Elsevier

Journal of Energy Storage

Volume 32, December 2020, 101796
Journal of Energy Storage

Nonlinear controllers for fuel cell, photovoltaic cell and battery based hybrid energy management system

https://doi.org/10.1016/j.est.2020.101796Get rights and content

Highlights

  • Three nonlinear controller for output voltage regulation for DC-DC converter and MPPT of PV has been proposed.

  • Using Lyapunov Stability Theory, asymptotic stability of the controller has been proved.

  • Tracking of maximum power from the PV array has been assured using MIMO converter.

  • The comparison is done with Perturb & Observe method and Fuzzy Logic controllers.

Abstract

Due to limitations of conventional energy sources like petrol, diesel, hydro, nuclear etc., hybridization of green energy sources like photovoltaic cell, wind, fuel cell etc. has become a challenging task. In this research photovoltaic (PV) and fuel cells (FC) have been considered as primary sources of energy while battery as a storage unit for a Hybrid Energy Storage System (HESS). Extraction of maximum power from PV panel and output voltage regulation is another challenge due to its nonlinear characteristics. In this paper, single stage multi input multi output (MIMO) buck converter has been considered and four controllers: Fuzzy Logic Based (FLB) robust, nonlinear Backstepping (BS), Integral Backstepping (IBS) and Synergetic controllers have been proposed to track the output voltage, to control the battery charging and to extract maximum power from the PV cell. Asymptotic stability of the proposed controllers has been proved using Lyapunov theory. The performance of nonlinear controllers has been checked under input power and load variations on the converter having only one inductor and two input sources. They have been compared with each other and conventional PID controller under different operating conditions by simulations in MATLAB/Simulink. The results have also been validated by an experimental setup on a lab prototype.

Introduction

Due to life threatening environmental pollution, renewable energy sources are becoming important for commercial and residential purposes [1], [2]. HESS and HEMS using different combinations of PV, FC, wind, battery, ultra-capacitor etc. (for instance, for hybrid electric vehicles or smart grid applications) have become the focus of the researchers around the globe. PV is widely used in small-size applications. It is the most promising candidate for large-scale research and development, as less expensive PV devices are being produced today [3]. Its power generation, by converting solar radiation directly into electricity, offers many significant benefits. For example, it provides power where no electricity was available before. Under varying weather conditions, an operating point of PV changes, resulting in large variation in its output power. One way of overcoming the problem is to integrate PV with other power sources like fuel cell, battery [4], wind and diesel engine [5].

In a micro-grid, the backup system of power supply can improve efficiency, power density and diversified the load pressure at power distributed generations [6]. Fuel cells are a very attractive option to use with PV for both standalone and grid connected applications because of their fast load response, instantaneous recharging capability and high efficiency [7]. For a micro-grid, regulation and power management are two main aspects [8]. The first is to control the voltage of DC bus and the second is to balance the power between input sources and the load. Power fluctuations occur when environmental dependent PV source is connected with micro-grid. This is due to nonlinear characteristics of the PV that is affected by solar irradiance and temperature resulted in randomness of PV power generation which decreases the stability of grid [9].

For such a system, an efficient converter acting as a hybrid energy system is required to integrate multiple renewable energy sources [10]. In [11], MIMO converter has been used in which number of input sources and loads are arbitrary. However, simultaneous power from all input sources cannot be delivered to the inductor which causes input current ripples to be high. In [12], boost MIMO converter with one bidirectional port and other unidirectional ports has been presented. In this topology, it is not possible to transfer simultaneous power from the input sources to the load. A triple input single output converter for high gain application is proposed in [13]. One bidirectional port is used for charging and discharging of the battery and two input ports are unidirectional. Moreover, conduction losses of switches are high due to high number of conducting current. Also three input single output step up converter has been proposed in which PV, fuel cell and battery are inputs [14]. However, the number of loads cannot be extended to any number. In [15], MIMO converter with arbitrary number of inputs and output can be connected. The main drawbacks are; input sources cannot be used simultaneously and power flow is unidirectional. For bidirectional power flow, dual input single output converter has been proposed in [16] and [17], which can operate in both buck and boost modes. Though many sources can be integrated but the problem is the number of sources are proportional to the number of inductors which may make it costly and less efficient [18].

Many converter topologies have been used in the literature where some linear or nonlinear control techniques have been applied to solve the various problems. Stability analysis has been done for the case of hybrid energy storage system in terms of robustness and non-oscillatory dynamic behavior and to meet certain requirements like output voltage regulation, maximum power point tracking (MPPT) and power factor correction [19], [20], [21], [22], [23]. However, the design and implementation of adequate control scheme for a nonlinear PV system, is still a challenging task. The nonlinear characteristics of the PV due to variations in irradiance and temperature results in unpredictability of PV power generation which ultimately decreases the stability of grid. Linearized model has mostly been used to design control strategy of the PV system in microgrids. However linear control systems can provide satisfactory performance only near an operating point [24] and under varying weather conditions the operating point of PV changes, resulting in large variation in its output power. Consequently the control scheme at this operating point can enter in chaotic behavior and the overall system can become unstable [25], [26], [27]. To address the issue, the nonlinear controllers for an efficient and reliable power electronics interface, have been developed to ensure reliable performance and global stability [28].

The techniques like sliding mode control are proposed to provide robust tracking against the uncertainties of a grid-connected PV system [29], [30] where a time varying sliding surface is used for designing the controller. However, the selection of such a sliding surface is not an easy task and a chattering problem occurs due to imperfect control switching. To ensure fast response of grid system, Hysteresis controller is proposed [31]. But its operation requires high variable switching frequency. In [32], [33], to improve the performance of converter for grid-connected inverter applications, feedback linearization technique has been used. This technique has removed the limitation of linearization and allowed to operate over the whole range. However, the design procedure of such converters is complex due to their dependency on system parameters. In [34], the nonlinear composite sliding mode controller (SMC) has been designed to control charging of the battery, to enhance the system reliability for standalone areas and to mitigate the chattering issue of conventional SMC [35], [36]. To control the DC bus voltage in DC micro-grid, an Adaptive Backsteping controller has been proposed under various operating conditions in [37]. Moreover, for the system backup, diesel generator has been equipped along with the battery [38], which is not an efficient solution due to its slow dynamic behavior.

Other than micro-grid, several nonlinear controllers have been designed to find a solution to the various problems [39]. The nonlinear Fuzzy logic based controller (FLBC) has been applied on SISO boost converter to extract maximum power from PV [40]. Its rise time is slow and has oscillations of larger magnitude around the Maximum Power Point (MPP) because its implementation depends on domain knowledge and set of rules [41] due to which decision-making issues arise [42]. The issues in Fuzzy controller have been resolved in [43] and [44] by designing Backstepping and Integral Backstepping nonlinear controllers. The results of both controllers were better than FLBC but these techniques have been applied only on SISO buck/buck-boost converters in which load regulation and incorporation of multiple input sources have not been done. Moreover, Backstepping controller tracks the reference efficiently [45] and the results of Integral Backstepping controller are better as compared to Backstepping because it reduces the steady state error to almost zero. They have been proposed using SISO converters but if the system is complex and has more states, designing of such controllers becomes a difficult task.

In this paper, considering PV as a main source, FC as a secondary source and battery as the storage unit, four nonlinear controllers have been proposed using a dual input triple output (DITO) DC-DC Buck converter for the output voltage regulation, control of battery charging and extraction of maximum power from PV. The fuel cell has the potential of catering for the requirements of load when battery and PV are not providing energy. The converter has two input ports and three output ports in which one port is unidirectional for the battery storage and one port for the load. The block diagram of the proposed system has been shown in Fig. 1.

The rest of paper has been organized as follows: the section-II details the proposed methodology and operation of the converter. Section-III, presents the modeling of the DITO buck converter. Section-IV, describes the derivation of Synergetic controller. Section-V presents the simulation results under power and load variations. Section-VI shows experimental results. In the last section, the conclusion is drawn on the basis of controller’s performance.

Section snippets

Proposed methodology and converter topology

The operating principle of traditional linear controller and proposed nonlinear algorithms is quite different. For PV, the proposed system senses the values of temperature and irradiance and by using the relationship of these two measured values with maximum voltage (VMPP), the reference is generated which can be tracked by the controller to extract maximum power. Designing of the controller depends on the converter topology which changes the mathematical modeling. For output voltage regulation

Mathematical modeling of dito buck converter

The following assumptions for the modeling of the converter are made: 1) All diodes and semiconductor switches are ideal. 2) The converter is operated in CCM. 3) Resistances of all capacitors and inductor are zero. 4) Sw3 and Sw4 are complementary switches. 5) Sw1 and Sw2 operate at the same time. 6) R2 is taken as its internal resistor to track the battery voltage.

The converter has three modes of operation as shown in Fig. 4. In mode 1, Sw1, Sw2 and Sw3 are closed/conducting, while Sw4 and Sw5

Design of synergetic controller

The designed controller gives μ and μ1 as outputs that determine the duty cycles for switches Sw3 and Sw4. Sw3 tracks the output voltage at 12V and Sw4 controls charging of the battery at 24V.

Simulation results

To show the performance of proposed controllers, the simulation results have been presented by using MATLAB/Simulink. For comparative study of the proposed controllers, they have been compared with each other and conventional PID controller. In Tables 1 and 2, all values of components and parameters of battery and PV used for the simulation results have been listed. The values of gains in Table 1 are selected by hit and trial to minimize the error. The gains of PID controller are: proportional

Experimental results

A hardware prototype has been developed for the validation of simulation results, as presented in Fig. 18. Two DC sources are used instead of PV and fuel cell on the input side. The microchip DSPIC30F2020-30I/SP controller is used for hardware implementation which is connected to a PC via. a PICkit to run the algorithm of controller. The proposed Synergetic controller has been tested under both power and load variations as shown in Figs. 19 and 20 respectively. For the input power variation,

Conclusion

In this paper, PV has been considered as primary source, fuel cell as secondary one and battery as a storage unit for a hybrid energy storage system. Four nonlinear controllers: Synergetic, Backstepping, Integral Backstepping and Fuzzy logic based controllers have been proposed in order to track the output voltage, control the charging/discharging of the battery and MPPT of PV array under all type of input power and load variations, implemented on dual input triple output DC-DC Buck converter.

Declaration of Competing Interest

No conflict of interest

Kiran Liaqat is a student of master in School of Electrical Engineering and Computer Science, National University of Sciences and Technology (NUST), Islamabad, Pakistan. She received her B.S. degree in electrical engineering from the National University of Computer and Emerging Sciences, Islamabad, Pakistan, in 2017.

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    Kiran Liaqat is a student of master in School of Electrical Engineering and Computer Science, National University of Sciences and Technology (NUST), Islamabad, Pakistan. She received her B.S. degree in electrical engineering from the National University of Computer and Emerging Sciences, Islamabad, Pakistan, in 2017.

    Dr. Zubair Rehamn is serving as an Assistant Professor at Department of Electrical Engineering, School of Electrical Engineering, and Computer Science, National University of Sciences and Technology (NUST), Islamabad, Pakistan. Earlier, he has done his Ph.D. in Electrical Engineering, from the Massey University New Zealand.

    Dr. Iftikhar Ahmad is serving as an Assistant Professor at Department of Electrical Engineering, School of Electrical Engineering, and Computer Science, National University of Sciences and Technology (NUST), Islamabad, Pakistan. Earlier, he has done MS in fluid mechanical engineering from University Paris VI (University Pierre Marie Curie, Paris) and has done his Ph.D. in Robotics, Control and Automation, from the Universite de Versailles France.

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