Advanced controller design based on gain and phase margin for microgrid containing PV/WTG/Fuel cell/Electrolyzer/BESS

Highlights

• Linearized model of PV/WTG/PEM fuel cell/Electrolyzer/BESS based islanded microgrid is presented.

• PEM fuel cell is implemented as a backup generator to compensate for the lack of power.

• An advanced controller that guarantees to provide the desired dynamic features is used to LFC of the fuel cell microgrid.

• Simulations are carried out under the actual data of solar and wind, and appropriate changes of load.

• Electrolyzer and fuel cell subsystems are considered as a solution to the need for sustainability.

Abstract

Nowadays, with the increase in the amount of power generation related to renewable energy resources, the need for energy storage and management is raised. In this regard, the hydrogen energy plays a critical role in the development of renewable technologies. In view of the above, advanced controller design is presented in this paper to effectively perform load frequency control of islanded fuel cell microgrid based on the wind turbine, photovoltaic, fuel cell, electrolyzer, battery energy storage systems, and residential and commercial loads. The controller design is based on the determination of the controller parameters that the fuel cell microgrid system will provide the desired dynamic properties. In the proposed controller design, virtual gain and phase margin testers are added to provide the desired dynamic properties. The controller's stable parameter plane is determined with the help of the stability boundary locus method, taking into account time delay, gain, and phase margin. First, the accuracy of the stable parameter plane determined for the proposed controller design is demonstrated by means of time domain and eigenvalue analyzes. Finally, in order to show the performance of the advanced controller design and the success of the fuel cell as a backup generator, analysis studies have been carried out using actual data of solar and wind, and appropriate changes of load in studied microgrid.

Introduction

The rapid increase in the population and industrialization in our world cause increased energy demand. This increase in demand leads to a rise in fossil fuel consumption and serious environmental damage. That's why powerful motivation can be realized to use sustainable energy sources such as wind, solar energy [[1], [2], [3], [4]]. The amount of power generation based on renewable energy sources (RES) with fluctuating and intermittent outputs constantly increases. Therefore, the need for energy storage and management arises, and hydrogen energy is an essential solution for this need [5]. A big leap towards sustainable energy development can be achieved through the development of advanced processes for hydrogen generation from RESs [6,7]. It is recommended to use hydrogen, which is consumed by fuel cells and produced by water electrolysis, as an energy store in the electricity network [8].

Small-scale energy sources and storages placed near the electricity demand site are called distributed energy resources (DER), and this technological solution strengthens the opinion of using RES based clean generation technologies. The most assuring new electrical grid structure that will provide better use of DERs is the microgrid [9]. Microgrids containing various DERs for energy supply, especially in distance and remote areas, are a controllable small grid [10,11]. The microgrid handles all DER's, including distributed generator, demand response, and distributed energy storage as a single subsystem and allows important control capabilities over its operation. Microgrids can be controlled as a group with foreseen generation and demand [9]. The control [12,13] and energy management [14] of DER and microgrids are two crucial areas of research for effective use of RESs.

Electricity supply and demand must be balanced in electric power grids. The increase in the gap between these binary situation causes voltage and frequency deviations in the electric power system. These deviations in frequency and voltage seriously threaten the stability of such systems and this even may lead to major power failure situations [15]. One of the main problems for microgrid is frequency control. It is essential to ensure a real-time match between generation and demand so that the microgrid system can operate stably and maintain the system's frequency at nominal value. A load frequency control (LFC) mechanism provides a solution to this requirement [16]. Microgrids are operated as an islanded [10] or grid-connected [17] mode. LFC will be one of the most important working tasks in this mode, as microgrid operating in islanded mode does not receive support from the main grid [18]. In Ref. [19], fuzzy logic controller is proposed for frequency/voltage control of microgrid based on photovoltaic (PV), battery energy storage system (BESS), and solid oxide fuel cell. In Ref. [18], optimal active power control is proposed to perform the coordination between the secondary and tertiary control of the LFC of an islanded microgrid. In Ref. [20], target-adjusted model predictive control is proposed for LFC of microgrids.

The control signals between the grid elements and the controller are transmitted via the communication network in LFC of microgrid. However, the implementation of the communication networks introduces time delay to the LFC of microgrids which should be taken into account in the control stage of such systems [21]. Up to now, significant attempts have been devoted to the LFC problem in context of time-delayed microgrid. For example, in Ref. [22], fuzzy based controller is proposed for the future 5G network based secondary LFC in shipboard microgrids, taking into account time delay. In Ref. [23], adaptive technique based on online adjustment of the gain of an integral controller is presented for the LFC of microgrid with time delay.

The stability of power systems has been extensively studied by contemporary researchers for a long time. The stability boundary locus (SBL) method, one of the power system stability analysis methods, is a graphical based control method [24]. In Ref. [25], SBL method is used in PID controller design for LFC system with communication delay. In Ref. [26], the SBL method is used in the design of a structured PI-PD controller for the unstable processes with dead time. In Ref. [27], optimum additional frequency controller design based on SBL method is presented for LFC of a wind farm. In Ref. [28,29] the SBL method is used to determine the gain margin (GM) and phase margin (PM) based parameter values of the conventional PI controller used for a shipboard microgrid and microgrid LFC.

The number of microgrids and RES-based production are constantly increasing. Because of the intermittent and uncertain structures of the RESs, energy storage is vital for these systems. In terms of sustainability, storage based on hydrogen energy offers very important advantages. Hydrogen-based RES storage is intensively investigated both academic and industrial. Nowadays, Power to X systems, which offer many options at a sustainable energy point, are one of the most important areas of the state of art in the field of energy. Here, Power to Hydrogen (P2H) generally constitutes the first step of the transformations that form the X part. The microgrid system created in this study is an example of P2H systems. The main purpose of this study is to create a microgrid model based on hydrogen energy and to offer an advanced controller design based on GM and PM for LFC of this microgrid. As far as the author knows, there is no study in this field in the literature.

This paper is to develop a microgrid system consisting of wind energy, solar energy, fuel cell, electrolyzer, battery systems, and residential and commercial loads. This paper presents an advanced controller design for the fuel cell unit used as the backup generator in fuel cell microgrid system. For this purpose, the stable parameter plane of the controller is determined by the SBL method. A gain and phase margin tester (GPMT) has been added to the fuel cell microgrid. GPMT provides the desired dynamic features to the fuel cell microgrid. The fuel cell microgrid without GPMT only meets the marginal stability requirement. In this case, the fuel cell microgrid may have to operate in areas where unwanted frequency oscillations may occur. The proposed controller design has the following advantages over the state-of-the-art method.

• In the literature, constant power changes are used in many microgrid LFC studies [21,29]. On the contrary, in this study, actual data of solar and wind, and appropriate changes of load are used in simulation studies.

• In the literature, time delays are neglected in many microgrid LFC studies [10,30]. On the contrary, in this study, time delays are taken into account to ensure system reality.

• In the literature, diesel generator and micro turbine are used as backup generators in many microgrid LFC systems [16,31]. On the contrary, in this study, a fuel cell backup generator is used to increase sustainability.

• In literature, optimization [18,23,32] and artificial intelligence [22,33] based controller structures are used in many microgrid LFC systems. These systems require a high online processing load. On the contrary, the parameter values of the proposed controller in this study are calculated offline using the SBL method.

• In the literature, only control techniques that guarantee asymptotic stability of the system are also used in offline controller parameter calculations of microgrid LFC systems [34,35]. These methods cannot guarantee that the system will provide the desired dynamic properties. In this study, GM and PM criteria are included in the stability area calculations in the controller design. In this way, the system provides the desired dynamic performance.