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A low-cost, open-source peer-to-peer (P2P) energy trading system for a remote community is presented in this paper. As a result of its geographic location, this community has never been able to access electricity and other modern amenities. This study aims to design and implement a P2P energy trading system for this remote community that allows residents to take advantage of distributed energy resources. A Raspberry Pi 4 Model B (Pi4B) hosts the main server of the trading system that includes the user interface and a local Ethereum blockchain server. The Ethereum blockchain is used to deploy smart contracts. The Internet-of-Things (IoT) servers run on ESP32 microcontrollers. Sensors and actuators connected to the ESP32 are field instrumentation devices that facilitate acquiring, monitoring, and transferring energy data in real-time. To perform trading activities, React.JS open-source library was used to develop the blockchain-enabled user interface. An immutable blockchain network keeps track of all transactions. The proposed system runs on a local Wi-Fi network with restricted authorization for system security. Other security measures such as login credentials, private key, firewall, and secret recovery phrases are also considered for information security and data integrity. A Hypertext Transfer Protocol is implemented for communication between the servers and the client. This explains the overall system design, implementation, testing, and results. [ABSTRACT FROM AUTHOR]

Frequency is a useful parameter for ensuring the proper functioning of the power system operation, control, and protection. In this article, a fast and accurate frequency estimator (FE) is developed using a zero crossing and a peak, occurring in the buffered data, unlike the commonly used two zero crossings. Prior to this, the signal is preprocessed using the sliding Goertzel filter (SGF) that mitigates the impact of undesirable features such as harmonics, noise, etc., from the signal. The two FEs, with and without SGF, then work in tandem to form the hybrid estimator and are named as $Z_{C}P_{k}$ - ${{HFE}}$. The estimated frequency is chosen based on the minimum error computed from the two parallel estimators. The performance of the estimator is, then, validated using the simulated signals polluted with harmonics, noise, transients, etc. The article also discusses the protection-oriented applications of the proposed FE in active distribution network (ADN). Moreover, the evaluation results with the real-time field data and the IEEE-13 ADN incorporated with photovoltaic using dSPACE1104 and real-time digital simulator show its capability to estimate the real-time frequency with satisfactory output. [ABSTRACT FROM AUTHOR]

Distributed generation (DG) has environmental as well as economic benefits and develops new concepts to make the power network more effective and minimize pollution in the environment. Being the fluctuation behavior of renewable energy sources (RESs), generation, balance, and demand is not an easy task to control because it is not desirable to have a constant power generation from RESs due to natural prospects. As a result, the dynamic stability of power flow and control of frequency is becoming more challenging due to the high penetration impacts of RESs. In this article, we have proposed a control algorithm with two scenarios for a high-penetration/hybrid diesel wind-based energy storage system to maintain the dynamic stability of power flow and control the frequency in the overall power system. The results show, using an integral–derivative (I–D) controller, the transient time of wind power flow and the fluctuation rate of frequency are reduced significantly compared to the prior research of publication. To regulate the network frequency, a storage system (battery) was used to store the excess energy without throwing it to the secondary/dump load (DL) and minimize the wastage of power produced by the wind turbine. The battery was supplied the excess wind power when there is a high load demand. [ABSTRACT FROM AUTHOR]

Multi-microgrid formation (MMGF) is a promising solution for enhancing power system resilience. This paper proposes a new deep reinforcement learning (RL) based model-free on-line dynamic MMGF scheme. The dynamic MMGF problem is formulated as a Markov decision process, and a complete deep RL framework is specially designed for the topology-transformable micro-grids. In order to reduce the large action space caused by flexible switch operations, a topology transformation method is proposed and an action-decoupling Q-value is applied. Then, a convolutional neural network (CNN) based multi-buffer double deep Q-network (CM-DDQN) is developed to further improve the learning ability of the original DQN method. The proposed deep RL method provides real-time computing to support the on-line dynamic MMGF scheme, and the scheme handles a long-term resilience enhancement problem using an adaptive on-line MMGF to defend changeable conditions. The effectiveness of the proposed method is validated using a 7-bus system and the IEEE 123-bus system. The results show strong learning ability, timely response for varying system conditions and convincing resilience enhancement. [ABSTRACT FROM AUTHOR]

Capacitor Allocation (CA) and Network Reconfiguration (NR) are the traditional methods extensively applied by the researchers for power loss reduction and node voltage improvement in radial Distribution Network (DN) for the past four decades. In recent years, simultaneous optimization of CA and NR is considered to maximize the power loss reduction in a proficient manner in comparison to individual optimization of CA and NR. To solve the objective functions, this work proposes an application of Autonomous Group Particle Swarm Optimization (AGPSO) by optimal allocation and sizing of capacitors with and without NR, under four different cases, subject to satisfying operating constraints. In addition, to ascertain the impact of real power injection on further power loss reduction, this work considers placement and sizing of Distributed Generation (DG) units from single to three optimal nodes in capacitive compensated optimal DN. This proposed methodology is demonstrated using standard IEEE 33 and 69 bus test system and the results obtained by each test case have been compared with other optimization techniques. A significant amount of power loss gets minimized after optimal DG allocation in reactive power compensated optimal DN.

ABSTRAK Peningkatan kebutuhan listrik tanpa ada penambahan sumber listrik yang terus menerus akan mengakibatkan masalah pada voltage stability. Untuk menyelesaikan masalah tersebut dengan penerapan energi terbarukan yang memungkinkan adalah model pembangkit tersebar / Distributed Generation (DG). Penyulang Watu Ulo Jember merupakan penyulang kelistrikan 10,03 KV 75 bus yang bertempat pada Jember bagian selatan dimana potensi energi terbarukan dapat dilakukan. Pada penelitian ini optimasi penempatan DG dengan level penetrasi dilakukan untuk mengetahui kenaikkan pembebanan kelistrikan yang maksimal (loadability) pada penyulang Watu Ulo Jember dengan mempertimbangan faktor perbaikan level tegangan menggunakan algoritma PSO. Penelitian ini diharapkan salah satunya dapat menjadi kajian ilmiah pemerintah kabupaten Jember terhadap potensi pemasangan DG untuk meningkatkan loadability dalam pemenuhan kebutuhan beban pelanggan listrik. Kata kunci: Energi Terbarukan, Pembangkit Tersebar (DG), Loadability, Algoritma PSO, Voltage Stability. Â ABSTRACT The increase in electricity demand without the addition of a continuous power source will cause problems in voltage stability. To solve this problem with the application of renewable energy that is possible is the Distributed Generation (DG) model. The Watu Ulo Jember feeder is a 10.03 KV 75 bus electricity feeder located in the southern part of Jember where the potential for renewable energy can be carried out. In this study, an optimization of DG placement with penetration level was carried out to determine the maximum increase in electrical loading (loadability) on the Watu Ulo Jember feeder by considering the voltage level improvement factor using the PSO algorithm. It is hoped that this research can become a scientific study of the Jember district government on the potential of installing DG to increase loadability in meeting the needs of electricity customers. Keywords: Renewable Energy, Distributed Generation (DG), Loadability, PSO Algorithm, Voltage Stability.

Islanding detection is imperative for the protection of distribution system supported by distributed generation. The accuracy of islanding detection technique mainly depends on the selection of suitable parameter. In this work, the 6 different power system parameters are classified based on sensitivity and performance ability. This is the basic step in the selection of suitable parameter for islanding detection technique. The behavior of different power system parameters is examined using mathematical morphology by considering all possible islanding and non-islanding situations. It has been found, from data interpretation, that dilated reactive power parameter using inclined line structuring element indicates the best competence, among the other parameters, to detect the minute disturbances in power supply. Further, the selection of dilated reactive power parameter is justified mathematically to validate its significance. Moreover, islanding detection technique is proposed consisting of dilated reactive power parameter to distinguish the islanding from other events of similar signatures.

In recent years, due to increase in load demand, distribution networks have got substantial attention to get optimized. It is significant to optimally place the distributed generators (DGs) in distribution networks to minimize power losses and voltage drops. However, the DGs incur certain investment and operational costs, and their placement is only viable if these costs overcome energy losses. Therefore, current paper investigates the optimal sizing and placement of DGs in distribution networks with a novel concept to simultaneously minimize total energy cost along with total power loss and average voltage drop. Artificial bee colony (ABC) algorithm is proposed to solve the considered multi-objective problem. The performance of the proposed ABC algorithm is tested with standard algorithms. Newton Raphson load flow (NRLF) analysis is conducted on IEEE 33 and 69-bus radial networks and on CIGRE medium voltage (MV) benchmark grid. Two test cases have been formed and investigated. The results prove that proposed ABC algorithm mostly outperforms other algorithms.

Highly reliable and flexible control is required for distributed generation (DG) to efficiently connect to the grid. Smart inverters play a key role in the control and integration of DG into the power grid and provide advanced functionalities. In this paper, an energy-based single-phase voltage-source smart inverter (SPV-SSI) of 5 kVA is designed and analyzed in detail. SPV-SSI is capable of supplying the power to local load and the utility load up to the rated capacity of the inverter, injecting the power into the grid, storing the energy in lead-acid battery bank, controlling the voltage at the point of common coupling (PCC) during voltage sags or faults, and making decisions on real-time pricing information obtained from the utility grid through advanced metering. The complete design of smart inverter in dq frame, bi-directional DC-DC buck-boost converter, IEEE standard 1547 based islanding and recloser, and static synchronous compensator (STATCOM) functionalities is presented in this paper. Moreover, adaptive controllers, i.e., fuzzy proportional-integral (F-PI) controller and fuzzy-sliding mode controller (F-SMC) are designed. The performances of F-PI controller and F-SMC are superior, stable, and robust compared with those of conventionally tuned PI controllers for voltage control loop (islanded mode) and current control loop (grid-con-nected mode).

The demand of electricity and environmental issues associated with conventional power generation plants are increasing significantly. Modern technology has transformed the conventional power system through the integration of distributed generation (DG). With the help of modern power electronic technology, the conventional power system is able to support the integration of DGs based on renewable energy sources (RESs). The systematic combination of DGs with energy storage system forms a microgrid (MG), which can operate in islanded mode or grid-connected mode. The intermittent nature of RES and varying load pose substantial obstacles such as voltage and frequency instability, and the unreliability of RES. Unequal feeder impedances and non-linear loads are considered as present challenges in MG control. Hierarchical control has been useful in undertaking solutions to these issues. This paper covers the deep insight of different control methods applied at the primary and secondary control levels in hierarchical control. In primary control, the classification based on droop and non-droop controls is discussed. The virtual synchronization machine (VSM) based control method is reviewed. Voltage and frequency restoration control and economical operations at decentralized and centralized secondary control are analyzed in detail. Based on the existing literature, critical discussion on MG control and future trends are also presented to provide future research perspectives.

The region-based method has been applied in transmission systems and traditional passive distribution systems without power sources. This paper proposes the model of total quadrant security region (TQSR) for active distribution networks (ADN) with high penetration of distributed generation (DG). Firstly, TQSR is defined as a closed set of all the N-1 secure operation points in the state space of ADN. Then, the TQSR is modeled considering the constraints of state space, normal operation and N-1 security criterion. Then, the characteristics of TQSR are observed and analyzed on the test systems with different DG penetrations. TQSR can be located in any quadrant of the state space. For different DG penetrations, the shape and security features of TQSR are also different. Finally, the region map is discovered, which summarizes the features of different types of distribution networks.

Due to the sheer global energy crisis, concerns about fuel exhaustion, electricity shortages, and global warming are becoming increasingly severe. Solar and wind energy, which are clean and renewable, provide solutions to these problems through distributed generators. Microgrids, as an essential interface to connect the power produced by renewable energy resources-based distributed generators to the power system, have become a research hotspot. Modern research in the field of microgrids has focused on the integration of microgrid technology at the load level. Due to the complexity of protection and control of multiple interconnected distributed generators, the traditional power grids are now outmoded. Microgrids are feasible alternatives to the conventional grid since they provide an integrating platform for micro-resources-based distributed generators, storage equipment, loads, and voltage source converters at the user end, all within a compact footprint. A microgrid can be architected to function either in grid-connected or standalone mode, depending upon the generation, integration potential to the main grid, and consumers’ requirements. The amalgamation of distributed energy resources-based microgrids to the conventional power system is giving rise to a new power framework. Nevertheless, the grids’ control, protection, operational stability, and reliability are major concerns. There has yet to be an effective real-time implementation and commercialization of micro-grids. This review article summarizes various concerns associated with microgrids’ technical and economic aspects and challenges, power flow controllers, microgrids’ role in smart grid development, main flaws, and future perspectives.

Increased electric vehicles (EVs) penetration into the distribution network burdens the system during the charging process. But the same turns out to be advantageous if the EVs are used to support the utility based on the requirement. In this work, an attempt is made to efficiently schedule both the grid-to-vehicle and vehicle-to-grid operational modes of EVs with the objective of reducing power loss in the distribution system in presence of distributed generation (DG). The EVs are modeled by considering the dominating factors, such as EV State of Charge (SoC), trip conditions, EV battery capacity, charging/discharging levels. An improvement to the existing grasshopper optimization technique is also suggested in this article, which enhances the exploring capability of the metaheuristic algorithm. The presented methodology is a combination of smart charging method, voltage stability index, and enhanced grasshopper optimization algorithm (EGOA), which decides the size of DGs to be placed in the system. The proposed hybrid approach tries to schedule both the EVs and DGs so as to achieve reduced power loss and improved voltage profile. In order to test the robustness of the proposed strategy, various analyses considering uncertainty in EVs and load conditions are performed. [ABSTRACT FROM AUTHOR]

The decentralized economic scheduling of multimicrogrid is an important aspect in the operational planning of microgrids (MGs). This article proposes an approach to maximize economic benefit among MGs through cooperative scheduling. The cooperative scheduling is achieved via price signals so that MGs are encouraged to share power among themselves for economic benefit. An MG operator generates a time-variable tariff based on energy trading status so that the parking lot operator and distributed battery energy storage system aggregator participate with flexibility in the MG’s energy management. The Shapley value method is used for generating fair price signals. The stochastic Dantzig–Wolfe decomposition is used to solve the resulting optimization problem in a decentralized manner. The uncertainties related to load demand and renewable energy sources are captured using scenario-based methods, whereas the uncertainty associated with plug-in hybrid electric vehicles is modeled using copula theory based estimation. The simulation studies and comparison with the existing methods establish that the proposed approach effectively reduces the total energy cost in a decentralized manner with the minimum amount of information exchange. [ABSTRACT FROM AUTHOR]

In case of high-impact low-probability events, in order to restore the critical loads of the distribution network as much as possible, it is necessary to employ all available resources such as microgrids and distributed generations. This article presents a two-stage method for critical load restoration after an extreme event utilizing the coordination of all available distributed generations, microgrids, and demand response programs. In the first stage, the postdisaster reconfiguration of the network is determined, and in the second stage, the demand response outputs of the responsive loads and the restoration status of all critical loads are ascertained. In the first stage, an algorithm is proposed to determine electrical islands, and in the second stage, a new model based on the generalized Benders decomposition algorithm is proposed, which considers demand response programs and all operational constraints and aims to maximize the restored critical loads. The effectiveness of the proposed method is verified by simulating the 33- and 69-bus test systems. [ABSTRACT FROM AUTHOR]

With increased penetration of renewable power and the nonlinear loads in the distributed generation (DG) systems, increased power quality concerns are exhibited in the active distribution networks, especially the challenges associated with the current and voltage harmonics in the system. Various conventional harmonic compensation techniques are developed for voltage-controlled DG inverters in past, majority involve either multiple proportional-integral (PI) or proportional-resonant (PR) controllers in eliminating grid current harmonics. The current-controlled inverters, on the other hand, are not preferred in industrial applications, accounting to their wide variations in the switching frequency. A novel and adaptive harmonic voltage control is developed here, for voltage-controlled DG inverters, which neither uses any PI regulators nor imposes stability issues associated with nonideal implementation of infinite gains of PR controllers. Interestingly, the developed control logic can be used for DG inverters, both in grid-connected and off-grid operational modes. Furthermore, this strategy allows a network operator to use this as an additional supplement that can be enabled/disabled as per the network requirement. The control logic exploits the property of an optimal-switching-vector controller, i.e., accurate output voltage tracking. Simulations results demonstrate the effectiveness of the controller, to suppress grid current harmonics and load voltage harmonics in grid-interfaced (GI) and off-grid modes, respectively, ultimately satisfying the mandatory IEEE standard-1547. Experimental results verify the viability of the controller for practical applications. [ABSTRACT FROM AUTHOR]

In conventional low-voltage grids, energy-storage devices are mainly driven by final consumers to correct peak consumption or to protect against sources of short-term breaks. With the advent of microgrids and the development of energy-storage systems, the use of this equipment has steadily increased. Distributed generations (DGs), including wind-power plants as a renewable energy source, produces vacillator power due to the nature of variable wind. Microgrids have output power fluctuations, which can cause devastating effects such as frequency fluctuations. Storage can be used to fix this problem. In this paper, a grid-connected wind turbine and a photovoltaic system are investigated considering the atmospheric conditions and wind-speed variations, and a control method is proposed. The main purpose of this paper is to optimize the capacity of energy-storage devices to eliminate power fluctuations in the microgrid. Finally, the conclusion shows that, in microgrids with supercapacitors, the optimal capacity of microgrid supercapacitors is determined. This method of control, utilizing the combined energy-storage system of the battery supercapacitor, in addition to reducing the active power volatility of the wind turbine and photovoltaic generation systems, also considers the level of battery protection and reduction in reactive-power fluctuations. In the proposed control system, the DC link in the energy-storage systems is separate from most of the work conducted, which can increase the reliability of the whole system. The simulations of the studied system are performed in a MATLAB software environment. [ABSTRACT FROM AUTHOR]

Islanding detection and prevention are involved in tandem with the rise of large- and small-scale distribution grids. To detect islanded buses, either the voltage or the frequency variation has been considered in the literature. A modified passive islanding detection strategy that coordinates the V-F (voltage–frequency) index was developed to reduce the non-detection zones (NDZs), and an islanding operation is proposed in this article. Voltage and frequency were measured at each bus to check the violation limits by implementing the proposed strategy. The power mismatch was alleviated in the identified islands by installing a battery and a diesel generator, which prevented islanding events. The proposed strategy was studied on the three distinct IEEE radial bus distribution systems, namely, 33-, 69-, and 118-bus systems. The results obtained in the above-mentioned IEEE bus systems were promising when the proposed strategy was implemented. The results of the proposed strategy were compared with those of methods developed in the recent literature. As a result, the detection time and number of islanded buses are reduced. [ABSTRACT FROM AUTHOR]

The power systems are transitioning to renewables. The power system infrastructure digitalization is the next stage in this evolution. A digitalized future distribution network (DN) has an opportunity to evolve into real-time analysis based on a huge volume of data. Such real-time analysis will be feasible through the integration of the theoretical background of fault analysis and machine learning techniques. Fault location is one of the major issues to improve reliability indices. The voltage sags characterization is used to locate faults in the DN. This article presents a methodology to characterize voltage sags using fault analysis and deep convolutional neural networks. The voltage divider model allows the characterization and the discrete wavelet transform is used in signal processing. The machine learning and deep learning models used allow estimating the sag magnitude, fault location, phases involved, duration, and impact of distributed generation (DG) in each event. The IEEE 13-node test feeder including DG was used to validate the effectiveness of the proposed methodology. This paper provides a way to handle a Big Data stream in the DN control center and to efficiently locate faults in several operational scenarios. [ABSTRACT FROM AUTHOR]

This paper presents a simulated analysis for the first time using the MATLAB Simulink tool prototype model to find the best configuration of the Superconducting Fault Current Limiter (SFCL) Impedance method. The goal here is to maintain the short circuit current within the circuit breaker's power. To improve the reliability of the power system, various forms of decentralized generation plants (DGP) can be connected to the traditional electric grid (PS). Interconnected Decentralized Generation (DG) to an existing electric system provides a variety of benefits, including increased distribution system reliability, enhanced power quality, and decreased short circuit current, which can damage protective equipment. Since it gives virtually zero resistance in a steady-state, the Superconducting Fault Current Limiter (SFCL) is an ideal technology for reducing the magnitude of fault current (FC) in PS. Finally, the SFCL technique was used in the conventional grid interconnected with the wind farm to determine its optimal location in the smart grid (SG) with DG. However, we investigate the best location for SFCL in the smart grid, and our findings show that SFCL at the integrating point is the right alternative. [ABSTRACT FROM AUTHOR]

Renewable energy resources are deemed a potential energy production source due to their cost efficiency and harmless reaction to the environment, unlike non-renewable energy resources. However, they often fail to meet energy requirements in unfavorable weather conditions. The concept of Hybrid renewable energy resources addresses this issue by integrating both renewable and non-renewable energy resources to meet the required energy load. In this paper, an intelligent cost optimization algorithm is proposed to maximize the use of renewable energy resources and minimum utilization of non-renewable energy resources to meet the energy requirement for a nanogrid infrastructure. An actual data set comprising information about the load and demand of utility grids is used to evaluate the performance of the proposed nanogrid energy management system. The objective function is formulated to manage the nanogrid operation and implemented using a variant of Particle Swarm Optimization (PSO) named recurrent PSO (rPSO). Firstly, rPSO algorithm minimizes the installation cost for nanogrid. Thereafter, the proposed NEMS ensures cost efficiency for the post-installation period by providing a daily operational plan and optimizing renewable resources. State-of-the-art optimization models, including Genetic Algorithm (GA), bat and different Mathematical Programming Language (AMPL) solvers, are used to evaluate the model. The study's outcomes suggest that the proposed work significantly reduces the use of diesel generators and fosters the use of renewable energy resources and beneficiates the eco-friendly environment. [ABSTRACT FROM AUTHOR]

This paper concentrates on the impacts of distributed generation (DG) placement on the radial distribution system. Distributed generation is a term that refers to the generation of energy close to the point of consumption, in order to improve the performance of the electricity grid. It is a well proven fact that if the DGs units are placed in the right place in the distribution system and operating at optimal size, it will help in reducing the line losses and improving the voltage profile and as a consequence the reliability, stability and efficiency of the electrical system are preserved. In this paper, three types of DG units are considered and both Moth-flame optimization (MFO) and Grasshopper optimization (GOA) are applied to find the optimal DG sizing for a typical radial distribution system (IEEE-85 bus radial distribution test systems). The required location of the DG unit bus is selected using the index vector method (IVM) and the voltage stability index (VSI). The obtained results show that the two algorithms produce very same values. The best result in loss reduction and minimum bus voltage is attained for the DG unit at a power factor of 0.93 when compared to other DG types. However, this requires a large DG versus the other types. [ABSTRACT FROM AUTHOR]

Using distributed generations (DGs) with optimal scheduling and optimal distribution feeder reconfiguration (DFR) are two aspects that can improve efficiency as well as technical and economic features of microgrids (MGs). This work presents a stochastic copula scenario-based framework to jointly carry out optimal scheduling of DGs and DFR. This framework takes into account non-dispatchable and dispatchable DGs. In this paper, the dispatchable DG is a fuel cell unit and the non-dispatchable DGs with stochastic generation are wind turbines and photovoltaic cells. The uncertainties of wind turbine and photovoltaic generations, as well as electrical demand, are formulated by a copula-based method. The generation of scenarios is carried out by the scenario tree method and representative scenarios are nominated with scenario reduction techniques. To obtain a weighted solution among the various solutions made by several scenarios, the average stochastic output (ASO) index is used. The objective functions are minimization of the operational cost of the MG, minimization of active power loss, maximization of voltage stability index, and minimization of emissions. The best-compromised solution is then chosen by using the fuzzy technique. The capability of the proposed model is investigated on a 33-bus MG. The simulation results show the efficiency of the proposed model to optimize objective functions, while the constraints are satisfied.

Line losses are the most significant challenge faced by Pakistan's energy department. 6.5% of the country's GDP, a large figure of $1.8 billion is lost every year due to line losses in power generation, transmission, distribution and consumption. In distribution systems, researchers are attracted by the penetration of distributed generation (DG) nowadays. The performance of a distribution network is affected by the significant role of number, capacity and situation of DG units. This study will focus on the distributed generation of a centralized national grid and provide an algorithmic model that implements Improved Particle Swarm Optimization to reduce the system power loss and improve the voltage profiles via optimization of the locations and sizes of multip1le DG(s). The overall sensitive feature was determined and utilized efficiently to reduce research space for the algorithm. In the case of IEEE 33Bus test system, 10% of candidate buses are selected as possible DG situations. The IPSO methodology produced severe loss reduction and improve the voltage profiles in all the three types of DGs considered using the IEEE 33-Bus system. The percentage decrease in active power losses was reduced 68.10492%, 66.91669% and 58.89211% for DG type -1, DG type-2 and DG type-3 respectively. At the same time, reactive power losses were reduced 53.095%, 53.0922% and 50.4145% for DG type -1, DG type-2 and DG type-3 respectively.

Regarding the advances in technology and anxieties around high and growing prices of fossil fuels, government incentives increase to produce cleaner and sustainable energy through distributed generations. This makes trends in the using microgrids which consist of electric demands and different distributed generations and energy storage systems. The optimum operation of microgrids with considering demand-side management increases efficiency and reliability and maximize the advantages of using distributed generations. In this paper, the optimal operation scheduling and unit commitment of generation units installed in a microgrid are investigated. The microgrid consists of technologies based on natural gas that are microturbine and phosphoric acid fuel cell and technologies based on renewable energy, including wind turbine and photovoltaic unit along with battery energy storage system and plug-in electric vehicle commercial parking lot. The goal of the paper is to solve a multi-objective problem of maximizing revenues of microgrid operator and minimizing emissions. This paper uses an augmented epsilon constraint method for solving the multi-objective problem in a stochastic framework and also implements a fuzzy-based decision-maker for choosing the suitable optimal solution amid Pareto front solutions. This new model implements the three type of the price-based and incentive-based demand response program. It also considers the generation reserve in order to enhance the flexibility of operations. The presented model is tested on a microgrid and the results demonstrate the efficacy of the proposed model economically and environmentally compared to other methods.

In response to the rapid changes in the international energy environment, developing renewable energy (RE)-based distributed generation (DG) and various smart micro-grid systems is crucial for creating a robust electric power grid and new energy industries. In this aspect, there is an urgent need to develop hybrid power systems suitable for coexistent AC and DC power grids, integrated by high-performance wide ban gap (WBG) semiconductor-based power conversion interfaces and advanced operating and control strategies. Due to the intrinsic feature of variation in RE-based power generation, the design and integration of energy storage devices, real-time regulation of power flow, and intelligent energy control schemes are key technologies for further promoting DG systems and micro-grids. This paper investigates an integrated control scheme for multiple GaN-based power converters in a small- to medium-capacity, grid-connected, and RE-based power system. This is the first time that a complete design case demonstrating three GaN-based power converters with different control functions integrated with a single digital signal processor (DSP) chip to achieve a reliable, flexible, cost effective, and multifunctional power interface for renewable power generation systems is presented. The system studied includes a photovoltaic (PV) generation unit, a battery energy storage unit, a grid-connected single-phase inverter, and a power grid. Based on system operation condition and the state of charge (SOC) of the energy storage unit, two typical operating modes and advanced power control functions are developed with a fully digital and coordinated control scheme. Hardware of the GaN-based power converters and digital controllers are designed and implemented. The feasibility and effectiveness of the designed controllers and overall performance of the proposed control scheme are verified with results from simulation and experimental tests on a 1-kVA small-scale hardware system.

This work presents and discusses the application of power electronics for the integration of several distributed generation sources, as well as those related to it, the microgrids and the smart grids, to the power sector. Trends and challenges are addressed for the area of study and an embracing overview of the main technologies and techniques is presented for future investigation. As there are many power electronics devices available for employment, in each one of these crucial, modern, sustainable electrical systems, it is important for students, researchers and professionals to understand and compare the state of the art of them all, for the right choice in their respective uses. These apparatuses not only allow grid matching, but also provide new functions that enhance these artifacts' operations, and of the entire power system. Thus, in this paper, the relationship between power electronics and distributed generation is detailed, with the role and classification of each static converter for the improved operation of wind power, photovoltaic systems, fuel cells, small hydro and microturbines exposed. While the first two are more widely covered in the literature, the last three are rarely discussed and differentiated, in terms of their power electronics interfaces. Then, the same is made for microgrids and smart grids, also scarcely approached in other works, with regard to the characteristics of the power converters applied, confirming their superior performances with the use of power electronics. Finally, conclusions are given. [ABSTRACT FROM AUTHOR]

This manuscript presents a novel control architecture for the E-STATCOM (STATCOM integrated with Energy Storage System (ESS)) that is common for both the Stand-Alone (SA) as well as the Grid-Connected (GC) modes of operation of a microgrid operating under unbalanced conditions. The proposed control architecture fulfils the aim of regulating the E-STATCOM in such a manner so as to smoothen the power fluctuations of a nearby renewable energy source (solar, wind, etc) and also to maintain the voltage and frequency at the Point of Common Coupling (PCC) within the normal range of operation. Hence, the resultant real power injected by the renewable energy source along with the E-STATCOM is constant in magnitude, irrespective of whether the microgrid is in the GC or the SA mode of operation. Dynamically varying limits are introduced to provide inherent VSC over-current protection. In order to illustrate the performance of these control architectures, a model of the IEEE 34 node power distribution network that is being supplied by a solar Photo-Voltaic (PV) Distributed Generation (DG) unit, a wind DG unit and two identical E-STATCOMs (for compensating the power fluctuations from the PV and wind DG units) has been considered for study in PSCAD/EMTDC. [ABSTRACT FROM AUTHOR]

Most of the generated electricity is lost in power loss while transmitting and distributing it to the consumer end. The power losses occurring in the distribution network cause deviation in voltage and lower stability due to increased load demand. The integration of multiple Distributed Generation (DG) will enable the existing radial electrical distribution network efficient by minimizing the power losses and improving the voltage profile. Metaheuristic optimization techniques provide a favorable solution for optimal location and sizing of DG in the distribution network. A novel modern metaheuristic Transient Search Optimization (TSO) algorithm, inspired by the electrical network's transient response of storage components implemented in the proposed work. The TSO formulated optimal DGs allocation to minimize total active power loss, voltage deviation and enhance voltage stability index as minimization optimization problem satisfying various equality and inequality constraints. The installation of multiple DG units at unity, fixed, and optimal power factors were examined. The TSO algorithm's effectiveness was tested on standard IEEE 33-bus and 69-bus radial distribution networks, including various operating events developed in the form of single and multi-objective fitness functions. The active power loss reduced to 94.29 and 94.71% for IEEE 33 and 69 bus distribution systems. The obtained results trustworthiness is confirmed by comparison with well-known optimization methods like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), combined GA/PSO, Teaching Learning Based Algorithm (TLBO), Swine influenza model-based optimization with quarantine (SIMBO-Q), Multi-Objective Harris Hawks optimizer (MOHHO) and other provided in the literature. The presented numerical studies represent the usefulness and out-performance of the proposed TSO algorithm due to its exploration and exploitation optimization mechanisms for the DG allocation problem meticulously. [ABSTRACT FROM AUTHOR]

In this article, a novel pulsewidth modulation (PWM) technique is proposed for an existing space vector hysteresis current controller (SVHCC) scheme. A three-level neutral-point-clamped (NPC) inverter is used for dual purpose of shunt active power filtering and solar photovoltaic (PV) power integration to a distribution grid. This dual-purpose NPC inverter utilizes the proposed PWM technique for solving the neutral-point voltage-balancing issue in a unique way. Due to the inherent advantages of the SVHCC, the current control is characterized by fast action and optimal switching. A single reference current required for both filtering and maximum PV power integration is generated using instantaneous power theory, where a diode bridge rectifier load is considered to demonstrate the controller performance while compensating nonlinear current components. Thus, not only a unique space-vector-based PWM technique is adopted for fast-tracking of currents, but also a sliding current error boundary is used for the first time. This sliding technique tackles the dc-link balance issue of the NPC inverter while controlling the output currents simultaneously. The simulation and hardware results prove the aforementioned performance and demonstrate the efficacy of the proposed PWM current controller. [ABSTRACT FROM AUTHOR]

This paper presents a novel and efficient optimization approach based on the Artificial Ecosystem Optimization (AEO) algorithm to solve the problem of finding optimal location and sizing of Distributed Generation (DGs) in radial distribution systems. The objective is to satisfy a fluctuating demand in a constant and instantaneous way while respecting the requirements of power loss reduction, operating cost minimization and voltage profile improvement within the equality and inequality constraints. The robustness of the proposed technique in terms of solution quality and convergence characteristics is evaluated using the IEEE-33 bus radial distribution network test system. The simulation results are compared with those of other methods recently used in the literature for the same test system. The experimental outcomes show that the proposed AEO approach is comparatively able to achieve a higher quality solution within a timeliness of computation. [ABSTRACT FROM AUTHOR]

Grid frequency variation causes phase angle deviation in current with respect to voltage. This is sensed at the phase-locked loop in the controller. In past studies the effect of grid frequency variation is neglected while designing the controller for power quality restoration. When modern grids are connected to large numbers of non-linear loads and various types of distributed generation (DG), it results in continuous variation in grid frequency. Thus it is necessary to consider the grid frequency variation for effective power quality restoration. However, tuning of conventional PI controller gains considering frequency variation is very difficult. Thus it is necessary to develop an adaptive intelligent nonlinear controller to tackle the effects of frequency variation, voltage distortion and non-linear load simultaneously. This paper presents the importance of considering the effects of the frequency variation, grid voltage distortion and non-linear load, while designing and deploying a controller for power quality restoration. The proposed controller supplies power to local load as well as transferring surplus power to the grid from DG along with the additional benefit of improving grid power quality. A DG with an ANFIS optimized PI current controller for power quality enhancement is proposed. The method is economical as it requires no additional hardware. Results are compared with PI, PI-RC and fuzzy current controllers to validate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

In the hilly regions of India, hydro power potential is available, but it is not completely utilized for power generation till date due to the unavailability of proper electrical structure. Nine micro/mini hydro power plants have been developed in the bageswar district in Uttarakhand. The development of the optimized Mini-grid structure is an effective and reliable solution for the full utilization of these MHPs potentials. Although Ajit Singh et al. proposed some Mini-grid structures for this area, their work is not appropriate due to their calculation method of reliability. For the determination of reliability (failure and repair time), they have considered only the line length. However, its demographic situations such as elevation level of MHPs, availability of roads, the presence of obstacles like streams will also affect the failure and repair time. This paper proposes an optimized Mini-grid structure for interconnection of these nine MHPs and load substations. All the MHPs are spreads in two blocks, namely Kapkote and Bagheswar, so two substations (load canters) are considered. These MHPs and substations are mapped through the Google Earth software and the optimization data such as distances between MHPs and substations, their elevation levels, the highest and lowest elevation in the connecting path and the path profile are collected through it. The Mini-grid structure is optimized through the Genetic Algorithm using the MATLAB tool. The optimization is performed by making the cost function as an objective function considering the line lengths and reliability of the path for its parameters. [ABSTRACT FROM AUTHOR]

Due to decarbonisation and decentralisation of energy sectors, the rise of distributed generation (DG) will modify generation and demand patterns at grid supply points (GSPs), where the interface between distribution and transmission systems takes place. With the increasing penetration of such devices, methodologies able to evaluate its contribution to both local distribution network and transmission system become crucial. This article proposes an analytical method to evaluate the DG locational incremental contribution (LIC) to the interface with the transmission grid. Accordingly, the original model of the U.K. engineering recommendation P2 is enhanced by studying the impacts from high-voltage distribution networks (i.e., ≤ 132 kV) under normal and contingent conditions. This approach enables a more accurate network security assessment, especially when considering contingencies such as distribution system faults. To illustrate the proposed method, the original P2 model is compared against different enhanced approaches on three basic distribution networks, followed by a case study and a sensitivity analysis on a revised IEEE 14-bus GSP system. The proposed LIC method produces results that assess a wider range of conditions including DG penetration, concentration, and system reliability. Furthermore, it provides an increased DG visibility for transmission planning and operation. [ABSTRACT FROM AUTHOR]

In this article, a novel hybrid voltage/current control scheme with low-communication burden is proposed for series-type inverters in a decentralized manner. All the inverter units are controlled by their individual local controllers without a real-time central global-communication. Among them, a few inverters serve as the current controlled inverters (CCIs) to regulate the grid current, and the rest inverters work as the voltage controlled inverters (VCIs). Under this control architecture, five main control targets are achieved: 1) frequency self-synchronization of each VCI inverter based on local current phase-angle signals; 2) fault-tolerant capability of all inverters without one-to-all-failure; 3) high disturbance-rejection-capability to grid variations; 4) adjustable grid power factor; and 5) independent power control for inverters with unbalanced power sources. As the central high-bandwidth communication is avoided, it has the features of decreased cost, increased scalability, and reduced geographic restrictions of inverters. Compared with conventional decentralized approaches, only a few CCI units acquire the grid phase-angle signal to achieve grid synchronization by communication, and the most VCI units are local self-synchronization via the local line-current-phase signal rather than real-time grid-voltage-phase communication signal. Thus, the proposed control can be realized with a very low-communication burden, which is more cost-effective and higher reliability in terms of communication faults. The feasibility of the proposed method is verified by experimental results of eight different cases, such as source power change, large power gap, grid voltage/frequency deviation, grid harmonics, and one-fault redundancy. [ABSTRACT FROM AUTHOR]

Less energy consumption and more efficient use of renewables are among the sustainable energy targets of modern societies. The essential activities to be achieved under these objectives are to increase distributed generation (DG) structures’ applicability. DG systems are small-scale versions of the traditional power grid; they are supported by micro turbines, photovoltaics (PV) modules, hydrogen fuel cells, wind turbines, combined heat and power systems, and energy storage units. The aim of this research is to detail the performance analysis of a proton-exchange membrane fuel cell (PEMFC)-based grid-connected distributed generation system with the help of empirical calculations. To this end, we aimed to establish the system and analyze the performance of the reliable operation of the system with experimental verifications. The findings demonstrate how much power can be generated annually, through real meteorological data, to dispatch to constantly variable loads. While 53.56% of the total energy demand is met by the utility grid, 46.44% of the demand is met by the produced energy i.e., from the DG. The PEMFC-based DG system analyzed in detail in this study was located at Marmara University. According to the results of the performance analysis, significant points of this study will be highlighted to assist the researchers working in this field. Our results are encouraging and can be certified by a larger sample size with neat weather conditions in terms of the percentage of procurement of energy.

Because of the worldwide trend of microgrid (MG) and renewable energy (RE)-based distributed power generation (DG), advanced power flow control schemes with wide bandgap (WBG) semiconductor technologies to ensure high-level performance of grid-connected MGs is one of the crucial research topics. In grid-connected MGs, a static switch (SS) is commonly used at the point of common coupling (PCC) of two systems. In this paper, the role of SS is replaced by a SiC-based three-phase back-to-back (BTB) inverter system for seamless switching between grid-connected and standalone modes through advanced power flow control schemes. According to scenarios of different grid/load conditions and available DG capacities in an MG, various advanced control functions can be developed for both MG operating modes: bidirectional control of active and reactive power flows, seamless switching between operating modes, improvement of grid power quality (PQ), and voltage stabilization. In this paper, mathematical models of the BTB inverter in a synchronous reference frame (SRF) is first derived, and the required controllers are then designed. For functional testing, two typical cases are simulated and analyzed in a MATLAB/Simulink environment and then verified through 1kVA small-scale hardware implementation with Texas Instruments (TI) digital signal processor (DSP) TMS320LF2812 as the control core. Results show satisfactory performances of power flow control and PQ improvement of MG.

Summary: The purpose of this paper is to present a model for optimal placement of distributed generation units and sectionalizing switches (relocation of the existing switches and installation of new ones) to increase distribution network resilience against the threat of transmission system outage. The proposed model is formulated as a multi‐objective optimization problem with the objectives of minimizing investment costs and maximizing load restoration. In this regard, distribution system operation during normal conditions as well as transmission system outages is considered. In addition, the unique characteristics of the real power grid in Khuzestan province in southwestern of Iran are addressed in the proposed model which makes the model applicable to the real networks with similar characteristics in many parts of the Middle East. This grid has two completely different load patterns (in terms of load curve shape and peak load) corresponding to two hot and temperate periods, which causes completely different concerns for the network's operator. The proposed model is solved using multi‐objective genetic algorithm (NSGA‐II), and it is implemented on the 33‐node test system and the results are analyzed. Moreover, it is applied to the 327‐node real‐world test system in Khuzestan province to demonstrate its applicability to large networks. In both cases, the results confirm the effectiveness of the proposed optimization model. [ABSTRACT FROM AUTHOR]

The reactive power control (RPC) technique is a hopeful solution for the islanding issue in distributed generation (DG). Existing RPC approaches have downsides of inhibiting the required load reactive power or injecting/drawing undesirable excessive reactive power into the utility during normal operation. To overcome these limitations, the positive sequence voltage of point common coupling (PCC) is included in the reference of reactive power, which helps the frequency to deviate rapidly outside its thresholds. Further, power system transients which considered normal events can drift the frequency and result in a false islanding detection. In this article, different operating conditions such as load switching, voltage variations, and faults are considered. To address this issue, the suggested strategy includes a second decision-making criterion based on the discrete wavelet transform of the subtraction of sensed and nominal positive sequences of the PCC voltage. Simulation and experimental findings show that the suggested islanding detection method detects islanding rapidly and with zero nondetection zone. Furthermore, the DG and load reactive powers are closely matched under normal operation, and nonislanding situations are successfully prevented. [ABSTRACT FROM AUTHOR]

A compact interlinking converter modular (ICM) for hybrid ac/dc microgrids with a distributed storage (DS) bus for storage integration is proposed in this article. The advanced ICM for hybrid ac/dc/ds microgrids involves the nine-switch topology with compact configuration and decreased number of active operating switches, which structurally equivalents to afford a dc interconnection port for dc subgrid, an ac interconnection port for ac subgrid, a ds interconnection port for ds subgrid, and two dc–dc converters for the interconnection ports for parallel DSs. In addition to the popular advantage of component elements saving, the suggested ICM, aggregating various interlinking converter cells (ICCs) into an ICM, is also proficient of participating computations from all ICC sensors to enhance the overall modular performance without building extra communication connection links between ICCs. With this in mind, a decentralized power management control strategy is realized by employing a coordination power control methodology to systematically handle various distributed generations (DGs), DSs, and ICM in a decentralized manner with improved communication fault ride-through capability. The controller hardware-in-the-loop experiments on a real-time digital simulator platform validates the achievement of the advanced ICM application in hybrid ac/dc/ds microgrids and the effectiveness of the associated decentralized power management scheme. [ABSTRACT FROM AUTHOR]

In this article, a hybrid connected unified power quality conditioner integrating distributed generation (HCUPQC-DG) is proposed. Two dc ports are created at the dc link of the HCUPQC-DG, in which one low-voltage (LV) dc port is directly connected to distributed generation (DG), and the other high-voltage (HV) dc port is indirectly connected to DG through the front-end dc–dc converter. With the hybrid connected configuration, the HV is designed to ensure the dc–ac voltage conversion capability, whereas the LV, i.e., the voltage of DG, can be relatively low and vary in a wide range. Besides, most active power can be directly transferred from DG to the ac load or grid through the direct power flow path. Hence, the conversion efficiency is enhanced, and the power capacity of the front-end dc–dc converter is significantly reduced. The operating principle and the control and modulation strategies of the proposed HCUPQC-DG are discussed. Moreover, the power flow through the HCUPQC-DG is analyzed in detail to understand the system operation. Experimental results with a 3-kVA prototype are provided to verify the feasibility and effectiveness of the proposed HCUPQC-DG. [ABSTRACT FROM AUTHOR]

This article presents a new mathematical model to solve the restoration problem in balanced distribution systems with distributed generators (DGs) considering closed-loop topology operation during the restorative state. The restorative state is comprised of the interval of time since the permanent fault has been isolated until the time at which the faulted zone is repaired. During this interval of time, switching operations are performed to minimize the negative effects resulting from the occurrence of a permanent fault in the network. In this way, the two main objective functions of the restoration problem are to minimize the amount of load curtailment in the restored system and to minimize the number of switching operations. Conventionally, the network topology is maintained radial throughout the restorative state. In this article, the possibility of forming loops is considered for improving both objective functions. As such, a new mixed-integer second-order cone programming model is proposed, considering the temporary formation of operational loops in the restorative state, and both connected and islanded operation of the DGs. Several tests are carried out using a 53-node test system and a 2313-node system for single and multiple fault scenarios. The results obtained with the proposed model outperform the solutions achieved when only open-loop configurations are considered for the restoration problem. Moreover, it is verified that the islanded operation of the DGs provides more flexibility to the network, allowing more load to be restored. [ABSTRACT FROM AUTHOR]

In order to compensate voltage unbalance at the point of common coupling (PCC) for the islanded microgrid, a novel strategy based on PCC negative‐sequence voltage feedforward is proposed. Through the PCC negative‐sequence voltage feedforward, a virtual voltage source is added to the DG terminal at the negative‐sequence. Then, the effective impedance between the distributed generation (DG) unit and the PCC can be reduced proportionally to the compensation coefficient, thereby reducing the unbalanced voltage caused by the unbalanced load. On this basis, an adaptive mechanism of the compensation coefficient is proposed to achieve compensation effort equalization among parallel DGs. Different from the widely adopted virtual impedance method, the additional unbalanced voltage droop (caused by the virtual impedance) can be avoided. In addition, the H∞ repetitive controller is designed to obtain good voltage control performance for the parallel operation. Finally, microgrid simulations are provided to demonstrate the effectiveness of the proposed control strategy. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper presents the Stud krill herd algorithm (SKHA) implementation to find the optimal location and sizing of DG units in a radial distribution system. In recent years, distributed generation (DG) plays an important role in the electric power industry. DG units are connected to the system mainly for improving voltage stability, real power loss reduction, reliability, grid strengthening, and reduction of SO2, CO2 gas emission. The problem formulation is based on the multi-objective function. This work focuses on real power loss reduction, cost minimization, and improvement of voltage stability and formulates a single objective function with suitable weightage preference subject to various constraints like voltage limit, DG real power limit, power balance constraint, and DG location limit. The algorithm has been tested on IEEE 33 bus, 69 bus, and 94 bus radial systems at different load levels with DG placement. The obtained simulation results are compared with other methods. The comparison reveals that the proposed algorithm offers a better solution for the optimal placement of DG in the radial distribution system with faster convergence. [ABSTRACT FROM AUTHOR]