Proposed Microgrid System Research Articles

A systematic decision-making approach to optimizing microgrid energy sources in rural areas through diesel generator operation and techno-economic analysis: A case study of Baron Technopark in Indonesia

Microgrid systems are part of the most reliable energy supply technologies for rural communities that do not have access to electricity but the system is generally dominated by diesel generators (DG). The implementation of de-dieselization programs to ensure efficient diesel operations requires addressing several scenarios such as the replacement of diesel completely with 100% renewable energy sources at a significant cost. The design and selection of appropriate configuration, as well as operating patterns, need to be considered in adopting economical and reliable microgrid systems. Therefore, this study aimed to design an optimal configuration and operational pattern for microgrid systems for the frontier, outermost, and least developed (3T) regions using Baron Techno Park (BTP) in Indonesia as a case study. The optimization was conducted through HOMER software combined with benefit-cost analysis and the focus was on daily load variations, selection of control algorithms, reconfiguration of the power supply system, and setting of the diesel generator operating hours. The results showed that the optimum configuration was achieved using loads of resort, 24 kWp of PV, 288 kWh of BESS, load-following (LF) as dispatch controller, and 25 kVa of DG. Moreover, the proposed microgrid system produced 12% excess energy, 36% renewable fraction (RF), 13.25 tons reduction in CO2 emissions per year, $0.28 LCOE per kWh, $250,478 NPC, and a benefit-cost ratio (BCR) of 0.89. It also had a potential energy efficiency savings of 55.56% and a cost efficiency of 20.95% compared to existing system configurations. In conclusion, the study showed that the addition of DG to microgrid systems in 3T areas was more optimal than using only PV and batteries. An effective operating schedule for the DG was also necessary to improve RF and reduce expenses. Furthermore, other energy storage devices considered less expensive than batteries could be introduced to improve the economics of microgrid systems in the 3T region.

Control techniques for operation of roof-top solar photovoltaics based microgrid in islanded mode

This paper presents the control techniques for the operation of roof-top solar photovoltaics based single-phase ac microgrid in islanded mode. The proposed microgrid consists of four roof-top photovoltaics on various buildings, battery energy storage system in each building, and loads. In each building, the roof-top photovoltaic system is connected to the single-phase ac loads and proposed single-phase ac microgrid through the two-stage converter, which consists of dc-dc boost converter and bidirectional single-phase voltage source converter. A bidirectional dc-dc converter is used to connect the battery energy storage system to the photovoltaic system. The control technique of the bidirectional single-phase voltage source converter, using the feed-forward and feed-back control signals, has been suggested into a rotating d-q synchronous reference frame, with the dual controllers, for controlling the power mismatch and rated sinusoidal ac voltage of the microgrid. The control technique of the bidirectional dc-dc converter, used for the battery energy storage system, is implemented with two voltage controllers and one current controller for managing of the power mismatch in the proposed microgrid system. In this work, the power control algorithms have also been developed, which are aimed to manage the power balance in the single roof-top PV based building as well as in the proposed microgrid, under islanded mode, for various operating scenarios including fault condition.

Modified Differential Evolution Algorithm for Governing Virtual Inertia of an Isolated Microgrid Integrating Electric Vehicles

In modern power systems, there is a greater penetration of renewable sources, resulting in the expansion of microgrid. By implementing RES instead of conventional synchronous machines, the system’s overall inertia is significantly reduced. Modern and future power systems must reduce system inertia and keep the frequency at its nominal value since frequency oscillation impacts on the functionality, stability, and resilience of the system. Therefore, creating a stable, scalable, and reliable virtual inertia control system is crucial to effectively minimize the deviations during significant contingencies. Consequently, taking into account the probable issues, the foremost objective of this research work is to improve the dynamic security of an island microgrid through the implementation of a frequency control concept based on virtual inertia control. In the research study, the proposed microgrid system comprises of photovoltaics, wind-generating units, thermal power units, storage units, electric vehicles (EVs), and loads. A cascaded PIDFN controller is optimally designed using a novel metaheuristic modified differential evolution (MDE) algorithm that regulates the frequency based on virtual inertia control. In the MATLAB®/SIMULINK environment, various operating situations such as load variations, RES, and EVs disconnection are investigated, and the performance of the VIC-based MDE controller was compared to that of other controllers based on evolutionary optimization algorithms such as DE and TLBO. The results validate that the recommended virtual inertia control strategy enhances the reliability of the system.

Modelling and control of grid connected microgrid with hybrid energy storage system

<p class="JESAbstract"><span lang="EN-US">This paper presents a photovoltaic (PV) microgrid with battery and super capacitor hybrid energy storage systems. The proposed microgrid system is designed for both grid connected and standalone mode with coordinated control-based energy management system, which controls DC link voltage, voltage and frequency balance at point of common coupling. DC link voltage control is implemented using dual loop PI controller-based voltage controller and inverter control is based on D-Q reference frame technique. The microgrid system is demonstrated in MATLAB/Simulink. The</span><span lang="EN-US"> presentati</span><span lang="EN-US">on</span><span lang="EN-US"> of the planned energy supervision system is analyzed for varying generation and load condition. In the proposed microgrid the battery energy storage system is utilized to provide long term energy during average power requirement and supercapacitor energy storage system is utilized to provide short term power requirements during sudden load variation, generation variation and during transition of modes. Designed energy management system performs effectively in grid connected mode, standalone mode with smooth transition between the modes. And it maintains dc bus voltage of the microgrid constant irrespective of load and generation variations and also during mode changing conditions.</span></p>

Operational strategy and capacity optimization of standalone solar-wind-biomass-fuel cell energy system using hybrid LF-SSA algorithms

This paper presents a framework for the efficient design and evaluation of a standalone hybrid renewable energy system (HRES) to meet the energy requirements of a rural community in the north-eastern region of Nigeria. The proposed microgrid system incorporates solar photovoltaic, wind turbines, biomass gasifier, fuel cell, and Battery storage. The sizing of each component is determined through the utilization of real local meteorological data and the load demand over a year, employing the Levy flight-salp swarm algorithms (LF-SSA). The optimization objective is to minimize the annualized system cost (ASC) of the HRES, while also considering the reliability constraint of Loss of power supply probability (LPSP). The comparative outcomes demonstrate that the LF-SSA surpasses other examined algorithms, namely the salp swarm, genetic algorithm, and HOMER software by achieving substantial cost savings of $29033, $50796, $191771 respectively in relation to the proposed HRES. The result further shows that, the LF-SSA provides the lowest LCOE of $0.933162/kWh, in contrast to SSA at $0.947737/kWh, GA at $0.958660/kWh, and HOMER at $1.075351/kWh. Additionally, the results indicate that the implemented Energy Management System (EMS) has successfully facilitated the establishment of an environmentally friendly and cost-effective energy system.

Synergetic process between wind power and sewage sludge pyrolysis in a novel renewable-energy microgrid system

AbstractTo relieve the stress of sewage sludge (SS) disposal and effectively increase the use of renewable energy, a novel renewable-energy microgrid system (REMS) was developed, specifically designed to integrate a wind power plant (WPP) with energy storage and the SS pyrolysis process for heat and power generation. Based on a lab-scale pyrolysis experiment and 7-day numerical analysis, we studied the energy-recycling potential of SS and simulated the operational behaviours of REMS. According to the results, the calorific values of the pyrolytic gaseous and liquid products were better than those of the raw material, at 16.19 and 33.53 MJ/kg, respectively. The proposed REMS performed well in power supply and energy utilization with a design performance index of 99.23 when the WPP capacity was 200 MWe and the initial wind-energy curtailment rate was 30%. It indicates that by converting SS into flammable gas, condensable liquid and carbon-rich solid residue, curtailed wind energy could be saved and the synergy between wind power and the SS pyrolysis process enabled the proposed microgrid system to effectively utilize renewable energy and provide reliable on-demand power service. The REMS installed with a 155-MWe WPP achieved the optimal design in system performance, environmental benefit and construction cost under the initial wind-curtailment rate of 34.12%. The design scheme makes REMS capable of satisfying the 15.10-GWh power demand of end users and the 1700-t/day SS disposal need, and the curtailed wind energy could be reduced to zero.

Dynamic modeling and experimental validation of a standalone hybrid microgrid system in Fukuoka, Japan

Microgrids are essential for creating next-generation energy systems because they allow loads, energy storage systems (ESS), and distributed energy resources (DER) to be efficiently and seamlessly integrated. This study presents the dynamic modeling and simulation of an off-grid direct current (DC) microgrid consisting of the photovoltaic (PV) panel, wind turbine, battery, and a DC load incorporating simple, comprehensible, and well-established component-based power control strategies for quality power output. In addition, the main emphasis is on the real-time experimental validation of the dynamic simulation model achieved by designing and developing an indoor test system architecture. A 48-hourly meteorological dataset from Fukuoka, Japan, was used to validate the developed model. The results show a reasonable range of Root-mean-square deviation (RMSE), suggesting that the simulation model can precisely depict the model the dynamic operation of a hybrid DC microgrid system. Furthermore, detailed scenario analysis for sunny, windy, rainy, and cloudy considering real-time meteorological conditions for 72 h of simulation reveals that the proposed microgrid system can effectively meet the load in any situation with a sufficiency factor above 1, making it a self-sustaining hybrid renewable microgrid for residential areas in Japan. The study highlights the significance of understanding microgrid operation energy management with actual implementation.

Fast reaching law based integral terminal sliding mode controller for photovoltaic-fuel cell-battery-super capacitor based direct-current microgrid

In this paper, a fast reaching law based integral terminal sliding mode controller has been designed for photovoltaic based DC microgrid system. The proposed microgrid system comprised of photovoltaic system as main energy source and fuel cell, battery and supercapacitor as auxiliary energy sources. To avoid the stress on individual energy sources, an energy management system has been devised to allocate the load among these energy sources. Using the Lyapunov stability criteria, the stability of proposed framework has been validated. The performance of the proposed controller has been verified by simulating the dc microgrid under varying environmental conditions and load demands in MATLAB/Simulink platform. The comparison of the proposed control laws against PID and lyapunov controllers has been provided in order to assess its accuracy and robustness. The hardware-in-loop experiments have been performed to verify the real-time efficacy of the proposed microgrid system.

Control of hybrid DC/AC microgrid system employing fuel cell and solar photovoltaic sources using grey wolf optimization

Abstract The outcome of this study is to improve and enhance the power quality of the hybrid DC/AC microgrid (MG). The photovoltaic (PV) system and the proton exchange membrane fuel cell (PEMFC) are used as renewable energy sources to deliver the optimum active power to the utility grid. The MG system based on the PV system, PEMFC and voltage source inverter is modelled mathematically. Also, the maximum power point tracking (MPPT)-based grey wolf optimization (GWO) is used to increase the PV module efficiency and enhance performance. Also, to improve the PEMFC performance, a digital proportional-integral controller is used to control the PEMFC circuit. The proposed inverter is controlled using synchronous reference frame theory, called the direct-quadrature (dq) control method. Hence, the performance of the proposed MG system is tested using MATLAB® for various weather and loading conditions. From the simulation results, the proposed MG system can deliver and absorb an active power based on the PV and fuel cell characteristics. As a result, the hybrid DC/AC MG is enhanced in terms of stabilization of the DC-bus voltage. Also, the power quality of the MG is improved using GWO optimization based on MPPT. Finally, good results are achieved using GWO in terms of the total harmonic distortion of the output current of 2.3% and higher efficiency of 98.9%.

Study of power management of standalone DC microgrids with battery supercapacitor hybrid energy storage system

<p>In the last years, renewable energy (RE) is increasing widely in the energy sector, and microgrid technology is overgrowing. In this paper, stand-alone microgrid using solar photovoltaic (PV) energy as a source of renewable energy is simulated to provide power for direct current (DC) loads with hybrid energy storage system (HESS) which consists of battery and supercapacitor bank. The proposed microgrid system is tested under various cases of load and variable irradiance to confirm and validate the proposed management strategy to remain the DC bus voltage within a stable limit. The performance of DC microgrid is comparing with and without supercapacitor (SC) bank and notes a desirable decrease in the magnitude of transient voltage when using HESS. The sun power SPR-E19-320 standard was simulated to analyze system performance taking into account the constant load demand. Note that HESS helps reduce transient of DC voltage very effectively in all situations. Very large transients arise due to sudden changes in load demand is also compensated by HESS. The results obtained indicate that the stand-alone DC microgrid with HESS is very beneficial for reducing transient of DC-link voltage that occurs due to sudden change in load or fault. The proposed system is performed by MATLAB/Simulink environment.</p>

Energy Management of a Renewable Hybrid Isolated DC Microgrid

Abstract: Hybrid microgrid is the key solution to energize remote rural areas. The microgrid system incorporates more than one Distributed Renewable Energy (DRE) source to complement one another. This paper proposes a hybrid DC microgrid system to be operated in isolated mode. The proposed microgrid consists of a PMSG based Wind Turbine, PV array, and Lead-acid battery as an energy storage device. The Wind Turbine generator is connected to the DC bus through a Three-phase Diode Bridge Rectifier. The PV array is tied to the DC bus by a Boost converter and incremental conductance algorithm is used to extract the maximum power from the PV array. The battery uses a bidirectional converter for charging and discharging. A simple PI-based closed-loop control system is incorporated for proper energy management. The bus voltage is maintained either by the boost converter or the bidirectional converter depending upon the operating condition. The proposed microgrid system is modeled in MATLAB/SIMULINK software. Simulation of this model is done for varying irradiance, temperature, wind condition, and different load condition. The simulation results show that the system is stable under various load and supply conditions. Keywords: Hybrid microgrid, Distributed Renewable Energy (DRE), PMSG, PV array, DC bus, Boost converter, incremental conductance, bidirectional converter

Techno economic analysis of microgrid with an efficient energy management system and inverter control strategies

A microgrid comprises of distributed energy resources with the capability of operating independently as an islanded mode or in a grid connected mode. The efficacy of a microgrid is based on the performance of the control strategy and the energy management strategy. Therefore, in this paper the feasibility of an efficient inverter control strategy and energy management strategy for microgrid are studied. The proposed microgridis implemented with master-slave energy management control and battery management system for effective power flow control in an islanded and grid connected mode. A three-layer hierarchical energy management strategy comprising of master-slave system to provide continuous supply at all conditions and effective switchover operations between grid connected and islanded modes of operation is proposed. The voltage-frequency control under standalone mode of operation and P-Q control using hysteresis current control under grid-connected mode of operation are developed and the system parameters like real power, reactive power and voltage at the PCC are analyzed after the implementation of proposed controllers under islanded and grid connected modes of operation. The proposed model achieves voltage and frequency regulation under varying system operating conditions. Also, a techno-economic analysis is performed in HOMER software where the cost of energy and return on investment are studied for the proposed microgrid system by which levelized cost and payback period is reduced. The proposed control algorithms are implemented through MATLAB simulation and tested in a real-time for 1 kW grid-connected solar PV system.

Renewable integrated UAPF fed microgrid system for power quality enhancement and effective power flow management

In this paper, renewable energy integrated universal active power filter (UAPF) is proposed for the microgrid system. Here, renewable energy sources such as solar and wind with the battery storage system are integrated at DC-link of UAPF. In the proposed microgrid system, the centralized microgrid controller (CMC) is implemented for power quality enhancement and effective power flow management. The main objective of the CMC is to achieve effective utilization of RES, seamless power transfer under various operating conditions, reliable and supplying quality power to the load. In CMC, the instantaneous power balance theory (IPBT) is implemented to generate the switching pulses to shunt active power filter (ShAPF) and series active power filter (SeAPF) for power quality enhancement. In addition, the power flow management strategy is integrated into CMC to generate the appropriate reference signals to the various DC-DC converters for efficient power flow management. The system with the proposed control scheme is simulated on MATLAB/Simulink and the same is validated in the experimental setup under various modes such as interconnected, isolated, and floating mode. In real-time hardware setup, a field-programmable gate array is used for parallel processing of microgrid components.

Supervisory control strategy for the effective solar energy utilization in a residential microgrid system using a cost-effective controller

In developing countries, load shedding is a frequent phenomenon to meet the high load. Therefore, a backup power system (battery with inverter) is a common alternative in an average middle-class house. Nowadays, solar-based grid-connected systems are also widely used during load shedding. However, these systems have some drawbacks, e.g., the solar photovoltaic (PV) gets underutilized when the battery is fully charged and the PV power is more than load demand. Moreover, solar power gets properly utilized only under the load shedding condition. Therefore, this paper proposes a novel supervisory control scheme to ensure maximum harnessing of solar power with effective utilization of stored energy. The proposed control action is based on the battery voltage, solar irradiance, and grid supply to decide the utilization of power from the solar PV or grid. The proposed rule-based control employs these three input parameters to achieve a reliable power supply for the residential microgrid. The proposed microgrid system is realized through simulation and experimental analysis, and the performance results are found to be efficient. Furthermore, comparison is also made with recently published work on the same system to illustrate the superiority of the proposed strategy.

Sliding Mode Control of Hybrid Renewable Energy System

This paperpresents an ANFIS based adaptive sliding mode control (ASMC) of a standalone single phase microgrid system. The proposed microgrid system integrates a micro-hydro turbine driven single-phase two winding self-excited induction generator (SEIG) with a wind driven permanent magnet brushless DC (PMBLDC) generator, solar photo-voltaic (PV) array and a battery energy storage system (BESS). These renewable energy sources are integrated using a single-phase voltage source converter (VSC). The ASMC based control algorithm is used to estimate the reference source current which controls the single-phase VSC and regulates the voltage and frequency of the microgrid in addition to harmonics current mitigation. The adaptive sliding mode control with ANFIS is used to maintain the energy balance among wind, micro-hydro, solar PV power and BESS, which controls the frequency of standalone microgrid. Simulation results from MATLAB/SIMULINK of the proposed microgrid shows that the grid voltage and frequency are maintained constant while the system is following various changes in dynamic state such as sudden change in wind speed, changes in solar insolation level and changes in loads.

ANN-based dynamic control and energy management of inverter and battery in a grid-tied hybrid renewable power system fed through switched Z-source converter.

The multidimensional purposes of grid-tied hybrid renewable system such as tracking of maximum power, increasing the power conversion efficiency, reducing the harmonic distortions in the injected current and control over power injected into the grid are presented in this paper by developing a laboratory-scale setup. To ensure continuous current operation at the shoot through mode of grid connected inverter, a switched Z-source converter is utilized at the PV side. The PWM rectifier connected with the wind turbine transforms AC power into dc. Individual power converters with conventional PI controllers have been dedicated for each power source, and control strategy uses only one reference voltage so as to increase the maximum power tracking speed from both PV and wind sources. The battery energy management is performed by artificial neural network (ANN) to enhance the stable power flow and increase the lifespan of the storage system. Finally, the voltage at the point of common coupling is fed to ANN-based space vector-modulated three-phase inverter and the converted AC power is injected to the grid. The overall system performance is measured by estimating the quality of injected power. A stable operation of the proposed microgrid system is verified by varying input and load at the grid. A continuous-time simulation model is realized in MATLAB and is validated using experimental prototype. This benchmark system provides various research scopes for the future smart grids.

Voltage stability enhancement in grid-connected microgrid using enhanced dynamic voltage restorer (EDVR)

Microgrid (MG) has extensive properties to overcome common problems of local distribution system. Some of those problems are generation and demand difference, blackout and brownout, environmental concerns due to burning of natural resources in power stations (indirectly), and reliability issues. Research on microgrid is being conducted to enhance its features to mitigate power quality (PQ) problems associated with distribution system. Voltage sag and swell have been major power quality problems for decades, loads in distribution system are heavily affected due to these power quality problems. In the distribution system, microgrid and power quality compensation strategy should be existed in order to ensure reliability and voltage sag/swell mitigation. Dynamic voltage restorer (DVR) is comprehensive power electronics based Flexible Alternating Current Transmission System (FACTS) device, it is third-generation FACTS device as its control scheme selection flexibility and power line coupling approach make it advance when compare to first and second-generation FACTS devices. In this paper, an Enhanced Dynamic Voltage Restorer (EDVR) is presented to efficiently mitigate voltage sag/swell in grid connected microgrid. On the one side, the presence of microgrid structure ensures reliability of distribution system for local loads on the other side, EDVR ensures voltage sag/swell free power supply for loads. The control strategy of EDVR is based on enhanced synchronous reference frame (ESRF) approach and fuzzy technique system. ESRF is specially design for fast and precise operation of EDVR whereas; fuzzy technique system is responsible for standardized voltage supply for local loads. DC link voltage of EDVR is effectively regulated with the help of proposed control scheme at the time of voltage sag/swell compensation. Stability analysis of ESRF control has been done using modeling of VSC and eigenvalue analysis system. Simulation results on MATLAB/Simulink verified the performance of EDVR under presented control approach hence the specific loads in distribution system are more secure under proposed microgrid system with EDVR.

Voltage Regulation of Hydro Standalone 1-Φ Micro Grid using Fuzzy Logic Based Adaptive Sliding Mode Control Algorithm

This paper presents an adaptive sliding mode control (ASMC) of an improved power quality standalone single phase microgrid system. The proposed microgrid system integrates a governor-less micro-hydro turbine driven single- phase two winding self-excited induction generator (SEIG) with a wind driven permanent magnet brushless DC (PMBLDC) generator, solar photo-voltaic (PV) array and a battery energy storage system (BESS). These renewable energy sources are integrated using only one single-phase voltage source converter (VSC). The ASMC based control algorithm is used to estimate the reference source current which controls the single-phase VSC and regulates the voltage and frequency of the microgrid in addition to harmonics current mitigation. The proposed ASMC estimates the reference real and reactive powers of the system, which is adaptive to the fluctuating loads. The sliding mode control is used to estimate the reference real power of the system to maintain the energy balance among wind, micro-hydro, solar PV power and BESS, which controls the frequency of standalone microgrid. The proposed microgrid is implemented in real time using a DSP (Digital Signal Processor) controller. Test results of proposed microgrid shows that the grid voltage and frequency are maintained constant while the system is following a sudden change in loads and under intermittent penetration of wind and solar energy sources.

Adaptive Neural Fuzzy Inference System Based Adaptive Sliding Mode Control of a Standalone Single-Phase Microgrid

This paperpresents an ANFIS based adaptive sliding mode control (ASMC) of a standalone single phase microgrid system. The proposed microgrid system integrates a micro-hydro turbine driven single-phase two winding self-excited induction generator (SEIG) with a wind driven permanent magnet brushless DC (PMBLDC) generator, solar photo-voltaic (PV) array and a battery energy storage system (BESS). These renewable energy sources are integrated using a single-phase voltage source converter (VSC). The ASMC based control algorithm is used to estimate the reference source current which controls the single-phase VSC and regulates the voltage and frequency of the microgrid in addition to harmonics current mitigation. The adaptive sliding mode control with ANFIS is used to maintain the energy balance among wind, micro-hydro, solar PV power and BESS, which controls the frequency of standalone microgrid. Simulation results from MATLAB/SIMULINK of the proposed microgrid shows that the grid voltage and frequency are maintained constant while the system is following various changes in dynamic state such as sudden change in wind speed, changes in solar insolation level and changes in loads

Frequency control of microgrid system based renewable generation using fractional PID controller

This paper addresses a control frequency scheme of the microgrid system using a fractional order PID controller. The proposed Microgrid system is consisted of a Photovoltaic System, Wind Turbine Generator, Diesel Engine Generator, Fuel Cell, and different storage systems like Battery Energy Storage Systems, and Flywheel Energy Storage Systems. The principal objective of the present paper is to limit the frequency and power deviations by the application of the proposed controller which has five parameters to be determined through optimization techniques. Krill Herd algorithm is used for determining the optimum fractional order PID controller parameters using the Integral of Squared Error. A comparison between the Genetic Algorithm and Krill Herd is done, and the obtained simulation results presents that the investigated controller-based Krill Herd outperforms the Genetic Algorithm in terms of fewer fluctuations in power and frequency deviation.