International Journal of Industrial Electronics, Control and Optimization
Volume:6 Issue: 2, Spring 2023

Active front end (AFE) rectifiers are introduced with bidirectional power transfer capability for the power factor correction and current harmonics elimination. This paper proposes an adaptive model predictive control (MPC) for a single-phase AFE rectifier. The AFE topology used in this paper, is a half-bridge boost converter. In comparison with other single-phase AFEs, this topology has higher efficiency due to a lower number of active semiconductor devices. Considering the presence of one leg of capacitors in this topology, the balancing of the these capacitors voltages is known to be a challenge, along with other control objectives. Also, this paper benefits from an MPC control approach by which the switching signal for every switching state is chosen such that the defined cost function becomes minimized in operation state to achieve all control goals based on the predefined model of the rectifier. Furthermore, an adaptive algorithm for the inductor current estimation is presented to robust the control system against any unwanted disturbance in the control system. As a demonstration of the superior performance of the proposed method, a 1kW rectifier setup with 700Vdc output voltage fed from a 230Vrms/50Hz grid is built in the laboratory. The applicability of the MPC controller is verified and all operation waveforms of the test setup are presented. The proposed method offers a high-quality input current with total harmonic distortion (THD) below 5% and a high power factor (PF) close to one. Also, the efficiency is comparable with the available commercialized rectifiers

This paper contributes to the design, modeling, and planning of a distributed generation (DG) network with wind and solar by means of the particle swarm algorithm (PSO) algorithm in the IEEE 33-bus network, aiming to minimize The results indicate an adequate performance in a variety of environments, and the presence of distributed wind/solar energy generators decreases network stress by feeding loads locally. These systems (wind and solar) can be used in remote areas without power networks, or even in areas where there is a tendency to use renewable energy despite the presence of a power network. They can also supply the output load for most of the day and night. Probability distribution functions are used, and the outputs are expressed as probability density distribution functions instead of absolute numbers. In addition, there is a high degree of uncertainty regarding the state of the system, which is an associated renewable energy source within the power system elements. By means of MATLAB software, the proposed method is implemented in order to ensure effectiveness and validate the results.

This work is trying to introduce a fractional order floated pole controller as a fast and robust approach. We designed a robust variable structure control that yields a continuous and constrained control signal, also a fast response in the presence of model uncertainties and external disturbances. In the proposed controller, we employed the pole placement algorithm, then by designing proper polynomials gave it robust property, then due to a simple optimization routine, we make it fast and faster within the stability region. Finally, to evaluate the proposed method, numerical examples in different situations of the presence of noise, disturbance, and model uncertainties, also comparative results are presented. This paper proposed an accurate, fast, and robust controller. This can improve the performance of the perturbed functional systems used in the industrial fields. It is proposed to spread the benefit of fractional calculus in the control of complex systems in practical situations.

In this paper, a synchronization balancing control is proposed based on the contraction theory of stability for inverted pendulum. The control scheme is applied to balance an inverted pendulum mounted on a moving cart with two wheels. The equations of motion of the system are divided into two cascade systems using the control law partitioning method, which allows the designer to split the control design process into simpler parts for each isolated fragment of the main system. Then two control laws are planned for the corresponding partitions. The main aim of the closed-loop system is to balance the pendulum and synchronize the transient behavior of the system state with a reference model with time-varying parameters. The stability of method is guaranteed using the contraction theory, and the proposed control mechanism is investigated through the simulation study. The simulation result confirms the performance of the proposed controller and illustrate the feasibility of method.

In this paper, a new basic unit is proposed for multilevel inverters. Then, a series connection of the proposed basic unit is used to recommend a new topology for multilevel inverters. To determine the magnitude of dc voltage sources, a new algorithm is presented. For the proposed algorithm, different performance parameters such as total voltage rating of switches (TVRS), number of gate drivers, and number of required sources are calculated as a function of the number of output voltage levels and are compared with other topologies. The comparison proves that the proposed cascaded topology requires fewer components and gate driver circuits than most of the other conventional topologies. Moreover, the voltage rating of switches is less than the other topologies which result lower cost and control complexity. Finally, the correctness of the theoretical analysis and the performance of the proposed inverter are verified using the laboratory and simulation results under different scenarios.

Power electronics converters application has increased in the modern distribution systems due to their advantages to control and process the power flow. Unfortunately, these converters generate harmful harmonics and inject to the grid. The modern standards of the systems accepts which the grid includes harmonics but they have to be less than specified value. In order to satisfy standards, power filters must be added to nonlinear loads. In this paper, a new hybrid power filter is proposed which achieves them. Furthermore, the conventional six-switch inverter of active power filters is substituted to decrease the overall cost and complexity of the system. In order to design the parameters of the passive part of the filter, the SPEA-II meta-heuristic optimization algorithm is used which minimized the overall cost as well as harmonics suppression. Consequently, the four-switch inverter along with optimized design of the passive part makes the proposed hybrid active filter attractive for practical applications. The THD of the injected current to the grid as a critical index in different nonlinear and dynamic loads is less that 2%. Simulation results in different scenarios show the effectiveness of the proposed hybrid filter.

Demand response programs (DRPs) are considered a promising solution to address the variability and uncertainty of renewable generations. Heat pumps (HPs) as responsive loads are prone to participate in DRPs. HPs participation in DRPs will lead to changes in the buildings’ temperature and, correspondingly, the occupants’ thermal comfort (OTC). If these programs are not planned wisely, HPs owners’ tendency to participate in DRPs will reduce, and power system operators will be deprived of the DRPs benefits. This work proposes a new ASHRAE55-based framework to guarantee the OTC. Information gap decision theory (IGDT) is also used to address the uncertainty of renewable generation. Then, an objective function is defined to simultaneously optimize the power consumption of HPs and the uncertainty of wind turbine generators. To find the optimal solution, the standard and adaptive fuzzy PSO algorithms are used. For determining the participation of HPs in the DRPs, there is a conventional scenario in which the temperature of each residence should be limited to the range defined by the occupant(s). The simulation results verify the superiority of the proposed scenario over the conventional one.