Hybrid Pv Wind System Matlab

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Dynamic Modeling and Simulation of a Grid-Connected PV- wind hybrid Microgrid System Using MATLAB/SIMULINK Ibrahim E. Abdualkafi1, Abdelbaset M. Ihbal2*.

Sabratha, Libya

The Libyan Academy for Postgraduate Studies, Tripoli, Libya

Abstract

Hybrid renewable Energy System (HRE) in a system configured with renewable energy sources requires storage facilities or backup generation to maintain continuity of supply to loads when the renewable energy sources alone are not sufficient. HRE systems are widely familiar as efficient power generation mechanisms due to their low operating costs, high reliability, and flexibility in grid-connected operations. This paper presents and investigate a model a Grid-Connected PV-wind hybrid Microgrid (MG) System. The system consists of a PV system, a wind turbine and an ultracapacitor as an energy storage element. All generation units have been connected to the distribution network to run in grid-connected mode. Maximum Power Point Tracking (MPPT) has been adopted to increase the power output then array efficiency of PV systems. For short-term transient simulations, dynamic models are developed for each system module. Utilizing MATLAB/Simulink, the simulated test-bed is created. Simulations are used to examine the test-bed's behaviors during steady state, abrupt variations in wind speed, and when facing a line fault. The outcomes of this study demonstrated that DER, UCESS, as well as the proposed control technique all support system stability under transient disturbance. The developed model might be seen as an effective tool for enhancing the functionality of the grid.

KEYWORDS: renewable energy source; grid-connected; hybrid AC/DC microgrid;

I. Introduction

Increased power demand will drive the deployment of energy storage (ES) and power generation at distribution level. Distributed Energy Resources (DERs) are small-scale energy sources that can be harvested to deliver reliable and efficient electricity to meet a regular demand of consumers, usually in close proximity to consumers. will be split. .

Most distributed energy sources are connected to the power grid and consumer loads via DC-AC voltage inverters. DER systems typically use renewable energy sources such as solar. small hydro, biogas, wind, and biomass [2, 3].

However, due to the intermittent nature of renewable energy, it requires the support of an Energy Storage System (ESS) to provide ancillary services and store excess energy for later use. ESS policies have been proposed in some countries to support renewable energy integration and grid stability. A microgrid (MG) can be easily achieved by simply installing distributed power resources to supply power to on-site consumers. DER, energy storage system and load define a microgrid that can operate in parallel with the main grid (grid-tied mode) or independently.

Microgrids (MG) have been applied in several practical areas such as industrial use, remote areas, residences, and commercial buildings [3, 4, 5, 6, 7]. The two most well- known sources of electrical distributed energy resources are wind turbines and solar power. Batteries, superconducting coils, flywheels, or supercapacitors are common energy storage devices used in numerous applications because of their rapid load acceptance and capability of storing and releasing energy within a short duration of time .

Microgrids can be confidential as DC microgrids, AC microgrids, or hybrid AC/DC grids . Wind turbines are

While

ultracapacitors solar cells and are direct current (DC) devices. Figure 1 shows the main components of a solar and wind hybrid energy system. The DC and AC microgrids are

Both Combined To Form A Hybrid Microgrid. Control

strategies and bidirectional power electronics are needed to govern hybrid AC/DC grids to attain stable performance

While Connected To The Ac Utility Grids . Dynamic

modeling of MG is performed to study steady-state and transient responses. Modeling includes storage systems, energy resources, controllers and power electronics devices.

The purpose of this study is to create a complete model of

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electronics, controls and steady-state loads to study transient behavior with changing inputs. The system is simulated in his MATLAB/Simulink. The evaluation of results is discussed.

Generation Microgrid Modeling

This section describes the formation of a grid-tied hybrid AC/DC microgrid for a hybrid solar and wind turbine power generation system. The proposed system consisting of a wind turbine, a photovoltaic array, a DC/DC converter with an isolation transformer that ensures that the photovoltaic array operates at its MPP, a DFIG, and an ultracapacitor ESS and AC /DC/AC thyristor-controlled double-bridge converters is shown in Figure 2. The system frequency is 50Hz and the rated voltage is 400V.

Fig.2. Grid-connected PV- wind hybrid AC/DC microgrid

Modeling Of Dc Microgrid

Figure 3 shows the structure of the DC microgrid. Here, a PV array and an energy storage device are connected to a

Dc Bus, Which Is Connected To The Grid Through An

inverter. Fig. 3. Structure of the DC microgrid. The PV arrays have boost converters and linked to a

Common Dc Bus. The Ultracapacitors Are Similarly

connected to a common DC bus via bidirectional DC/DC converters. DC motors and DC resistors are the two different types of DC load. PV power units are managed to produce a maximum power.

Photovoltaic Cell

Solar cells are basically pn junctions fabricated on thin semiconductor wafers. Electromagnetic radiation from solar energy can be converted directly into electricity by the PV effect. When a semiconductor is exposed to sunlight, photons with energies larger than the semiconductor's bandgap energy cause a proportional number of electron- hole pairs to form. Figure. 4 below shows the equivalent circuit of a solar cell.

Fig 4. Single-Diode Solar Cell Equivalent Circuit

The current source Iph represents the cell photocurrent. Rs and Rsh are the inherent series and shunt cell resistances respectively. Usually, the value of Rsh is very large and the value of Rs is very small and can be ignored for simplicity of analysis. . PV cells are grouped into large units called PV modules and connected in a parallel-series configuration to form a PV array. A photovoltaic module can be mathematically modeled as in equations (1)-(4). [12- 14].

Is

Ns : number of series-connected cells., Np - number of parallel connected cells.

Voc = Vpv, 36 = Ns =& Np = 1

The specifications of the proposed PV models (including

Pv Manufacturing Datasheets) Are Exposed In

Table I. Electrical SpecificationS for Solar PanelS at

55

Impp (Rated) [A] 3.15 Vmpp (Rated) [V[ 17.4 Isc [A]

3.45

Voc [V]

B. Maximum Power Point Tracking (Mppt)

MPPT is a method commonly used in PV solar systems to maximize power production regardless of the environment . Figure 5 shows the MPPT tracking circuit.

Fig.5. Circuit Arrangement Of Mppt

By altering the IGBT's duty cycle in the converter for boost,

Mppt Can Be Matched. Mppt Aims To Use Control

algorithms to confirm that the PV system is working at the MPPT. The Perturbation & Observation (P&O) technique is one of the most commonly used MPPT methods, due to its simplicity and less requirements for measured variables.

The P&O algorithm constantly measures the current and voltage at the solar array terminals, constantly perturbs the voltage with small perturbations, and observes the change in output power to determine the next control signal. If the output power rises, the disturbance continues in similar way in the next step, otherwise the direction of the disturbance is reversed. To improve the tracking speed and accuracy of the algorithm, the perturbations should be continuously adjusted .

Observing the PV cell characteristics curve satisfy the following slope of the PV curve equations: equation

Determines Whether The Pv Module'S Operating

point is at the MPP. On the other hand, equations (

Act On The Left And Right Sides Of The Well-

defined operating point of the PV curve. Fig 6. Flow-chart for variable-step P&O method.

C. Uc Energy Storage Systems

Ultracapacitors (UC) are energy storage devices that have lifetimes exceeding 1,000,000 charge-discharge cycles, high power densities, great reliability, almost instantaneous

Extreme

temperatures, and high efficiency.

1) Uc Model

UC model consists of a series resistor (ESR), an ideal capacitor, and a shunt resistor (EPR). The ESR is small, simulating heat loss and transient charge/discharge voltage mutations in the discharge/charge process. EPR with a large resistor represents current leakage impact and affects long term energy storages. The classical model for UC is represented in Figure 7.

Fig 7 Classical model for UC.

Control System

UC energy storage consists of an UC, a bidirectional DC to DC converter and a control system. This configuration should allow the ultracapacitor to operate in bidirectional mode. The bidirectional converter control system is shown in Figure 8. The main goal is to keep the voltage of the common dc link circuit constant . In this manner, the voltage of the common dc link remains stable regardless of whether the ultracapacitor is being charged or discharged, resulting in the lowest capacitor voltage ripple.

When the DC-link voltage is less than the reference, switch S2 becomes active and the converter operates similar to that of boost converters. When the DC-link voltage is greater

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than the reference, switch S1 becomes active and the converter operates similar to that of buck circuit. In case of steady state, the input and output voltages satisfy

(Buck) (6)

Where, D is the switching signal duty cycle. Fig 8. Control of Bidirectional DC- DC converter .

Most Wind Power Systems Use Variable Speed Pitch-

controlled wind turbines with doubly fed induction generators (DFIGs). This is because it has some advantages over other types of wind turbine generators such as conversion of wind energy with high efficiency and control

Of Both Reactive And Active Power, Decrease Power

fluctuations and produce high-quality of power . The basic structure of a grid-connected DFIG wind turbine is shown in Figure 9. The rotor is powered by an AC/DC/AC converter and the stator is directly connected to the 50 Hz grid.

Fig 9 . Arrangement of the DFIG wind power .

1. Model Of Wind Turbine

The wind turbine's generated mechanical power can be

(7)

where ρ is the air density in Kg/m3, A =πR2 is the swept

Is Wind Speed In ( M/S ) ,

is the power coefficient that is a function of a tip speed ratio

(Λ ,Β ) Is The

measurement of the amount of wind energy that a turbine

(Λ ,Β ) ., The Following

expression is employed. The electromechanical equations of motion of shaft system

(10)

Where, Hwt and Hgen are stiffness coefficients of the turbine and the generator. ωwt and ωgen are the rotational speeds of the generator and the turbine, respectively, in rad/s; Twt and Tgen are the torques of the turbine and the generator; Jgen and Jwt are the moments of inertia of the generator and the turbine, respectively; Dgen and Dwt are the coefficients of linear damping of the both generator and turbine; and Hgen and Hwt are the coefficients of stiffness for the generator and the turbine.

2. Modeling Of Induction Generator

Figure 10 illustrates the induction machine's electrical circuit in reference frame (dq frame). Fig 10. Electrical circuit for the induction machine in

Reference Frame

The following set of equations can be used to compute the

Deployment In Out-Of-Position Situations

D. Bendjaballah1, A. Bouchoucha1, M. L. Sahli1,2* and J-C. Gelin2

Abstract

Side-impact collisions represent the second greatest cause of fatality in motor vehicle accidents. Side-impact airbags have been installed in recent model year vehicle due to its effectiveness in reducing passengers’ injuries and fatality rates. In meeting these requirements, simulations of folding and deploying airbags are very useful and are widely used. The paper presents a simulation method for the deploying airbags using three materials in different working conditions. Finite element analysis is primarily used to evaluate this concept. In these simulations, the gas flow is described by the conservation laws of mass, momentum, and energy. The numerical results indicate that the FE method in this paper is capable of capturing airbag deploying process accurately.

Keywords: Airbag simulations, Out-of-position, Crash, Modeling, Out-of-position

Background

The passive safety of cars has become a very high prior- ity issue for the automotive industry. Today, there are not only one or two airbags in a car; certain models have ten times more than that. With the increasing usage of airbags, the number of accidents where the airbag itself can cause an injury to the occupant also increases

(Augenstein Et Al. 2003; Gabauer And Gabler 2010;

Audrey et al. 2011). As is well known, safety belts are also now devices designed to provide protection to the users of vehicles during crash events, minimizing the loads necessary to adapt their movement to the move- ment of the car (Freesmeier and Butler 1999; Schmitt et al. 1997). In general, the seat belt is designed to restrain the occupant in the vehicle and prevent the

Occupant From Having Harsh Contacts With Interior

surfaces of the vehicles. The airbag acts to cushion any impact with vehicle structure and has positive internal pressure, which can exert distributed restraining forces over the head and face. As a safety component of auto- mobile, an airbag decreases occupants’ injury likelihood effectively in case of an accident (Ruff et al. 2007). These safety elements can reduce the death rates on the roads, and its protection effects have been widely approved (Crandall et al. 2001; Teru and Ishikawa 2003). With computational tools such as finite element methods designed for dynamic contact problems, crashworthiness simulations can now be used with reliable accuracy to evaluate occupant protection in various collision condi- tions with safety metric/parameters such as acceleration, head injury criteria, intrusion distance, intrusion vel- ocity, and neck forces (neck injury risk or whiplash).

Thus, new types of airbag products are being developed to handle different collision scenarios.

Become Standard Equipment On Most New Passenger

vehicles (Braver and Kyrychenko 2004; Teng et al. 2007; Yoganandan et al. 2007). The airbag cushion is com- posed of a woven fabric which is rapidly inflated during a car crash. The airbag dissipates the passenger’s kinetic energy thereby reducing injury through biaxial stretching of the fabric bag and escaping gas through vents. There- fore, the performance of the airbag is greatly influenced by the mechanical properties of the fabric. Generally, air bags are designed to deploy in a crash that is equivalent to a vehicle crashing into a solid wall at 8 to 14 mph.

Air bags most often deploy when a vehicle collides with another vehicle or with a solid object like a tree. There are various types of airbags: frontal, side-impact, and curtain airbags. In general, the passenger side airbags are usually larger than the driver airbags (see Fig. 1).

Besançon, France

© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Bendjaballah et al. International Journal of Mechanical

Doi 10.1186/S40712-016-0070-2

Extensive studies have shown that the airbag deploy- ment in load cases consists of two occupant loading phases: a punch-out effect where the airbag bursts out of its container with the airbag and airbag module cover accelerating towards the occupant and a second loading phase during which the airbag is taking on its deployed shape and volume (membrane-loading effect). Bankdak et al. (2002) developed an experimental airbag test system to study airbag-occupant interactions during close proximity deployment. The results provided insight for simulating the effect of inflation energy and mass flow on target response. Bedard et al. (2002) found that while left-side (driver-side) impacts accounted for only 13.5% of all crashes, the fatality rate among these

Crashes Was 68.3% In Comparison To Front Impact

(48.3%), right-side impact (31.3%), and rear impact (38.4%). These studies underscore the importance of oc- cupant safety during side-impact collisions. In the last years, the current market requested to reduce the time and cost airbag development. In order to achieve this result, virtual simulations play an important role since they allow to minimize the number of experimental tests (Pei et al. 2013; Cao et al. 2014). Several simulation models of airbag were established (Wang et al. 2007). It is feasible to optimize the parameters of airbag deploy- ment using simulation technology. Experimental and numerical studies have quantified injury risks to close- proximity occupants from deploying side airbags. These studies have focused on the prevention of the most ad- verse effects of airbag deployment (Duma et al. 2003).

Other studies have proposed airbag characteristics to minimize particular biomechanical responses (Haland and Pipkorn 1996). In a more recent study, Marklund and Nilsson (2003) compared deformation patterns with experimental data as well as the computational costs associated with three different airbag deployment simu- lation methods; they concluded that the SPH method is relatively inexpensive and produces incremental deform- ation patterns that compare most closely to the experi- mental results. The process of inflation of an airbag is one of the determining factors in saving lives. The duration from the initial impact of the crash to the full inflation of an airbag is about 40 ms, and during this time, the airbag goes from being in a folded state to a fully inflated state, with a high internal pressure. After achieving this state, the airbag begins to deflate, thus providing a nice cushion for the body impacting it.

Ideally, the person in the crash should come into contact with the airbag at this time. In the present study, a large volume passenger side airbag model is developed to handle different collision scenarios. The main aim is evaluate the performance of deploying of passenger side airbag using finite element methods (FEM).

Materials

The tensile specimens were made in different airbags (P: Peugeot, R: Renault, and VW: Volkswagen) with a length of 200 mm long and a width of 40 mm. Table 1 shows the mechanical properties of the airbag.

Tensile Tests

To determine the mechanical properties of the material of airbag used in the test pieces, tensile tests were performed on Lloyd EZ20 universal testing machine in Constantine. These tests were conducted using rect- angular samples. The axial force and axial displacement acquired during a test are converted into stress and the strain in order to be used for the fabric material model.

The continuous recording of the stress-strain data was performed during both the load and unload phases. A minimum of five samples were made in order to check the repeatability of the measurements. All the data was collected by using a PC-based data acquisition system and analyzed by commercial software. The picture frame test device that is made for this study is shown in Fig. 2.

Fig. 1 a Frontal and side airbags. b Oblique view of facet occupant model in sitting posture following airbag deployment (Lim et al. 2014)

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Bendjaballah et al. International Journal of Mechanical and Materials Engineering (2017) 12:12

Page 2 Of 9

Figure 3 shows the stress-strain relationship of the airbag sample under axial tensile loads. The results are showing a linear increase in extension with the increas- ing stresses. This is an expected output and it confirms with the theoretical behavior of a sample subjected to tensile stress. The rupture strain values for different airbags (R/P/VW) were 0.322, 0.441, and 0.472, respect- ively. The measured elastic parameters (i.e., Young’s modulus E and initial yield strength) and Poisson’s ratio are summarized in Table 2. The tensile tests of the woven fabrics can show differences on mechanical prop- erties because woven fabrics can resist in-plane shear loads once the yarn lock-up angle has been reached. The differences of material property on material direction can affect the shape of fully deployed bag (see Fig. 3b).

Theoretical Background

Numerical simulations of airbags use very complex and techniques such as an orthotropic model to identify the mechanical behaviors during the airbag inflation and the fluid mechanics (gas flow) to describe the inflator gas flow (pressure gradient) and improve the representation of the pressures within the airbag. To model the airbag as an orthotropic model, three material constants have to be provided. Assuming a plane stress condition, the

Ð1Þ

where σ is the normal stress and τ is the shear stress, the subscript refers to the principal material directions, i.e., the fill and warp directions. Also, ε and γ are the strain components. The material elastic constants Qij are

Ð2Þ

where E1 and E2 are the Young’s modulus in the fill and wrap directions and G12 is the shear modulus of the fabric material. νij is the Poisson ratio of the material.

The gas exerts a pressure load on the airbag causing it to expand. This expansion puts the airbag under tensile stress lowering the expansion rate. In this study, heat conduction and heat transfer is not taken into account.

Fig. 2 A photograph of Lloyd EZ20 universal testing Fig. 3 Stress versus strain using Lloyd EZ20 machine for a three different airbags at 0° and 90° and b VW airbag test specimens at

Different Angles

Table 2 Physical and mechanical properties of the airbag

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In the deployment of an airbag, an inflator supplies high velocity gas into an airbag causing it to expand rapidly. The gas inside the airbag is assumed to be ideal, to be of constant entropy, and to satisfy the equation of state:

Ð3Þ

Here p, ρ, and e are respectively the pressure, density, and specific internal energy, and γ is the ratio of the heat capacities of the gas. The gas flow is described by the conservation laws for mass, momentum, and energy that

Ð4Þ

here, V is a volume, A is the boundary of this volume,

N Is The Normal Vector Along The Surface A, And U

denotes the velocity vector in the volume. Applying Bernoulli’s equation in the case of an ideal gas with

Ð5Þ

Here, the subscript ex denotes quantities at the throat of the tube. Furthermore u, p, and ρ denote the quan- tities inside that part of the tube that is supplying mass.

Materials And Boundary Conditions

The airbag system mainly consists of three parts: the airbag itself, the inflator unit, and the crash sensor or diagnostic unit. Thus, to study the behavior of the airbag using FE simulations, we need to have an FE model of the airbag in the folded position. A FE model of the airbag was used to simulate the test condition as shown in Fig. 5. LS-DYNA® material model FABRIC (MAT_34) is used to simulate the airbag material. It is a variation of the layered orthotropic material model. Additionally, in the LS-DYNA® material model, fabric leakage can be accounted for. However, for this CAB material, the leak- age is almost negligible and therefore no leakage is specified. The mechanical properties can be determined from the physical test. Typical material properties for airbag fabrics are taken as given in Chawla et al. (2004a) (Table 3). These properties are used to simulate inflation process of airbag (see Table 1). The car dashboard is modeled as the rectangular thin plate using a MAT_RI-

Gid Material, And The Degrees Of Freedom Are Con-

strained in all the directions. The similar properties of thermoplastic polymer are assigned for contact purposes. The porosity of the fabric is assumed zero. The nitro- gen gas is taken for inflating the airbag. Properties of nitrogen gas and initial bag conditions are shown in Table 4. The example on which we perform the study is a typical passenger side airbag. The geometric de- tails have been measured from a commercially avail- able airbag. The initial state of the airbag is a closed rectangular whose sides are to be finished to 482 × 635 mm2 and is shown in Fig. 4.

Table 3 Material properties of airbag and rigid plate used in FE

–

Table 4 Initial values used for FE simulation of the swelling of

3.33 × 10−4

Fig. 4 The initial airbag geometry in the form of a rectangular Bendjaballah et al. International Journal of Mechanical and Materials Engineering (2017) 12:12

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