Distributed Generators In Microgrid Research Articles

Controllable Transient Power Sharing of Inverter-Based Droop Controlled Microgrid

The transient power shared by inverter-based distributed generators (DGs) restricts the normal operating range and overstresses the power electronic devices under disturbing events. Additionally, the inevitable incorporation of DC side voltage dynamic during transient worsens the uncoupled dynamics between active and reactive power. Furthermore, unsafe transient power supplied by DGs can easily destabilize system operation. Therefore, this paper proposes a control strategy that controls the transient power distributed between several DGs integrated into a microgrid. To comprehensively design the proposed control, (i) an extended steady state and transient modeling of a microgrid that incorporates DC side dynamics in AC side-based model is first carried out. (ii) After that, designing the proposed control is systematically conducted and verified using frequency and time domain analyses. (iii) Moreover, the effectiveness of the proposed control is compared with state-of-the-art control strategies. The results demonstrate that the proposed control prevents power electronics-based DGs from sharing the majority of transient currents when integrated with other DGs, especially, inertial sources. The results show that the power overshoot and oscillation are reduced more than two times whereas the settling time is decreased by about three times, ensuring quick stabilized, and reliable integration of power electronics DGs in microgrids.

Twin Delayed Deep Deterministic Policy Gradient (TD3) Based Virtual Inertia Control for Inverter-Interfacing DGs in Microgrids

Environmental and energy security concerns lead to the continuous displacement of traditional fossil fuel-based power generation to power electronics interfaced distributed generations (DGs). Increasing penetration of renewable energy sources and the substitution of synchronous generators with power electronic converters have resulted in reduced power system inertia and damping. This causes large frequency deviations and a higher rate of change of frequency. The fast and flexible nature of the energy storage system with a designed controller can achieve frequency stability in low inertia microgrids (MGs). The conventional proportional-integral-based virtual inertia controller is unable to eliminate frequency instability in low inertia MG. To enhance frequency stability, this article proposes a virtual inertia emulation strategy using a twin delayed deep deterministic policy gradient (TD3) algorithm for fast frequency regulation of MGs with inverter-based DGs. A comparative analysis of the TD3 scheme and the conventional method is made. The results show that the TD3-based virtual inertia control provides better tracking with a 56.6% reduction in frequency deviation and faster transient recovery than the conventional virtual inertia control against a broad range of operational scenarios. Performance metrics and simulation results are shown to demonstrate the feasibility of the proposed control scheme.

Techno-economic optimal planning of an industrial microgrid considering integrated energy resources

Microgrids have benefited energy systems by getting rid of the abundant use of traditional energy resources, replacing them with distributed generations (DGs). The use of DGs in microgrids not only provides clean and green energy but also reduces the gigantic losses in transmission and distribution lines. Widespread adoption of renewable energy in microgrids saves customers from high fuel prices and provides a sustainable replacement for future fossil fuel depletion. Microgrids have proven to be the latest and most advanced power systems due to their new capabilities to operate in both grid-connected and isolated modes. Microgrids use multiple energy sources simultaneously, which can offset the intermittent behavior of renewable energy sources. In this study, we planned and optimized an industrial microgrid with an annual increase in load, which contains dispatchable generation, non-dispatched generation, and energy storage. In addition, to test the different behavior of a microgrid operating independently or in grid-tied mode, four typical days were selected to show the load demand and solar and wind energy forecast data for the entire year. The power output curves for each typical day were analyzed for every year in both stand-alone and grid-connected modes. Furthermore, to validate the feasibility of the microgrid, the investment and operations costs were also calculated in the paper.

Improved Model Predictive Direct Power Control for Parallel Distributed Generation in Grid-Tied Microgrids

This research proposes an improved finite control set direct power model predictive control method (FCS-DPMPC) for grid-tie distributed generation (DG). FCS-DPMPC predicts the system outcomes using the system model. During the next sampling time, a voltage vector is defined using the cost function to minimize the power ripple, consequently allowing flexibility for power regulation. Furthermore, the impact of implementing a one-step delay is studied and compensated through a model forecast pattern. In addition, a new two-step horizon technique has been developed to minimize switching frequency and computation burden. Simulation results for single DG and parallel operated DGs in a grid-tie manner confirm the effectiveness of the suggested control strategy, which signifies that this is an appropriate approach for distributed generation in microgrids.

Optimal Operation of a Distributed Generation Microgrid based on the Multi-Objective Genetic Algorithms

This document describes the application of multiobjective genetic algorithms as techniques and tools to optimize generation and distribution in small microgrids. In this way, genetic algorithms have been used for the allocation of distributed generation to reduce losses and improve the voltage profile. The IEEE14 network has been taken as a study and analysis model. This smart grid has 14 nodes and integrates several generation units, both conventional and renewable, transformers, and multiple loads. In this way, a multi-objective metaheuristic algorithm is proposed with the purpose of planning the power distribution grid based on a series of conditions such as the optimal generation configuration, the minimization of power losses in the lines, power transfer capacity, the reduction of CO2 emissions, and the optimization of the benefits obtained in renewable generation. The overall purpose is the development of an intelligent microgrid management system that is capable of determining the optimal configuration, by estimating demand, energy costs, and operating costs.

An Effective Non-Square Matrix Converter Based Approach for Active Power Control of Multiple DGs in Microgrids: Experimental Implementation

In this paper, a new modulation strategy based on the carrier-based switching strategy for the non-square direct matrix converters (MC) is proposed to control the active power of distributed generation (DG) units. In this strategy, the active power of DGs is controlled by the central input current control of the non-square direct MC independent from the voltage and frequency. Conventionally, each DG has a converter, and for supplying a load with N number of DGs, N number of converters are needed and each converter has its own modulation switching and control strategy to control the power output of each DG. Needless to say, in a microgrid with N number of DGs, the control strategy of each converter has more complex structure than that of a microgrid with one converter, and surely the former strategy entails more volume and price. Using the proposed converter in this paper, it is possible to supply a load with N number of DGs through one converter. Also, the power outputs of all DGs are controlled by a central control strategy. The proposed central control strategy is described and simulated for a typical microgrid. Experimental and simulation results validate the effectiveness of the proposed converter and the proposed strategy. The results demonstrate the applicability and efficiency of the system and verify the theoretical analysis.

Effective Communication-Based Reactive Power Sharing Scheme for Meshed Microgrid in an Islanded Mode

Microgrids (MGs) are the most sought out and feasible solution for the present energy crisis. MG is a group of Distributed Generators (DGs) interacting with each other to provide energy to a defined local area. The inclusion of DGs into the conventional power system at various voltage levels has altered the topology of the power system and their control techniques. Hence, the MGs can no longer be considered as a traditional radial network but rather a meshed network. The control and operation of such practical MGs become a challenge, especially when operated in the islanded mode. This research paper considers a realistic meshed MG operating in an islanded mode for study. In an islanded MG, the issues of real and reactive power sharing among DGs are addressed so that the power contribution of each DG is proportional to its rating, thus preventing overload and ensuring reliable operation. A communication-based virtual impedance estimation is proposed in addition to the droop controller for proportionate real and reactive power sharing among DGs in a meshed MG. With the increased complexity of meshed MG, the proposed communication-based control scheme offers an efficient reactive power sharing between DGs without the feeder and network impedance requirements. A MATLAB simulation study proves the effectiveness of the proposed control strategy for a meshed MG with equal DG ratings and unequal DG ratings under changing load conditions.

A survey on cooperative control strategies for DC microgrids

Distributed generators have been widely used in modern power systems, and microgrids are becoming a key concept for the integration of multiple distributed generators and clusters of loads with great efficiency and high system reliability. In a microgrid, the control strategy is one of the most important issues. Various control schemes have been proposed to achieve the cooperation of distributed generators in a microgrid. This paper surveys cooperative control strategies for multiple distributed generators in DC microgrids. The three popular coordinated control strategies are presented: decentralized control, centralized control, and distributed control. The advantages and drawbacks of the control strategies are compared. Some intelligent control methods such as fuzzy logic control and neural network approaches are also briefly introduced in the context of microgrids. Further research trends and challenges in this area are also discussed.

Harmonic Virtual Impedance Design for Optimal Management of Power Quality in Microgrids

Power quality is an important concern for practical microgrid (MG) applications due to the widespread use of nonlinear loads, and it is characterized by the implicit trade-off between voltage quality in the MG nodes and harmonic current sharing between distributed generators (DGs). Active and passive filters can be used to address this problem. Nevertheless, modification of the control system of the DGs represents a cheaper and more practical solution. To this end, virtual impedances (VIs) can be included in the controller. However, the power quality trade-off is difficult to adjust, especially in the presence of electrical distribution lines. In this article, an optimization algorithm for setting the harmonic VIs of the DGs in a multibus MG is presented. This optimization algorithm can be easily configured for any degree of harmonic current sharing between the DGs, while improving the voltage quality is set as the main objective. Compared to other works presented in the literature, power quality can be managed without relying on time-critical communications since only the values of the harmonic VIs are modified in the optimization problem. The optimization is executed periodically so that the VIs are adapted to changes in the grid. Theoretical developments were validated by simulation in a benchmark model, and in a laboratory environment.

Proportional Power-Sharing Control of Distributed Generators in Microgrids

This research addresses distributed proportional power sharing of inverter-based Distributed Generators (DGs) in microgrids under variations in maximum power capacity of DGs. A microgrid can include renewable energy resources such as wind turbines, solar panels, fuel cells, etc. The intermittent nature of such energy resources causes variations in their maximum power capacities. Since DGs in microgrids can be regarded as Multi-Agent-Systems (MASs), a consensus algorithm is designed to have the DGs generate their output power in proportion to their maximum capacities under capacity fluctuations. A change in power capacity of a DG triggers the consensus algorithm which uses a communication map at the cyber layer to estimate the corresponding change. During the transient time of reaching a consensus, the delivered power may not match the load power demand. To eliminate this mismatch, a control law is augmented that consists of a finite-time consensus algorithm embedded within the overarching power sharing consensus algorithm. The effectiveness of the distributed controller is assessed through simulation of a microgrid consisting of a realistic model of inverter-based DGs.

An Islanding Detection Technique for Inverter-Based Distributed Generation in Microgrids

This article proposes a new passive islanding detection technique for inverter-based distributed generation (DG) in microgrids based on local synchrophasor measurements. The proposed method utilizes the voltage and current phasors measured at the DG connection point (point of connection, PoC). In this paper, the rate of change of voltages and the ratio of the voltage and current magnitudes (VoI index) at the PoC are monitored using micro-phasor measurement units. The developed local measurements based decentralized islanding detection technique is based on the VoI index in order to detect any kind of utility grid frequency fluctuations or oscillations and distinguishing them from islanding condition. The simulation studies confirm that the proposed scheme is accurate, robust, fast, and simple to implement for inverter-based DGs.

Fuzzy Controller Based Power Quality Improvement for a Microgrid with Energy Management System

There is a drastic decrease in availability of conventional energy sources such as coal, natural gas and oil. The need for using non-conventional energy sources has increased due to the fast rate depletion in conventional energy sources and the ill effects of using them. Research work in the area of renewable energy sources has hence been increased throughout the world. The rate at which power demands are increasing, requires the need for interconnections of various power generation methods. For the proper use of conventional and non-conventional distributed generation microgrid is essential. Microgrid combines one or more generation units and helps to use the power generated in efficient manner. Microgrid includes the generating units, battery storage system with power electronic converters. The use of power converter is important, but the presence of converter generates harmonics usually so that the power quality issues have become serious. Many controllers are used to solve power quality problems, where one of them is the Unified Power Quality Controller (UPQC). Problems linked to power quality become serious due to the use of power electronics appliances. Microgrid power quality is maintained by using UPQC compensating devices. To control UPQC, there must be some controller to intimate the voltage sag, swell and flickers. In this paper the fuzzy logic controller is used for UPQC. An energy management system (EMS) is a system used by electrical utility network operators to monitor, regulate and optimize transmission and generation system efficiency. The system model is created using MATLAB by merging all DC-microgrid, EMS and UPQC, to solve power quality issues.

Calibrating synchronous-generator-interfaced DG models in microgrids using multiple event data

Microgrids, consisting of distributed generators (DGs), loads, and energy storage systems, play an important role in future smart grids. In order to evaluate microgrid operations and their dynamic response, it is necessary to develop accurate dynamic models of DGs in microgrids. This paper presents a systematic method to calibrate the model of a synchronous-generator-interfaced DG. Underlying parameters are categorized into two groups, namely, steady-state parameters and time constants, which are estimated in two successive stages using multiple event data. This methodology ensures that the validated model with the estimated parameters are applicable for a set of events. Moreover, assuming that power angle measurements of a synchronous-generator-interfaced DG are unavailable, a modified unscented Kalman filter (UKF) is proposed to facilitate parameter estimation. The effectiveness of the proposed method is validated using field test data of a 2600 kVA diesel generator which is part of an operational microgrid.

Simulation and Optimization of Microgrid Distributed Generation: a Case Study of University Abdelmalek Essaâdi in Morocco

Renewable energy based Distributed Generation (DG) in form of PV power system can tackle the growing demand of depletion of electrical energy resources and the increasing prices of oil. Smart grid is the innovation of recent infrastructure grid and DG is an essential part of it. The Moroccan government has also made significant changes to its renewable energy policy to promote clean energy. The aim of this paper is to show the way to implement the concept of simulating and optimizing the real time of dynamic data in university Abdelmalek Essaâdi with HOMER as platform software. According to the simulation result, it is seen that microgrid implementation in Morocco is beneficial with regards to both optimum solution and sensitivity analysis.

Research on Peer-to-Peer Control Strategy for Microgrid Distributed Generation

In between a plurality of microgrid in complex coordination control problems, this paper proposed a droop control strategy for microgrid distributed generation, which can realize micro grid by cutting load, micro grid operation mode switch to smooth the distributed power supply voltage and frequency control. This method bases on droop control principle, research on the effects of P-f and Q-U droop characteristics, design of the droop controller output filter, power controller, voltage current double loop controller based on the established simulation model of the droop controller and the equivalent control strategy of micro grid simulation model. The results of simulation by Matlab/Simulink, analysis of the variation of the micro grid distributed power switch in islanded and grid connected operation mode and the frequency voltage and power, to verify the correctness and feasibility of droop control strategy.

Analytical Modelling of Premises-Specific Solar-Energy Estimation

Solar energy is great potential for future energy due affordability of solar related panels and equipment. Solar-Energy Microgrid for serving DC and AC loads of areas under consideration. Microgrid is a new concept for making safe, clean, and renewable solar available for use. Most of the countries have developed it solar farm in order to harvest the energy and make it useable for daily use. This energy can be used either for premises-specific loads and also distributed to other regions through the national grid through what is called Distributed Generation (DG). Estimating solar energy potential estimation of premises under target is obviously an exercise that may prove in the design of such DG microgrids. This paper presents two analytical modelling approaches for estimating the solar energy potential of a given geographical location. The two approaches are explored for estimation two very closely related amount of solar energy in kWh for eleven hours of time of a day using Heliocentris Hybrid Energy Lab-System data. The approaches may find utility in the pursuits of the renewable energy estimation needed for designing PV-solar microgrid. The mismatch of 6.31% energy estimation between the two approaches may be due to parametric complaint inaccuracy instead of the approaches employed.

A Modified $Q-\dot{V}$ Droop Control for Accurate Reactive Power Sharing in Distributed Generation Microgrid

The droop-control technology, which can achieve an autonomous power sharing among distributed resources interface converters, provides the advantages of enhanced system reliability and reduced complexity. However, the reactive power sharing accuracy of the conventional Q - V droop method can be degraded due to its dependence on the line impedances. The Q - V̇ droop-control method was proposed to reduce the influence of line impedance. The reactive power sharing accuracy is improved but still affected by the V̇ restoration operation. In this paper, a modified V̇ restoration mechanism is proposed. Its influence on the power sharing is theoretically explained and analyzed. Both simulation and experiment results are presented to verify the proposed method.

Intelligent Fault Detection Scheme for Microgrids With Wavelet-Based Deep Neural Networks

Fault detection is essential in microgrid control and operation, as it enables the system to perform fast fault isolation and recovery. The adoption of inverter-interfaced distributed generation in microgrids makes traditional fault detection schemes inappropriate due to their dependence on significant fault currents. In this paper, we devise an intelligent fault detection scheme for microgrid based on wavelet transform and deep neural networks. The proposed scheme aims to provide fast fault type, phase, and location information for microgrid protection and service recovery. In the scheme, branch current measurements sampled by protective relays are pre-processed by discrete wavelet transform to extract statistical features. Then all available data is input into deep neural networks to develop fault information. Compared with previous work, the proposed scheme can provide significantly better fault type classification accuracy. Moreover, the scheme can also detect the locations of faults, which are unavailable in previous work. To evaluate the performance of the proposed fault detection scheme, we conduct a comprehensive evaluation study on the CERTS microgrid and IEEE 34-bus system. The simulation results demonstrate the efficacy of the proposed scheme in terms of detection accuracy, computation time, and robustness against measurement uncertainty.

Fault analysis for renewable energy power system in micro-grid distributed generation

<span>In distribution system, wind power plants are becoming popular renewable energy sources. It employs Doubly Fed Induction Generator (DFIG) to generate power based on wind conversion. Short and long transmission lines, presence of faults and presence of Static Synchronous Compensator (STATCOM) are highlighted issues in this paper. Basically, this research develops investigations on some electrical variables such as voltage and current to control them. Distribution Static Synchronous Compensator (DSTATCOM) is proposed in this paper. Wind farm acts as a source while DSTATCOM is connected to the distribution system with a DFIG based wind farm. The controller proposed is DSTATCOM is modeled and simulated in MATLAB/SIMULINK and the results are given. A microgrid based small signal analysis is performed in the laboratory using MATLAB and different comparisons are made and simulation case studies are presented and validated.</span>

State feedback control aware stochastic transmitting latency in cyber-physical power system

Distributed sensor networks with a great number of sensors realize information gathering, transmitting, and controlling, which will greatly improve the reliability and efficiency of industrial infrastructure systems, such as cyber-physical power system. Cyber-physical power system is one of the heuristic systems tightly coupled by a continuous-time electrical power system and a discrete-time information system. The transmitting latency, packets disorder, or loss will fail system convergence, even unstable under disturbance. This article studies the effect of long latency on cyber-physical power system frequency stability based on network control theory and establishes a heuristic model to express the continuous-time distributed generation system and the discrete-time distributed sensor network. A new state feedback controller is designed based on the stochastic optimal control theory to solve the micro-grid’s frequency stability problem with stochastic latency disturbance. Finally, we have conducted an extensive evaluation study using a real distributed generation micro-grid system. The simulation results show that the new controller reduces the influence of distributed sensor networks transmitting latency on the frequency stability, and the frequency dynamic process in the distributed generation micro-grid has smaller overshoot and obtains faster dynamic response speed.