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Parallel-connected fault current attenuator (PFCA) is a novel concept for active reduction of short-circuit currents through circuit breakers in power distribution grids. The sustained increase in the short-circuit currents could exceed the rating of the circuit breakers, dangerously spreading the fault. Several series-connected schemes to reduce these high currents, such as fault current limiters and series reactors have been proposed in recent decades. This paper designs and experimentally verifies the feasibility of a parallel-connected power converter to reduce the short-circuit currents, operating as a controlled current source by absorbing current from the fault point. This new configuration reduces the short-circuit currents in all circuit breakers of an electrical substation. The proposed parallel-connected fault current attenuator is implemented using a single-phase neutral-point clamped (NPC) converter and tested using a predictive current control scheme for short-circuits in a scaled-down power system. The experimental results prove the effectiveness of the proposed scheme, reducing significantly the first short-circuit current peak, even when the AC bus voltage is close to zero.

This article presents a novel simplified method to implement the finite set - model predictive control technique for photovoltaic generation systems connected to the ac network. This method maintains the advantages of the conventional finite set - model predictive control, such as fast response, simple implementation, and easy understanding; but it also eliminates the use of a cost function and hence the weighting factors, instead, it finds the optimal operating state directly from the model and the discrete number of valid states of the converter. Although the proposed algorithm does not compute a cost function, it is able to select the inverter state that minimizes the tracking error by using a hexagonal convergence region. The main advantage of this technique is to reduce the computational cost in 43% of the algorithm that selects the best state, presenting a simple and complete algorithm without compromising the predictive control performance. The proposed algorithm properly operates under various conditions such as changes in the network frequency and changes in the system parameters.

Over the last few decades, the consolidated goal of reducing greenhouse gasses has increased the relevance of renewable energy research, electromobility, energy storage, and distributed generation, micro-grids, among others. Micro-grids, systems working in islanding mode, are particular cases where some disadvantages are present due to the wide variations which may appear across their electrical quantities. Variations on the voltage amplitude and the frequency are intrinsic in the operation of weak grids, because they have low inertia and therefore the load must be able to cope with these variations, otherwise loads may trip electrical system protection. Particularly, on power electronic drives, these frequency deviations will lead to increased system nonlinearities, entailing a more critical controller design. To overcome these issues, this paper presents an implementation of a resonant controller with self-tuned gains. The strategy imposes a constant sampling time which allows these controllers to be used in variable frequency environments. In addition, the computational capacity required for the digital board is also considered. The simulated and experimental results provided demonstrate the good performance of this proposal.

The need to decarbonate the planet, due to the massive use of fossil energy, has led to turn to employ renewables energies in many applications. Among the most common energy sources are the wind, solar, and sea, being one of the most relevant the solar energy, particularly in some countries as Chile. To transport the energy, solar system must be connected to a middle voltage level lines and therefore different topologies have been proposed where some of them are based on H-Bride. This work presents the use of H-Bridge power converters connected in parallel in the dc side and connected to a transformer in the ac side to pump up to middle voltage level. Additionally, as all phases of the H-Bridge are connected in parallel in the dc side, the third harmonic, typical of this topology, is compensated and therefore the ac waveform results free of low frequency harmonics. To get the maximum power from the solar array, it is employed a maximum power point tracker which uses measuring cells, avoiding oscillations around the maximum power point. The results show the feasibility of the proposal.

Power conversion has gain relevance because of the capacity to transform the electric energy as needed in many applications such as electrical drives, electromobility, reactive power compensation, renewable energies, among others. In this context, the proper control of the power converter may lead to improve the efficiency and protect the entire power converter system. This paper presents a deadbeat control with the capability to enhance the fast dynamic response, typical of this technique, and therefore to be used for current and voltage control applications that require slower dynamic. The proposed technique is implemented in a three-phase power converter with satisfactory results; moreover, this technique is simple and light in computational cost. Finally, to corroborate the proposal, simulations are included with satisfactory results showing an improved dynamic and making the deadbeat control softer as some applications may require.

The use of renewable energies sources is taking great importance due to the high demand for electricity and the decrease in the use of fossil fuels worldwide. In this context, electricity generation through photovoltaic panels is gaining a lot of interest due to the reduction in installation costs and the rapid advance of the development of new technologies. To minimize or reduce the negative impact of partial shading or mismatches of photovoltaic panels, many researchers have proposed four configurations that depend on the power ranges and the application. The microinverter is a promising solution in photovoltaic systems, due to its high efficiency of Maximum Power Point Tracking and high flexibility. However, there are several challenges to improve microinverter’s reliability and conversion efficiency that depend on the proper control design and the power converter design. This paper presents a review of different control strategies in microinverters for different applications. The control strategies are described and compared based on stability, dynamic response, topologies, and control objectives. One of the most important results showed that there is little research regarding the stability and robustness analysis of the reviewed control strategies.

The cost function selection is considered one of the most relevant aspects for the implementation of Model Predictive Control strategies. In this paper a study of the most common cost functions used for the control of a two level voltage source inverter is presented. The paper introduces several cost function alternatives that could be considered for different power electronic converter applications to compare the implementation and resulting converter waveforms. The results show that Model Predictive Control is an alternative for the implementation of different control objectives in power electronic converters.

Renewable energies have gained the attention of society, governments, and researchers for bringing solutions to the growing need of continuous energy supply for homes and industries. Great efforts are being made to develop and adapt technologies that make possible to harvest inexhaustible energy sources such as wind, solar, waves, etc. There are different stages associated to renewable energy injection: first one is the energy extraction, this can be implemented with solar panels, turbines, etc.; the second stage considers power conversion, and in the final stage, transformers make possible energy transmission to users. This paper focuses in the design of a suitable control strategy for a power converter to inject energy from solar panels, tracking the maximum power point. In this paper, an optimal control strategy is tested in a Buck-Boost power converter which is capable to vary the voltage at the first stage to follow the inputs and extract the maximum amount of power, in spite of bounded variations in irradiance and temperature. Particularly, a Linear Quadratic Regulator (LQR) is combined with a Kalman Filter (KF) to regulate a Buck-Boost output for the rejection of constant disturbances, thus mitigating measurement noise. Obtained results show that the proposed controller achieves an acceptable performance for the target setting.

Renewable energies sources have grown regularly in the last year, because they have been a solution not only for reducing the power expenses but also to be employed in the remote areas and places, moreover, all companies will be obligated to produce or buy clean energy to reach carbon neutral in 2025. Thus, this paper makes the technical and economical analysis of including solar power system in a mayor berries agroindustry. The study includes all considerations the farmers should consider for solar panel installation in order to not only produce for themselves but also sell the surplus to the grid. This is important, since during winter season the irrigation energy requirements is minimal compare with the middle of the summer, and therefore the total amount of produced energy should be sold to the grid in order to improve the investment payback time. The complete analysis is illustrated based on the actual normative and tools to configure solar systems.

Severe climate change effects along with the increasing need for countries to become independent from fossil fuels are leading countries to seek more sustainable energy sources. This is not an easy task, as many renewables lack the portability and reduced variability which is required to properly satisfy energy demands. In this context, hydrogen technologies are a promising alternative to work towards this goal. This work presents a brief summary on hydrogen technology properties, focusing in particular on the description of hydrogen cells, their characteristics and main applications. Finally, the operation of a PEM cell is simulated using a computer model, in order to illustrate how these tools can be used to further characterize PEM cell performance when designing hydrogen-based solutions.

A power management control strategy for a photovoltaic micro-inverter with embedded hybrid energy storage system is proposed. The analyses are focused on the performance of the control scheme for feeding a local load. Three levels of control are proposed. Primary control is directly applied to power converters to manage the energy flow based on the reference current tracking. The secondary control oversees regulating the DC Bus voltage by means of the power balance, which ensures that the load power is equal to the power in the DC Bus. The tertiary control is in charge of the system dynamics, that is, it is responsible for responding adequately to sudden changes, in this case, when the load power increase. The primary control includes an input-output linearization control, allowing the use of linear controllers that are not limited to an operating point. A Maximum Power Point Tracking algorithm based on the incremental conductance is implemented on the photovoltaic panel. A suitable control scheme for the hybrid energy storage system is proposed to tracking both, DC link voltaje and AC output voltaje-current, alowing to stabilize the system to sudden changes. Simulated results are presented to validate the properness of the proposed control strategy.

In the last few years, a rise in the planet earth pollution has brought forward a necesity for renewable energies and different ways to exploit them in order to replace coal, oil and gas. In this context, the entire world is looking forward to produce electricity by the means of -mainly- solar and wind energy, but also searching for other clean alternatives. This electricity may be used to transport people into and out of the cities, helping to reduce pollution gases that every day saturates big towns. In fact, it is expected for electromobility to be the most important way to transport people by 2050, and therefore, the design and development of proper control algorithms for electric machines become imperative in order to improve driving and safety in modern powertrains. This paper studies and reviews some of the most important works, with a special mention about, regenerative braking, grip improvement, and vectorial torque control considering the entire car dynamics. As results, this document shows the importance of proper electric powertrain control such as MPC (model predictive control) which helps with critical safety decisions that make the car stable, DTC (direct torque control) which labor is to ensure the right amount of torque is produced by the power unit in order to comply with the decisions made by the MPC or the Fuzzy Logic Controllers. All these control strategies make cars even more flexible, safe and robust than traditional combustion ones.

This article presents a review of the predictive control techniques applied in a voltage source inverter to regulate the direct voltage (active power) and the reactive power injected into the grid. As Deadbeat and finite state control are based on the system model, they lead to a faster response and without overshoot, however, they are normally used in internal current control loops, in this case their applied behaviors are presented as such, but the application of a Deadbeat based on the general model of the static converter is also studied, thus contributing its advantages to the control of the DC voltage. When implementing the latter, some considerations related to the high power necessary to reach the references -especially in direct voltage- in a few control steps, in addition the device is protected by limiting the maximum power drained from the source. The mathematical development is carried out according to the power of the converter, limiting it, but tracking the references with high dynamics. The system is subjected to significant disturbances, demonstrating their robustness to such events.

Distributed power generation together with microgrids and renewable energy have brought the problem of power generation and electric system stability. These kinds of grids have shown problems related to the frequency and amplitude voltages. In effect, the literature shows variation up to 100% on the grid frequency, leading to carefully design the equipment that is connected to these grids. This paper studies the frequency variation, the sag, and swells effect on power converter by using the two most used topologies, the power converter as rectifier and inverter with their respective first order and second order filters respectively. The results show the large effect on the power converters and therefore demonstrate the importance of considering the frequency on the control design, since the entire operating region is affected.

Model predictive control strategies have recently emerged as a viable alternative for the control of power electronic converters in a range of applications. In this paper a new model predictive control technique for both the ux and torque of an induction machine is presented. The algorithm selects from the available switching states of the voltage source inverter, the chosen state in each sample period optimizes a cost function which is based on the tracking of the electromagnetic torque and the stator ux together with additional criteria to ensure the proper operation of the machine. The results demonstrate the fast torque-ux response with the required quasi sinusoidal stator machine currents.

Wind energy gains interest due to the diversification and decarbonization of the energy matrix to leave behind the use of fossil fuels that contribute to global warming. Obtaining energy from the wind is complex, since wind energy has a variability that strongly affects the quality of the energy generated, in addition, the wind turbine has non-linear characteristics that make the control stage even more difficult. Various techniques address this issue, and acclimatization is required. This work presents the pitch control design methodology for a large capacity wind turbine. Linearized dynamics and MPC controller are used to manage the pitch angle of the wind turbine. The results are validated with real data from southern Chile and show acceptable results for power smoothing. The obtained results help to understand the effects of constraints on the control strategy and its performance in practical applications, thus emphasizing the need for appropriate methods for nonlinear systems control.

Power converters have turned into a critical and every-day solution for electric power systems. In fact, the incorporation of renewable energies has led towards the constant improvement of power converter topologies and their controls. In this context, over the last 10 years, model predictive control (MPC) is positioned as one the most studied and promising alternatives for power converter control. In voltage source inverters (VSI), MPC has only been applied in the inner current control loop, accelerating and improving its dynamic response, but as mentioned, has been limited only to the current control loop. The fastest of the MPC techniques is the Deadbeat (DB) control, and in this paper, it is proposed to employ DB control on the entire system, therefore accelerating the time response not only for the current loops, but also for voltage loops. At the same time, this avoids overshoots and overpower in order to protect the power converter, leading to the fastest dynamic response according to VSI capabilities. For renewable energies, fast-dynamics entails fast maximum power tracking and therefore, maximizes energy harvesting, or in other words, reduces the losses due to the control dynamics. Thus, this paper gives a clear procedure and key points for designing a DB control for all the variables based on a mathematical model, which is corroborated by simulations and the experimental results.

This paper proposes a hybrid control scheme based upon both a linear and a predictive control approach for a grid-tie inverter for photovoltaic applications. The proposed strategy uses the complex representation of the switching states and splits them choosing the best one without using an iterative loop. The resulting algorithm, in terms of the dynamic and static response, performs like the traditional Finite Set Model Predictive Control (FS-MPC). However, the proposed scheme is easy to implement, it does not need to tune parameters nor need a cost function and nor require iterating all the possible states to choose the best. Over the abovementioned advantages, it has the capability to operate the photovoltaic module at the maximum power point (MPP) and the ability to impose a sinusoidal current at the grid side with a unitary displacement power factor. Preliminary results are presented to validate the proposed control method.

Solar energy is an interesting alternative to supply the growing energy requirements from industries and homes. In fact, many researchers have put effort to maximize the solar system efficiency. This paper, make a comparison between three alternatives of maximum power point tracking algorithms (MPPT) to inject the maximum power to the grid. The proposal includes only a three-phase inverter avoiding the DC-DC con- verter and therefore the control is performed throughout the DC link voltage reference. The comparison includes the total time to compute every algorithm where the TMS320F28335 DSP based board is employed. On the other hand, the three-phase power converter is controlled through nonlinear based control which decouples and linearizes the current response. The results give key lines to decide the proper MTTP algorithm considering the processing time and the desired performance.

Maximum Power Point Tracking (MPPT) methods have been widely discussed in many researches to improve the efficiency of the energy extraction from solar cells. On the other hand, to control process the most common way is to find a model, where the parameters are adjusted in order to achieve similarity between the model and the real plant. Solar cells have been modeled by nonlinear equations that allow to approximate the static behavior. However, the parameters evolved in these equations depend upon the construction and the type of solar cells. Thus, this paper proposes a parameter identification with a new simplified method to identify the parameters n, Rs and I0, by studying and analyzing the equations of the PV model and the information provided by the datasheets of the best-selling commercial PV panels in the world.

Control of power converter is being widely studied to properly manage the variables and convert the energy to reach the settled goals. Particularly, the insertion of renewable energies on the ac mains have focused the attention of researchers to applied suitable control methods to inject power to the grid. In this document, a nonlinear control strategy for a power converter is presented. The back-to-back topology allows decoupling grids by using a dc link between them. The energy transference and the power quality have to be controlled. Thus, primary controllers have to design to meet certain values. Loads sensitive to voltage variations need to be handled correctly. The proposal is tested by simulation, and the results validate the proposal.

This paper proposes a mixed linear control and model predictive control (MPC) scheme with extended horizon for a neutral point inverter topology (NPC) for photovoltaic applications connected to the AC network. The strategy is able to minimize the unbalance of the voltages of the capacitors in the DC link and to draw a sinusoidal current on the network with a unity displacement power factor. Unlike other MPCs, the resulting algorithm is easy to implement, the weighing factors of the cost function are not needed, and the computational cost is reduced. These advantages are added to the ability to operate the photovoltaic module at the point of maximum power (MPP).

Different maximum power point tracking methods have been developed for photovoltaics systems to extract and inject the maximum power to the grid. This paper introduces an algorithm based on the solar mathematical model and two measuring cells, one in open circuit and other in short circuit. The proposed method uses the model and adjusts the unknown PV internal system variables to specify where the maximum power point (MPP) is placed in the plane I-V or P-V. The PV array, together with a three-phase inverter, controlled by a nonlinear feedback control algorithm, are employed to inject electric power to grid, where the dc voltage of the power converter is regulated to track the MPP. Finally, the results show the feasibility of the proposal where the MPP is accurately estimated by the proposed algorithm.

The interest on weak and micro-grid systems has grown up substantially last time, specially tied up to distributed power generation systems (DPGSs), isolated systems as aircraft, or islanding power systems. These kinds of grids are usually under significant variation in their quantities, specifically in their voltage amplitude and/or frequency. On this line, many studies about synchronization methods have been developed, which may work under variations on the frequency value, unbalanced voltage, and even with harmonic distortion. However, power converters connected to this class of systems are poorly documented—specifically controlled rectifiers. In fact, most of the controlled grid connected converters (GCCs) are defined to work in a fixed frequency and balanced system. This paper deals with a GCC connected to a variable-frequency and unbalanced voltage supply system control through a predictive algorithm with a fixed resolution sampling strategy. Furthermore, the current references are imposed in order to help the weak-grid source subjected to unbalancing, taking more power from the phase with highest voltage amplitude and relaxing the other phases. This issue makes to calculate every phase current reference independently and accordingly the voltage amplitudes keep the dc-link voltage in a desired value. The results show the feasibility of the proposed algorithm, where the performance is highlighted by simulated and experimental waveforms.

The use of power converters has considerably grown up, in part, because refined control strategies have been recently proposed, including nonlinear schemes such as predictive control. This approach is used in this work considering a variable grid frequency environment in order to get an appropriate response for a wide ac mains frequency range. Indeed, in order to achieve appropriate, both dynamic and static, responses for all operating frequencies, the number of samples per period is kept constant and independent of the ac mains frequency. This allows a fixed resolution of the sensed voltages and/or currents, which is preferable if high-performance digital control schemes are required. However, imposing a constant number of samples per period requires a variable sampling time in systems that feature variable ac mains frequency. On the other hand, predictive control has been developed and well documented just for a constant sampling frequency. This work presents how to extend the predictive control algorithms for variable sampling time allowing high-performance waveforms and wider ac mains frequency range. Simulated and experimental results show the feasibility of the proposed control strategy which corroborates the mathematical and model analysis.

This paper proposes an algorithm capable of estimate the global maximum power point of a large photovoltaic (PV) array system operating under partially shaded conditions. The power-voltage characteristic of a photovoltaic array is a nonlinear function that becomes more complex under partial shading conditions, in fact, the power-voltage curve may exhibit multiple local maximum power points. The proposed algorithm uses two PV reference cells, every 900 m2, one operating in open-circuit and the other one in short-circuit, to estimate the solar radiation and the ambient temperature conditions of the PV arrays. The results show an estimation error of the ambient conditions lower than 1% of the actual values. As a result, the arrays provide the maximum power possible for any distribution of irradiance and temperature conditions.