Articles de revista
http://hdl.handle.net/2117/3669
2024-03-28T12:12:41Z
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Voltage support provided by three-phase three-wire inverters with independent reactive phase-current injection
http://hdl.handle.net/2117/404742
Voltage support provided by three-phase three-wire inverters with independent reactive phase-current injection
Iñiguez Amigot, José Ignacio; Duarte Mejia, Josue Neftali; Camacho Santiago, Antonio; Miret Tomàs, Jaume; Castilla Fernández, Miguel
During voltage sags, three-phase three-wire power inverters can provide voltage support with several current injection strategies. In general, good results are ob- tained, except in overvoltage situations when one or more phase voltages exceed the allowed limit in grid codes. In three-wire inverters, this is a challenging problem because phase voltages are coupled. In this article, we present a strategy that performs independent reactive current injec- tion for each phase, which solves the overvoltage problem. This approach also includes a current-limiting technique that guarantees the injection of the maximum active power under safe current conditions. A stability analysis is carried out based on the small-gain theorem. The properties of the proposed control are experimentally validated with selected tests in a laboratory setup. A performance comparison with state-of-the-art control strategies is also included in the experimental validation.
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2024-03-15T14:02:34Z
Iñiguez Amigot, José Ignacio
Duarte Mejia, Josue Neftali
Camacho Santiago, Antonio
Miret Tomàs, Jaume
Castilla Fernández, Miguel
During voltage sags, three-phase three-wire power inverters can provide voltage support with several current injection strategies. In general, good results are ob- tained, except in overvoltage situations when one or more phase voltages exceed the allowed limit in grid codes. In three-wire inverters, this is a challenging problem because phase voltages are coupled. In this article, we present a strategy that performs independent reactive current injec- tion for each phase, which solves the overvoltage problem. This approach also includes a current-limiting technique that guarantees the injection of the maximum active power under safe current conditions. A stability analysis is carried out based on the small-gain theorem. The properties of the proposed control are experimentally validated with selected tests in a laboratory setup. A performance comparison with state-of-the-art control strategies is also included in the experimental validation.
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Variations of the Gauss Seidel and the gauss implicit z-bus load flow methods for primary-secondary integrated distribution grids
http://hdl.handle.net/2117/403971
Variations of the Gauss Seidel and the gauss implicit z-bus load flow methods for primary-secondary integrated distribution grids
Barrenechea Gruber, Roberto Carlos; García de Vicuña Muñoz de la Nava, José Luis; Castilla Fernández, Miguel; Rypin, Federico; Paiva Mata, Pedro
The primary and secondary distribution grids are typically designed separately and operated with a radial configuration; therefore, specialized load flow methods only applicable to radial or weakly meshed networks are normally used. However, projections indicate that the distribution grids will be more interconnected in the future, mainly because of the inclusion of distributed generation, voltage and reliability optimization, as well as an efficiency improvement when the primary and secondary networks are considered in an integrated way. For this new meshed grids scenario, the efficient and precise typically used load flow methods for distribution networks are no longer applicable and it becomes necessary using load flow algorithms that are also applicable for meshed configurations, such as the ones classically used for transmission networks like the Newton-Raphson, Gauss-Seidel and Gauss Implicit Z-bus methods, while also procuring to avoid potential singularity problems which may arise when dealing with long radial grids. In this work, variations of the Gauss-Seidel and Gauss Implicit Z-bus methods are presented, that are adequate for low and medium voltage grids regardless of the network configuration. Additionally, a linear, direct, and non-iterative load flow variation is presented as well as a comparison between different possible convergence criteria for the classical methods.
2024-03-08T09:20:23Z
Barrenechea Gruber, Roberto Carlos
García de Vicuña Muñoz de la Nava, José Luis
Castilla Fernández, Miguel
Rypin, Federico
Paiva Mata, Pedro
The primary and secondary distribution grids are typically designed separately and operated with a radial configuration; therefore, specialized load flow methods only applicable to radial or weakly meshed networks are normally used. However, projections indicate that the distribution grids will be more interconnected in the future, mainly because of the inclusion of distributed generation, voltage and reliability optimization, as well as an efficiency improvement when the primary and secondary networks are considered in an integrated way. For this new meshed grids scenario, the efficient and precise typically used load flow methods for distribution networks are no longer applicable and it becomes necessary using load flow algorithms that are also applicable for meshed configurations, such as the ones classically used for transmission networks like the Newton-Raphson, Gauss-Seidel and Gauss Implicit Z-bus methods, while also procuring to avoid potential singularity problems which may arise when dealing with long radial grids. In this work, variations of the Gauss-Seidel and Gauss Implicit Z-bus methods are presented, that are adequate for low and medium voltage grids regardless of the network configuration. Additionally, a linear, direct, and non-iterative load flow variation is presented as well as a comparison between different possible convergence criteria for the classical methods.
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Remote multi-nodal voltage unbalance compensation in islanded AC microgrids
http://hdl.handle.net/2117/400829
Remote multi-nodal voltage unbalance compensation in islanded AC microgrids
Duarte Mejia, Josue Neftali; Velasco García, Manel; Martí Colom, Pau; Borrell Sanz, Ángel; Castilla Fernández, Miguel
Microgrids (MG) are exposed to voltage quality deterioration due to the presence of voltage unbalance. To deal with this problem, existing solutions based on Distributed Generation (DG) units interfaced by power electronics offer two type of strategies for voltage unbalance compensation depending on whether the compensation is performed at one remote node or at multiple local nodes. The first type is limited to a single node, and the second type is limited to apply at the DG units output (locally). This paper presents a multi nodal control scheme where DGs can compensate for voltage unbalance at multiple remote nodes of the MG, thus overcoming both state-of-the-art strategies limitations. In particular, negative-sequence voltage is eliminated at as many remote nodes as the number of available DG's. A systematic approach for the multiple-input/multiple-output (MIMO) nature of the problem is presented covering three aspects. First, a square MIMO control strategy is established and a feasibility test is derived to assess whether the problem can be solved. Second, the cross-coupling interaction between the multiple controllers is minimized by optimally selecting which DGs will contribute to mitigate the remote unbalances. Third, stability and transient dynamics are analyzed. Laboratory experimental results corroborate the control performance.
2024-02-02T08:35:51Z
Duarte Mejia, Josue Neftali
Velasco García, Manel
Martí Colom, Pau
Borrell Sanz, Ángel
Castilla Fernández, Miguel
Microgrids (MG) are exposed to voltage quality deterioration due to the presence of voltage unbalance. To deal with this problem, existing solutions based on Distributed Generation (DG) units interfaced by power electronics offer two type of strategies for voltage unbalance compensation depending on whether the compensation is performed at one remote node or at multiple local nodes. The first type is limited to a single node, and the second type is limited to apply at the DG units output (locally). This paper presents a multi nodal control scheme where DGs can compensate for voltage unbalance at multiple remote nodes of the MG, thus overcoming both state-of-the-art strategies limitations. In particular, negative-sequence voltage is eliminated at as many remote nodes as the number of available DG's. A systematic approach for the multiple-input/multiple-output (MIMO) nature of the problem is presented covering three aspects. First, a square MIMO control strategy is established and a feasibility test is derived to assess whether the problem can be solved. Second, the cross-coupling interaction between the multiple controllers is minimized by optimally selecting which DGs will contribute to mitigate the remote unbalances. Third, stability and transient dynamics are analyzed. Laboratory experimental results corroborate the control performance.
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Revisiting classical controller design and tuning with genetic programming
http://hdl.handle.net/2117/399081
Revisiting classical controller design and tuning with genetic programming
García Sánchez, Carlos Andrés; Velasco García, Manel; Angulo Bahón, Cecilio; Martí Colom, Pau; Camacho Santiago, Antonio
This paper introduces the application of a genetic programming (GP)-based method for the automated design and tuning of process controllers, representing a noteworthy advancement in artificial intelligence (AI) within the realm of control engineering. In contrast to already existing work, our GP-based approach operates exclusively in the time domain, incorporating differential operations such as derivatives and integrals without necessitating intermediate inverse Laplace transformations. This unique feature not only simplifies the design process but also ensures the practical implementability of the generated controllers within physical systems. Notably, the GP’s functional set extends beyond basic arithmetic operators to include a rich repertoire of mathematical operations, encompassing trigonometric, exponential, and logarithmic functions. This broad set of operations enhances the flexibility and adaptability of the GP-based approach in controller design. To rigorously assess the efficacy of our GP-based approach, we conducted an extensive series of tests to determine its limits and capabilities. In summary, our research establishes the GP-based approach as a promising solution for automating the controller design process, offering a transformative tool to address a spectrum of control problems across various engineering applications.
2024-01-10T12:48:03Z
García Sánchez, Carlos Andrés
Velasco García, Manel
Angulo Bahón, Cecilio
Martí Colom, Pau
Camacho Santiago, Antonio
This paper introduces the application of a genetic programming (GP)-based method for the automated design and tuning of process controllers, representing a noteworthy advancement in artificial intelligence (AI) within the realm of control engineering. In contrast to already existing work, our GP-based approach operates exclusively in the time domain, incorporating differential operations such as derivatives and integrals without necessitating intermediate inverse Laplace transformations. This unique feature not only simplifies the design process but also ensures the practical implementability of the generated controllers within physical systems. Notably, the GP’s functional set extends beyond basic arithmetic operators to include a rich repertoire of mathematical operations, encompassing trigonometric, exponential, and logarithmic functions. This broad set of operations enhances the flexibility and adaptability of the GP-based approach in controller design. To rigorously assess the efficacy of our GP-based approach, we conducted an extensive series of tests to determine its limits and capabilities. In summary, our research establishes the GP-based approach as a promising solution for automating the controller design process, offering a transformative tool to address a spectrum of control problems across various engineering applications.
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A comprehensive methodology for the statistical characterization of solar irradiation: application to the case of Morocco
http://hdl.handle.net/2117/389713
A comprehensive methodology for the statistical characterization of solar irradiation: application to the case of Morocco
Bouhorma, Naoufal; Martín Cañadas, María Elena; Hoz Casas, Jordi de la; Coronas Herrero, Sergio
The prediction and characterization of solar irradiation relies mostly on either the use of complex models or on complicated mathematical techniques, such as artificial neural network (ANN)-based algorithms. This mathematical complexity might hamper their use by businesses and project developers when assessing the solar resource. In this study, a simple but comprehensive methodology for characterizing the solar resource for a project is presented. It is based on the determination of the best probability distribution function (PDF) of the solar irradiation for a specific location, assuming that the knowledge of statistical techniques may be more widely extended than other more complex mathematical methods. The presented methodology was tested on 23 cities across Morocco, given the high interest in solar investments in the country. As a result, a new database for solar irradiation values depending on historical data is provided for Morocco. The results show the great existing variety of PDFs for the solar irradiation data at the different months and cities, which demonstrates the need for undertaking a proper characterization of the irradiation when the assessment of solar energy projects is involved. When it is simply needed to embed the radiation uncertainty in the analysis, as is the case of the techno-economic valuation of solar energy assets, the presented methodology can reach this objective with much less complexity and less demanding input data. Moreover, its application is not limited to solar resource assessment, but can also be easily used in other fields, such as meteorology and climate change studies.
2023-06-23T12:17:32Z
Bouhorma, Naoufal
Martín Cañadas, María Elena
Hoz Casas, Jordi de la
Coronas Herrero, Sergio
The prediction and characterization of solar irradiation relies mostly on either the use of complex models or on complicated mathematical techniques, such as artificial neural network (ANN)-based algorithms. This mathematical complexity might hamper their use by businesses and project developers when assessing the solar resource. In this study, a simple but comprehensive methodology for characterizing the solar resource for a project is presented. It is based on the determination of the best probability distribution function (PDF) of the solar irradiation for a specific location, assuming that the knowledge of statistical techniques may be more widely extended than other more complex mathematical methods. The presented methodology was tested on 23 cities across Morocco, given the high interest in solar investments in the country. As a result, a new database for solar irradiation values depending on historical data is provided for Morocco. The results show the great existing variety of PDFs for the solar irradiation data at the different months and cities, which demonstrates the need for undertaking a proper characterization of the irradiation when the assessment of solar energy projects is involved. When it is simply needed to embed the radiation uncertainty in the analysis, as is the case of the techno-economic valuation of solar energy assets, the presented methodology can reach this objective with much less complexity and less demanding input data. Moreover, its application is not limited to solar resource assessment, but can also be easily used in other fields, such as meteorology and climate change studies.
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Analysis of gas turbine compressor performance after a major maintenance operation using an autoencoder architecture
http://hdl.handle.net/2117/387553
Analysis of gas turbine compressor performance after a major maintenance operation using an autoencoder architecture
Castro Cros, Martí de; Velasco García, Manel; Angulo Bahón, Cecilio
Machine learning algorithms and the increasing availability of data have radically changed the way how decisions are made in today’s Industry. A wide range of algorithms are being used to monitor industrial processes and predict process variables that are difficult to be measured. Maintenance operations are mandatory to tackle in all industrial equipment. It is well known that a huge amount of money is invested in operational and maintenance actions in industrial gas turbines (IGTs). In this paper, two variations of autoencoders were used to analyse the performance of an IGT after major maintenance. The data used to analyse IGT conditions were ambient factors, and measurements were performed using several sensors located along the compressor. The condition assessment of the industrial gas turbine compressor revealed significant changes in its operation point after major maintenance; thus, this indicates the need to update the internal operating models to suit the new operational mode as well as the effectiveness of autoencoder-based models in feature extraction. Even though the processing performance was not compromised, the results showed how this autoencoder approach can help to define an indicator of the compressor behaviour in long-term performance.
2023-05-18T11:09:19Z
Castro Cros, Martí de
Velasco García, Manel
Angulo Bahón, Cecilio
Machine learning algorithms and the increasing availability of data have radically changed the way how decisions are made in today’s Industry. A wide range of algorithms are being used to monitor industrial processes and predict process variables that are difficult to be measured. Maintenance operations are mandatory to tackle in all industrial equipment. It is well known that a huge amount of money is invested in operational and maintenance actions in industrial gas turbines (IGTs). In this paper, two variations of autoencoders were used to analyse the performance of an IGT after major maintenance. The data used to analyse IGT conditions were ambient factors, and measurements were performed using several sensors located along the compressor. The condition assessment of the industrial gas turbine compressor revealed significant changes in its operation point after major maintenance; thus, this indicates the need to update the internal operating models to suit the new operational mode as well as the effectiveness of autoencoder-based models in feature extraction. Even though the processing performance was not compromised, the results showed how this autoencoder approach can help to define an indicator of the compressor behaviour in long-term performance.
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Improving voltage imbalance in inverter-based islanded microgrids during line-to-line short circuits
http://hdl.handle.net/2117/387136
Improving voltage imbalance in inverter-based islanded microgrids during line-to-line short circuits
Castilla Fernández, Miguel; Miret Tomàs, Jaume; García de Vicuña Muñoz de la Nava, José Luis; Borrell Sanz, Ángel; Alfaro Aragón, Carlos Arturo
Line-to-line short circuits are the transient disturbances that cause the highest currents as well as the largest voltage imbalances in inverter-based microgrids. This paper presents a control scheme for grid-forming inverters in islanded microgrids that limits the current to a safe value during these types of short circuits while providing a lower voltage imbalance compared to state-of-the-art current limiting techniques. This control scheme is based on reducing both the amplitude of the reference voltage with the maximum amplitude of the reference current and the instantaneous reference voltage with only the inductive component of the virtual impedance. The combination of these two control actions provides low voltage imbalance, as the theoretical and experimental studies reveal. This voltage imbalance improvement is the main contribution of this paper and is maintained when the microgrid supplies linear and non-linear loads. In the theoretical study, the paper includes control design guidelines to satisfy static and dynamic specifications. The theoretical predictions are validated by means of experimental results measured in a laboratory microgrid. A practical performance comparison of current limiting techniques based on experimental tests is also reported.
2023-05-05T10:19:46Z
Castilla Fernández, Miguel
Miret Tomàs, Jaume
García de Vicuña Muñoz de la Nava, José Luis
Borrell Sanz, Ángel
Alfaro Aragón, Carlos Arturo
Line-to-line short circuits are the transient disturbances that cause the highest currents as well as the largest voltage imbalances in inverter-based microgrids. This paper presents a control scheme for grid-forming inverters in islanded microgrids that limits the current to a safe value during these types of short circuits while providing a lower voltage imbalance compared to state-of-the-art current limiting techniques. This control scheme is based on reducing both the amplitude of the reference voltage with the maximum amplitude of the reference current and the instantaneous reference voltage with only the inductive component of the virtual impedance. The combination of these two control actions provides low voltage imbalance, as the theoretical and experimental studies reveal. This voltage imbalance improvement is the main contribution of this paper and is maintained when the microgrid supplies linear and non-linear loads. In the theoretical study, the paper includes control design guidelines to satisfy static and dynamic specifications. The theoretical predictions are validated by means of experimental results measured in a laboratory microgrid. A practical performance comparison of current limiting techniques based on experimental tests is also reported.
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Economic and regulatory uncertainty in renewable energy system design: a review
http://hdl.handle.net/2117/386202
Economic and regulatory uncertainty in renewable energy system design: a review
Alonso Travesset, Alexandre; Coppiters, Diederik; Martín Cañadas, María Elena; Hoz Casas, Jordi de la
Renewable energy is increasingly mobilizing more investment around the globe. However, there has been little attention to evaluating economic and regulatory (E&R) uncertainties, despite their enormous impact on the project cashflows. Consequently, this review analyzes, classifies, and discusses 130 articles dealing with the design of renewable energy projects under E&R uncertainties. After performing a survey and identifying the selected manuscripts, and the few previous reviews on the matter, the following innovative categorization is designed: sources of uncertainty, uncertainty characterization methods, problem formulations, solution methods, and regulatory frameworks. The classification reveals that electricity price is the most considered source of uncertainty, often alone, despite the existence of six other equally influential groups of E&R uncertainties. In addition, real options and optimization arise as the two main approaches researchers use to solve problems in energy system design. Subsequently, the following aspects of interest are discussed in depth: how modeling can be improved, which are the most influential variables, and potential lines of research. Conclusions show the necessity of modeling E&R uncertainties with currently underrepresented methods, suggest several policy recommendations, and encourage the integration of prevailing approaches.
2023-04-13T13:29:30Z
Alonso Travesset, Alexandre
Coppiters, Diederik
Martín Cañadas, María Elena
Hoz Casas, Jordi de la
Renewable energy is increasingly mobilizing more investment around the globe. However, there has been little attention to evaluating economic and regulatory (E&R) uncertainties, despite their enormous impact on the project cashflows. Consequently, this review analyzes, classifies, and discusses 130 articles dealing with the design of renewable energy projects under E&R uncertainties. After performing a survey and identifying the selected manuscripts, and the few previous reviews on the matter, the following innovative categorization is designed: sources of uncertainty, uncertainty characterization methods, problem formulations, solution methods, and regulatory frameworks. The classification reveals that electricity price is the most considered source of uncertainty, often alone, despite the existence of six other equally influential groups of E&R uncertainties. In addition, real options and optimization arise as the two main approaches researchers use to solve problems in energy system design. Subsequently, the following aspects of interest are discussed in depth: how modeling can be improved, which are the most influential variables, and potential lines of research. Conclusions show the necessity of modeling E&R uncertainties with currently underrepresented methods, suggest several policy recommendations, and encourage the integration of prevailing approaches.
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Maximum current injection method for grid-forming inverters in an islanded microgrid subject to short circuits
http://hdl.handle.net/2117/383563
Maximum current injection method for grid-forming inverters in an islanded microgrid subject to short circuits
Miret Tomàs, Jaume; Castilla Fernández, Miguel; Velasco García, Manel; Guzmán Solà, Ramon; García de Vicuña Muñoz de la Nava, José Luis
In islanded microgrids, when a short circuit or a sudden overload occurs, it provokes an abrupt increment in the currents supplied by the generation nodes, which feed the load collaboratively. This is particularly challenging for inverter-based nodes, due to its reduced power capacity. This work takes advantage of the droop-method basic configuration to propose an additional closed-loop control, which ensures maximum current injection during any kind of short circuit maintaining the underlying droop control. Ensuring that any node injects its maximum rated current during the short circuit, it emulates the most common low-voltage ride-through protocols for grid-feeding sources oriented to support the grid and, in this way, the voltage unbalance is reduced. To develop the control proposal, a model of the faulted system is presented in order to evaluate the stability of the closed-loop system. A general modelling methodology is introduced in order to derive the control for any microgrid configuration. Finally, selected experimental results are reported in order to validate the effectiveness of the proposed control.
2023-02-16T14:04:28Z
Miret Tomàs, Jaume
Castilla Fernández, Miguel
Velasco García, Manel
Guzmán Solà, Ramon
García de Vicuña Muñoz de la Nava, José Luis
In islanded microgrids, when a short circuit or a sudden overload occurs, it provokes an abrupt increment in the currents supplied by the generation nodes, which feed the load collaboratively. This is particularly challenging for inverter-based nodes, due to its reduced power capacity. This work takes advantage of the droop-method basic configuration to propose an additional closed-loop control, which ensures maximum current injection during any kind of short circuit maintaining the underlying droop control. Ensuring that any node injects its maximum rated current during the short circuit, it emulates the most common low-voltage ride-through protocols for grid-feeding sources oriented to support the grid and, in this way, the voltage unbalance is reduced. To develop the control proposal, a model of the faulted system is presented in order to evaluate the stability of the closed-loop system. A general modelling methodology is introduced in order to derive the control for any microgrid configuration. Finally, selected experimental results are reported in order to validate the effectiveness of the proposed control.
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An experimental approach for secondary consensus control tuning for inverter-based islanded microgrids
http://hdl.handle.net/2117/381060
An experimental approach for secondary consensus control tuning for inverter-based islanded microgrids
de Doile, Gabriel Nasser Doyle; Balestrassi, Pedro Paulo; Castilla Fernández, Miguel; Zambroni de Souza, Antonio Carlos; Miret Tomàs, Jaume
A microgrid is a group of interconnected loads and distributed energy resources that can fill the gap between the dependence on a bulk power grid and the transition to renewable energies. The islanded mode presents itself as the most interesting scenario, when local controllers should maintain the power quality standards based on several parameters. A tool specifically focused on the process of parameter tuning of the secondary consensus-based control for inverter-based islanded microgrids was proposed in this paper. One often-quoted drawback in this process is the great number of parameters that must be tuned, even for a very simple microgrid structure. To manage such a large number of parameters, the design of experiments was used in this study. The main motivation for this work was to present an optimized way to define the correct parameters for the secondary consensus control for inverter-based islanded microgrids. The study shows how experimental design methodology can be an efficient tool to tune microgrid parameters, which are typically multi-objective-based experiments. From the results, it is correct to state that the design of experiments is able to reach the optimal setting with a minimal number of experiments, which would be almost impossible to obtain with the trial-and-error method.
2023-01-25T07:53:58Z
de Doile, Gabriel Nasser Doyle
Balestrassi, Pedro Paulo
Castilla Fernández, Miguel
Zambroni de Souza, Antonio Carlos
Miret Tomàs, Jaume
A microgrid is a group of interconnected loads and distributed energy resources that can fill the gap between the dependence on a bulk power grid and the transition to renewable energies. The islanded mode presents itself as the most interesting scenario, when local controllers should maintain the power quality standards based on several parameters. A tool specifically focused on the process of parameter tuning of the secondary consensus-based control for inverter-based islanded microgrids was proposed in this paper. One often-quoted drawback in this process is the great number of parameters that must be tuned, even for a very simple microgrid structure. To manage such a large number of parameters, the design of experiments was used in this study. The main motivation for this work was to present an optimized way to define the correct parameters for the secondary consensus control for inverter-based islanded microgrids. The study shows how experimental design methodology can be an efficient tool to tune microgrid parameters, which are typically multi-objective-based experiments. From the results, it is correct to state that the design of experiments is able to reach the optimal setting with a minimal number of experiments, which would be almost impossible to obtain with the trial-and-error method.