Islanded Microgrid System Research Articles

Cost-effective synchronization strategy for distributed generators in islanded microgrids

A microgrid (MG) is an effective way to integrate various distributed generators (DGs) into a power distribution system. The synchronization of DG voltage with MG voltage is indispensable to prevent inrush currents before connection to a MG system and for working in parallel with other DGs in the MG. In the past, synchronization in terms of both phase and magnitude was realized using additional voltage sensors to measure the MG voltage. However, this increased the system cost. In this paper, a cost-effective synchronization strategy is proposed to allow a DG to connect with an islanded MG system without any additional voltage sensors. The feasibility and effectiveness of the proposed strategy were validated by experiment with a scaled-down islanded microgrid.

Design and implementation of an islanded hybrid microgrid system for a large resort center for Penang Island with the proper application of excess energy

AbstractThe energy demand is growing daily at an accelerated pace due to the internationalization and development of civilization. Yet proper economic utilization of additional energy generated by the Islanded Hybrid Microgrid System (IHMS) that was not consumed by the load is a major global challenge. To resolve the above‐stated summons, this research focuses on a multi‐optimal combination of IHMS for the Penang Hill Resort located on Penang Island, Malaysia, with effective use of redundant energy. To avail this excess energy efficiently, an electrical heater along with a storage tank has been designed concerning diversion load having proper energy management. Furthermore, the system design has adopted the HOMER Pro software for profitable and practical analysis. Alongside, MATLAB Simulink had stabilized the whole system by representing the values of 2068 and 19,072 kW that have been determined as the approximated peak and average load per day for the resort. Moreover, the optimized IHMS is comprehended of Photovoltaic (PV) cells, Diesel Generator, Wind Turbine, Battery, and Converter. Adjacent to this, the optimized system ensued in having a Net Present Cost (NPC) of $21.66 million, Renewable Fraction (RF) of 27.8%, Cost of Energy (COE) of $0.165/kWh, CO2 of 1,735,836 kg/year, and excess energy of 517.29MWh per annum. Since the diesel generator lead system was included in the scheme, a COE of $0.217/kWh, CO2 of 5,124,879 kg/year, and NPC of $23.25 million were attained. The amount of excess energy is effectively utilized with an electrical heater as a diversion load.

Risk assessment of renewable energy-based island microgrid using the HFLTS-cloud model method

Difficulty in power supply has always been the main factor hindering the sustainable development of islands. It is an effective way to address the energy supply issue of off-grid islands by building island microgrid system with abundant renewable energy, such as wind energy and solar energy. However, island microgrids offer a mix of the high penetration rate of renewable energy and the complex island environment, being confronted with many challenges in the whole life cycle. To implement the project smoothly and make full use of the advantages of renewable energy-based island microgrids, a risk assessment must be incorporated. In this study, based on a three-dimensional model, we take a holistic view of identifying risks that includes four categories (technical, economic, environmental and social aspects). Later, a reasonable and applicable risk assessment framework is constructed, in which the fuzziness and randomness of information are taken into consideration. The hesitant fuzzy linguistic term set is used to endow the index evaluation information, and the cloud model is used to transform the evaluation information. The final results show that the overall risk level of China’s island microgrids is “Slightly High”, particularly in the technical aspect. Furthermore, corresponding mitigation strategies are put forward. This study conducts a comprehensive study on the risk assessment and risk response measures of island microgrids, which is conducive to deal with potential risks, thereby to minimize the loss and promote the island microgrid development.

Double deep Q‐learning coordinated control of hybrid energy storage system in island micro‐grid

It is difficult for a single energy storage to meet both power and energy requirements in the island micro-grid because of the randomness of wind and solar irradiation. A reasonable way is to use hybrid energy storage in the island micro-grid. For the energy management and optimization control of energy storage systems, there are various problems with traditional methods, such as the large computational complexity in dynamic programming. Q-learning has recently been applied to the optimal control of energy storage systems. Due to the limitations of the Q-learning algorithm in the state space, this article uses the Double deep Q-learning (DQN) algorithm to design the control strategy of energy storage systems. It is applied to an island Micro-grid system consisting of photovoltaic (PV), wind turbine, hydrogen storage (long-term energy storage devices), and battery (short-term energy storage devices). Transform the coordinated control of the hybrid energy storage system into a sequence decision problem. Due to the influence of renewable energy, load and other factors, different control strategies have different effects. DDQN algorithm combines the perception ability of deep learning with the decision-making ability of reinforcement learning which can realize real-time online decision control after training. Experimental results show that, the method of this article can be effectively processed for different weather scenarios and increase utilization of renewable energy.

Deadbeat PQ Control for Islanded Smart Grids

The dynamic performance of smart (micro)grids depends on the proper selection of the controller gains and power-sharing parameters. This manuscript describes the control design to achieve a deadbeat desirable performance in terms of: i) Zero steady-state error. ii) Minimum rise time. iii) Minimum settling time. iv) Less than 2% overshoot/undershoot. This paper considers an Islanded microgrid system composed of two distributed generation (DG) units. Each DG unit includes three-phase pulse width modulation (PWM) inverter. The proposed controllers are proportional- integral (PI) type. The Controllers gains of the inverters and the Phase Locked Loop (PLL) parameters are designed to guarantee deadbeat dynamic performance in terms of minimal overshoot and system stability. The Particle Swarm Optimization (PSO) is used to tune the controller parameters of the current, PQ loops, and the PLL. The proposed controllers are compared with the traditional (Ziegler and Nichols), auto-tuned, and interior-point methods to shows the excellence of the proposed technique. Results authenticate and endorse the effectiveness of the proposed controllers and PLL design technique to achieve the desired deadbeat response of the study microgrid system.

State of Charge Control Integrated with Load Frequency Control for BESS in Islanded Microgrid

The dependence of distributed generations (DGs) on climate conditions and fluctuating load demands are the challenges for the implementation of battery energy storage systems (BESSs) in islanded microgrids. BESS participation in system frequency regulation becomes one of the solutions to those challenges. Frequency regulation by BESS can be realized by applying the load-frequency control (LFC) in BESS. However, this participation clearly poses problems for the battery state of charge (SOC), as the battery is often overcharged or undercharged. In this paper, a control that maintains SOC at a certain level is introduced. This control strategy focuses on the battery operation function, which is determined from five control scenarios. All scenarios are achieved by applying the droop reference shifting method in the LFC to allow battery operation change. Control verification is carried out on an islanded microgrid system that experiences load demand changes and photovoltaic (PV) output power changes. The test results show that the SOC is maintained at 45–75% by applying load and PV power variations. The results correspond to the predetermined criteria control.

Coordinated Control and Dynamic Optimal Dispatch of Islanded Microgrid System Based on GWO

As an effective carrier of renewable distributed power sources, such as wind power and photovoltaics, microgrids have attracted increasing attention as the energy crisis becomes more serious. This paper focuses on the symmetry between the dynamic optimal dispatch and the coordinated control of islanded microgrid to determine the optimal system configuration that can reliably meet energy needs. In order to solve energy management problems, operating costs and environmental benefits, a novel methodology that combines dynamic optimal dispatch and Grey Wolf Optimizer (GWO) is developed in this study to obtain the best output of different system components. This is to minimize the total cost of microgrid power generation and reduce pollutant emissions. In addition, a comparison is carried out between GWO and Particle Swarm Optimization (PSO). Moreover, the comparison between system configurations in six different scenarios and the effectiveness of GWO in solving optimization problems are presented. Finally, the simulation results show that GWO is more effective than PSO in determining the optimization parameters and the utilization rate of renewable energy in different scenarios is up to 92.96%. The simulations and experimental results verify the successful performance of the research method proposed in this study.

MESO-based robustness voltage sliding mode control for AC islanded microgrid

A new modified extended state observer (MESO)-based robustness voltage sliding mode control (SMC) strategy is proposed for an AC islanded microgrid under system uncertainties including system parameter and load variation. First, the disturbance effect on the system is regarded as a lumped uncertainty, and a state space model of the uncertain islanded microgrid system is established. Then, a modified extended state observer is designed to estimate external disturbances and internal perturbation. Finally, considering the lumped uncertainty, a sliding mode controller with a multi-power reaching law is proposed to enable the output voltage of the system to track its reference voltage rapidly and accurately, and to enhance the robustness of the system. The simulation results confirm that the proposed robustness voltage control strategy can perform satisfactory voltage control and demonstrate a strong capability to reject parameter and load variation.

Optimal design of a robust FO-Multistage controller for the frequency awareness of an islanded AC microgrid under i-SCA algorithm

ABSTRACTThe article contributes a research work on optimal designing of a Fractional Order-Multistage PD/(1 + PI) controller (FO-Multistage) for controlling the frequency of an islanded AC Microgrid under various uncertainties. The renewable energy-based proposed Microgrid system is configured with the penetration of numbers of distributed generation (DG) systems. However, the large uncertainties and low inertia of most DG system result in fluctuations of frequency in islanded microgrid system. To maintain nominal frequency, the article proposes a robust FO-Multistage controller to constitute a secondary control loop in the microgrid system. An improved-sine cosine algorithm (i-SCA) is suggested to optimally design the robust FO-Multistage controller under various uncertainties. The system performance is also verified under stochastic model-generated wind and solar power uncertainties. The viability of the proposed approaches is demonstrated through a suitable comparative analysis over some conventional approaches. It has been investigated that the system performance has been improved gracefully with the proposed i-SCA-optimised FO-Multistage controller.

An inversion-free sparse Zbus power flow algorithm for large-scale droop controlled islanded microgrids

A main feature of microgrid systems is their ability to operate in isolation from the main grid, i.e., islanded microgrid (IMG) operation. The power flow (PF) problem of IMGs has been shown to exhibit several distinct features compared to that of traditional distribution systems; namely: (1) having no slack bus, (2) frequency being a PF variable, and (3) generators controlled as droop units. Several studies in the literature have focused on and addressed these particularities. Still, existing IMG PF algorithms are not suitable for the analysis of large-scale IMG systems comprising thousands of buses. On the other hand, practical distribution systems and the IMGs created within such systems may in many cases comprise thousands of electric nodes. As such, the implementation of the microgrid concept in real distribution systems requires PF tools suitable for the analysis of large-scale IMGs. This paper proposes a Zbus PF algorithm for droop-controlled IMG that is particularly suited for sparse implementation. The proposed algorithm is inversion-free, does not require bus renumbering and is independent of third party sparse linear algebra libraries. The accuracy and effectiveness of the proposed algorithm is validated through several case studies considering balanced and unbalanced test systems.

Techno‐economic analysis of photovoltaic‐biomass‐based microgrid system for reliable rural electrification

Burning of crop residues aggravates already existing pollution caused by coal-based thermal power plants in most of the developing countries such as India. Crop residue consists mainly of organic compounds and can be efficiently utilized to produce biogas in a sustainable way through anaerobic digestion. This study proposes a microgrid (MG) system for the effective utilization of available renewable resources and reliable rural electrification. The detailed techno-economic analysis of the design of a solar and biomass-based MG system was performed. Two MG systems, namely, MG-A having photovoltaic (PV), biomass-based generating units, connected to an unreliable grid, and MG-B having PV, biomass, and battery units working in the isolated mode, were designed for reliable rural electrification. Different performance-assessment parameters such as generation responses, component cost, project feasibility, emissions, inflation rate, and fuel prices were taken into account during the investigation. This study concludes that a grid-connected MG system is more capable of providing reliable electricity with reduced energy costs than an islanded MG system. In addition, the proposed MG power system helps to mitigate pollutant emission into the atmosphere by effectively utilizing the abundant biomass resources.

Illustration of demand response supported co‐ordinated system performance evaluation of YSGA optimized dual stage PIFOD‐(1 + PI) controller employed with wind‐tidal‐biodiesel based independent two‐area interconnected microgrid system

This study proposes an earliest approach toward coordinated frequency stabilisation of wind turbine driven generator-tidal power generation-biodiesel driven generator-micro-turbine generator-based islanded two-area interconnected microgrid system with demand response support (DRS) mechanism. A recent bio-inspired optimisation technique, named yellow saddle goatfish algorithm (YSGA) is employed to optimally tune the controller gains. The comparative dynamic performance of conventional proportional–integral–derivative (CPID), fractional order (FO) PID, dual-stage PIFOD-one plus PI [PIFOD-(1 + PI)] controllers’ parameters optimised by several algorithmic tools such as particle swarm optimisation, firefly algorithmic tool, salp swarm technique and YSGA clearly designates the superiority of YSGA-PIFOD-(1 + PI) controller under different scenarios (considering the real-time recorded wind and load data) in terms of change in frequency, tie-line power fluctuation and objective function. Furthermore, the impact of the DRS mechanism in both areas is analysed first time under real-time wind and load disturbances. Finally, the rigorous sensitivity analysis of YSGA-optimised PIFOD-(1 + PI) controller has been conducted with the variation of wind turbine driven generator gain, ±30% change in synchronising tie-line factor, frequency bias value, microgrid system time constant and + 30% change in loading magnitude without retuning the optimal base condition values.

Effective Coordinated Virtual Impedance Control for Accurate Power Sharing in Islanded Microgrid

In a practical islanded microgrid system, the mismatched line impedance causes serious problems, such as inaccurate power sharing and circulating current. In order to overcome these issues, this article proposes a coordinated virtual impedance control strategy for distributed generation (DGs) units. In the proposed control strategy, both virtual resistance and virtual inductance are simultaneously tuned to compensate the mismatched line impedance among DGs, and the microgrid system stability is enhanced by increasing damping for the whole system. Also, the virtual impedance is adaptively regulated in order to guarantee a good power-sharing performance even if the communication is interrupted or the load changes suddenly. The controller design process and theoretical analysis of the whole system are presented in detail based on small-signal analysis. The feasibility and effectiveness of the proposed control strategy were validated by simulations and experiments with a 1.3-kVA prototype microgrid composed of three DGs.

SyRG-PV-BES-Based Standalone Microgrid Using Approximate Multipliers Based Adaptive Control Algorithm

This article deals with the adaptive control algorithm to maximize the distributed generations (DGs) in islanded microgrid. The approximate multiplier least mean square (AMLMS) control scheme is used for the extraction of fundamental load component with reduced steady state error and faster convergence to provide better performance than conventional LMS control. This control focuses on reduction of complexity of LMS by adding multipliers in the finite impulse response filter and updating the coefficients. The AMLMS control algorithm for a voltage source converter is also effective in compensating harmonics for power quality improvement of islanded microgrid system while feeding nonlinear load. In an islanded microgrid at ac side, a synchronous reluctance generator based pico-hydropower generator is used because it is economical than other conventional generators. At dc side, a photovoltaic array and a bidirectional dc–dc converter (BDC) are used. The BDC with a storage battery maintains the optimal power flow to provide the power equilibrium between load and sources through dc-link voltage regulation. The BDC also mitigates the second order harmonic from the battery charging and discharging current. Test and simulation results validate the effectiveness of AMLMS control under steady and dynamic conditions of solar insolation change and load unbalance.

Optimal performance of a self‐healing microgrid

This study proposes a multi-objective binary differential evolution algorithm to reconfigure the system and restore the loads within the stand-alone microgrid. The approach aims to attain a restoration path having maximum power flow with the minimum number of interrupted loads and switching operations. To execute the discrete optimisation strategy, the power network has been reframed as a capacitated graph, where the edges are capacitated by the loading capacity of the feeder. The strategy implements the maximum power flow theorem, which has been enhanced using the centrality index. The major operational constraints of the microgrid have been strictly followed to maintain system stability. The proposed restoration algorithm is examined on an islanded 13-bus microgrid system with the two test scenarios of irregular power generation, and the fault instance is isolating a healthy section of a microgrid. Moreover, the efficacy of the proposed approach has been further examined on a 39-bus system, and the results are compared with the other optimisation strategies implemented for restoration.

Density-based Global Sensitivity Analysis of Islanded Microgrid Loadability Considering Distributed Energy Resource Integration

With the proliferation of renewable energy and electric vehicles (EVs), there have been increasing uncertainties in power systems. Identifying the influencing random variables will reduce the effort in uncertainty modeling and improve the controllability of power systems. In this paper, a density-based global sensitivity analysis (GSA) method is proposed to evaluate the influence of uncertainties on islanded microgrids (IMGs). Firstly, the maximum IMG loadability evaluation model is established to assess the distance from the current operation point to the critical operation point. Secondly, the Borgonovo method, which is a density-based GSA method, is used to evaluate the influence of input variables on IMG loadability. Thirdly, to improve GSA efficiency, a modified Kriging model is used to obtain a surrogate model of IMG loadability, and Borgonovo indices are calculated based on the surrogate model. Finally, the proposed method is tested on a 38-bus IMG system. Simulation results are compared with those considering other methods to validate the effectiveness of the proposed method. Energy storage systems are considered to diminish the influence of critical uncertainties on IMG operation.

Robust Frequency Control of an Islanded AC Micro Grid using BDA Optimized 3DOF Controller under Plug in Electric Vehicle

The article presents the effectiveness of a Binary Dragonfly Algorithm (BDA) based 3-DOF controller for robust frequency control in an islanded AC micro-grid system under different uncertainties. A micro-grid is incorporated with the integration of various renewable energy based distributed generations (DG). The proposed micro-grid system is structured with wind turbine generator (WTG), Photo voltaic (PV) system, Diesel engine generator (DEG), Micro-turbines (MT), Aqua electrolyzer based Fuel Cells(FC) and with few energy storage devices i.e Battery energy storage (BES) and Flywheel energy storage (FES). Moreover a chargeable plug in electric vehicle is effected as load side demand while obtaining frequency control mechanism in micro-grid system. However large dynamics, low inertia and incurred uncertainties of most DG system affects system performance especially on system frequency seriously. In view of this to obtain robust control mechanism in islanded micro-grid system the article proposes a novel Binary Dragonfly Algorithm based 3-DOF controller to ensure servicing of good quality power to remote consumers. The performances of proposed BDA optimized 3-DOF controller is compared with conventional PSO, GA technique based PID and PI controller in order to justify supremacy of proposed approaches. Finally it has been suggested that the proposed BDA optimized 3-DOF controller is more effectiveness over other optimized controllers.

Distributed Resilient Adaptive Control of Islanded Microgrids Under Sensor/Actuator Faults

To compensate for the voltage and frequency deviations caused by the droop control in islanded microgrids (MGs), employing an additional control level, called the secondary control, is necessary. Therefore, distributed control methods based on the sparse communication network, are recently employed in secondary control of MGs, because they are more reliable and flexible. However, traditional methods use the centralized communication network, which is neither economical nor efficient due to its large communication burden. Distributed control methods solve many challenges in the secondary layer of MGs, such as disturbances, uncertainties, unmodelled dynamics, noises, delays, attacks, and actuator faults. This paper proposes the novel resilient adaptive consensus-based voltage and frequency control protocols to compensate for the adverse effects of both sensor and actuator faults in communication network channels of islanded MGs. To this end, local adaptive sensor and actuator compensators eliminate the adverse effects of failures on sensors and actuators. The robust stability analysis based on the Lyapunov analysis is given to validate the results. Finally, the understudy islanded MG system is built in MATLAB/SimPowerSystems to verify the theoretical results. It is shown that the proposed secondary control strategies based on the adaptive protocols can highly increase the reliability and resiliency of the MG system compared with the existing distributed resilient methods.

Tidal Energy Integrated Robust Frequency Control of an Islanded AC Microgrid with Improved-MFO Tuned Tilt Controller

In recent electrical energy scenario different renewable energy based distribution generation (DG) systems have been developed to provide electrical power to distant and remote consumers. In view of this current research article presents a Tidal Power Plant (TPP) and its integration with an Islanded AC Microgrid system. The tidal energy based TPP is modelled to generate required electrical power. However the inherent dynamic behaviour of TPP largely affects the microgrid system frequency especially in islanded mode of operation. In regard to this to obtain necessary control mechanism in an islanded AC microgrid system , present research article proposes a tilt multistage TDF/(1+TI) controller and to show effectiveness of proposed tilt controller for microgrid control it has been compared with multistage PDF/1+PI and PID controllers. To obtain optimal gain parameters of above implemented controllers an Improved- Moth Flame Optimization (I-MFO) technique has been proposed for this study. To justify viability of proposed I-MFO algorithm its performances have been compared with original MFO algorithm. Finally it has been noticed that to obtain robust frequency control in an islanded AC microgrid system, proposed I-MFO optimized tilt multistage controller exhibits outstanding performance under wind, solar and tidal energy uncertainties.

Optimal Configuration of Island Microgrid Considering Wind/Photovoltaic/Line/Storage and Seawater Desalination Load

Safe and reliable power supply is the basic guarantee for the development and construction of the island. Aimed at the problem of lack of electricity and water on the island, the paper proposes an optimal configuration method of island microgrid considering wind/photovoltaic/line/storage and seawater desalination loads. Firstly, the paper analyzes the load demand and the characteristics of renewable resources on the island, and proposes a grid-connected island microgrid system with multiple energy types and seawater desalination load. On this basis, an optimization model with the minimum annual cost as the objective function is established. The mixed integer linear programming(MILP) algorithm is used to optimize the capacity configuration and operation mode of the island microgrid system simultaneously. Finally, taking an island in the eastern coast of China as an example, the effectiveness of the optimal configuration method is verified through scenario analysis.