Showing 27 results for Microgrid
E. Alizadeh, A. Motie Birjandi, M. Hamzeh,
Volume 13, Issue 4 (12-2017)
Abstract
This paper proposes a decentralized control technique to minimize the total operation cost of a DC microgrid in both grid-connected and islanded modes. In this study, a cost-based droop control scheme based on the hourly bids of all participant distributed generators (DGs) and the hourly energy price of the utility is presented. An economic power sharing technique among various types of DG units is adopted to appropriately minimize the daily total operation cost of DC microgrid without a microgrid central controller. The DC microgrid may include non-dispatchable DG units (such as photovoltaic systems) and dispatchable generation units. Unlike other energy management techniques, the proposed method suffers neither from forecasting errors for both load demand and renewable energy power prediction modules, nor from complicated optimization techniques. In the proposed method, all DGs and the utility are classified in a sorting rule based on their hourly bids and open market price, and then the droop parameters are determined. The simulation results are presented to verify the effectiveness of the proposed method using MATLAB/SIMULINK software. The results show that the proposed strategy is able to be implemented in various operation conditions of DC microgrid with resistance to uncertainties.
S. Dolatabadi, S. Tohidi, S. Ghasemzadeh,
Volume 14, Issue 4 (12-2018)
Abstract
In this paper, a new active method based on traveling wave theory for islanding detection is presented. A standard power grid that combines a distributed generation source and local loads is used to test the proposed method. Simulations are carried out in MATLAB/Simulink and EMTP/rv which demonstrate fast response and zero non-detection zone (NDZ) of the method along with low perturbation.
S. M. Hoseini, N. Vasegh, A. Zangeneh,
Volume 16, Issue 2 (6-2020)
Abstract
In this paper, a robust local controller has been designed to balance the power for distributed energy resources (DERs) in an islanded microgrid. Three different DER types are considered in this study; photovoltaic systems, battery energy storage systems, and synchronous generators. Since DER dynamics are nonlinear and uncertain, which may destabilize the power system or decrease the performance, distributed robust nonlinear controllers are designed for the DERs. They are based on the Lyapunov stabilization theory and super-twisting integral sliding mode control which guarantees system stability and optimality simultaneously. The reference signals for each DER are generated by a supervisory controller as a power management system. The controllers proposed in this work are robust, have fast response times, and most importantly, the control signals satisfy physical system constraints. The designed controller stability and effectiveness are also verified using numerical simulations.
M. Sedighizadeh, S. M. M. Alavi, A. Mohammadpour,
Volume 16, Issue 3 (9-2020)
Abstract
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.
M. Khajevand, A. Fakharian, M. Sedighizadeh,
Volume 16, Issue 3 (9-2020)
Abstract
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.
P. Bhat Nempu, J. N. Sabhahit,
Volume 16, Issue 4 (12-2020)
Abstract
The hybrid AC-DC microgrid (HMG) architecture has the merits of both DC and AC coupled structures. Microgrids are subject to intermittence when the renewable sources are used. In the HMG, since power fluctuations occur on both subgrids due to varying load and unpredictable power generation from renewable sources, proper voltage and frequency regulation is the critical issue. This article proposes a unique method for operating a microgrid (MG) comprising of PV array, wind energy system (WES), fuel cell (FC), and battery in HMG configuration. The control scheme of the interlinking converter (ILC) regulates frequency, voltage, and power flow amongst the subgrids. Power management in the HMG is investigated under different scenarios. Proper power management is accomplished within the individual subgrids and among the subgrids by the control techniques adopted in the HMG. The system voltage and frequency deviations are found to be minimized when the FC system acts as the backup source for DC subgrid, reducing the power flow through the ILC.
M. Keshavarz, A. Doroudi, M. H. Kazemi, N. Mahdian Dehkordi,
Volume 17, Issue 2 (6-2021)
Abstract
The droop control strategy is the most common approach for microgrids control but its application is limited due to frequency deviation following a load change. Complementary control strategy has then been proposed to solve the problem using a communication network. However, under this strategy, regular loads profile produces a continuous change of output power of all distributed generators (DGs) and their generation changes seem to be permanent. This also causes continuous data exchange between DGs through communication links. This paper shows the possibility of adapting the droop/isochronous control methodology used by synchronous generators in conventional power systems to provide frequency control and power balance to inverter-based distributed generation power systems. To this end, this paper presents a centralized complementary control framework for the management of power-sharing and sustaining frequency in its nominal range in microgrids using a hybrid droop-isochronous control system. The proposed method is event-triggered based and communication between DGs is only needed when the output power of the isochronous generator exceeds its power limits. The method provides an efficient and reliable control system and has a simple concept, easy, and cost-effective implementation. Simulations in MATLAB/SimPower are performed on a typical microgrid under various conditions to evaluate the performance of the proposed controller.
A. Karimpour, A. M. Amani, M. Karimpour, M. Jalili,
Volume 17, Issue 4 (12-2021)
Abstract
This paper studies the voltage regulation problem in DC microgrids in the presence of variable loads. DC microgrids generally include several Distributed Generation Units (DGUs), connected to electrical loads through DC power lines. The variable nature of loads at each spot, caused for example by moving electric vehicles, may cause voltage deregulation in the grid. To reduce this undesired effect, this study proposes an incentive-based load management strategy to balance the loads connected to the grid. The electricity price at each node of the grid is considered to be dependent on its voltage. This guide moving customers to connect to cheaper connection points, and ultimately results in even load distribution. Simulations show the improvement in the voltage regulation, power loss, and efficiency of the grid even when only a small portion of customers accept the proposed incentive.
Shankarshan Prasad Tiwari, Ebha Koley,
Volume 18, Issue 4 (12-2022)
Abstract
In recent years, DC microgrid has attracted considerable attention of the research community because of the wide usage of DC power-based appliances. However, the acceptance of DC microgrid by power utilities is still limited due to the issues associated with the development of a reliable protection scheme. The high magnitude of DC fault current, its rapid rate of rising and absence of zero crossing hinders achieving reliable protection in DC microgrid. Further, the intermittency associated with the non-conventional distributed generators demands adaptiveness under varying weather conditions. In this paper, the above-mentioned issues are addressed by developing a bagging tree-based protection approach for a multi-terminal DC microgrid. The proposed scheme addresses the intermittency associated with renewable sources. It performs the functions of mode detection, fault detection/classification, and faulty section identification using local information of current and voltage signals only. The same avoids the communication network related drawbacks like data loss and latency.
Hamid Salarvand, Meysam Doostizadeh, Farhad Namdari,
Volume 18, Issue 4 (12-2022)
Abstract
Owing to the portability and flexibility of mobile energy storage systems (MESSs), they seem to be a promising solution to improve the resilience of the distribution system (DS). So, this paper presents a rolling optimization mechanism for dispatching MESSs and other resources in microgrids in case of a natural disaster occurrence. The proposed mechanism aims to minimize the total system cost based on the updated information of the status of the DS and transportation network (TN). In addition, the characteristics of the protection system in DS (i.e., relays with fixed protection settings), the constraints related to the protection coordination are examined under pre- and post-event conditions. The coordinated scheduling at each time step is formulated as a two-stage stochastic mixed-integer linear program (MILP) with temporal-spatial and operation constraints. The proposed model is carried out on the Sioux Falls TN and the IEEE 33-bus test system. The results demonstrate the effectiveness of MESS mobility in enhancing DS resilience due to the coordination of mobile and stationary resources.
M. Dodangeh, N. Ghaffarzadeh,
Volume 18, Issue 4 (12-2022)
Abstract
An intelligent strategy for the protection of AC microgrids is presented in this paper. This method was halving to an initial signal processing step and a machine learning-based forecasting step. The initial stage investigates currents and voltages with a window-based approach based on the dynamic decomposition method (DDM) and then involves the norms of the signals to the resultant DDM data. The results of the currents and voltages norms are applied as features for a topology data analysis algorithm for fault type classifying in the AC microgrid for fault location purposes. The Algorithm was tested on a microgrid that operates with precision equal to 100% in fault classification and a mean error lower than 20 m when forecasting the fault location. The proposed method robustly operates in sampling frequency, fault resistance variation, and noisy and high impedance fault conditions.
Mitesh Kumar, Shivam Shivam,
Volume 18, Issue 4 (12-2022)
Abstract
The idea of a microgrid is created by utilizing more diverse ac or dc distributed generation (DG) sources along with an energy storage system (ESS) and loads. The most efficient and reliable selection of ac and dc microgrids is a hybrid ac/dc microgrid. The hybrid microgrid largely overcomes the shortcomings of standalone ac or dc microgrids. A bidirectional interlinking converter (BIC) is utilized in the interface for controlling power flow between subgrids. In order to improve voltage and frequency regulation with effective power sharing, the BIC based on the proposed control scheme is implemented for power flow between ac and dc sub-grid in Islanding mode. The control scheme is modified based on conventional droop control with voltage and frequency variation in order to improve bus voltage and frequency regulation with effective power sharing for intermittent sources. The operation of the islanded hybrid ac/dc microgrid is performed with solar, wind, and energy storage system under variable generation and load conditions. In order to make robustness of the system, there are considered different cases for generation and load scenarios. In the transient state, the overshoot and settling time of frequency and voltage are improved, as well as the frequency and voltage regulations are found within the permissible limit in the steady state. Furthermore, the corresponding variations are shown in tabular form in the simulation result. The actual data of solar irradiance and wind speed have been taken from the National Renewable Energy Laboratory. The performance of the system is verified in MATLAB/Simulink environment.
Seyed Masoud Barakati, Farzad Tahmasebi,
Volume 19, Issue 3 (9-2023)
Abstract
Increasing the penetration of distributed generation (DG) systems in power systems has many advantages, but it also has problems, including interference with the proper functioning of the protection systems. This problem is severe in microgrid systems that contain many DGs. Overcurrent relays are one of the most critical protection equipment of protection systems. The DG sources significantly change the characteristics of fault currents and the protection designs as well as the coordination of overcurrent relays. This paper proposes a coordination method for directional overcurrent relays with dual adjustment to resolve the interference problem in the protection system of a microgrid in the presence of distributed generation sources based on the electronic power converter (inverter). This is done by considering the curve of different standard characteristics according to the IEC60255 standard in two operating modes, the grid-connected and islanded. A genetic optimization algorithm is used to reduce the total operating time of the relays. The simulation results verify the effectiveness of the proposed coordination method. The results show that the protection coordination scheme with dual adjustment relays and the use of combined characteristic curves can significantly reduce the operating time of the total relays.
Fatemeh Zare-Mirakabad, Mohammad Hosein Kazemi, Aref Doroudi,
Volume 19, Issue 3 (9-2023)
Abstract
This paper proposes a robust H ∞ -LMI-based primary controller using the Linear Parameter Varying (LPV) modeling for an AC islanded Micro-Grid (IMG). The proposed controller can regulate the frequency and voltage of the IMG under various scenarios, such as load changes, faults, and reconfigurations. Unlike most previous studies that neglected the nonlinearity and uncertainty of the system, this paper represents the system dynamics as a polytopic LPV model in the novel primary control structure. The proposed method computes a state-feedback control by solving the corresponding Linear Matrix Inequalities (LMIs) based on H ∞ performance and stability criteria. The robust primary control is applied to a test IMG in the SIM-POWER environment of MATLAB and evaluated under different scenarios. The simulation results demonstrate the effectiveness and efficiency of the proposed method in maintaining the stability of the frequency and voltage of the IMG.
Nasreddine Attou, Sid-Ahmed Zidi, Samir Hadjeri, Mohamed Khatir,
Volume 19, Issue 3 (9-2023)
Abstract
Demand-side management has become a viable solution to meet the needs of the power system and consumers in the past decades due to the problems of power imbalance and peak demand on the grid. This study focused on an improved decision tree-based algorithm to cover off-peak hours and reduce or shift peak load in a grid-connected microgrid using a battery energy storage system (BESS), and a demand response scheme. The main objective is to provide an efficient and optimal management strategy to mitigate peak demand, reduce the electricity price, and replace expensive reserve generation units. The developed algorithm is evaluated with two scenarios to see the behavior of the management system throughout the day, taking into account the different types of days (weekends and working days), the random profile of the users' demand, and the variation of the energy price (EP) on the grid. The simulation results allowed us to reduce the daily consumption by about 30% to 40% and to fill up to 12% to 15% of the off-peak hours with maximum use of renewable energies, demonstrating the control system's performance in smoothing the load curve.
S. Prasad Tiwari,
Volume 19, Issue 3 (9-2023)
Abstract
In spite of the numerous benefits over the traditional power distribution system, protection of the microgrid is a challenging and complex task. The varying fault resistances due to dissimilar grounding conditions can affect the performance of the protection scheme. Under such conditions, the magnitude of the fault current can vary from lower to higher level. In addition to the above, the dissimilar magnitude of fault current during grid connected and islanded mode demands a protection scheme that can easily discriminate the mode of operation. The magnitude of fault current in grid-connected and islanded modes needs a robust protection scheme. In this regard, an ensemble of subspace kNN based robust protection scheme has been proposed to detect the faulty conditions of the microgrid. The tasks of the mode detection, fault detection/classification as well as faulty line identification has been carried out in the proposed work. In the proposed protection scheme, discrete wavelet transform (DWT) has been used for processing of the data. After recording the voltage and current signals at bus-1, the protection scheme has been validated. The validation of the protection scheme in Section 6 reveals that the protection scheme is efficiently working.
Jayati Vaish, Anil Kumar Tiwari, Seethalekshmi K.,
Volume 19, Issue 4 (12-2023)
Abstract
In recent years, Microgrids in integration with Distributed Energy Resources (DERs) are playing as one of the key models for resolving the current energy problem by offering sustainable and clean electricity. Selecting the best DER cost and corresponding energy storage size is essential for the reliable, cost-effective, and efficient operation of the electric power system. In this paper, the real-time load data of Bengaluru city (Karnataka, India) for different seasons is taken for optimization of a grid-connected DERs-based Microgrid system. This paper presents an optimal sizing of the battery, minimum operating cost and, reduction in battery charging cost to meet the overall load demand. The optimization and analysis are done using meta-heuristic, Artificial Intelligence (AI), and Ensemble Learning-based techniques such as Particle Swarm Optimization (PSO), Artificial Neural Network (ANN), and Random Forest (RF) model for different seasons i.e., winter, spring & autumn, summer and monsoon considering three different cases. The outcome shows that the ensemble learning-based Random Forest (RF) model gives maximum savings as compared to other optimization techniques.
Shankarshan Prasad Tiwari,
Volume 20, Issue 1 (3-2024)
Abstract
In recent years, due to the widespread applications of DC power-based appliances, the researchers attention to the adoption of DC microgrids are continuously increasing. Nevertheless, protection of the DC microgrid is still a major challenge due to a number of protection issues, such as pole-to-ground and pole-to-pole faults, absence of a zero crossing signal, magnitude of the fault current during grid-connected and islanded mode, bidirectional behaviour of converters, and failure of the converters due to enormous electrical stress in the converter switches which are integrated in the microgrid. Failure of the converter switches can interrupt the charging of the electrical vehicles in the charging stations which can affect transportation facilities. In addition to the above mentioned issues protection of the DC microgrid is more challenging when fault parameters are varying due to dissimilar grounding conditions and varying operational dynamics of the renewable sources of energy. Motivated by the above challenges a support vector machine and ensemble of k-nearest neighbor based protection scheme has been proposed in this paper to accurately detect and classify faults under both of the modes of operation. Results in the section 5 indicate that performance of the protection scheme is greater as compared to other algorithms.
Nurul Husna Abd Wahab, Mohd Hafizuddin Mat, Norezmi Md Jamal, Nur Hidayah Ramli,
Volume 21, Issue 2 (6-2025)
Abstract
In islanded microgrids, circulating currents among parallel inverters pose significant challenges to system stability and efficient power distribution. Traditional droop control methods often struggle to manage these currents effectively, leading to inefficiencies and potential system damage. This study introduces an advanced fuzzy-robust droop control strategy that integrates fuzzy logic with robust droop control to address these challenges. By incorporating fuzzy logic, the proposed strategy enhances the adaptability of droop control to varying system conditions, improving the management of circulating currents and ensuring more accurate power sharing among inverters. Comprehensive mathematical modeling and extensive simulation analyses validate the performance of this control strategy. The results show that the fuzzy-robust droop control method significantly outperforms conventional approaches, achieving up to a 70% reduction in circulating currents. This improvement leads to a substantial reduction in power losses and enhances the dynamic response under varying load conditions. Additionally, the strategy improves voltage and frequency regulation, contributing to the overall stability and reliability of the microgrid. The findings provide a robust solution to the longstanding issue of circulating currents, optimizing microgrid operations, and paving the way for more efficient and resilient distributed energy systems. The advanced control strategy presented in this study not only addresses critical challenges but also demonstrates the potential for innovative methodologies to meet the growing demands of future energy infrastructures, where reliability and efficiency are essential.
Mahdi Arabsadegh, Aref Doroudi,
Volume 21, Issue 4 (11-2025)
Abstract
This paper presents an advanced methodology for post-storm power system restoration. A real-time Condition Index (CI)-based classification scheme is introduced to categorize circuit breakers into high-reliability (Type A) and moderate-reliability (Type B) groups. Leveraging this classification, a genetic algorithm (GA) optimizes microgrid configurations to maximize power restoration probabilities by explicitly modeling the stochastic failure risks associated with circuit breakers under severe weather conditions. The approach was validated on the IEEE 118-bus system with five critical breakers deactivated due to storm conditions. The GA achieved a 92.5% load restoration after 200 iterations, surpassing a baseline Monte Carlo simulation that attained 85.2%. Computational efficiency was significantly improved, reducing execution time to approximately 15 minutes compared to 60 minutes for traditional methods, with enhanced accuracy indicated by a 1.8% error margin versus 7.5%. Key contributions include utilizing live CI data for dynamic breaker classification, which resulted in a 20% reduction in computational time, and demonstrating scalability and effectiveness on large-scale test systems such as the 118-bus network. The methodology's performance decreases to 78.3% load restoration when more than 14 breakers are compromised. Future research will focus on integrating detailed storm modeling—including wind speed profiles—and incorporating renewable energy resources to enhance grid resilience.
