DC Micro Research Articles

High voltage gain multiphase interleaved DC-DC converter for DC micro grid application using ıntelligent control

This paper presents Multiphase Interleaved Boost Converter (MIBC) with Voltage Multiplier Cell (VMC) supplied for DC micro grid application. The main focus of this research is to increase the voltage gain and reduce the voltage stress across the switch. The improvement in voltage gain is acheievd by recycling the stored energy in the inductor, VMC and voltage lift capacitor. In the proposed MIBC the input current is divided among the three converters. Hence, the rating of devices used in the converter can be reduced, which in turn minimises the ohmic loss of the switch. In addition, the interleaved converter decreases the voltage stress across the switch. The MIBC is compared with existing converters for various parameters such as voltage gain, voltage stress of the main switch and diode and the number of components used. The hardware is implemented for the propoosed MIBC to validate performance in real time application.

Design of an Input-Parallel Output-Parallel LLC Resonant DC-DC Converter System for DC Microgrids

Compared with the centralized power system, the distributed modularized power system is composed of several power modules with lower power capacity to provide a totally enough power capacity for the load demand. Therefore, the current stress of the power components in each module can then be reduced, and the flexibility of system setup is also enhanced. However, the parallel-connected power modules in the conventional system are usually controlled to equally share the power flow which would result in lower efficiency in low loading condition. In this study, a modular power conversion system for DC micro grid is developed with 48 V dc low voltage input and 380 V dc high voltage output. However, in the developed system control strategy, the numbers of power modules enabled to share the power flow is decided according to the output power at lower load demand. Finally, three 350 W power modules are constructed and parallel-connected to setup a modular power conversion system. From the experimental results, compared with the conventional system, the efficiency of the developed power system in the light loading condition is greatly improved. The modularized design of the power system can also decrease the power loss ratio to the system capacity.

Regulated Voltage Simulation of On-board DC Micro Grid Based on ADRC Technology

Output voltage is an important index of on-board DC micro grid, and its stability is affected by many aspects. In the process of power generation, there exist multiple disturbances like speed fluctuations, load changes and time-varying parameters. If various influence factors are not effectively compensated, it will reduce the effectiveness of the system simulation and control precision of practical application. To deal with the problem, an ADRC was applied to on-board DC micro grid and simulated under severe interference conditions. Simulation results based on ADRC were compared with those of the traditional PID controller. The research shows that on-board DC micro grid using ADRC can compensate external disturbances effectively, and has a highly regulated voltage output performance, which verifies the feasibility of the proposed method.

Genetic Algorithm Optimization for DC Micro Grid Design, a Case of Study

Generation of electric energy through renewable sources remains an important task, due to the increased interest in production of green energy around the world. In the past 20 years, several efforts have been made to optimize network planning, as well as production and operation of power systems in standalone and distributed configurations to guide evolution towards Smart Grids. Optimization of the power grid has been mainly focused on power dispatch, forecasting, and efficient and reliable production and distribution. Such optimization problems present optimal results with the use of conventional tools; however, and despite the incredible advances in that regard, the non-linear and non-convex nature of such an optimization problem require more complex processing techniques. With the aim of providing a tool to calculate micro grid systems, this article shows the development of an optimization algorithm used to calculate the better configuration for a micro grid implementation based on photovoltaic panels and batteries layout.

Comparative analysis of data-driven methods online and offline trained to the forecasting of grid-connected photovoltaic plant production

Actual technology improvements are contributing to DC and AC micro grid diffusion characterized by renewables photovoltaic and storage systems. Photovoltaic technologies have the advantage of a capillary distribution, but they are characterized by an intrinsic variable behavior due to continuously changing weather conditions. This drawback can be overcome by an appropriate temporal and energetic match among photovoltaic generation and storage capacity, so increasing micro grids reliability and efficiency levels. An accurate forecast of photovoltaic production can contribute to smooth photovoltaic systems intermittency problems so supporting generation and storage balance.Many different forecasting algorithms have been proposed in literature to provide long, medium and short-term predictions of photovoltaic production. A criterion for selection among them is not a priori and it is not uniquely identifiable. In this paper, the attention is focused on eleven data-driven models to obtain 12h ahead forecast, also including some models not usually used in solar field but successfully employed in other expertise fields. This study addresses simple linear models, as Multiple Linear Regression, nonlinear models, such as Classification And Regression Tree, Model Tree M5, Extreme Learning Machines, weighted k-Nearest Neighbors, Multivariate Adaptive Regression Spline, Support Vector Machines, Bayesian Regularized Neural Networks and ensemble methods, as Random Forests, Cubist and Extreme Gradient Boosting. The goal is to compare methods characterized by different complexity levels to understand if a higher complexity model can provide better performances. Furthermore, the considered forecasting methodologies are compared applying two different training methodologies (online and offline) to identify the most performing training mode. The application of optimization algorithms permits to identify optima parameters and the optimum training dataset length for each model. After the optimization step, a statistical analysis is carried out to compare methods forecasting performances for the production of a 1kWp photovoltaic plant installed at the ENEA Research Center of Portici. The case study results demonstrate promising forecasting performances applying the online training mode. Among all studied methods, Support Vector Machines, M5 and the Cubist can assure minima prediction errors and satisfying accuracy with optima dataset lengths. Cubist and M5 represent the best performing models since they are able to minimize prediction errors both in case of optima and minima training datasets.

DC Microplasma Jet for Local a:C-H Deposition Operated in SEM Chamber.

A DC micro plasma jet for local micro deposition of a:C-H film in the ambient vacuum of scanning electron microscope (SEM) chamber is proposed. Acetylene (C2H2) gas was locally fed into the chamber through an orifice shaped gas nozzle (OGN) at 6.6 sccm in flow rate by applying 80 kPa-inlet pressure with an additional direct pumping system equipped on the SEM chamber. As a cathode, a cut of n-type silicon (Si) wafer was placed right in front of the OGN at 200 μm gap distance. By applying a positive DC voltage to the OGN, C2H2 plasma was generated locally between the electrodes. During discharge, the voltage increased and the current decreased due to deposition of insulating film on the Si wafer with resulting in automatic termination of discharge at the constant source voltage. A symmetric mountain-shaped a:C-H film of 5 μm height was deposited at the center by operation for 15 s. Films were deposited with variation of gas flow rate, gap distance, voltage and current, and deposition time. The films were directly observed by SEM and analyzed by surface profiler and by Raman spectroscopy.

A novel control strategy for grid connected hybrid renewable energy systems using improved particle swarm optimization

Abstract This paper proposes a novel hybrid centralized and distributed control of hybrid renewable energy system consisting of AC/DC micro grids. An Interlinking Converter ( IC ) is used to connect both sides of the micro grid systems together. Improved Particle Swarm Optimization ( IPSO ) which acts as a master controller is used to control the power of the sources based on IC control. Also, there are different slave controllers for 100 kW photovoltaic, fuel cells and 100 kW wind, which are designed to supply continuous load power. Coordination between two grids is satisfied through droop control for both AC and DC micro grids to achieve power sharing process and control of renewable energy sources supplying different loads. The model has been implemented in MATLAB/SIMULINK. The proposed controller succeeded to manage energy between micro grids under different scenarios. The control technique using IPSO strategy improves the dynamics of the hybrid system connected to the grid.

Model Predictive Direct Power Control of DC Micro Grid Rectifier Based on Neutral Point Potential Balance

Aimed at the problem of DC micro grid rectifier control delay and the DC bus voltage stability, the method of two-step model predictive direct power control (TMPDPC) combined with neutral point potential control is proposed. Model predictive direct power control (MPDPC) is designed for rectifier. A cost function is then used to evaluate the active and reactive power ripples, from which the vector that generates the lowest power ripple will be applied during the next sampling interval. Two-step predictive control is designed to compensate for the delay of one-step predictive control. On the basis of this, the two-capacitor voltage unbalance problem in DC side is considered, and the neutral point potential control is added. In the Matlab/Simulink simulation, compared with control effect of direct power control (DPC) and one-step model predictive direct power control (OMPDPC), the control strategy of neutral point potential added to TMPDPC can make the system stability and control accuracy better. The validity of this scheme was validated by physical simulation at last.

Research on the Hierarchical Control of DC Microgrid Based on Droop Control

为改进传统下垂控制较差的电压调节的性能，本文提出了一种基于下垂控制的直流微网的分层控制策略，实现合理的电流和功率的分配，同时补偿母线电压的偏离。首先分析了传统下垂控制的特点及引发的电压偏离问题；其次引入二级控制器解决了电压跌落的问题，并分析二级控制器稳定性；同时给出了直流微网的三级控制的整体设计。最后在Matlab/Simulink环境下的仿真结果验证了该方法的有效性，且在dSACE实验平台上验证了下垂理论和电压跌落补偿。 For the sake of improving the performance of poor voltage regulation of traditional droop control, this paper proposes a hierarchical control strategy of DC microgrid based on droop control, which can achieve a reasonable distribution of current and power, and compensate the deviation of the bus voltage. Firstly, the characteristics of the traditional droop control and the problem of the voltage deviation are analyzed. Then, the two stage controller is introduced to solve the problem of voltage sag, and the stability of the two stage controller is analyzed. In the meantime, the overall design of the three stage control of DC micro grid is presented. Finally, simulation results in Matlab/ Simulink environment verify the effectiveness of the proposed method, and experimental results are carried out to evaluate the droop concept as well as secondary voltage compensation.

Effective performance and power transfer operation of a current controlled WRIG based WES in a hybrid grid

This paper deals with the performance and possible power transfer modes of Wound Rotor Induction Generator (WRIG) based Wind Energy System (WES) in a hybrid grid (AC and DC Micro grid (DCM)) delivering power in islanded and utility tied conditions. The current controlled Rotor Side Converter (RSC) with its DC end connected to DCM facilitates bidirectional slip power flow. In islanded mode, a decoupled voltage vector control with cascaded PI loops is used for regulating stator voltage and stator frequency. In utility tied mode, reference current generation technique based on Instantaneous Power Theory (IPT) is adopted for slip power transfer by PWM rectification/inversion of RSC. The excitation is supplied via rotor and stator during islanded and utility tied conditions respectively. All possible operational modes are formulated aiming incessant power transfer by WRIG. Maximum power extraction during occasional situations like short circuit faults/low wind/overload and no load claims the merit of the system. The dynamic power transfer operation to maintain the power balance during hybrid mode is analyzed through laboratory experimentation on a 500 W induction machine. Experimental findings confirm the efficacious working of WRIG based WES.

Control and maximum power tracking operation of hybrid excited variable speed induction generator

This paper describes a method of voltage regulation, maximum power extraction and power transfer operation in a variable speed wind-driven Induction Generator (IG) feeding DC micro grid (DCM). The IG is self-excited in a hybrid manner with fixed capacitor and a current controlled, voltage source converter (CCVSC). The control principle of CCVSC which intends to provide the VAR requirement of IG based on the power curves along with voltage regulation and maximum power tracking (MPT) with PI (proportional-integral) based controllers claims the merit of the setup. The sinusoidal reference current templates of CCVSC are generated with voltage loop delivering the peak value and MPT loop delivering phase value. The frequency synchronization is effected with a 1Ø Phase Locked Loop (PLL). The wind power is utilized by meeting the load demand and supplying the excess power to DCM through PWM rectification of CCVSC without dissipating it through any dump load. During conditions of machine stall, the system amenably transfers power to AC loads by PWM inversion of CCVSC with fixed modulation index and frequency. When there is any fall in DCM voltage, DC voltage regulation is effected by the PWM rectification operation of CCVSC. To execute the reliable power transfer scheme, a supervisory control is employed for the automatic smooth change over in the modes of operation depending on load and wind availability. The successful operation of the system for various load/speed conditions is proved through extensive MATLAB based simulation and dSPACE 1104 controller based experimentation on a 500W induction machine.

Isolated Buck/Boost Bidirectional DC-Three Phase Topology

In this paper a new topology, isolated Buck/Boost bidirectional DC-AC three phase, for interconnecting a DC micro grid with conventional three-phase AC network, is presented. Its operating principle is explained, and a switching strategy is presented to reduce total harmonic distortion and operate the devices with minimal switching losses. Finally the simulation results are shown to evaluate the performance of the converter.

Li-ion 배터리 충/방전 시스템의 안정적 운영에 관한 연구

When the operation of battery is converted at charging and discharging system based on a DC micro grid, the voltage is fluctuated. And excessive voltage fluctuation could cause damage or failure of charging and discharging equipment. Therefore, in this paper, we studied the operating schedule of the charging and discharging system based on the DC micro grid and a design point of the capacitor which was able to reduce the voltage fluctuation. A result of computer simulation showed that when a fluctuation-reducing capacitor which had an initial value of 600V/35mF was applied at the charging and discharging system based on a DC micro grid which was operated with three charging battery se ts and five discharging battery sets, voltage fluctuation by charging and discharging operation was reduced by about 63.3%. Furthermore, voltage fluctuation which occurred when initial network voltage was stabilized was reduced by about 73%.

Optimization and Design of PV-Wind Hybrid System for DC Micro Grid Using NSGA II

The world is heading towards renewable energy, but the two key disputes that stop its well-known adoption are the power production level and the price of the production. Distributed generation (DG), and hybrid systems with battery backup are the solution for uninterrupted power supply. It is obtained using the Multi-Objective Genetic Algorithm (NSGA II). Techno-economic methodology is used in this proposed system for the size optimization. The result is based on the system cost, in order to meet the load requirements. The effect of temporal sampling is optimized using low-rate temporal data. It is compared with hybrid DC microgrid, which has been optimized using high temporal resolution data.

Approach for Negotiation Problems in Multi-Agent Systems for DC Micro Grid Using Multi-Objective Evolutionary Algorithms

The work is devoted to solve allocation task problem in multi agents systems using multi-objective genetic algorithms and comparing the technique with methods used in game theories. The paper shows the main advantages of genetic algorithms and the way to apply a parallel approach dividing the population in sub-populations saving time in the search and expanding the coverage of the solution in the Pareto optimal space.

Optimal control strategy of a DC micro grid

Microgrids include distributed energy resources, controllable loads, and storage devices, and they can be classified into AC and DC types, depending on the characteristics of the supply voltage. In this paper, an optimal control strategy for a DC microgrid is proposed, and the strategy is aimed at minimizing the daily total energy costs. The DC micro grid can include non-dispatchable generation units (such as photovoltaic power generation) and dispatchable generation units, energy storage systems (batteries), and controllable/not controllable loads. The control strategy is based on a two-step procedure, i.e., (1) the implementation of one day-ahead scheduling and (2) a very short-time predictive control. The day-ahead scheduling is formulated using integer linear programming methodology and is aimed at achieving the optimal scheduling of controllable loads. The very short-time predictive control is based on the solution of a non-linear, multi-period, optimization problem and is aimed at achieving the real-time optimal charging/discharging profile of storage powers and the real-time optimal profile of powers of dispatchable generators thereby minimizing the cost of total daily energy. For both procedures, optimization models were formulated and solved, including technical constraints that guaranteed an adequate lifetime of the storage system. Case studies relative to a DC microgrid obtained by a modification of the actual structure of the electrical power plant of an Italian industrial facility were investigated in order to show the feasibility and the effectiveness of the proposed approach.

Multi Port Single Stage Power Electronics Converter and Wind PFC Converter for DC Micro Grid Applications

In this study multi port AC/DC-DC single stage power electronics converter proposed for grid power supply. The topology includes reduced number of active element and passive element. Passive element is used to provide to achieve improved voltage gain and to reduce the voltage stress of input side switches. The active-clamp circuits are used to recycle the energy stored in the leakage inductors and to improve the system performances. Here two input port (wind and battery unit) and output port connected to dc grid, battery act as charge unit and source. Efficient wind power conversion is achieved by PFC boost dc-dc converter. Controlled and high step up voltage is supplied to multi-port converter from wind source.

Design & Analysis of Hybrid Micro Grid with DC Connection at Back to Back Converter

A micro grid is a localized grouping of electricity generation, energy storage, and loads that normally operate connected to a traditional centralized grid (macro grid). This single point of common coupling with the macro grid can be disconnected. The micro grid can then function autonomously. Generation and loads in a micro grid are usually interconnected at low voltage. From the point of view of the grid operator, a connected micro grid can be controlled as if it were one entity. Micro grid generation resources can include fuel cells, wind, solar, or other energy sources. The necessity of an AC or DC micro grid is governed by available micro sources and connected loads. A hybrid structure can ensure a sustainable configuration blending both the forms. In this paper, a hybrid micro grid structure for a grid connected micro grid with DC connection at back to back (B2B) converters is proposed. While a B2B connection between two AC systems could bestow a reliable, isolated and efficient coupling,an extra DC bus connection can facilitate use of the DC micro sources. The DC bus can supply the local DC loads and can also trade part of the power with the AC grids. The voltage support at the DC link (of the B2B converters) can be used for the DC bus formation. Different power management strategies with fixed power references or decentralized power distribution in AC/DC sides are proposed and validated with simulations in MATLAB.

Trajectory Planning and Realizing of an Exoskeleton Device for Hand Rehabilitation Based on sEMG Control

This paper presents a novel exoskeleton training system for hand rehabilitation with the surface electromyography signals (sEMG) feedback to meet the kinematics characteristics of finger joints. In this system, the sEMG is obtained by means of the surface electrodes loaded the forearm antagonistic muscle. The sEMG is amplified about 100 times again after it was preliminarily amplified about 200 times and filter,. Through threshold and the equivalent calculation, the control signal was input into the driving circuit of DC micro motor to control the hand Exoskeleton. The experimental results show that the processed sEMG can drive the hand exoskeleton for rehabilitation training, and the bending angular of joints agree well with bionics laws. The results possess guideline value for bionics motion control of hand rehabilitation with function damage.

Comparative Analysis of Solar Photovoltaic Lighting Systems in India

This study is based on extensive survey of selected photovoltaic (PV) programs in India and presents a comparative analysis of four prevalent solar lighting technologies, namely Solar Home System, Solar Charging Station, Solar AC Mini Grid and Solar DC Micro Grid employed for rural electrification in India. The study is focused on technical, financial, and institutional aspects of these programs along with the social impact assessment of PV based electrification in rural households. The findings of this study revealed that private entrepreneurship based delivery model have shown better performance as compared to the subsidy based delivery model. It is also found that beneficiary ownership play a vital role in the performance and sustainability of PV programs. We suggest that financial support, local need based technical innovations, developing local technical expertise and sensitization and training of all stakeholders are key parameters to enhance the operational sustainability of the PV programs.