The growing share of renewable energies, as well as the rising demand for electricity for transport and heating, are increasing the importance of power converters and the requirements for reliability and control. Intelligent control can increase converter efficiency, reducing size and weight. The application of intelligent control techniques to power converters has therefore recently become a focus of research.
Intelligent Control of Medium and High Power Converters summarizes the state of the art in the control of electric power converters. After an overview of the topic, the chapters cover optimization, bi-directional DC-DC converters, high-gain converters, GaN-based synchronous converters, control design, sliding mode control of three-phase inverters and three-level grid-connected inverters, neurological control, low-frequency switching operation, and a comparison and overview chapter. Comparing control methods for different converters helps users find the best solution for each type of converter and application.
The book is a valuable resource for researchers and manufacturers involved with converters and power grids, as well as for advanced students.
Inspec keywords: invertors; DC-DC power convertors; variable structure systems; power generation control; power grids
Other keywords: invertors; photovoltaic power systems; DC-DC power convertors; power grids; maximum power point trackers; intelligent control; nonlinear control systems; variable structure systems; power generation control; power system simulation; high power convertors
Subjects: General and management topics; General electrical engineering topics; Power electronics, supply and supervisory circuits; Multivariable control systems; DC-DC power convertors; Power systems; DC-AC power convertors (invertors); Control of electric power systems
The importance of power converters in power processing applications has increased in recent years with the proliferation of wind power and photovoltaic, electric vehicles, microgrids, and direct current (DC) distribution systems. Power converters are devices that are used to convert electrical power from one form to another. There are many types of power converters, including DC-DC converters, alternating current (AC)-DC converters, DC-AC converters, and AC-AC converters.
This chapter presents the state-of-the-art of DC-DC and DC-AC converters with respect to their constructions, classifications, topologies, applications, and challenges.
Bidirectional DC-DC converter plays a critical role in the development of smart grid applications using electric vehicles. With bidirectional DC-DC converters, the electric vehicle battery returns a portion of the stored energy to the power grid to realize the vehicle-to-grid (V2G) operation. To enhance the overall performance of the bidirectional DC-DC converter, sliding mode controller (SMC) is adopted. The optimal selection of sliding mode parameters is crucial for improving performance and extending the battery life of electric vehicles, which is executed using the Harris Hawks Optimization (HHO) algorithm. The performance of the converter with the SMC is evaluated for different operating conditions during charging and discharging operations. The efficacy of the HHO-based sliding mode controller in the DC-DC converter is verified by comparing it with conventional PI controllers. The results of the tests show that HHO-based sliding mode controller is effective in controlling the charging-discharging properties of bidirectional converters.
This chapter presents a novel approximation-based extremum-seeking control (AESC) method for the maximum power point tracking (MPPT) problem for the solar photovoltaic (PV) system. Generally, rapid solar radiation and temperature variations make the MPPT problem more challenging in the solar PV system. Besides solving the MPPT problem, the model-free nature of the suggested (AESC) method makes it easy to implement. This feature leads to more precise and faster tracking of maximum power point (MPP) in sudden changes of ambient temperature and solar irradiation as an important factor in MPPT. A high voltage-gain DC-DC converter is utilized in combination with the AESC approach to track the MPP which acts as a power interface between load and panels. The utilized structure has several advantages such as high gain step-up ability per used devices, continuous input current, simple structure, and common ground between source and load. Simulations were performed in MATLAB®-Simulink® and the proposed approach was studied for two scenarios that investigate the impacts of solar radiation and temperature on the solar system. Based on simulation results, the proposed method reduces the oscillations around the MPP of the PV system more significantly compared to the conventional P&O method and tracks MPP faster than the conventional P&O method.
Half-bridge switch cells are frequently employed in DC-DC converter circuits to improve efficiency. However, under light-load conditions, employing both switches degrades efficiency as the switching and driver losses become dominant. In metal-oxide-semiconductor field-effect transistor (MOSFET)-based converters, the sync field-effect transistor (FET) is turned OFF to eliminate these losses and during this duration sync FET's body diode enables reverse conduction. In a gallium nitride (GaN) FET, reverse conduction is possible through its 2-D electron gas (2DEG) channel when the voltage across source-to-drain is higher than the gate threshold voltage. Unlike MOSFET's body diode, it has no reverse recovery loss. However, the voltage drop across source-to-drain during reverse conduction is significantly higher than forward drop of the MOSFET's body diode. The voltage drop can be reduced using a Schottky diode in anti-parallel configuration with the sync FET. MOSFET-based converters also use zero current detection (ZCD) circuitry to enable discontinuous conduction mode (DCM) of operation using the sync FET. Both the above-mentioned techniques use additional components to realize DCM; therefore, the techniques are not cost effective. To optimize the efficiency under light load conditions, this chapter proposes a novel control scheme that can emulate the discontinuous conduction mode (DCM) of operation without using a Schottky diode or a ZCD circuitry. Furthermore, the proposed control technique is simple to implement and it can be easily combined with the existing light-load control techniques. A prototype of the GaN boost converter is designed and a field-programmable gate array (FPGA) device is used to implement the proposed scheme.
Recently, there is a rapid growth in the deployment of both high and medium power converters to interconnect renewable energy resources to the network. These inverter-interfaced energy resources (IIERs) provide clean and green production of energy, which can be either connected to the grid or can operate in off-grid mode [1]. As the operating challenges related to intermittent power generation through these renewable sources of energy (like solar, wind, etc.) can be overcome by interconnecting these sources to the grid, hence this chapter elaborates the intelligent control technique of these inverters. A brief overview of various inverter topologies along with a detailed study of the control architecture of grid-connected inverters is presented. An implementation of the control scheme on two different testbeds is demonstrated. The first is the real-time (RT) co-simulation testbed and the second is the power hardware-in-loop testbed (PHIL). A test case for each of the testbeds is presented to demonstrate the ability of these testbeds.
This chapter proposes a sliding mode approach (SMA) for voltage source inverter (VSI) to regulate the powers injected into the grid. A VSI is employed to connect the wind power system (WPS) to the electrical network system (ENS) and to process the energy generated by this system. The SMA is used for both the three-phase inverter and the rectifier. The inverter is commanded to control the delivered power to the ENS and to sustain invariable the voltage of the DC-link, whereas the rectifier is controlled to guarantee the maximum power point (MPP) for the wind turbine (WT). So, the active current reference is produced via an external loop that has the function of keeping constant voltage of DC-link, but the reactive current reference is fixed to zero to guarantee unity power factor (UPF). The stability of the regulators is achieved via Lyapunov analysis. Simulation results confirm the success of the presented approach and show it can work consistently under diverse conditions. Also, it reduces the impact of short-circuit and fluctuations of voltage on the grid. The comparative results and analysis for the presented SMA strategy and the conventional vector control (VC) are presented for different grid voltage conditions to indicate the excellent performances of SMA method including smoother transient responses and less fluctuation under fault conditions.
In this chapter, a super-twisting SMC (STSMC) will be used to control a three-phase natural clamped point (NPC) inverter with LCL filter. The main objective is to ensure a regulated output AC current with a low Total Harmonic Distortion (THD) value. MATLAB®/Simulink® is used to show the effectiveness of the STSMC strategy. The benefits of the proposed control strategy can be summarized as compliance with the standards imposed by the electrical grid managers without the use of onerous filters at the output of the NPC inverter. Furthermore, the proposed control strategy exhibits an accurate tracking response with low THD of the injected currents while ensuring grid voltage synchronization.
Renewable power is transferred to the utility grid via three-phase inverters. The transfer of the desired power from the inverters with high dynamic performance requires an advanced control strategy that can suppress unknown time-varying disturbances and ensure accurate tracking performance. This chapter presents a neuro-sliding mode control strategy to achieve this objective. A radial basis function neural network (RBFNN) architecture is utilized to estimate the unknown time-varying disturbances. A Lyapunov candidate function is used to highlight the asymptotic convergence of the tracking errors. Simulation results demonstrate the impact of the suggested control method.
This chapter explains the low switching frequency operation of multilevel converters for high-power applications with a focus on selective harmonic minimization for controlling the harmonic magnitude from the output waveform. The intelligent solving techniques have been employed to obtain the optimal switching angles that will provide desired fundamental component and control on selected harmonics component magnitude. The insights provided in this study will benefit the researchers and engineers working on high-power application of multilevel converter systems.
The control performance of the power electronics converter plays an important role in the modern electrical system. There are many advanced control methods that are intended to improve the control performance of these converters. In this chapter, a systematic review of the most advanced control methods has been developed. The advanced control methods are generally classified into two categories: linear controller and nonlinear controller. These are basically based on the characteristics of the controller and how to model the controlled installation. In addition, the performance comparison of these advanced control methods for different converters is performed, which can help engineers to choose the appropriate control methods for an individual converter.
