodologies for overcoming challenging conditions. This paper discusses and evaluates an optimal DC bus voltage regulation approach: an intelligent controller using an adaptive fuzzy logic controller (FLC) and a novel supervisory power management strategy for PV systems with BAT. The objectives are to keep a stable power flow in the system and guarantee the continuity of service by ensuring that the system components do not exceed their limits. In this manner, the DC bus voltage regulation of the PV/BAT system can be improved in comparison with conventional regulation. Therefore, the most important contributions of this work are as follows. (1) Development of comprehensive and modular novel energy management system (EMS): its originality is related to the inclusion of the control system limits with faster SOC balancing and smaller DC bus voltage fluctuation. (2) Providing a simple power flow management implementation that considers the optimal energy flow between PV system, BAT system, and load: a balance between minimal energy flow in the connecting line and the least requirements of BAT capacity is kept, reducing component constraints with a very straightforward structure. (3) Furthermore, FLC offers high robustness and smooth performances. FLC is added to the control strategy design requirements to reduce DC bus voltage deviation. (4) Real-time simulation/experimentation-based complete cases utilizing Matlab/Simulink and DSpace are illustrated to testify the effectiveness of the proposed FLC and EMS. [ABSTRACT FROM AUTHOR]

This paper compares the efficiency of a modified wireless power transfer (WPT) system with a current-fed dual-active half-bridge converter topology and a complete bridge converter topology for a current-fed resonate compensation network with current sharing and voltage doubler. Full-bridge topologies are widely used in current WPT structures. The C-C-L resonate compensation networks for dual-active half-bridge converter and full-bridge converter topologies are built in this paper on both the transmitter and receiver sides. Due to higher voltage stress around inverter switches, series-parallel (S-P) tanks are not recommended for current-fed topologies because they are not ideal for medium power applications. A series capacitor is connected to reduce the reactive power absorbed by the loosely coupled coil. As a consequence, the C-C-L network is used as a compensation network. Dual-active half-bridge topology is chosen over full-bridge topology due to the system's component count and overall cost. Soft-switching of the devices is obtained for the load current. The entire system is modelled, and the effects are analysed using MATLAB simulation. [ABSTRACT FROM AUTHOR]

Grid‐connected Single‐Stage Boost Inverters (SSBI) are extensively being researched in the area of photovoltaic energy conversion systems. Owing to their single‐stage boosting capability, this class of power converters results in higher efficiency and reliability. This power circuit configuration is constituted by two mutually dependent sub‐converters, in that a front‐end quasi‐Z‐source (qZS) part is integrated to a back‐end multilevel inverter (MLI). The MLI provides the shoot‐through state to the qZS, while the qZS provides the pulsating DC input to the MLI. In general, solar photovoltaic inverters suffer from the disadvantage of leakage current that flows from solar panels to the grid/load. This paper introduces a dual quasi‐Z‐source based multilevel inverter, which achieves the following benefits: (a) five‐level output voltage, (b) reactive power capability, (c) shoot‐through immunity, (d) continuous input current, and (e) reduced leakage current based on VDE 0126‐1‐1 standards. In this paper, a modified modulation scheme, which is based on the employment of phase‐disposed and level‐shifted carrier signals, has been used to reduce the leakage current. To reduce the leakage current further, a passive filter is employed to eliminate high frequency variations across the parasitic capacitance. The working principle of the proposed power converter and the effectiveness of the modulation scheme have been validated with simulation studies in both standalone and the grid‐connected mode. Finally, the simulation studies are verified through an experimental prototype of 500 W rating. [ABSTRACT FROM AUTHOR]

With a high proportion of renewable distributed generation and time-varying load connected to the distribution network, great challenges have appeared in the reactive power optimization control of the active distribution networks. This paper first introduces the characteristics of active distribution networks, the mechanism and research status of wind power, photovoltaic, and other renewable distributed generators, and time-varying loads participating in reactive power and voltage optimization. Then, the paper summarizes the methods of reactive power optimization and voltage regulation of active distribution network, including multi-timescale voltage optimization, coordinated optimization of network reconfiguration and reactive power optimization, coordinated optimization of active and reactive power optimization based on model predictive control, hierarchical and zoning control of reactive power, and voltage and power electronic switch voltage regulation. The pros and cons of the reactive power optimization algorithms mentioned above are summarized. Finally, combined with the development trend of the energy Internet, the future directions of reactive power and voltage control technology in the active distribution network are discussed. [ABSTRACT FROM AUTHOR]

Summary: These frequency responses in tandem with spinning reserve are a prominent problem in the future smart grid environment due to the increase of non‐dispatchable energy sources. However, this new environment allows incorporating new technologies, that is, distributed energy resource (DER), energy storage systems (ESSs), and shiftable loads, to prevent emergency situations and blackouts. This paper proposes a novel, energy reserve operational scheduling method for future smart grid frequency enhancement considering wind generation, ESSs, thermal generating units, shiftable loads, and power system frequency response characteristics. The proposed method divides the reserve into two different parts, that is, active power reserve, which is responsible for smoothing the frequency fluctuations due to load variations and the second part is essential to control the frequency after large disturbances. The spinning reserve required for safe operation of the power system is determined based on a reliability criterion, that is, total expected energy not supplied (TEENS). The proposed method aims to maintain the frequency response in a stable mode by incorporating active power reserve from both generation and demand‐sides. IEEE 30‐bus and RTS‐96 systems are utilized to verify the proposed reserve scheduling methods using GAMS programming environment. The obtained results verify the superiority and usefulness of the proposed method over others. [ABSTRACT FROM AUTHOR]

According to increasing growth of DC loads, DC microgrids (MGs) have an effective role in future power systems. Improvement of power management is one of the important issues in DC MGs. In this paper, in order to provide an accurate power management in standalone low‐voltage DC (LVDC) MG, including photovoltaics (PVs) and battery energy storage systems (BESSs), an AC component is superimposed to the output voltage of DC‐DC converters by inspecting the frequency droop control of the synchronous generators. In addition, two corrective terms based on the calculation of AC active and reactive powers are added to this AC component, which is named improved frequency droop method (IFDM). Different operating modes for PV system comprising maximum power point tracking (MPPT) and voltage control mode (VCM); and BESS consisting of charge, discharge, and idle are considered in the proposed power management scheme based on the state of charge (SoC) of local BESS. On the other hand, the conventional proportional‐integral (PI) controllers in DC‐DC converters' control structure present poor transient dynamic performance and low loading level. Hence, fractional order PI (FOPI) controllers are designed by optimization of integral time absolute error (ITAE) criteria. The effectiveness of the proposed FOPI controllers combined with IFDM scheme is evaluated by simulations conducted in MATLAB/SIMULINK software. The FOPI‐IFDM approach provides accurate current sharing and better voltage regulation without dependence on communication link in comparison with PI‐IFDM under load, line impedance, and solar irradiance variations. [ABSTRACT FROM AUTHOR]

Summary: Identifying maximum penetration level (MPL) of Solar Photo‐Voltaic Generation (SPVG) in the distribution system is crucial for system planners and network operators to keep the system parameters within the acceptable limits. This paper provides a systematic and extensive procedure for evaluation of MPL of SPVG and its enhancement methods in distribution systems. More importantly, it illustrates a novel algorithm for affixing the penetration cap of Solar PV. The methodology initially derives a new stability index for locating SPVGs in the system, including both active and reactive power support from SPVGs. The study shows the utility of redefining MPL of SPVGs by considering the reactive power injection through solar inverters also. Deviating from the practice of considering the conventional constraints of voltage rise and maximum loading for MPL estimation, the paper considers loss minimization as the major constraint. The algorithm has potential to identify distributed integration scenario of SPVGs compared to the limited number of placements in the extant algorithms. This paper provides a novel algorithm to evaluate of maximum penetration level (MPL) of solar photo voltaic generation (SPVG) and its enhancement methods in distribution systems. The utility of redefining the MPL of SPVG by considering the reactive power injection through solar inverter is illustrated. The algorithm has distinct advantages over the extant algorithms in identifying a distributed integration scenario. [ABSTRACT FROM AUTHOR]

In this paper, the research status of topology and control strategy of energy storage grid-connected system is analyzed, and aiming at the working characteristics of the repurposed battery, a cascade power electronic transformer (CPET) with independent DC output is proposed. The working principle of current fed isolated bidirectional DC-DC converter (CF-IBDC) and cascaded H-bridge (CHB) is analyzed, and the decoupling control strategy is designed. In this paper, a hierarchical control strategy is designed for the repurposed battery energy storage (RBES) grid-connected system based on CPET, which consists of three layers: energy layer, power layer, and state of charge (SOC) layer. The energy layer responds to active and reactive power scheduling instructions, the power layer controls the grid-connected current and tracks the grid voltage, and the SOC layer equates the charged state of repurposed batteries. A 3 MVA/12 kV three-phase grid-connected simulation system was established, and a 1 kW single-phase system experiment platform was designed. The simulation and experimental results can verify the correctness of the theoretical analysis and the feasibility of the control strategy. [ABSTRACT FROM AUTHOR]

Summary: According to the recent grid codes, wind turbine systems (WTSs) are required to stay connected to the grid during grid faults and provide reactive power to support the grid. Therefore, this paper proposes a noncontrolled fault current limiter (NCFCL) with reactive power support for transient stability improvement of DFIG‐based WTSs under grid faults. The proposed NCFCL is based on a nonsuperconducting reactor located in the rotor side. The NCFCL considerably limits the rotor and stator overcurrents and improves the transient stability of the doubly fed induction generator (DIFG). In addition, the proposed strategy reduces DC‐link overvoltage and electromagnetic torque oscillations and also provides reactive power to the grid to support the grid voltage recovery. In this way, the fault ride‐through (FRT) requirements of the latest grid codes can be fulfilled without affecting the DFIG stability in normal operation. Simulation studies using MATLAB/Simulink‐2019a are performed on a 2‐MW DFIG‐based WTS to confirm the effectiveness and feasibility of the proposed FRT strategy. Simulation results reveal that the proposed strategy provides better performance compared to the crowbar protection to improve the FRT capability. [ABSTRACT FROM AUTHOR]

This paper presents grid-oriented multiobjective harmony search algorithm (GOMOHSA) to incorporate the multiple grid parameters for minimization of the active power loss, reactive power loss, and total voltage deviations (TVD) in a part of practical transmission network of Rajasthan Rajya Vidyut Prasaran Nigam Limited (RVPN) in southern parts of Rajasthan state of India. This is achieved by optimal deployment of optimally sized renewable energy (RE) generators using GOMOHSA. Performance indexes such as active power loss minimization index (APMLI), the reactive power loss minimization index (RPMLI), and the total voltage deviation improvement index (TVDII) are introduced to evaluate the health of the test network with different load scenarios. Performance of proposed GOMOHSA has been tested for five different operating scenarios of loads and RE generation. It is established that the proposed GOMOHSA finds the optimal deployment of optimally sized RE generators, and the investment cost of deployment of these RE generators can be recovered within a time period that is less than 5 years. Performance of GOMOHSA is superior compared to a conventional genetic algorithm (GA) in terms of performance indexes, RE generator capacity, payback period, and parameter sensitivity. Study is performed using MATLAB software for loading scenario of base year 2021 and projected year 2031. [ABSTRACT FROM AUTHOR]

A fuzzy logic- (FL-) based control technique for unified power flow controller (UPFC) to resolve the power quality issues in transmission network is presented in this paper. MATLAB/Simulink is used to design the FL-based controllers for shunt and series converters of UPFC, which is validated on 4-bus system. In addition, the performance of the suggested FL-based UPFC is compared with PI (proportional integral), HC (hysteresis controller), MPC (model predictive controller), and FLC (fuzzy logic controller), and the outcomes are compared in terms of settling time and steady-state error. The consequences characterize that the higher enactment of closed loop hybrid power flow controller (HPFC) 4-bus system with FLC UPFC controller's (FL based) robustness is ensured from the simulation results as it has overcome the power quality issues like reactive power compensation, voltage sag mitigation, and THD reduction of transmission line current below 5% as per IEEE standard. Settling time of CL FBS is abridged from 0.87 to 0.62 sec, and steady-state error of voltage in CL FBS is abridged from 0.9 to 0.1 V using FLC. [ABSTRACT FROM AUTHOR]

Isolated microgrids (MGs) face challenges in performance stability and active/reactive power sharing as a result of frequency/voltage deviations and mismatched line impedance issues. In this paper, a consensus-based multiagent system (MAS) is proposed as a solution to restore voltage/frequency deviations and enable true power sharing. The invention of an Intelligent Distributed Secondary Control Scheme (IDSCS) can efficiently achieve hoped-for outcomes. The proposed IDSCS features estimation and compensation sublayers. For the estimation sublayer, discrete dynamic consensus algorithm-based state estimators are presented to collect average information of frequency, voltage, and reactive power. Each DG is viewed as an agent sharing information with its immediate neighbors through a sparse cyber communication network. In the compensation sublayer, online tuned proportional integral (PI) controllers using artificial neural networks (ANNs) are proposed as an intelligent voltage and frequency compensators. This combination uses the simplicity of the PI controller mathematical formula and ANN's ability to deal with parameter variations and nonlinearity. Due to the global nature of the frequency parameter, the active power-sharing compensator is unnecessary. For compensating reactive power deviations, ANNs-based reactive power controllers are proposed. Furthermore, at the primary control level, the proposed strategy employs discrete-time proportional resonant (PR) controllers in a stationary reference frame, eliminating the need for any α β / d q or d q / α β transformations. Distributed implementation of the proposed method guarantees system scalability without MG topology or demand pattern expertise. The control scheme was validated using hypothetical MAS in MATLAB Simulink platform. The simulation findings indicate the proposed MG system can effectively distribute power among the DGs while maintaining voltage and frequency stable. [ABSTRACT FROM AUTHOR]

FACTS tools in modern power systems provide a vital solution to the problems of voltage deviation and fault ride-through (FRT) capability in electrical power systems especially during the integration of wind power. Many distinct journals highlight that the wind-driven squirrel cage generator (SCIG) still accounts for around 15% of operating wind generators so far. To enhance voltage stability and FRT capacity, this paper recommends a cost-effective static VAR compensator (SVC) which has a size rating of six MVAR, and this improves the efficiency of the electrical power system. Different events are considered in this study such as high turbulent wind speed, low turbulent wind speed, unsymmetrical faults, and symmetrical faults to validate the suggested option. Moreover, the suggested solution is compared with the static synchronous compensator (STATCOM) and a fixed capacitor to ensure that during the studied wind speed profiles and faults, voltage stability, reactive power consumption, and FRT capability are realized. An overall comparison among them is performed under all studied scenarios to summarize their benefits and impacts. The simulated results show the effectiveness and superiority of SVC in improving the operation of an integrated wind system based on a grid-linked SCIG and the performance of the power system. The modeling of SCIG, SVC, and STATCOM is designed by MATLAB/Simulink toolbox. [ABSTRACT FROM AUTHOR]

Power loss reflects the effective utilization rate of energy and the management level of power grids. In this paper, we propose a combined power loss reduction strategy optimization framework to improve the power loss reduction effect in a distribution network. The weak points of the distribution network are analyzed based on power flow calculation. The corresponding power loss reduction strategies are generated considering the following three aspects: replacing distribution lines, distribution transformers, and reactive power compensation. A combined power loss reduction strategy optimization model considering the comprehensive benefits of power loss reduction is established. A method for solving the optimization model based on the cost-benefit ratio is also proposed. Experiments based on the dataset from Tianjin show that the proposed loss reduction optimization method can effectively reduce power loss and formulate a reasonable loss reduction modification scheme in the distribution network. [ABSTRACT FROM AUTHOR]

After losing one or two poles of the high-voltage DC (HVDC) line, power systems may experience angular oscillations among the synchronous generators (SGs), possibly followed by tripping of the SGs and blackouts of the loads. To suppress the oscillations, the difficulty lies in the optimization methods and the countermeasures. For the former, parameter optimization based on the eigen-analysis for a given scenario is not suitable for angular oscillation after a large disturbance lasting for several seconds or longer. For the latter, adjusting the active power of the SGs is effective but responds slowly. Adjusting the excitation system of the synchronous condensers (SCs) is seldom studied since the relation of the power angle with the reactive power is not clearly described. Adjusting the control parameters of the remaining HVDC has limited effect and is not enough. The set-points for the controller of the HVDC are adjusted to suppress the oscillation but are to be restored after the oscillation, which is different from optimization of the control parameters. In this paper, coordinated optimization of the control parameters and the set-points of the SC and the HVDC is proposed to suppress the angular oscillations among the SGs. At first, the relation of the reactive power of the SC with the power angles is validated to provide the basis for optimizing the control parameters and the set-points of the SC. Since the analytical expression between the power angle and the control parameters or the set-points related to the reactive power is not explicit and the optimization periods of different parameters are different, an improved analytical model of the trajectory sensitivity (TS) is proposed. Based on the indication indices, the control parameters and the set-points of the constant current controller and the excitation system to be optimized are decided. The gradients of the objective function are extended to derive a coordinated multiparameter optimization model to suppress the angular oscillation among the SGs. The numerical results validate the accuracy of the improved TS by comparing it with the perturbation method. The time-domain analysis in different scenarios shows that the angular oscillations in the AC/HVDC system are effectively suppressed with the proposed optimization model. [ABSTRACT FROM AUTHOR]

Bidirectional isolated dual active bridge is a vital component for low voltage distribution network. Conventionally dual active bridge is operated using single phase shift control technique. At unity voltage conversion ratio, it operates efficiently, but when voltage conversion ratio differs from unity, its efficiency decreases and current stress increases due to more reactive power. Moreover, voltage obtained at primary side of high frequency transformer is of 2‐level only, which increases voltage stress across switching devices. Furthermore, it has only one degree of freedom, which confines its ability to regulate power flow. In this paper, a transistor clamped dual active bridge DC‐DC converter is proposed with three degrees of freedom, which improves its ability to regulate power flow, and because of incorporation of 5‐level voltage on primary side of high frequency transformer, current stress in switches decreases significantly. It also leads to reduction in voltage stress across switching devices. Modeling of the proposed converter has been carried out to obtain power flow equation. In addition to the phase shift control, proposed converter has two more control parameter, which enhances the power flow controllability of the converter. It has higher efficiency as compared to conventional 2‐level DAB. Performance of the proposed converter is validated via simulation and experimentation on developed laboratory prototype. [ABSTRACT FROM AUTHOR]

This paper is inspired by the question, "if the multi‐phasetransmission system becomes commercially possible in future, then which type of variable speed induction generators will feed electric power to multi‐phase transmission system?" In this paper, a novel six‐phase DFIG through Asymmetrical Winding Structure is developed to extract electric power from the wind energy generation system (WEGS). Due to the spread of pandemic disease (Covid‐19), the attention of power engineers is increasing toward the reliability (in terms of fault tolerance capability) of AC generators. The principle contribution of this manuscript is the modeling (mathematical and simulation‐based modeling) of novel asymmetrical six phase doubly fed induction generator (ASPDFIG). Furthermore, this paper presents the complete modeling of WEGS which contains the modeling of supporting components (6‐phsase transformer, appropriate rotor side converter, grid side converter, dc link etc.), aerodynamic system. In addition to modeling, the analysis, and the controlling strategy for ASPDFIG, wind turbine also discussed. The elegant advantages such as fault tolerance, high efficiency, reduced torque pulsation and reduced per leg converter rating of ASPDFIG are also discussed. The simulation results, particularly the stator voltage, phase current, active and reactive power, are given to validate the theoretic investigation. [ABSTRACT FROM AUTHOR]

Background: Nowadays, Distributed generations play a key role in power distribution system planning. Aims: This paper presents the genetic algorithm (GA)‐based multi‐objective optimization for performance index‐based size and site determination of distributed generations (DGs) planning in distribution systems with constant impedance (Z), constant current (I), constant power (P) load models from the minimization of the entire real power loss of the system viewpoint. Materials & Methods: The various forms of DGs are considered for an analysis point of view. The various forms of constant impedance (Z), constant current (I), constant power (P) load models (ZIP‐LMs) are considered for DG planning for system performance indices enhancement. System performance indices just like the real power loss index (% ILP), the reactive power loss index (% ILQ), voltage deviation index (% IVD), and reduction of short circuit current (% IC), the active power DG penetration (% PWDGP) and reactive power DG penetration (% PWDGQ) are calculated during this paper. Results: The feasibility of the proposed approach has been tested on the 16‐bus distribution test system. The 16‐bus system could be a sub‐system of the 37‐bus system. Discussion: The comparative analysis of the system performance of various forms of DGs planning in distribution systems with ZIP load models has been analyzed. Conclusion: It is observed that the operation of diesel and the internal combustion engines are the optimal solution for the distribution system with ZIP load models. [ABSTRACT FROM AUTHOR]

Voltage rise is the main obstacle to prevent the increase of distributed generators (DGs) in low-voltage (LV) distribution grids. In order to maintain the power quality and voltage levels within the tolerance limit, new measurement techniques and intelligent devices along with digital communications should be used for better utilization of the distribution grid. This paper presents a real-time sensor-based online voltage profile estimation technique and coordinated Volt/VAR control in smart grids with distributed generator interconnection. An algorithm is developed for voltage profile estimation using real-time sensor remote terminal unit (RTU) which takes into account topological characteristics, such as radial structure and high R/X ratio, of the smart distribution grid with DG systems. A coordinated operation of multiple generators with on-load tap changing (OLTC) transformer for Volt/VAR control in smart grids has been presented. Direct voltage sensitivity analysis is used to select a single DG system for reactive power support in multi-DG environment. The on-load tap changing transformer is employed for voltage regulation when generators' reactive power contributions are not enough to regulate the voltages. Simulation results show that the reported method is capable of maintaining voltage levels within the tolerance limit by coordinated operation of DG systems and on-load tap changing transformer. [ABSTRACT FROM AUTHOR]

To reduce the complexity of multiarea power systems during power flow study and security assessment, equivalencing of external power systems is essential. In this paper, external power systems are modeled as adaptive loads representing the tie-line flows varying with system operating conditions. The fuzzy inference system tuned by hybrid genetic-simulated annealing (HGSA-FIS) is proposed to predict the active and reactive power of adaptive loads from forecasted renewable energy (RE) generation and loads demand. The performance of proposed equivalent has been evaluated with an RTS-GMLC by comparing the power flow results in the internal system before and after equivalencing under varying RE and load demand scenarios. The results demonstrate the robustness of HGSA-FIS-based equivalent under varying RE generation and load demand. Furthermore, the proposed equivalent performs close to ANN-based equivalent and outperforms ANFIS-based equivalent. To practically implement the proposed approach, the neighboring system operators are required to exchange only the forecast data of RE generation and load demand, and the equivalent needs to be updated upon major grid changes. [ABSTRACT FROM AUTHOR]

This paper presents a performance evaluation of an off-grid PV-wind-biomass hybrid energy system for a remote area named Kuakata in Bangladesh considering dispatch strategy-based control, power system response, and reliability analysis-based stability and feasibility study. The simulation and optimization of operations of the system have been done by the HOMER software using the real-time field data of solar radiation, wind speed, and biomass of that particular area for ensuring economical and environmental feasibility offering the least net present cost (NPC), cost of energy (COE), and CO2 emission. The result shows that NPC has been reduced by 88 percent, CO2 emissions have been reduced by 99 percent, the operating cost has been lowered by 99 percent, and COE has been reduced by 92 percent than another available work. Besides, in comparison to traditional power sources, COE has been reduced by 40 percent, NPC has been lowered by 90 percent, and CO2 emissions have been reduced by 99 percent. The proposed system has also been analyzed utilizing DIgSILENT PowerFactory software to find the power system responses, i.e., active, reactive powers, voltage, and frequency responses of the proposed microgrid in a per unit fashion on the occurrence of a three-phase fault. To establish the feasibility of the microgrid, a reliability study considering different reliability indices has also been done. The analyzed hybrid energy system might be applicable to other regions of the world where there are similar climatic conditions. [ABSTRACT FROM AUTHOR]

In this paper, an alternative strategy for real-time control of active distribution network voltage is developed, not by controlling the bus voltage as in the various centralized, decentralized, and local approaches presented in literature but rather by only eliminating the impact produced by active and reactive power of distributed generation (DG) units on the voltage of all network nodes and keeping the traditional voltage control systems dealing with the same constraints of passive systems. In literature, voltage deterioration introduced by DGs has been reported as one of the main obstacles for the interconnection of large amounts of DG units to the existing networks. In this paper, the novel control strategy is based on a sensitivity formula developed to calculate the compensation needed for additional distributed flexible AC transmission system (D-FACTS) devices to push and pull the exact reactive power and to eliminate the impact produced by DGs on the network voltage profile. The criteria of the allocation of the var devices and the required network reinforcement are developed in this paper, considering all possible topology structures, and an innovative codification method is introduced to reduce the needed computation time and communication data to actualize the sensitivity coefficients and get the proposed control approach flexible with network topology reconfiguration. The risk of the conflict of the proposed control system with the traditional voltage equipment is reduced due to the fast capability of D-FACTS devices to regulate their reactive power in finer granularity. A case study of two meshed IEEE 15-bus feeders is introduced to compare the voltage behavior with and without the presence of DG units and to evaluate the total system losses. The proposed method could be used for the interconnection of the first generation units in emerging networks, which does not yet have an active voltage control strategy, as it could be used for DG units not able to be connected to existing centralized control systems and it could also be used as the principal voltage control strategy, with the extension for several neighboring units and the preservation of the traditional voltage control systems. [ABSTRACT FROM AUTHOR]

This paper presents the development of an accelerated real-time cosimulation and testing platform, especially for long-term simulations of power systems. The platform is planned to be utilized in the development and testing of active network management functions for microgrids and smart grids. Long-term simulations are needed in order to study, for example, the potential weekly, monthly, or yearly usage of distribution-network-connected distributed energy resources for different technical flexibility services. In order to test new algorithms in long-term study cases, real-time simulations or hardware-in-the-loop tests should be accelerated. This paper analyzes the possibilities and challenges of accelerated long-term simulations in studying the potential use of a large-scale wind turbine for reactive power flow control between distribution system operator (DSO) and transmission system operator (TSO) networks. To this end, the reactive power flow control is studied for different voltage levels (HV and MV) in the Sundom Smart Grid in Vaasa, Finland. The control of reactive power flow between HV and MV networks is realized with a reactive power window control algorithm for a 3.6 MW MV-network-connected wind turbine with a full-scale power converter. The behaviour of the reactive power controller during long-term simulations is studied by offline and real-time simulations. Moreover, the real-time simulations are performed with both software-in-the-loop and controller-hardware-in-the-loop. [ABSTRACT FROM AUTHOR]

Summary: Large photovoltaic (PV) penetrations into the electric grid resulted in new challenges such as reverse power flow and violation of voltage profile. The traditional methods for voltage regulation in a grid‐connected PV system are hardly adaptable to these changes as they only contain the local information which is used without the knowledge of how the control action affects the overall system. To address this problem, this paper extends the reactive power control capability of solar PV inverters by combining them with static power electronic devices for regulating voltage during grid faults. For efficient identification of grid faults, a support vector machine‐based fault classification mechanism is developed. The proposed method prioritizes the reactive power control using PV inverter by adapting a predefined hierarchical control structure. The complete methodology is realized by testing it with a two‐stage single‐phase grid‐connected PV system. The experimental results verify the accuracy of the classification algorithm and depict the effectiveness of the proposed controller in both under and overvoltage situations. [ABSTRACT FROM AUTHOR]

Summary: Dynamic voltage restorer (DVR) can preserve a sensitive load against electrical distribution system interruption. After connecting DVR to the system, voltage sag is quickly resolved and no voltage oscillation caused by malfunction of sensitive loads occur. When there is a high voltage sag in distribution or transmission, in order to compensate voltage to the value before fault, both reactive compensation and active power compensation should be performed which requires a DC source in DC link of power quality compensators; if there is only one capacitor in DC link, only reactive power compensation can be performed, as a result significant voltage drops cannot be modified. Distributed generation sources like photovoltaic (PV) can be used as a battery instead of DC link supply of D‐FACTS devices due to DC nature of their output voltage. Performance of DVR in modifying power quality indices depends on performance of its control system. In this paper, a fuzzy adaptive controller is used instead of the conventional PI controller in the control system of the DVR‐PV hybrid compensator to improve its performance in compensating voltage interruption and different types of voltage sag. DVR based on fuzzy controller performs better than DVR based on other controllers like PI. Simulation of electrical distribution system is done in the presence of DVR based on fuzzy‐adaptive control scheme and PV using Matlab/Simulink. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a new configuration of ultracapacitor (UC)‐based energy storage system is proposed aiming applications at higher power level. The configuration can provide active and reactive power support together. The UC is chosen due to its longer life cycle and fast transient response. The UCs are integrated at the DC link of a modular multilevel converter (MMC) through distributed DC‐DC converters. This configuration possesses better features in terms of power quality, modularity, redundancy, and efficiency compared with conventional two‐/three‐level topologies. The integration of ultracapacitors with the MMC and associated control related issues is discussed in this paper. An algorithm to balance the state of charge among the distributed energy storage modules is also proposed. The performance of the proposed system and the associated control methods are verified for a wind energy generation system using PSCAD/EMTDC simulation and the results show satisfactory performance. [ABSTRACT FROM AUTHOR]

The increase in demand for electricity and, in particular, green energy has put renewable energy systems at the focal point of energy policy worldwide. The higher reliability of brushless doubly fed induction generators (BDFIGs) makes them suitable for offshore and remote wind energy generation (WEG) applications. Besides, controlling the active and reactive powers in an electrical power system is critical for optimal voltage regulation, reduced power losses, and enhanced utilization of installed equipment. However, the existing literature on BDFIG's active and reactive power control highlights the poor dynamic response and high transients with harmonic generation during inductive load insertion. It is because the Ziegler technique was employed to select PI gains, and the instantaneous reactive power theory was used to mitigate harmonics. Considering that, this paper proposes a vector control (VC) method for BDFIGs in wind turbines, in which the proportional-integral (PI) gains for internal model control (IMC) are optimized to improve the dynamic response of the active and reactive power during inductive load insertion. The proposed method reduces the complexity, time consumption, and uncertainty in making the optimal choice. In addition, to reduce a double fundamental frequency component to the point-of-common-coupling (PCC) voltage, the excellent characteristics of the notch filter are utilized in the grid-side converter (GSC)-based vector control scheme. The simulation results in MATLAB/Simulink show that the proposed IMC-based vector control scheme with a notch filter provides satisfactory results with a minimum peak value compared to existing techniques. [ABSTRACT FROM AUTHOR]