Autonomous Microgrid Operation Research Articles

Reactive power planning with the help of multi-objective genetic algorithm and flexible AC transmission systems devices

In this paper power quality of 3-bus solar-based hybrid system has been presented (where one or more than one distribution generator unit is connected to the grid). The injection of solar power into grid-connected systems creates power quality problems such as current consistency, electrical fluctuations, and inefficient power demand. A power quality control strategy based on a real-time self-regulation method for autonomous microgrid operation has been presented. In this paper solar farm design and satisfactory performance tests such as PV-static synchronous compensator (STATCOM) to improve the power quality of grid-based systems have been presented using the MATLAB/Simulink environment. Pulse width modulator (PWM) with proportional-integral derivative (PID) controller used for frequency control, reactive var compensation is used to control voltage profile. Multi-objective genetic algorithm (MOGA) for reactive power planning (RPP) with the objective of reactive power minimization is introduced. The optimization variables are generator voltage, transformer tap changer, and various operational constraints.

Reactive power planning with the help of multi-objective genetic algorithm and flexible AC transmission systems devices

In this paper power quality of 3-bus solar-based hybrid system has been presented (where one or more than one distribution generator unit is connected to the grid). The injection of solar power into grid-connected systems creates power quality problems such as current consistency, electrical fluctuations, and inefficient power demand. A power quality control strategy based on a real-time self-regulation method for autonomous microgrid operation has been presented. In this paper solar farm design and satisfactory performance tests such as PV-static synchronous compensator (STATCOM) to improve the power quality of grid-based systems have been presented using the MATLAB/Simulink environment. Pulse width modulator (PWM) with proportional-integral derivative (PID) controller used for frequency control, reactive var compensation is used to control voltage profile. Multi-objective genetic algorithm (MOGA) for reactive power planning (RPP) with the objective of reactive power minimization is introduced. The optimization variables are generator voltage, transformer tap changer, and various operational constraints.

A Novel High Impedance Fault Detection Strategy for Microgrid Based on Differential Energy Signal of Current Signatures and Entropy Estimation

The non-linearly deterministic fault current characteristics with low current magnitude of high impedance fault (HIF) have thrown an inevitable challenge to the microgrid protection system. Moreover, differentiating HIF from non-fault events is also a challenging task under different operating scenarios of the microgrid. In order to address this, a simple and fast protection algorithm, based on Empirical Mode Decomposition (EMD) in conjugation with Teager-Kaiser Energy Operator (TKEO) is proposed in this article. This scheme process the current signals retrieved from both ends of the line through EMD, and subsequently, the current signal energy is extracted by TKEO. The incidence of a fault is affirmed by measuring the energy difference signal and estimation of entropy. By employing the second layer algorithm using entropy analysis, the non-fault disturbances, such as capacitor and load switching, temporary overloading, and DG outage, have been effectively distinguished from HIFs. The proposed technique is tested for grid-tied and autonomous microgrid operation modes with several HIF and non-fault cases. It is inferred that the proposed technique can detect and differentiate HIFs from other system perturbations seamlessly in less time. Compared to other methods, this scheme has procured excellent accuracy and reliability, and is also not affected by the dynamic current behavior of the microgrid. The PSCAD-EMTDC software is used to build and simulate the test system, and the MATLAB programming interface is utilized to develop and test the suggested method.

Bi-stage planning framework for a solar-battery based micro-grid using techno-socio-economic evaluation

ABSTRACT Solar based microgrids provide an environmentally benign alternative to conventional generation. However, their capital intensive structure and variability compels comprehensive examination of planning scenarios. This paper presents a bi-stage planning framework for a solar-battery microgrid. In the first stage of planning, sizing is carried out for autonomous operation. The second stage extends analysis to grid connected mode wherein four cases of microgrid operation are investigated. The analysis involves techno-socio-economic evaluation of constrained and unconstrained power flow. The parameters such as risk state probability, unmet load fraction, levelized cost of energy and social cost of carbon are used to evaluate and compare different cases for a solar-battery based microgrid located in Jaisalmer, Rajasthan, India. The results demonstrate that storage integration is essential for sustaining reliability in autonomous operation of microgrid. It can be inferred from the results that permitting reverse power flow renders considerable economic benefits and fetches lowest cost.

An Islanding Detection and Control Strategy to Realize the Stable and Autonomous Operation of Microgrids Using the Virtual Synchronous Generator

Abstract: An islanding detection and based control strategy is created in this exploration to accomplish the steady and independent activity of microgrids using the neural network based Virtual Synchronous Generator (VSG) idea during unplanned grid reconfigurations . Maybe of utilizing a design-orientedmethodology, this paper gives a rigorous and extensive hypothetical investigation and reaches a concise conclusion that is easy to execute and successful even in complex situations. Based on the results of the mutation sequence and voltage wavering, a neural network based islanding identification calculation is proposed, which requires less constraint strategy. The proposed neural network approach outperforms the thefrequency measured passive detection method in terms of detection speed and reliability. Broad recreations affirm the reasonableness of the proposed islanding location and control methodology. Additionally, think about the results of the reproductions for the PI regulator, fluffy organizations, and neural organizations. Keywords: Virtual Synchronous Generator, Islanding detection, Islanding operation, Droop control, Stability, Microgrids.

Integrated energy management system for Microgrids of building prosumers

In this paper, an easy to apply and computationally efficient energy management system (EMS) for microgrids of building prosumers is proposed. It is based on a hierarchical multi-agent system (MAS), aiming to minimize the operation cost of a microgrid comprising a group of buildings, renewable energy sources (RES), energy storage systems (ESS) and plug-in electric vehicles (PEVs). The optimization problem is suitably set up to ensure low computation requirements and it is solved with particle swarm optimization (PSO). Optimal operation scheduling for grid-connected and autonomous operation of microgrids of building prosumers, considering their thermal and electrical systems, integrated RES, conventional and dynamic ESS is proposed. The models used are not computationally demanding, allowing the application to complex systems and they are not being limited to one building scale which is the case for the majority of relative research. Another innovative feature of the proposed algorithm, among others, is that it ensures autonomous operation at certain time periods without the use of any emergency generator sets. Detailed simulation results of different operation scenarios, showed that cost savings in range of 11% can be achieved while a large number of operation and technical constraints are satisfactorily met in grid-connected and autonomous operation.

Space Microgrids for Future Manned Lunar Bases: A Review

Several space organizations have been planning to establish a permanent, manned base on the Moon in recent years. Such an installation demands a highly reliable electrical power system (EPS) to supply life support systems and scientific equipment and operate autonomously in a fully self-sufficient manner. This paper explores various technologies available for power generation, storage, and distribution for space microgrids on the Moon. Several factors affecting the cost and mass of the space missions are introduced and analysed to provide a comprehensive comparison among the available solutions. Besides, given the effect of base location on the design of a lunar electrical power system and the mission cost, various lunar sites are introduced and discussed. Finally, the control system requirements for the reliable and autonomous operation of space microgrids on the Moon are presented. The study is complemented by discussing promising future technological solutions that could be applied upon a lunar microgrid.

LMSRE-Based Adaptive PI Controller for Enhancing the Performance of an Autonomous Operation of Microgrids

Microgrids take a large part in power networks thanks to their operational and economic benefits. This research introduces a novel implementation of an adaptive proportional plus integral (PI) controller to boost the autonomous microgrid operation efficiency. The least mean and square roots of the exponential algorithm are utilized in the adaptive PI control strategy. The multi-objective function for both sunflower optimization (SFO) and particle swarm optimization (PSO) algorithms is obtained by The Response Surface Methodology. The system is evaluated under different environments, which are stated as follows: 1) disconnect the system from the grid (islanding), 2) autonomous system exposure to load variability, and 3) autonomous system exposure to a symmetrical fault. The proposed practicality of the control plan is shown by the data of the simulation, which is extracted from PSCAD/EMTDC software. The strength of the suggested adaptive control is confirmed through matching its results with those obtained using the SFO and PSO based optimal PI controllers.

Power flow incorporating cost-based droop control strategies for ac autonomous microgrids

Several methods of power flow analysis for autonomous microgrids have been suggested; however, the implementation of these methods is challenging because of the lack of a swing bus and droop control characteristics. This paper puts forward an innovative technique for the load flow study of microgrids that autonomously operate according to droop control strategies incorporating cost rather than traditional droop schemes. This approach aims to extend the application of conventional power flow methodologies. In this approach, the incremental cost that is derivative of the fuel cost curve with respect to power output is embedded in droop schemes. The proposed approach deploys the iterative procedure to impose complex power that injects through the swing node to zero, which represents the autonomous operation of microgrids. Test results validate that this approach is exact and straightforward to implement; therefore, it can be highly beneficial for operating and planning microgrids

Autonomous Operation of Microgrid and Minimization of Fault in Case of Failure in High-Voltage Lines

The manual reaction approach to faults is exhibited in conventional grid. Manual operations are slow in many cases and resulting in big fault and power cut. Turkey has experienced it by living on March 31, 2015. The switching to smart grids is inevitable in order to minimize human errors and avoid big failures. It is a solution to turn the appropriate zones back to the island mode, especially in case of emergency load shedding due to the basic frequency. However, large power fluctuations occur in the microgrids when switching to the island mode or connecting to the grid. Therefore, In Matlab / Simulink, a microgrid is designed that can operate in island mode in accordance with the smart grid structure to minimize the damage of symmetrical and asymmetrical of high voltage lines on loads, grid and its components in this study. Also the effects of Superconducting Fault Current Limiter (SFCL) have been studied to limit power fluctuations in the microgrid when switching to island mode and exit island mode. In addition, autonomous maneuver management has been carried out on the designed high voltage line to prevent faults resulting in long term power cut.

Small-Signal Stability Analysis for Microgrids Under Uncertainty Using MALANN Control Technique

Microgrids are often considered as the solution for affordable and clean energy in the distribution sector. This article presents the small-signal stability analysis of a distributed generation unit in an autonomous microgrid operation. The purpose of the proposed strategy is to optimally improve the capacity of the power system to restore the reasonable operating condition following a small physical disturbance. The proposed strategy is the joined execution of both the modified antlion optimization algorithm (MALO) and artificial neural network (ANN), and hence it is abbreviated to MALANN. In this article, the proposed controller comprises two control loops, namely the inner current control loop and the outer power control loop. The MALO technique is incorporated to generate the dataset of possible proportional integral (PI) gain parameters. By using the accomplished dataset of MALO, the ANN is trained, and convincing estimate execution is brought out through the entire machine working condition. The proposed strategy is implemented in MATLAB/Simulink, and the results are examined with two test cases and compared with various solution techniques such as base method and ant-lion optimization. The results prove that the stability analysis is reasonably accurate, and the controller offers a reliable system's operation.

An islanding detection based on droop characteristic for virtual synchronous generator

This paper proposes an islanding detection and control strategy to realize the stable and autonomous operation of microgrids using the virtual synchronous generator (VSG) concept under unplanned grid reconfigurations (e.g., islanding operation). Instead of a design-oriented method, this paper presents a detailed and comprehensive theoretical analysis and draws a brief conclusion, which is easy to implement and still effective under complex situations. Based on the results of mutation sequence and voltage oscillation, a rapider and more reliable islanding detection algorithm is proposed, which hardly needs parameter design. Comparing with frequency measured passive detection method, the proposed algorithm has higher detection speed and reliability. The feasibility of the proposed islanding detection and control scheme is verified by extensive simulations.

New voltage feedback‐based islanding detection method for grid‐connected photovoltaic systems of microgrid with zero non‐detection zone

This study proposes a fast and precise voltage feedback-based islanding detection method (IDM) for grid-connected photovoltaic systems (GCPVSs) based microgrid. In this algorithm, a disturbance containing the absolute deviation of the output voltage is injected into the inverter's d-axis reference current which tunes the active power output. In islanded mode, the applied disturbance reduces the active power output and consequently point of common coupling voltage beyond the standard setting while its effect at the presence of the grid is negligible. The assessment of the proposed IDM has been conducted in the MATLAB/Simulink platform under extensive scenarios defined by IEEE 1547-2008 and UL 1741 standards for a case study system with two large-scale GCPVSs. The provided outputs remark accurate islanding classification in all cases within 810 ms, much lower than the maximum permissible time postulated in islanding standards. This time is short enough to restore GCPVS for autonomous operation of microgrid as well. The comparative analysis of the proposed strategy with a few existing IDMs confirmed its overall superiorities in the terms of non-detection zone, detection time, being applicable into the microgrid, simple threshold determination, and straightforward and cost-effective implementation.

A Building Block Method for Modeling and Small-Signal Stability Analysis of the Autonomous Microgrid Operation

The task of the whole microgrid state-space matrix creation is usually done in a preferred textual programming language, and it presents a complicated, time-consuming, and error-prone job for a researcher without good coding practices. To ease the modeling task, contribute to the adaptation of new microgrid structures, control algorithms, and devices, and to improve the flexibility of the model, a graphical element building block method is proposed in this paper. With the proposed approach model creation of the whole microgrid is reduced to the creation of the individual element state-space model that is linked with other elements in a logical way with a graphical connection. Elements are then grouped into meaningful wholes and encapsulated with the appropriate graphical user interface that enables easy parameter modification and model complexity change. More detailed DC/DC and DC/AC models of converters than those in the literature concerning microgrid stability are presented in this paper. Those converters are incorporated in a microgrid, whose model is created using the proposed approach in MATLAB/Simulink. The dynamic response examination of the model remains easy, just as with all Simulink models, while for the linear system analysis, a specialized toolbox is used.

A rule-based approach for improvement of autonomous operation of hybrid microgrids

The work presented in the article proposes a new rule-based energy management algorithm to improve the autonomy of hybrid (AC/DC) microgrids consisting of higher quantum of heating loads and renewable energy sources. The objective of the algorithm is to make the microgrids more autonomous by reducing the power import from the utility grid, during generation deficits. The heating or lighting loads in this work are considered as non-critical loads, and all other voltage sensitive loads are classified as critical loads. The presented strategy makes the AC and DC non-critical loads operate in power saving modes during generation insufficiency by controlling the electric springs based on the voltage produced by the renewables. Usage of electric springs in the microgrids consisting of AC and DC loads and a couple of renewable sources to improve the autonomous operation of microgrids is probably the first attempt. The advantage of using the suggested methodology is that it operates the voltage insensitive loads, based on the prevailing power generation condition without completely curtailing them. Further, the effectiveness of the algorithm is tested by developing suitable simulation models in MATLAB and also a scaled down laboratory setup is developed using dSPACE 1104 real-time operating system. The simulation and experimental results prove that the algorithm is effective enough in reducing the power import from the main grid.

A New Adaptive Load-Shedding and Restoration Strategy for Autonomous Operation of Microgrids: A Real-Time Study

Islanding operation is one of the main features of a MicroGrid (MG), which is realized regarding the presence of distributed energy resources (DERs). However, in order to deal with the control challenges, which an MG faces during island operation, particularly when the transition is associated with certain excessive load, an efficient control strategy is required. This paper introduces a Central Management Agent (CMA) which maintains the stability of the MG, once it is islanded, by controlling an Energy Storage System (ESS) and a Central Synchronous Generator (CSG). Further, this paper proposes a new adaptive load-shedding/restoration schemes that calculates the amount of power imbalance based on frequency measurements combined with the mean value of the frequency gradient. The primacy of the proposed scheme over existing schemes, like instantaneous frequency gradient-based load shedding scheme, is its robustness against frequency oscillations. Moreover, the proposed method acts compatible with the control routine of DERs and the intermittent nature of the PV plant. As another salient feature of this paper, a Hardware In the Loop (HIL) testbed for real-time simulation is developed under which the proposed scheme and related communication with CMA along with other components are evaluated. The obtained results show that the control strategy can confidently conserve the stability of the MG in islanded mode and meet smooth reconnection to the grid-connected mode.

Distributed Optimal Control for Multiple Microgrids in a Distribution Network

The ever-increasing demand for more reliable and flexible energy supply for customers has pushed up the microgrids (MGs) to the center stage in the developments of distribution networks. If managed and coordinated efficiently, MGs can provide distinct benefits to the suppliers as well as energy consumers. In this paper, a distributed optimal control framework is proposed to coordinate the multiple MGs in a distribution network as well as to achieve the optimal control within the MGs. For each MG, a two-level control methodology is adopted. The upper-level control optimizes the generation output of multiple MGs cooperatively in a distributed manner, while the lower-level control tracks the optimal generation setting of each generator in the MG under both the grid-connected and islanded modes. The proposed control facilitates the autonomous operation of MGs in the distribution network while still achieves the optimal operation. Simulation studies with a four-MG system demonstrate the effectiveness of the proposed distributed approach.

Flocking‐based adaptive granular control strategy for autonomous microgrids in emergency situations

In this study, the authors study the operation of autonomous microgrids (MGs) in emergency situations such as the presence of large physical disturbances or cyber attacks. Traditional approaches to enhance system-wide stability, such as automatic generation control, are insufficient for stabilising MGs in some emergency situations due to the correspondingly lower capacity of distributed energy resources. To address this challenge, in this study, they develop an adaptive flocking-based framework that provides control-based MG resilience. The contribution of the authors’ work is three-fold. First, they effectively model the complex and dynamic dependencies amongst MG components by exploiting flocking theory. Second, they propose an adaptive granular control strategy based on the modelled dynamic dependencies. Third, they also explore the role of energy storage systems to facilitate distributed generations in achieving autonomous MG power balance in the presence of disruptions of different natures. Case studies demonstrate the effectiveness of the proposed strategy in stabilising MGs in response to physical disturbances and cyber attacks.

An Improved Control Strategy for Three-Phase Power Inverters in Islanded AC Microgrids

Microgrids (MGs) are composed of multiple distributed generators (DGs) interfaced to micronetwork through paralleled connected power inverters (PIs). Load sharing among multiple DG units is an important task for autonomous operation of microgrids. In order to realize satisfactory power sharing and voltage regulation between DG units, different voltage droop control strategies have been reported in the literature. In the medium voltage (MV) microgrids, power sharing, and voltage regulation often deteriorate due to dependence on nontrivial feeder impedances. The conventional control strategies are subject to steady-state active and reactive power-sharing errors along with system voltage and frequency deviations. Furthermore, complex microgrid configurations either in looped or meshed networks often make power balancing and voltage regulations more challenging. This paper presents an improved control strategy that can be extended for radial networks in order to enhance the accuracy of power sharing and voltage regulation. The proposed control strategy considers load voltage magnitude regulation as opposed the voltage regulation at inverters terminals. At the same time, a supervisory control loop is added to observe and correct system frequency deviations. This proposed method is aimed at replacing paralleled inverter control methods hitherto used. Simulation studies of the proposed scheme in comparison with the conventional control strategy in MATLAB/Simulink validate the effectiveness of the proposed strategy.

Decentralized DC Microgrid Monitoring and Optimization via Primary Control Perturbations

We treat the emerging power systems with direct current (DC) MicroGrids, characterized with high penetration of power electronic converters. We rely on the power electronics to propose a decentralized solution for autonomous learning of and adaptation to the operating conditions of the DC Mirogrids; the goal is to eliminate the need to rely on an external communication system for such purpose. The solution works within the primary droop control loops and uses only local bus voltage measurements. Each controller is able to estimate (i) the generation capacities of power sources, (ii) the load demands, and (iii) the conductances of the distribution lines. To define a well-conditioned estimation problem, we employ decentralized strategy where the primary droop controllers temporarily switch between operating points in a coordinated manner, following amplitude-modulated training sequences. We study the use of the estimator in a decentralized solution of the Optimal Economic Dispatch problem. The evaluations confirm the usefulness of the proposed solution for autonomous MicroGrid operation.