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In this paper, an AC/DC microgrid is proposed to reduce processes of multiple reverse conversions in the AC or DC microgrids and to facilitate the connection of the AC and DC energy resources and loads. Beside, according to the research the control of the voltage and frequency is a very important issue in the microgrids. Therefore, control schemes studied in this paper, are developed and published in order to improve the voltage and frequency stability of the microgrid operated in the stand-alone (islanded) mode. Results are achieved considering short-circuit fault and the uncertainty of the generators and loads verifying the correctness, accuracy and robustness of the controllers to stabilize and restore quickly the voltage and frequency of the proposed microgrid due to these disturbances.

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Microgrids are a new generation of power systems in small scale, which can fulfils the power requirements of their customers independently from the main power system. One of the characteristics of these systems is their ability to integrate distributed generation units with renewable energy sources, which are inherently probabilistic and intermittent. This, highlights the necessity of studying the reliability of the microgrid to make sure that enough reliability is maintained, and if necessary, to take measures to improve the reliability. In this paper, using the probabilistic methods, it is tried to optimize the combination of distributed generation units and electric vehicles with the goal of improving the reliability of the microgrid. Optimization of a combination of generating units along with electric vehicles to improve the reliability of microgrid, presenting a new method in charge and discharge plans for electric vehicles, and probabilistic modeling of the power injected to the microgrid are amongst the contributions of the present paper.

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In this paper a new power sharing control method is proposed for islanding microgrids. With regard to low dynamic distributed generators like fuel cells, microgrid capability is enhanced to face the different load scenarios. In the new method there is not the need for energy storage devices like batteries and super capacitors in coordination with low dynamic energy resources. So the productivity of the installed capacity is enhanced. Any change in the load is automatically detected by the proposed method and the controller manages the dynamic distributed generator power in its transient time. Back to back voltage and current controllers are also embedded beside power controller to enhance the transient stability of the microgrid in sudden load changes. In order to evaluate the new method, a sample microgrid is considered. Simulation results show the proper power sharing among the generators while satisfying the frequency stability of the system. Technical and economical comparison show the effectiveness of the proposed power sharing method with respect to the conventional methods.

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In this paper, we propose a general framework to study the impact of contractual agreement between hybrid system and microgrid on hybrid system profit composed of wind farm, photovoltaic and pump-storage hybrid system considering uncertainties. The proposed method is concerned with optimal scheduling of pump-storage hybrid system, aiming to maximize the hybrid system profit under frequency based pricing for a day ahead electricity market. The pump-storage hydro plant is utilized to minimize unscheduled interchange flow and maximize the system benefit by participating in frequency control based on energy price. Because of uncertainties in power generation of renewable sources, generation scheduling is modeled by a stochastic optimization problem. In order to verify the efficiency of the method, the algorithm is applied for various scenarios with different wind and photovoltaic power cases in a day ahead electricity market. The numerical results demonstrate the effectiveness of the proposed approach.

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Using of DFIG-Based wind turbine in distribution network is increasing day by day. Despite different advantages of DFIG such as ease controllability, low cost and ability to work in different wind speeds, they are very sensitive to the grid voltage drop and when a fault occurs, the rotor current is increased and this may leads to damage the DFIG power electronics converters. Also, voltage swell caused by large loads switching off, large capacitor banks energizing and unbalanced faults may damage the DFIG converters. Dou to necessity of compliance of grid codes, a novel approach is proposed in this paper to improve the low voltage ride through (LVRT) and high voltage ride through (HVRT) capability of the DFIG in microgrid by using superconducting magnetic energy storage (SMES) and superconductive fault current limiter (SFCL), simultaneously. The simulation is carried out by using PSCAD/EMTDC software and the simulation resultsillustrate the effectiveness of proposed approach to improve fault ride through capability of DFIG in microgrid during voltage swell and voltage sag.

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In this paper, a hybrid algorithm has been presented for energy management in multi-microgrid systems considering security constraints. The energy management system is responsible for accurately dispatching the amount of required energy among multiple microgrids and units in a muti-microgerid system. The energy management procedure is done hierarchically, in a way that each microgrid performs a local energy management, which determines surplus and shortage amounts of energy at each time interval. Accordingly, Independent System Operator (ISO), schedules the units. Each microgrid, contains a wind turbine (WT) and Photovoltaic (PV) panels as renewable and nondispatchable resources and a diesel generator as a dispatchable energy resource. Also an energy storage system (ESS) is responsible for balancing the produced and consumed energy. A demand response program (DRP) is performed through energy management system for the objective of MG load management and flattening the load curve and reducing the operation cost. Finally, the proposed approach is tested on IEEE 33-bus distribution test system, in presence of microgrids, using GAMS and MATLAB softwares. The simulation results would be presented in the final section to show the effectiveness of the proposed algorithm.

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This paper presents a novel approach for optimal planning of the multi microgrids (MMGs) under uncertainties in load and renewable power generation. The proposed approach is applied for optimally determining the size, type, number, and site of renewable and dispatchable distribution generation (DG) with optimal allocation of switch for clustering distribution systems into a number of microgrids to economical and reliable structure. The optimization aim is to minimize the totally microgrid planning cost including investment cost, operation and maintenance cost, power losses cost, the pollutants emission cost and the cost of energy not supply (ENS). The system uncertainties are considered using a set of scenarios and a scenario reduction method is applied to enhance a tradeoff between the accuracy of the solution and the computational burden. Cuckoo optimization algorithm (COA) is implemented to minimize the objective function as an optimization algorithm. Also, the effect of optimization coefficients on the planning problem and the robustness of the proposed algorithm are investigated using sensitivity analysis. The efficiency of the proposed method are validated on 33-bus distribution system and the obtained results show that the proposed framework can be considered as an efficient tool for planning of multi microgrids under uncertainty.

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Microgrid is a collection of electric loads, distributed generation units and battery storage operating as a controllable load which is able to supply the local loads. Air pollutions due to fossil fueled vehicles increase by factories development. Besides, shortage in fossil fuels increase the trends into electric vehicles. In this paper, optimal stochastic operation problem of microgrid in presence of electric vehicles and demand response loads is solved with the objectives of operation cost minimization and improving the security indices of the system in an acceptable level of the reliability. Besides, the optimal placement of PEV stations is performed. The proposed problem is formulated as mixed integer linear programming (MILP). Gams software is used as the simulation tool, and a 24-bus test system including a number of DGs, and PEV stations is studied to validate the efficiency of the proposed model

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Abstract:
Due to the increasing use of microgrids, investigation of their stability is of special interest. One of the disadvantages of an inverter-based distribution unit is that at any given time, phase and frequency information at the point of common coupling (PCC) is required that can affect the stability. The synchronization techniques include synchronous reference frame phase-locked loop (SRF-PLL), virtual inertia, and constant K. To minimize cost and improve reliability, the minimum DC link capacitance should be determined. In this article, finding the minimum DC link capacitance is defined as an optimization problem where the particle swarm optimization (PSO) algorithm is used for the solving of the problem, where the stability is studied through eigenvalue analysis. In the stability analysis, harmonics and negative sequence of grid voltage, increasing the grid inductance, changes in the grid frequency, and changes in the solar irradiation intensity are considered. The effect of various synchronization methods on the stability of grid-connected inverters and DC link capacitance value is investigated.
 

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Problems with the cost and pollution of fossil fuels have increased the incentive to operate on electric vehicles. However, the use of these vehicles is a challenge due to the additional loads which imposed on the power grid. Accordingly, a method has been proposed to improve the electrical parameters of the network including losses and voltage profiles by optimally managing the charge and discharge of plug in hybrid electric vehicles (PHEVs). The optimal management of the present paper involves the simultaneous management of active and reactive power of PHEVs. In order to implement the optimal management, in this paper, the probabilistic behavior of consumers and PHEVs are modeled on the factors affecting them. Regarding the multiplicity of factors considered and the non-convergence of the problem by conventional methods of optimization, a two-stage optimization method is proposed which provides the ability to achieve the desired goals by managing active and reactive power of PHEVs. The advantages of the proposed method can be to reduce the computational volume with respect to problem solving in each step of the time independently and thus reduce the optimization problem solving time. The proposed method is implemented by performing Monte Carlo repetitions on six power management scenarios implemented by GAMS and DIgSILENT software on real network of 20 kV distribution of Sirjan in Kerman province. The results of various scenarios show that the management of charge and discharge of PHEVs has smooth the voltage profile and reduced network losses. Therefore, using the proposed method, the additional loads imposed by the electric vehicle on the grid will not only increase the energy losses, but, with the proper management of the PHEVs, the network losses will be reduced compared to the absence of them.

 

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The conventional real power-frequency and reactive power-voltage droop characteristics are commonly employed to share the electric power among parallel distributed generation (DG) units. Despite some advantages such as easy implementation and no need for communication infrastructure, inaccurate reactive power sharing is one of the main disadvantages of conventional droop control. This paper presents a modified droop control scheme based on changing the y-intercept of the voltage droop characteristic. In this method, the initial control of the inverter-based DG units is performed using conventional droop characteristics. Then, the reactive power sharing error for each DG unit is determined by injecting a small real power disturbance and making a coupling between the real and reactive powers. Accordingly, the modified reactive power controller modifies the generated reactive power of each DG unit by changing the output voltage. As this process should be simultaneously implemented in all DG units and employment of the central controller and the communication link for activation of the modification procedure has some disadvantages, this paper presents a local activation mechanism. The proposed scheme operates based on a significant change of reactive power and ensures the execution of all stages of modified droop control and its reactivation to respond to the microgrid power changes. Several simulation case studies using a low voltage microgrid network verify the effectiveness of the proposed control scheme.

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In recent years, multi-energy microgrids including electricity, gas and thermal are more grown; that presents demand response (DR) models considering multi-energy storages and renewable resources. Appropriate DR management with storages may lead to optimal flexibility. In this paper, a probabilistic linear model is introduced to assess the effect of flexibility and DR. In the proposed model, electrical and thermal DR, multi-energy storages, and participation in reserve market are considered as the main contribution. The proposed model guarantees thermal comfort as well as increasing flexibility and reserve commitment. By applying the proposed method on a distribution network in UK, it is illustrated that by utilization of the proposed DR program the flexibility of microgrid increases and the cost of operation decreases.

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Energy supply is one of the main challenges of the present century. Population growth, rising energy demand, fossil fuel scarcity, and environmental concerns have made energy security as major issue for all countries in the world. Traditional power system, including low-efficiency generation, long-distance transmission and then a complex distribution system, face various challenges that make it inappropriate as a future secure energy system. 
Today, the energy hub as a framework of generation, conversion, storage and consumption of different energy carriers, is considered by many researchers as the prospect of a future secure energy system.
This research analyzes and classifies the latest innovative research achievements in this field. A review of research in the field of long-term energy hub planning, optimal operation of this multi carrier energy infrastructure, and the concepts of micro and macro energy hubs is presented in this paper. 
A bibliographic study is also discussed with a historical review of the energy hub researches. In addition, one of the main goals of this research is to explain the concept of smart city consisting of smart energy hubs using a review of recent research by researchers in this field.
 

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Microgrid has a precious role in new power systems. Load balancing, voltage stability and load supporting in peak times are some great issues of microgrid. Besides these advantages, some challenges such as cost of microgrid must be considered. Energy storage system (ESS) and Demand response (DR) program can improve the performance of the microgrid in terms of more voltage stability and cost reduction. In this paper using the renewable distributed generators, ESS and DR program, the cost function is defined where cost minimization of microgrid is performed based on the evolutionary algorithm, bee colony optimization (BCO). It is worth mentioning that battery wear and maintenance cost is also considered in the cost function. Simulation results show that considering the optimized location and capacity of ESS and efficient DR program, the overall cost is noticeably reduced and the microgrid performance is greatly improved.

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In today’s industrial world, it is indispensable to strengthen the power distribution network infrastructure against unexpected power losses and financial damages caused by earthquakes. This paper presents a new tri-level framework for multi-microgrid expansion planning (MMEP) against seismic risks stemming from the earthquake in which the lower level describes short-term corrective actions as the distribution network operator (DNO)’s reaction after the seismic risks to apply feeder reconfiguration and generation resource redispatch. The intermediate level meticulously models the destructive effects of seismic risks on the power distribution network components, such as substations, feeders, and distributed energy resources (DERs) through a well-defined seismic scenario generation method (SSGM). In the SSGM, with a new point of view, maximum horizontal ground acceleration is modeled using a reduction procedure in terms of effective seismic parameters, including soil type, seismic magnitude, occurrence depth, and surface distance. Additionally, and more importantly, the probability of complete destruction of the power distribution network components is estimated by predetermined fragility curves. Relying on maximum horizontal ground acceleration and probability of complete destruction, multiple seismic scenarios are generated by maximizing the technical-economic damage subject to structural constraints. Then, the worst-case seismic scenario is selected. In the third level, however, the resilient optimal microgrid expansion plans, as the long-term preventive actions after the seismic risks, are identified. The MMEP objectives, modeled through the third level, are the minimization of the investment and operation costs and maximization of participation profits while satisfying long- and short-term constraints over the planning horizon. A potent melody search algorithm (MSA) is widely employed to solve the proposed large-scale mixed-integer linear tri-level framework. The proposed planning framework is implemented on a standard 9-bus 33-kV test system to demonstrate the feasibility and effectiveness of the newly developed framework. The simulation results corroborate the effective performance of the proposed planning framework in improving the resilience of power distribution networks against seismic risks.

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Power systems are complex systems that are not easy to understand and analyze. Also, many faults and incidents occur in these systems, many of which are mended without human interference. Meanwhile, electricity companies are responsible for the security of power systems and operators because if any part of the power system acts as an unwanted island, it may be unsafe for grid personnel and may result in serious damages to grid equipment. Therefore, it is important and necessary to identify the parts of the grid, which have become islands, and apply load shedding to abolish these islands. This paper proposes a new approach for load shedding in the islanded microgrid in the presence of distributed generations. Features of the proposed method include high flexibility, speed, and accuracy. The proposed method is simulated by powerful DIgSILENT software, and the simulation results support the capability of the proposed method.

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Nowadays, renewable energy is increasingly used in smart grids and microgrids to reduce the use of fossil fuels and improve network efficiency. Like all power system devices, microgrids are subject to transient and steady-state faults, such as short circuits. These faults impair reliability and consumer dissatisfaction. To accurately, automatically, and economically determine the location of a fault, a robust fault location method is needed to stabilize and repair the damaged part of the network. Given the access to the data of all nodes, the fault in these networks can be located based on the data on the two terminals. Accordingly, this paper proposes a method for determining fault distance and faulty section in the island and grid-connected microgrids. The proposed method uses distributed parameters line model and calculates the location of double-phase faults in the microgrid based on voltage and current data on both sides of each section, taking renewable energies and electric vehicles into account. At first, the measurement devices receive and store the current and voltage data at the beginning and end of each section. If a fault occurs, the fault distance is determined by calculating the difference between voltages and currents on both sides of the fault. According to the sampling rate, many voltage and current samples are obtained during the fault. The proposed method calculates a fault distance for each sample. As a result, many fault distances are obtained. These calculations are done for all sections. In the next step, the distances obtained for each section are plotted on the coordinate axis, and a curve is obtained for each section. Among the curves obtained, one curve has a global minimum, which indicates the faulty section. Other curves are ascending or descending. In addition, the global minimum point indicates the calculated distance of the fault from the beginning of the section. This method is not sensitive to electric vehicle models and distributed generation sources and uses only less than half-cycle data to execute the algorithm. The performance of the method is investigated with the simulation of a 9-bus microgrid in MATLAB/SIMULINK. The effects of changes in line parameters (two scenarios), different fault locations, fault resistance (0, 25, and 50 Ω), fault inception angles (36, 90, 180, and 270 degrees), different DGs operation modes (three scenarios), and measurements error (±3%) are studied. The maximum and minimum errors of this method are obtained to be 0.97% and 0.02%, respectively. The results indicate the high accuracy of the proposed method compared to other fault location methods.