Modeling and Simulation of an Intelligent Hybrid Energy Source based on Solar Energy and Battery

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ScienceDirect ScienceDirect Energy (2019)000–000 97–106 Energy Procedia Procedia 162 00 (2017) www.elsevier.com/locate/procedia Special Issue on Emerging and Renewable Energy: Generation and Automation

Special Issue on Emerging and Renewable Energy: Generation and Automation Modeling and Simulation of an Intelligent Hybrid Energy Source based on Solar and Battery Modeling and Simulation of anEnergy Intelligent Hybrid Energy Source The 15th International Symposium on District Heating and Cooling based on Solar Energy and Battery a a demand-outdoor Assessing the feasibility of using heat AsmaMESKANI , Ali the HADDI Advanced Sciencesfunction and Technologies for Team, University of ABDELMALEK ESSAÄDI,a(ENSATe) 93030, Morocco temperature a long-term district heat Tetouan demand forecast a AsmaMESKANI , Ali HADDI a

a

Advanced Sciences and Technologies Team, University of ABDELMALEK ESSAÄDI, (ENSATe) Tetouan 93030, Morocco

Abstract a

I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc

IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b

Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract Today, the world suffer from air pollution due to the presence of chemicals, particulate matters and biological materials in the air. c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France All these elements have negative impacts on human health, environment and economy. Vehicle emissions are considered a major source of pollution. is one sources of air pollution around the world. Vehicle pollution Today, theair world suffer Transportation from air pollution dueof to the the main presence of chemicals, particulate matters and biological materials takes in the two air. forms, theelements emissionhave of greenhouse gases on (global impact the environment, global warming) and particulate emissionsa major (local All these negative impacts human health,onenvironment and economy. Vehicle emissions are considered impact,ofdeterioration of air quality). In order to tackle this problem, the solution is to encourage the development of hybrid source Abstractair pollution. Transportation is one of the main sources of air pollution around the world. Vehicle pollution takes two vehicles. forms, the emission of greenhouse gases (global impact on the environment, global warming) and particulate emissions (local This paper will shed light onquality). a new hybrid generator topology, equippedthe with a photovoltaic energy conversion system,of a battery impact, deterioration of air In order to tackle this problem, solution is to encourage the development hybrid District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the vehicles. with its DC / DC converter is adopted to replace the fuel cells in order to solve the problems which are: high consumption with a greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat high paper cost inwill terms energy. contribution this work consistswith in the use of fuzzyenergy logic; conversion indeed the system, use of the fuzzy This shedoflight on aAnother new hybrid generatorof topology, equipped a photovoltaic a battery sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, logic system is used as an autonomous control device. logic has been used primarily adapt parameters with its DC / which DC converter is adopted to replace the fuel cellsFuzzy in order to solve the problems whichtoare: highcontrol consumption withina prolonging the investment return period. ordercost to improve of the systemofwhile its in stability. high in termstheofoverall energy.robustness Another contribution this maintaining work consists the use of fuzzy logic; indeed the use of the fuzzy The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand logic system which is used as an autonomous control device. Fuzzy logic has been used primarily to adapt control parameters in forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 order to improve the overall robustness of the system while maintaining its stability. buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district Copyright© 2019Elsevier Ltd. All rights reserved. scenariosPublished were developed (shallow, ©renovation 2019 The Authors. by Elsevier Ltd intermediate, deep). To estimate the error, obtained heat demand values were Selection and peer-review under responsibility of the scientific committee of the Special Issue on Emerging and Renewable Selection peer-review under responsibility of themodel, scientific committee of the 6th comparedand with results from a dynamic heat demand previously developed andInternational validated by Conference the authors. on Emerging and Energy: Generation and Automation. Copyright© 2019Elsevier Ltd. All rights reserved.ICEREGA 2018. Renewable The resultsEnergy: showedGeneration that when and onlyAutomation, weather change is considered, the margin of error could be acceptable for some applications Selection and peer-review under responsibility of the scientific committee of the Special Issue on Emerging and Renewable (the errorHybrid in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation Keywords: vehicles; photovoltaic energy; battery; fuzzy logic Energy: Generation and Automation. scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the Keywords: Hybrid vehicles; photovoltaic energy; battery; fuzzy logic decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations.

© 2017 The Authors. PublishedLtd. by Elsevier 1876-6102Copyright© 2019Elsevier All rightsLtd. reserved. Peer-review under responsibility of the Committee of The 15th International Symposium on District Heating and Selection and peer-review under responsibilityScientific of the scientific committee of the Special Issue on Emerging and Renewable Energy: Generation Cooling. and Automation. 1876-6102Copyright© 2019Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Special Issue on Emerging and Renewable Energy: Generation Keywords: Heat demand; Forecast; Climate change and Automation.

1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the scientific committee of the 6th International Conference on Emerging and Renewable Energy: Generation and Automation, ICEREGA 2018. 10.1016/j.egypro.2019.04.011

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Introduction The movement of a vehicle from point "A" to point "B" involves the combustion of a fossil fuel, a process that emits gases and affects the environment. According to the United States Environmental Protection Agency, more than half of all air pollution in the world is caused by mobile sources, mainly automobiles, given the use of fluids that can harm the environment in the event of a leak, for example, and thus contribute even more to the pollution potential of cars [21]. One solution to overcome the current emissions problems is hybrid vehicles, because they offer lower emissions than gasoline or diesel cars. Fuel cell (FC) technologies should become an appropriate substitute for conventional generators and network applications for residential applications, as they are more efficient and environmentally friendly compared to other conventional generators. However, in order to provide a demand for power from a residential load, it may be necessary to over-size the power module of the fuel cell, which is not economically desirable. In addition, due to the slow dynamic response of the fuel cell in transient events, there will be a charging problem [22]. Not to mention the consumption of diesel fuel and the energy costs that make the CF less efficient (Figure 4.1). In such cases, renewable energy, such as PV panel, has been incorporated to overcome these problems [23]. In an electric vehicle using a single source of power, the power required is transferred from the permanent source, the PV panel for example, to the load. The permanent source must frequently feed or absorb power peaks resulting from acceleration and braking. This dual use of the permanent source, as a source of energy and as a source of power, is highly disadvantageous: the losses and the weight are increased and the life of the energy source is reduced [1].One solution to deal with this problem is the hybridization of the source with a battery that manages power peaks. The permanent source can only provide the average power that ensures the energy autonomy of the vehicle. The battery system provides power to the vehicle during periods of high power demand, such as vehicle acceleration or high constant speed travel. Hybrid sources allow for average sizing of the dissociated power from the peak of transient power, the goal being to reduce volume and weight [2,3]. In this document, a hybrid power source using a PV panel and a battery providing a load is proposed to make the system highly efficient and reliable. Firstly, a dynamic modeling of the overall system is given. Secondly, a description of the components of the proposed system is provided. Finally, the simulation results in the presence of DC bus voltage variations and load resistance disturbances, using Matlab-Simulink, are presented. [4] Moreover, the second objective in this paper is to regulate the VBUS voltage of the DC bus or EBus energy of the DC bus using a fuzzy controller. 1. Dynamic modeling The converter topology for the renewable hybrid system is shown in Fig 1.

Fig 1.Hybrid System Configuration (PV / Battery). [4]

1.1. Modeling the PV panel A photovoltaic PV generator consists of an assembly of solar cells, connections, protective parts, supports, etc. Solar cells consist of semiconductor materials (usually silicon) specially treated to form a positive electric field on one side and negative on the other (towards the sun). When solar energy (photons) hits the solar cell, the electrons are detached from the atoms in the semiconductor material, creating electron / hole pairs.



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If the electrical conductors are then attached to the positive and negative sides, forming an electrical circuit, the electrons are captured as electrical current (photocurrent) [5][28]. The simplified equivalent circuit of a solar cell consists of a diode and a current source connected in parallel (Fig 2). The current source produces the photocurrent, which is directly proportional to solar irradiance. The two key parameters often used to characterize a PV cell are its short-circuit current and open-circuit voltage that are provided by the manufacturer's data sheet [6]. In Fig 2, the RS, RP and C components can be neglected for the ideal model [5]. The p-n junction has some depletion layer capacity, which is typically neglected for solar cell modeling. At an increased reverse voltage, the depletion layer becomes wider so that the capacitance is reduced similarly to the stretching of the electrodes of a plate capacitor. Thus, solar cells represent a variable capacitance whose size depends on the voltage present. This effect is considered by the capacitor C located in parallel with the diode. The RS series resistor consists of the contact resistance of the cables as well as the resistance of the semiconductor material itself. The parallel resistance or shunt RP includes the "leakage currents" at the edges of the photovoltaic cell to which the ideal shunt reaction of the p-n junction can be reduced. This is usually in the kU region and therefore has virtually no effect on the current voltage characteristic [7][27]. The diode is the one that determines the current voltage characteristic of the cell. The output of the current source is directly proportional to the light falling on the cell. The open circuit voltage increases logarithmically according to the Shockley equation which describes the interdependence of current and voltage in a solar cell [7] [8][24]. 𝑞𝑞𝑞𝑞 (1) I=Ipv-I0(𝑒𝑒𝐾𝐾𝐾𝐾 - 1) U=

𝐾𝐾𝐾𝐾 𝑞𝑞

(2)

ln(1-(I-Ipv)/I0)

Where : the Boltzmann constant (1.3806 10e23 J / K); T: the reference temperature of the solar cell; the elementary charge (1.6021 10e19 As); U: the solar cell voltage (V); I0: the saturation current of the diode (A); IPV: the photovoltaic current (A).

Fig 2.Diagram of the equivalent circuit of a solar cell.

The model of the photovoltaic energy system was developed under Matlab / Simulink as shown in Fig 3:

Fig 3. Model of the PV system developed under Matlab-Simulink. [4]

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1.2. Battery 1.2. Battery 1.2. battery Battery has the characteristics of high energy density and The The battery has characteristics of density relatively low power density. Internal resistance the main factor and for The battery has the the characteristics of high highisenergy energy density and relatively low power density. Internal resistance is the main factor for limited current discharge. The equivalent internal series relativelyload low and power density. Internal resistance is the main factor for limited load and current discharge. The equivalent internal series resistanceload has different valuesdischarge. in the charging discharging conditions. limited and current The and equivalent internal series resistance different values and discharging conditions. Charge andhas arecharging non-linear of current and resistance hasdischarge differentefficiency values in in the the charging andfunctions discharging conditions. Charge and discharge efficiency are non-linear functions of current and state of and charge (SOC).efficiency The battery can be modeled as of an current equivalent Charge discharge are non-linear functions and state of charge (SOC). The battery can be modeled as an equivalent circuitofsuch as a voltage and internal resistance (Fig 4). state charge (SOC). source The battery can be modeled[2][9][25] as an equivalent circuit such as source and resistance [2][9][25] (Fig Fig 4.Electrical model of the battery. circuit as aa voltage voltagepanel source and and internal internal resistance (Fig 4). 4). As thesuch photovoltaic the battery have[2][9][25] advantages and Fig 4.Electrical model of the battery. Fig 4.Electrical model of the battery. As the panel the battery have advantages and drawbacks, it is advantageous to have in which As the photovoltaic photovoltaic panel and and the hybrid batteryenergy have sources, advantages and drawbacks, it is advantageous to have hybrid energy sources, in which the photovoltaic provides base energy whilesources, the battery provides maximum power for rapid acceleration drawbacks, it is system advantageous to the have hybrid energy in which the system the and photovoltaic captures the braking energy.[27] the photovoltaic system provides provides the base base energy energy while while the the battery battery provides provides maximum maximum power power for for rapid rapid acceleration acceleration [27] and captures the braking energy. battery perform two main [27] functions: andThe captures thecan braking energy. The battery can two functions: • The source function, formain which the battery is complementary to the main source (FC) (or any other power Thepower battery can perform perform two main functions: •limited The power source function, for which the battery complementary the source), to reduce the for volume and entire system to [10]. • The power source function, which theweight batteryofis isthe complementary to the main main source source (FC) (FC) (or (or any any other other power power source), to reduce the volume and weight of the entire system [10]. •limited The energy source function, since the batteries are electrochemical accumulators, limited source), to reduce the volume and weight of the entire system [10]. ••The The energy source function, since the batteries are source is studied work concerns this secondaccumulators, function. Thehybrid energy sourcewhich function, since in thethis batteries are electrochemical electrochemical accumulators, The hybrid source which is studied in this work concerns this second The hybrid source which is studied in this work concerns this second function. function. 2. Command Strategy 2. 2. Command Command Strategy Strategy 2.1. Description of the proposed hybrid system 2.1. Description of proposed hybrid system 2.1.hybrid Description of the the proposed hybrid The structure proposed in Fig 1 issystem composed of a PV generator as a main source PV, a DC / DC boost The hybrid structure proposed in Fig 1 is composed of as aa main source PV, aa DC DC converter, a DC bus, a battery, a bidirectional DC / DC converter and a RLE modeling The The hybrid structure proposed in Fig 1 is composed of aa PV PV generator generator as load main source the PV,electric DC //motor. DC boost boost converter, a DC bus, a battery, a bidirectional DC / DC converter and a RLE load modeling the electric motor. The DC bus is powered by the photovoltaic system via its DC / DC boost converter which maintains the bus voltage at its converter, a DC bus, a battery, a bidirectional DC / DC converter and a RLE load modeling the electric motor. The DC bus is powered by the photovoltaic system via its DC / DC boost converter which maintains the bus voltage at its reference value. The battery is connected to the DC bus via its bidirectional DC / DC converter. DC bus is powered by the photovoltaic system via its DC / DC boost converter which maintains the bus voltage at its reference value. The is to connected the bus via DC converter. The role of the PVbattery panel is provide to power to the thebidirectional role of the battery is to provide the additional power reference value. The battery connected to the DC DC busload; via its its bidirectional DC // DC DC converter. The role of the PV panel is to provide power to the load; the role of the battery is to provide the additional required by the load during the transient states and to recover the energy generated by the braking. The role of the PV panel is to provide power to the load; the role of the battery is to provide the[23] additional power power required by the load during the transient states and to recover the energy generated by the braking. [23] To handle theload power exchange between the DC and thethe storage element, three required by the during the transient states and bus to recover energy generated byprocedures the braking.may [23]exist: To To handle handle the the power power exchange exchange between between the the DC DC bus bus and and the the storage storage element, element, three three procedures procedures may may exist: exist:      

Charging mode: where the main Charging mode: the source (photovoltaic panel) powers Charging mode: where where the main main source (photovoltaic panel) powers the battery. source (photovoltaic panel) powers the battery. the battery. Unload mode: where the battery and Unload the battery the mainmode: sourcewhere provide Unload mode: where thepower batterytoand and the main source provide power the load. the main source provide power to to the load. the load. mode: where the load Recovery Recovery mode: the provides power the battery (Fig Recovery mode:towhere where the load load provides power to the battery 5). [4] power to the battery (Fig provides (Fig 5). 5). [4] [4]

Fig 5.Structure of the hybrid source. [4]

Fig 5.Structure of the hybrid source. [4] Even with higher efficiency, the goal is to Fig 5.Structure of the hybrid source. [4] Even with higher efficiency, the goal is to maximize the power of the photovoltaic system under various lighting conditions. Even with higher efficiency, the goal is to maximize the power of the photovoltaic system under various lighting conditions. MPPT (Maximum Power Point Tracking) is used to obtain the maximum power of this system [Fig 6]. maximize the power of the photovoltaic system under various lighting conditions. MPPT (Maximum Power Point Tracking) is used to obtain the maximum power MPPT (Maximum Power Point Tracking) is used to obtain the maximum power of of this this system system [Fig [Fig 6]. 6]. The Fig 6.Hybrid system with the MPPT method. [4] The Fig 6.Hybrid system with the MPPT method. [4] The Fig 6.Hybrid system with the MPPT method. [4]



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2.2. Peak Power Point Tracking (MPPT) In order to acquire the maximum power point (MPP) of the photovoltaic generator, it is necessary to keep it at its optimum operating point. MPP varies with solar radiation and temperature. The characteristic curves specify a single operating point at which maximum power is delivered. At the MPP, the PV system operates at its highest efficiency [11][31] (Fig 7) There are many different approaches to maximizing the power of a PV system. The method that has been adopted is the MPPT Perturb and Observe (P & O) algorithm. The disturbance and observation method has been widely used because it is a simple feedback structure and fewer measured parameters are required. It operates by periodically disturbing Fig 6.Characteristic of the PV cell.

(incrementing or decrementing) the voltage across the network and comparing the PV output power with that of the previous disturbance cycle. If the power increases, the disturbance will continue in the same direction in the next cycle, otherwise the disturbance direction will be reversed. The flow diagram of this method is shown in Fig 7 [12, 13, 14].

Fig 7.The flowchart of the P&O algorithm.

Fig 8. (a) Output voltage of the PV generator with the P & O technique; (b) Output current of the PV generator with the P & O technique. [15] [4]

The voltage and the output current of the photovoltaic generator, with a compromise and an observation technique, are shown respectively in Fig 5 (a) and (b). 2.3. Results of the simulation Fig 8 shows the system response to VD and VDC DC bus voltage reference changes. The DC bus voltage follows the reference. A very small overshoot is observed, no stable state error is examined. Figure 4.16 shows the battery voltage and the VB & IB response current in the presence of DC bus voltage variation. The battery supplies energy to the load in the transient and in the steady state no energy is extracted since the battery current is zero. It can be seen that the battery provides and absorbs transient peak power.

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DC Voltage Voltage DC DC Voltage Voltage Reference Reference DC

46 46 44 44

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DC Voltage DC Voltage Reference

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40 40 Vd & Vdc

Vd Vd&& Vdc Vdc

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Fig 9.The DC bus voltage and its reference. Fig 9.The DC bus voltage and its reference.

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55

Ibat Ibat

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Fig 10. (a) Battery voltage. (b) Battery current

3. Fuzzy Logic

Fig 10. (a) Battery voltage. (b) Battery current

3. Fuzzy Logic

Smart tools are increasingly used in the design, modeling and control of complex systems such as robots, biological processes, road vehicles, etc. Intelligent tools are understood to mean soft computing techniques such as Smart tools are increasingly used in the design, modeling and control of complex systems such as robots, fuzzy logic, artificial neural networks and metaheuristics. The fuzzy logic introduced by Zadeh in the sixties is a biological processes, vehicles, etc. Intelligent toolsand areknowledge understood very powerful toolroad for the representation of vague terms [1].to mean soft computing techniques such as fuzzy logic, artificial neural networks and metaheuristics. The fuzzy logic introducedsciences. by Zadeh the ofsixties Since the early 1990s, these intelligent techniques have entered the engineering Theingoal the is a very powerful tool for the representation of vague terms and knowledge [1]. researchers is to design artificial systems that retain the important mechanisms of natural systems. SinceMost the early 1990s, thesecan intelligent techniques have entered the engineering sciences. The goaltheof the non-linear systems be modeled under sometimes quite restrictive assumptions that can make implementation of artificial the resulting control schemes difficult. It is mechanisms therefore necessary to take into account all the researchers is to design systems that retain the important of natural systems. inaccurate and uncertain about theunder system.sometimes The theory quite of fuzzy subsets developed by Lotfi Zadeh in the Most non-linear systemsinformation can be modeled restrictive assumptions thatA. can make 1965 [1] allowed treatmentcontrol of inaccuracies uncertainties. applications are then developed in variousall the implementation of thetheresulting schemesanddifficult. It is Many therefore necessary to take into account fields,and where no deterministic modelabout existsthe or is difficultThe to obtain. advantage of a fuzzy inference systemA.(SIF) inaccurate uncertain information system. theoryThe of fuzzy subsets developed by Lotfi Zadeh in is that only the knowledge of the process behavior to be controlled is sufficient for the synthesis of the control law 1965 [1] allowed the treatment of inaccuracies and uncertainties. Many applications are then developed in various and they raise a wide interest, both theoretical and practical, in the identification and control of complex and nonfields,linear where no deterministic exists oron is the difficult to obtain. advantage of a fuzzy inference processes. This is duemodel to the fact that, one hand, RIS do The not require the existence of an analyticalsystem model (SIF)

is that only the knowledge of the process behavior to be controlled is sufficient for the synthesis of the control law and they raise a wide interest, both theoretical and practical, in the identification and control of complex and nonlinear processes. This is due to the fact that, on the one hand, RIS do not require the existence of an analytical model

11



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of the process to be controlled and little information is sufficient to implement the control loop and on the other hand, SIF are non-linear systems and are thus more suited to control non-linear processes. The design of a fuzzy inference system involves the determination of its structure and parameters. In many cases, the structure is determined, empirically, by choosing a priori the type of approximate linguistic or relational reasoning, the number of fuzzy subsets for each input variable and taking all possible combinations to build the basis of rules. [29] The key objective of this section is to regulate the VBUS voltage of the DC bus or EBus energy of the DC bus using a fuzzy controller. But before that, we will devote a part to describe the basic elements of the fuzzy systems theory. 3.1. Description of the control A hybrid renewable energy system, powered by a photovoltaic (PV) source with a storage battery has been studied in the previous chapters. The PV is used as the primary source, the battery, in turn, works as an auxiliary source and storage system in case of PV power deficiency A mathematical model (reduced order model) is described for the control of the electrical system. A fuzzy logic system is used as a standalone controller, based on the flatness property for regulating the DC voltage of the network. Fuzzy logic is used primarily to adapt controller parameters to improve the overall robustness of the system while maintaining control stability. This is the main innovative contribution of this paper part. [30][32] 3.2. Stabilization of the VDC bus

Fig 11.Control law based on the differential flatness theory of DC bus energy regulation for the hybrid system.

Fuzzy control algorithms offer many advantages over traditional controls because they provide fast convergence, are insensitive to parameters, and accept noisy and inaccurate signals [16], [17] The objective of the control is to regulate the voltage of the DC bus VDC or the EDC continuous bus energy (= y1) using the fuzzy logic. The controller contains a Takagi - Sugeno (TS) inference engine and two fuzzy inputs: the energy error e1 (= y1REF-y1) and the differential energy error (e1) ̇, which are carefully adjusted in using the proportional gain KP and the derived gain KD respectively. In addition, the fuzzy output level can be adjusted by the proportional gain K0 (Fig 11). [18] [19][26]. The triangular and trapezoidal membership functions are chosen for the two fuzzy inputs, as shown in Fig 12(a). There are seven membership functions for each entry, including NB (large negative), NM (negative mean), NS (small negative), Z (zero), PB (large positive), PM (positive mean), and PS (small positive). For the output singleton membership function, the Zero-order Sugeno model is used, the membership functions being specified symmetrically, as follows: NB = -1, NM = -0.66, NS = -0.33, Z = 0, PB = 1, PM = 0.66, and PS = 0.33, as shown in Fig 12 (b).

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For the rule base, an experimental approach and a trial and error technique were used to define the relationships between inputs and outputs. The representation of the data is in the form of an IF-THEN rule, as shown in the following example:

IF e1i is NS and 𝑒𝑒̇ 1i is NS

THEN zi (= output) is NB.

As Fig 12 (c) shows, the total number of rule bases is therefore 49 rules. [18]

Figure 12: Rule base and membership functions. (a) Membership function entries. (b) Output membership function. (c) Rule base

3.3. Simulation result Using fuzzy logic-based intelligent control for dc stabilization based on the flatness property, we have proposed a simple solution to fast response and stabilization problems in the case of the nonlinear system. This strategy is based on a regulation of the VDC DC bus voltage. Indeed, the fuzzy controller makes the tracking error small enough to generate less vibration and greatly improves system performance without changing the controller algorithm or increasing the cost or complexity of the system. The simulation results the authentication of the control algorithm and the control laws.



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Fig 13.Comparison between before and after using the fuzzy controller. [19]

Conclusion Dynamic modeling of a hybrid source system composed of a photovoltaic source and a battery ispresented. Photovoltaic generation is the technique that uses the photovoltaic cell to convert solar energy into electrical energy. Nowadays, PV production is growing faster and faster as a source of renewable energy. However, the disadvantage is that PV generation is intermittent to depend on weather conditions. Thus, the energy storage of the battery is necessary to obtain a stable and reliable output of the PV generation system for the loads and to improve the stable and dynamic behaviors of the whole generation system [20]. This work illustrates detailed transient models of the grid-connected hybrid (PV / Battery) system, and all of these models are simulated using MATLAB / Simulink. The photovoltaic generator is first connected to the common bus D / C by a boost converter, the battery is also connected by a bidirectional DC / DC converter. Maximum Power Point Tracking (MPPT) allows the PV Generators to generate the maximum power of the network, and battery energy storage can be charged and discharged to balance the power between the PV Generator and the distribution network. . Finally, different cases are simulated and the results verified the validity of the models and control schemes. Encouraging simulation results have been obtained, as well as showing the robustness of the proposed controllers with respect to load resistance variations. Many benefits can be expected from the proposed structure, such as providing and absorbing power peaks by using a battery that also recovers energy. At the same time, it can significantly reduce the harmonics on the line. The important contribution of the second part of this work is to improve the quality of the results obtained. For this purpose, a smart fuzzy logic control is applied to the hybrid PV / battery source. Using intelligent fuzzy logic control for DC link stabilization, we have proposed a simple solution to fast response and network stabilization issues. The fuzzy controller has been implemented using MATLAB / Simulink using the application tool provided by the specialized toolbox for fuzzy logic. The results of the simulation authenticated the validity of the control algorithm adopted. References [1] [2]

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