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12 pages, 4540 KiB

Open AccessArticle

High-Precision Switched Capacitor Device with an Energy Estimation Circuit

by Krzysztof Musioł, Kordian Dudzik and Marian Kampik

Energies 2023, 16(3), 1086; https://doi.org/10.3390/en16031086 - 18 Jan 2023

Viewed by 1448

Abstract

This article introduces a device for the precise testing of the non-linearities of inductive voltage dividers and digitizers used in digital impedance bridges. The device is based on switched capacitors composed of an NP0 dielectric, in addition to high-quality microwave relays. The article [...] Read more.

This article introduces a device for the precise testing of the non-linearities of inductive voltage dividers and digitizers used in digital impedance bridges. The device is based on switched capacitors composed of an NP0 dielectric, in addition to high-quality microwave relays. The article discusses issue concerning the symmetrization of the device as one of the main ways to achieve a high accuracy. Furthermore, a temperature-stabilization system for the device is presented. The system uses a battery management system to estimate the quantity of the energy available in the supply battery. The article further discusses problems encountered with the design of heating elements, which are situated on a laminate with an aluminum substrate. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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14 pages, 961 KiB

Open AccessArticle

A Deep Understanding of Romanian Attitude and Perception Regarding Nuclear Energy as Green Investment Promoted by the European Green Deal

by Adrian Tantau, Greta Marilena Puscasu, Silvia Elena Cristache, Cristina Alpopi, Laurentiu Fratila, Daniel Moise and Georgeta Narcisa Ciobotar

Energies 2023, 16(1), 272; https://doi.org/10.3390/en16010272 - 27 Dec 2022

Cited by 4 | Viewed by 2698

Abstract

The analysis of public attitudes towards nuclear energy represents an issue that is commonly investigated, especially considering the new context of classifying some nuclear power plants as green investments under the European Green Deal. The importance of this topic is critical to the [...] Read more.

The analysis of public attitudes towards nuclear energy represents an issue that is commonly investigated, especially considering the new context of classifying some nuclear power plants as green investments under the European Green Deal. The importance of this topic is critical to the future of nuclear power generation. The purpose of this study is to identify the relationships that exist between the different factors and the attitude of the public towards nuclear energy in the context of the European Green Deal. The article identifies and analyzes the main factors that influence this relationship. In this context, a questionnaire-based survey was conducted regarding the identification of the relationship between public knowledge, degree of cooperation, perceived risks, trust and attitude towards nuclear energy. The sample was chosen using the snowball method. The analysis was made up of 578 respondents from different segments of age, gender, place of residence, field of activity, work experience and income. Following the survey, the main conclusion was that over 30% of the respondents do not want nuclear energy and are adamantly opposed to it. At the same time, the results indicate that the respondents’ attitude is not directly influenced by the risks they perceive in relation to nuclear energy. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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20 pages, 12035 KiB

Open AccessArticle

Design and Robust Performance Analysis of Low-Order Approximation of Fractional PID Controller Based on an IABC Algorithm for an Automatic Voltage Regulator System

by Abdelhakim Idir, Laurent Canale, Yassine Bensafia and Khatir Khettab

Energies 2022, 15(23), 8973; https://doi.org/10.3390/en15238973 - 27 Nov 2022

Cited by 29 | Viewed by 2450

Abstract

In this paper, a low-order approximation (LOA) of fractional order PID (FOPID) for an automatic voltage regulator (AVR) based on the modified artificial bee colony (ABC) is proposed. The improved artificial bee colony (IABC) high-order approximation (HOA)-based fractional order PID (IABC/HOA-FOPID) controller, which [...] Read more.

In this paper, a low-order approximation (LOA) of fractional order PID (FOPID) for an automatic voltage regulator (AVR) based on the modified artificial bee colony (ABC) is proposed. The improved artificial bee colony (IABC) high-order approximation (HOA)-based fractional order PID (IABC/HOA-FOPID) controller, which is distinguished by a significant order approximation and by an integer order transfer function, requires the use of a large number of parameters. To improve the AVR system’s performance in terms of transient and frequency response analysis, the memory capacity of the IABC/HOA-FOPID controller was lowered so that it could fit better in the corrective loop. The new robust controller is named the improved artificial bee colony (IABC) low-order approximation (LOA)-based fractional order PID (IABC/LOA-FOPID). The performance of the proposed IABC/LOA-FOPID controller was compared not only to the original ABC algorithm-tuned PID controller, but also to other controllers tuned by state-of-the-art meta-heuristic algorithms such as the improved whale optimization algorithm (IWOA), particle swarm optimization (PSO), cuckoo search (CS), many optimizing liaisons (MOL), genetic algorithm (GA), local unimodal sampling (LUS), and the tree seed algorithm (TSA). Step response, root locus, frequency response, robustness test, and disturbance rejection abilities are all compared. The simulation results and comparisons with the proposed IABC/LOA-FOPID controller and other existing controllers clearly show that the proposed IABC/LOA-FOPID controller outperforms the optimal PID controllers found by other algorithms in all the aforementioned performance tests. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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25 pages, 6803 KiB

Open AccessArticle

Black Start Capability from Large Industrial Consumers

by Gayan Abeynayake, Liana Cipcigan and Xiaolin Ding

Energies 2022, 15(19), 7262; https://doi.org/10.3390/en15197262 - 3 Oct 2022

Cited by 4 | Viewed by 3265

Abstract

The way of control and operation of an electrical power system has been changing rapidly with the integration of renewable energy sources (RES). One of the emerging issues that require addressing is the capability of RES to participate in the restoration process upon [...] Read more.

The way of control and operation of an electrical power system has been changing rapidly with the integration of renewable energy sources (RES). One of the emerging issues that require addressing is the capability of RES to participate in the restoration process upon a total or partial system failure. However, with the continuous shutdown of large-centralised generators, which traditionally provided the black start support together with the variability of RES, the restoration process becomes much more complex. Primarily, the RES should have enough capacity to energise the load at the time of the restoration. Nonetheless, due to significant advantages, there is an increasing trend to use RES to meet the local energy demand by large industrial customers. The flexibility of shifting loads together with the surplus of RE generation could support the system operator during the system energisation process after a blackout. This paper mainly focuses on identifying the capabilities and factors that should be accounted for to participate in the system restoration process by large industrial consumers. The case study conducted on a large-scale steel factory in the UK reveals the possibility of supporting the restoration process under the bottom-up approach. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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23 pages, 12939 KiB

Open AccessArticle

Machine Learning Approach for Short-Term Load Forecasting Using Deep Neural Network

by Majed A. Alotaibi

Energies 2022, 15(17), 6261; https://doi.org/10.3390/en15176261 - 28 Aug 2022

Cited by 30 | Viewed by 4045

Abstract

Power system demand forecasting is a crucial task in the power system engineering field. This is due to the fact that most system planning and operation activities basically rely on proper forecasting models. Entire power infrastructures are built essentially to provide and serve [...] Read more.

Power system demand forecasting is a crucial task in the power system engineering field. This is due to the fact that most system planning and operation activities basically rely on proper forecasting models. Entire power infrastructures are built essentially to provide and serve the consumption of energy. Therefore, it is very necessary to construct robust and efficient predictive models in order to provide accurate load forecasting. In this paper, three techniques are utilized for short-term load forecasting. These techniques are deep neural network (DNN), multilayer perceptron-based artificial neural network (ANN), and decision tree-based prediction (DR). New predictive variables are included to enhance the overall forecasting and handle the difficulties caused by some categorical predictors. The comparison among these three techniques is executed based on coefficients of determination R² and mean absolute error (MAE). Statistical tests are performed in order to verify the results and examine whether these models are statistically different or not. The results reveal that the DNN model outperformed the other models and was statistically different from them. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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20 pages, 6325 KiB

Open AccessArticle

Projecting and Forecasting the Latent Volatility for the Nasdaq OMX Nordic/Baltic Financial Electricity Market Applying Stochastic Volatility Market Characteristics

by Per Bjarte Solibakke

Energies 2022, 15(10), 3839; https://doi.org/10.3390/en15103839 - 23 May 2022

Cited by 1 | Viewed by 1962

Abstract

In this empirical study, multifactor stochastic volatility models for the financial Nordic/Baltic power markets are developed, implemented, and analyzed. Stochastic volatility projections are the primary aim, followed by volatility forecasts and market repercussions. The research provides a functional variant of the conditional distribution [...] Read more.

In this empirical study, multifactor stochastic volatility models for the financial Nordic/Baltic power markets are developed, implemented, and analyzed. Stochastic volatility projections are the primary aim, followed by volatility forecasts and market repercussions. The research provides a functional variant of the conditional distribution

(f (x | y))

based on conditional moments and a long-simulated state vector realization (MCMC-GMM) that is evaluated on observed data (a non-linear Kalman Filter) and applicable for step-forward volatility forecasts. For front year and quarter financial electricity contracts, the SV model creates two mean-reverting factors: one persistent and slowly moving component and one choppy, rapidly moving component. According to these factors, static volatility predictions with optimum and generous lags have a Theil covariance percentage of well over 97 percent for the front year contracts and 86 percent for the front quarter contracts. The volatility visibility and its associated static forecasts improve market transparency and will eventually make diversification and risk management easier to implement. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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10 pages, 1299 KiB

Open AccessArticle

The Errors of Electronic Energy Meters That Measure Energy Consumed by LED Lighting

by Artur Skórkowski, Marian Kampik, Krzysztof Musioł and Adam Nocoń

Energies 2022, 15(9), 3254; https://doi.org/10.3390/en15093254 - 29 Apr 2022

Cited by 5 | Viewed by 5685

Abstract

Various metrological aspects for the correct measurements of electrical energy that is consumed by energy-saving (mainly LED) single phase loads are discussed in this paper. One of the most important problems presented here concerns the question of how strong distortions of the current [...] Read more.

Various metrological aspects for the correct measurements of electrical energy that is consumed by energy-saving (mainly LED) single phase loads are discussed in this paper. One of the most important problems presented here concerns the question of how strong distortions of the current waveform, introduced by typical LED lighting, affects the operation of electronic energy meters. Measurement results for the energy consumption of different LED lamps used in households in various conditions, alongside comparative results that were obtained by electronic and electromechanical energy meters, were also offered and the appropriate conclusions were then drawn. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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22 pages, 4968 KiB

Open AccessArticle

Enhanced Salp Swarm Algorithm for Multimodal Optimization and Fuzzy Based Grid Frequency Controller Design

by Smrutiranjan Nayak, Sanjeeb Kumar Kar, Subhransu Sekhar Dash, Pradeep Vishnuram, Sudhakar Babu Thanikanti and Benedetto Nastasi

Energies 2022, 15(9), 3210; https://doi.org/10.3390/en15093210 - 27 Apr 2022

Cited by 9 | Viewed by 2083

Abstract

In the present study, an Enhanced SSA (ESSA) has been proposed where the parameter of the SSA technique, which balances the exploration and exploitation phases, has been modified. Additionally, the variable scaling factor is engaged to regulate the salp’s position during the search [...] Read more.

In the present study, an Enhanced SSA (ESSA) has been proposed where the parameter of the SSA technique, which balances the exploration and exploitation phases, has been modified. Additionally, the variable scaling factor is engaged to regulate the salp’s position during the search procedure to minimize the random movement of salps. To demonstrate the effectiveness of the enhanced SSA (ESSA), a set of multimodal test functions are engaged. The statistical outcomes demonstrate that ESSA profits from local optima evasion and quick convergence speed, which aids the proposed ESSA algorithm to outclass the standard SSA and other recent algorithms. The fair analysis displays that ESSA delivers very promising results and outclass current methods. Next, frequency control of power systems is executed by designing a Combined Fuzzy PID (CFPID) controller with the projected ESSA method. Next, a Partially Distributed CFPID (PD-CFPID) controller is designed for a distributed power system (DPS). It is shown that the ESSA method outclasses the SSA method in engineering problems. It is also noted that the ESSA-based PD-CFPID scheme has become more operative in monitoring the frequency than similar structured centralized fuzzy PID (CFPID) as well as PID controller. Finally, the outcomes of the PD-CFPID controller are equated with CFPID and PID for various uncertain situations to validate the benefit of the proposed control approach. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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19 pages, 14085 KiB

Open AccessArticle

Hardware Development and Interoperability Testing of a Multivendor-IEC-61850-Based Digital Substation

by Tanushree Bhattacharjee, Majid Jamil, Majed A. Alotaibi, Hasmat Malik and Mohammed E. Nassar

Energies 2022, 15(5), 1785; https://doi.org/10.3390/en15051785 - 28 Feb 2022

Cited by 9 | Viewed by 3944

Abstract

Substations are becoming increasingly reliant on international electrotechnical commission (IEC)-61850-enabled devices. However, device compatibility with these standards does not guarantee interoperability when devices are taken from different manufacturers. If interoperability of multivendor devices can be achieved, then power utilities will be in a [...] Read more.

Substations are becoming increasingly reliant on international electrotechnical commission (IEC)-61850-enabled devices. However, device compatibility with these standards does not guarantee interoperability when devices are taken from different manufacturers. If interoperability of multivendor devices can be achieved, then power utilities will be in a position to implement multivendor devices in substations. The study here presents the development and testing of a digital substation test platform that incorporates devices from different manufacturers. The process bus communication and protection operation of the intelligent electronic devices (IEDs) were tested to validate device interoperability. The testbed was tested for two IED process bus communications, generic object-oriented substation event (GOOSE) and sampled measured value (SMV). The GOOSE is travelling between IED to IED with an end-to-end (ETE) delay of 2 ms and the SMV read by the IEDs are the same as the injected real-time substation inputs 220 kV and 1 kA. Three IED protection studies (overcurrent, earth fault, and overvoltage) were performed, and IED response curves were obtained. In addition, data monitoring and client–server communications were studied using installed software tools. The testbed configuration in this study has faced some real-time challenges regarding differences in device edition, device firmware, and ethernet switch due to its multivendor approach. All the mentioned configuration issues were resolved in this study with successful testing and validation of the testbed. The study of this testbed will provide solutions to the problems associated with a multivendor system faced by substation engineers and will help them in opting for multivendor installations. This system can be extended in the future by installing more multivendor devices with complex network topology and a SCADA system. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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25 pages, 2477 KiB

Open AccessArticle

Model Reference Tracking Control Solutions for a Visual Servo System Based on a Virtual State from Unknown Dynamics

by Timotei Lala, Darius-Pavel Chirla and Mircea-Bogdan Radac

Energies 2022, 15(1), 267; https://doi.org/10.3390/en15010267 - 31 Dec 2021

Cited by 12 | Viewed by 2640

Abstract

This paper focuses on validating a model-free Value Iteration Reinforcement Learning (MFVI-RL) control solution on a visual servo tracking system in a comprehensive manner starting from theoretical convergence analysis to detailed hardware and software implementation. Learning is based on a virtual state representation [...] Read more.

This paper focuses on validating a model-free Value Iteration Reinforcement Learning (MFVI-RL) control solution on a visual servo tracking system in a comprehensive manner starting from theoretical convergence analysis to detailed hardware and software implementation. Learning is based on a virtual state representation reconstructed from input-output (I/O) system samples under nonlinear observability and unknown dynamics assumptions, while the goal is to ensure linear output reference model (ORM) tracking. Secondary, a competitive model-free Virtual State-Feedback Reference Tuning (VSFRT) is learned from the same I/O data using the same virtual state representation, demonstrating the framework’s learning capability. A model-based two degrees-of-freedom (2DOF) output feedback controller serving as a comparisons baseline is designed and tuned using an identified system model. With similar complexity and linear controller structure, MFVI-RL is shown to be superior, confirming that the model-based design issue of poor identified system model and control performance degradation can be solved in a direct data-driven style. Apart from establishing a formal connection between output feedback control, state feedback control and also between classical control and artificial intelligence methods, the results also point out several practical trade-offs, such as I/O data exploration quality and control performance leverage with data volume, control goal and controller complexity. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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20 pages, 6733 KiB

Open AccessArticle

Structural and Parametric Optimization of S-CO₂ Thermal Power Plants with a Pulverized Coal-Fired Boiler Operating in Russia

by Andrey Rogalev, Vladimir Kindra, Ivan Komarov, Sergey Osipov and Olga Zlyvko

Energies 2021, 14(21), 7136; https://doi.org/10.3390/en14217136 - 1 Nov 2021

Cited by 11 | Viewed by 2317

Abstract

The Rankine cycle is widely used for electricity production. Significant weight and size characteristics of the power equipment working on superheated steam are the main disadvantages of such power plants. The transition to supercritical carbon dioxide (S-CO₂) working fluid is a [...] Read more.

The Rankine cycle is widely used for electricity production. Significant weight and size characteristics of the power equipment working on superheated steam are the main disadvantages of such power plants. The transition to supercritical carbon dioxide (S-CO₂) working fluid is a promising way to achieve a significant reduction in equipment metal consumption and to increase energy efficiency. This paper presents the results of thermodynamic analysis of S-CO₂ thermal power plants (TPPs) utilizing the heat of combustion products of an energy boiler. It was found that the net efficiency of the developed S-CO₂ TPP with a pulverized coal-fired boiler reached 49.2% at an initial temperature of 780 °C, which was 2% higher compared to the efficiency level of steam turbine power plants (STPPs) at a similar turbine inlet temperature. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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15 pages, 4315 KiB

Open AccessArticle

A Method for Assessing the Stability of Digital Automatic Control Systems (ACS) with Discrete Elements. Hypothesis and Simulation Results

by Vladimir Kodkin, Alexander Baldenkov and Alexander Anikin

Energies 2021, 14(20), 6561; https://doi.org/10.3390/en14206561 - 12 Oct 2021

Cited by 6 | Viewed by 3258

Abstract

The article presents a new approach to the analysis of the stability of automatic systems with discrete links. In almost all modern automatic control systems (ACS), there are links that break signals in time. These are power controlled switches—transistors or thyristors operating in [...] Read more.

The article presents a new approach to the analysis of the stability of automatic systems with discrete links. In almost all modern automatic control systems (ACS), there are links that break signals in time. These are power controlled switches—transistors or thyristors operating in a pulsed mode and digital links in regulators. Time discretization significantly affects the stability of processes in the automatic control system. The theoretical analysis of such systems is rather complicated and requires a significant change in engineering approaches to analysis. With the improvement of digital controllers and a significant increase in their performance, this problem has practically been forgotten. However, its mathematical “content” has not changed since the 1980s when discreteness began to play a major role in hindering the transition to digital automatic control systems. In this paper, we propose a new approach that consists of interpreting the sampling operation by a link with the proposed frequency characteristic, which determines the suppression of input high-frequency signals. This link greatly simplifies engineering calculations and demonstrates the new capabilities of sampling systems. These possibilities include the rational distribution of digitalization resources—the number of bits and the sampling interval between the regulator channels, depending on the frequency range of the efficiency of these channels. We verify and confirm our theoretical statements through simulations and show how this approach makes it possible to formulate new principles of construction of seemingly well-known controllers—PID (Proportional Integral Differential) controllers and variable structure systems (VSS). Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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13 pages, 1677 KiB

Open AccessArticle

Intelligent Control System Architecture for Phosphorus Production from Apatite-Nepheline Ore Waste

by Maksim Dli, Andrey Puchkov, Artem Vasiliev, Elena Kirillova, Yuri Selyavskiy and Nikolay Kulyasov

Energies 2021, 14(20), 6469; https://doi.org/10.3390/en14206469 - 9 Oct 2021

Cited by 6 | Viewed by 2188

Abstract

This paper proposes multilevel architecture for an intelligent control system for the complex chemical energy technological process of yellow phosphorus production from apatite-nepheline ore processing waste. The research revealed that, when controlling this process, one has to deal with large amounts of multiformat [...] Read more.

This paper proposes multilevel architecture for an intelligent control system for the complex chemical energy technological process of yellow phosphorus production from apatite-nepheline ore processing waste. The research revealed that, when controlling this process, one has to deal with large amounts of multiformat and polymodal information, and control goals differ at different levels not only in effectiveness criteria, but also in the structuredness of the level problems. On this basis, it is proposed that intelligent methods be used for the implementation of information processes and control goals at individual levels and the whole system. The artificial intelligence methods underlying the informational model of a control system offer solutions to problems of analyzing control processes at different hierarchy levels, namely the initial level of sensing devices, the levels of programmable logic controllers, dispatching of control and production processes, enterprise management and strategic planning. Besides, the intelligent control system architecture includes analytical and simulation models of processes occurring in the multistage procedure of ore waste processing by a plant consisting of a granulating machine, a conveyor-type multichambercalcining machine, and an ore thermal furnace. The architecture of information support for the control system comprises a knowledge-based inference block intended for implementing the self-refinement of neural network and simulation models. Fuzzy logic methods are proposed for constructing this block. The paper considers the deployment of control algorithms for a phosphorus production system using the Matlab software environment on the basis of a modern complex system development paradigm known as the model-oriented design concept. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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15 pages, 508 KiB

Open AccessArticle

Observer Design for a Variable Moment of Inertia System

by Jerzy Baranowski

Energies 2021, 14(18), 5850; https://doi.org/10.3390/en14185850 - 15 Sep 2021

Viewed by 2554

Abstract

Variable moment of inertia systems are common, and a popular laboratory system of this type is the “ball-and-beam”. Such systems are, however, nonlinear and often unstable. Efficient control requires full state information (or at least partial velocities), which are generally difficult to measure. [...] Read more.

Variable moment of inertia systems are common, and a popular laboratory system of this type is the “ball-and-beam”. Such systems are, however, nonlinear and often unstable. Efficient control requires full state information (or at least partial velocities), which are generally difficult to measure. That is why the design of state observers is a relevant problem. In this paper, a new design of an observer is proposed. This new nonlinear observer uses partial output injection and the circle criterion to ensure semiglobal stability. Moreover, we present a complete modeling of the system and systematic testing of the observer in comparison to a baseline in the form of a linear observer. The results show that the designed observer outperforms its linear counterpart and does not impede control. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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11 pages, 2373 KiB

Open AccessArticle

Energy System Monitoring Based on Fuzzy Cognitive Modeling and Dynamic Clustering

by Vadim Borisov, Maksim Dli, Artem Vasiliev, Yaroslav Fedulov, Elena Kirillova and Nikolay Kulyasov

Energies 2021, 14(18), 5848; https://doi.org/10.3390/en14185848 - 15 Sep 2021

Cited by 1 | Viewed by 1686

Abstract

A feature of energy systems (ESs) is the diversity of objects, as well as the variety and manifold of the interconnections between them. A method for monitoring ESs clusters is proposed based on the combined use of a fuzzy cognitive approach and dynamic [...] Read more.

A feature of energy systems (ESs) is the diversity of objects, as well as the variety and manifold of the interconnections between them. A method for monitoring ESs clusters is proposed based on the combined use of a fuzzy cognitive approach and dynamic clustering. A fuzzy cognitive approach allows one to represent the interdependencies between ESs objects in the form of fuzzy impact relations, the analysis results of which are used to substantiate indicators for fuzzy clustering of ESs objects and to analyze the stability of clusters and ESs. Dynamic clustering methods are used to monitor the cluster structure of ESs, namely, to assess the drift of cluster centers, to determine the disappearance or emergence of new clusters, and to unite or separate clusters of ESs. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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19 pages, 53619 KiB

Open AccessArticle

Traffic Noise Modelling Using Land Use Regression Model Based on Machine Learning, Statistical Regression and GIS

by Ahmed Abdulkareem Ahmed Adulaimi, Biswajeet Pradhan, Subrata Chakraborty and Abdullah Alamri

Energies 2021, 14(16), 5095; https://doi.org/10.3390/en14165095 - 18 Aug 2021

Cited by 27 | Viewed by 5119

Abstract

This study estimates the equivalent continuous sound pressure level (L_eq) during peak daily periods (‘rush hour’) along the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia, using a land use regression (LUR) model based on machine learning, statistical regression, and [...] Read more.

This study estimates the equivalent continuous sound pressure level (L_eq) during peak daily periods (‘rush hour’) along the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia, using a land use regression (LUR) model based on machine learning, statistical regression, and geographical information systems (GIS). The research utilises two types of soft computing methods including machine learning (i.e., decision tree, random frost algorithms) and statistical regression (i.e., linear regression, support vector regression algorithms) to determine the best approach to create a prediction L_eq map at the NKVE in Shah Alam, Malaysia. The selection of the best algorithm is accomplished by considering correlation, correlation coefficient, mean-absolute-error, mean-square-error, root-mean-square-error, and mean absolute percentage error. Traffic noise level was monitored using three sound level meters (TES 52A), and a traffic tally was done to analyse the traffic flow. Wind speed was gauged using a wind speed meter. The study relied on a variety of noise predictors including wind speed, digital elevation model, land use type (specifically, if it was residential, industrial, or natural reserve), residential density, road type (expressway, primary, and secondary) and traffic noise average (L_eq). The above parameters were fed as inputs into the LUR model. Additional noise influencing factors such as traffic lights, intersections, road toll gates, gas stations, and public transportation infrastructures (bus stop and bus line) are also considered in this study. The models utilised parameters derived from LiDAR (Light Detection and Ranging) data, and various GIS (Geographical Information Systems) layers were extracted to produce the prediction maps. The results highlighted the superior performances by the machine learning (random forest) models compared to the statistical regression-based models. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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15 pages, 2170 KiB

Open AccessArticle

The Model of Support for the Decision-Making Process, While Organizing Dredging Works in the Ports

by Adam Kaizer and Tomasz Neumann

Energies 2021, 14(9), 2706; https://doi.org/10.3390/en14092706 - 9 May 2021

Cited by 8 | Viewed by 3027

Abstract

The aim of the research was to create a decision-making model, which would be able to support planning, organizing and conducting the dredging works in the port area. The proposed solution is a multiple element system which enables to verify, in a comprehensive [...] Read more.

The aim of the research was to create a decision-making model, which would be able to support planning, organizing and conducting the dredging works in the port area. The proposed solution is a multiple element system which enables to verify, in a comprehensive way, the majority of the aspects determining the quality and the time of dredging enterprise realization. The paper presents an original approach to the decision-making process during the organization of dredging works, using the computer program. In order to achieve the main goal of the study, the conditions of dredging works were considered. Furthermore, the factors that have an influence on the schedule of the project were evaluated and algorithms, as well as process organization schemes, were developed. If it is not enough, the decision models corresponding to the discussed issue were analysed and the computer program was created. And last but not the least, the proposed project and equipment were verified using a simulation model. While creating this model, the method of multiple criteria AHP (Analytic Hierarchy Process) decision support was used. Moreover, the mass service model with the priority queue regulations, the expert study, and statistical analysis of the traffic flow, were provided. The model was developed in reliance to multiple criteria studies, based on the opinions of multinational experts. These enabled to adjust each element of the system in accordance with various locations. As a result of the research, the following thesis has been proven, that detailed analysis of the conditions of dredging works and taking into account the received conclusions enables to reduce the costs and shorten the time of dredging projects realizations. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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26 pages, 5120 KiB

Open AccessArticle

Virtual State Feedback Reference Tuning and Value Iteration Reinforcement Learning for Unknown Observable Systems Control

by Mircea-Bogdan Radac and Anamaria-Ioana Borlea

Energies 2021, 14(4), 1006; https://doi.org/10.3390/en14041006 - 15 Feb 2021

Cited by 23 | Viewed by 3432

Abstract

In this paper, a novel Virtual State-feedback Reference Feedback Tuning (VSFRT) and Approximate Iterative Value Iteration Reinforcement Learning (AI-VIRL) are applied for learning linear reference model output (LRMO) tracking control of observable systems with unknown dynamics. For the observable system, a new state [...] Read more.

In this paper, a novel Virtual State-feedback Reference Feedback Tuning (VSFRT) and Approximate Iterative Value Iteration Reinforcement Learning (AI-VIRL) are applied for learning linear reference model output (LRMO) tracking control of observable systems with unknown dynamics. For the observable system, a new state representation in terms of input/output (IO) data is derived. Consequently, the Virtual State Feedback Tuning (VRFT)-based solution is redefined to accommodate virtual state feedback control, leading to an original stability-certified Virtual State-Feedback Reference Tuning (VSFRT) concept. Both VSFRT and AI-VIRL use neural networks controllers. We find that AI-VIRL is significantly more computationally demanding and more sensitive to the exploration settings, while leading to inferior LRMO tracking performance when compared to VSFRT. It is not helped either by transfer learning the VSFRT control as initialization for AI-VIRL. State dimensionality reduction using machine learning techniques such as principal component analysis and autoencoders does not improve on the best learned tracking performance however it trades off the learning complexity. Surprisingly, unlike AI-VIRL, the VSFRT control is one-shot (non-iterative) and learns stabilizing controllers even in poorly, open-loop explored environments, proving to be superior in learning LRMO tracking control. Validation on two nonlinear coupled multivariable complex systems serves as a comprehensive case study. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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17 pages, 7286 KiB

Open AccessArticle

Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems

by Phong B. Dao

Energies 2021, 14(2), 420; https://doi.org/10.3390/en14020420 - 13 Jan 2021

Cited by 2 | Viewed by 2685

Abstract

Multiagent control system (MACS) has become a promising solution for solving complex control problems. Using the advantages of MACS-based design approaches, a novel solution for advanced control of mechatronic systems has been developed in this paper. The study has aimed at integrating learning [...] Read more.

Multiagent control system (MACS) has become a promising solution for solving complex control problems. Using the advantages of MACS-based design approaches, a novel solution for advanced control of mechatronic systems has been developed in this paper. The study has aimed at integrating learning control into MACS. Specifically, learning feedforward control (LFFC) is implemented as a pattern for incorporation in MACS. The major novelty of this work is that the feedback control part is realized in a real-time periodic MACS, while the LFFC algorithm is done on-line, asynchronously, and in a separate non-real-time aperiodic MACS. As a result, a MACS-based LFFC design method has been developed. A second-order B-spline neural network (BSN) is used as a function approximator for LFFC whose input-output mapping can be adapted during control and is intended to become equal to the inverse model of the plant. To provide real-time features for the MACS-based LFFC system, the open robot control software (OROCOS) has been employed as development and runtime environment. A case study using a simulated linear motor in the presence of nonlinear cogging and friction force as well as mass variations is used to illustrate the proposed method. A MACS-based LFFC system has been designed and implemented for the simulated plant. The system consists of a setpoint generator, a feedback controller, and a time-index LFFC that can learn on-line. Simulation results have demonstrated the applicability of the design method. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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14 pages, 2128 KiB

Open AccessArticle

Influence of Variable Damping Coefficient on Efficiency of TMD with Inerter

by Piotr Brzeski, Mateusz Lazarek and Przemyslaw Perlikowski

Energies 2020, 13(23), 6175; https://doi.org/10.3390/en13236175 - 24 Nov 2020

Cited by 5 | Viewed by 2511

Abstract

In this paper, we study the dynamics of a two-degree freedom system consisting of the main body and tuned mass damper with inerter (TMDI). We add the dash-pot with variable damping coefficient to TMDI to study the overall efficiency of the device. We [...] Read more.

In this paper, we study the dynamics of a two-degree freedom system consisting of the main body and tuned mass damper with inerter (TMDI). We add the dash-pot with variable damping coefficient to TMDI to study the overall efficiency of the device. We investigate different types of the non-linear characteristic of the dash-pot. We investigate devices in which damping coefficient change according to the relative displacement or the relative velocity between the damped mass and tuned mass damper. We also include in the investigation of different types of control functions. We show the two-parameter diagrams presenting the main body’s maximum amplitude versus the frequency of excitation of the damped body and different control parameter. We show how the application of a non-linear damper lets us control the main system’s oscillation amplitude. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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14 pages, 1817 KiB

Open AccessArticle

Particular Methods of Simultaneous Collection of Personal Mobility Research Data from Several Points

by Adrian Tantau, Ileana Gavrilescu and Laurentiu Fratila

Energies 2020, 13(22), 6053; https://doi.org/10.3390/en13226053 - 19 Nov 2020

Cited by 1 | Viewed by 2420

Abstract

Until three or four decades ago, humanity was no longer constrained by the depletion of certain natural resources (especially energy) and the intensified degradation of the natural environment. The consequences of these major crises—such as the economic, financial, and social upheaval of the [...] Read more.

Until three or four decades ago, humanity was no longer constrained by the depletion of certain natural resources (especially energy) and the intensified degradation of the natural environment. The consequences of these major crises—such as the economic, financial, and social upheaval of the world, dramatic climate change, and the entry of politics into a Brownian sarabande—necessitate the transition of civilization to another viable formula. Adequate, timely, and sustainable solutions are being sought, from the subsistence ones to those of economic efficiency. Thus, the mobility revolution is credited as one of the most important levers of change. Starting from the reality that most cars in traffic are not occupied at their maximum capacity, some ideas have already been advanced and even put into practice—“inspired”—which would improve the efficiency in this regard. For example, the reduction in the number of seats in cars and, correspondingly, the considerable reduction in the dimensions of cars are already found in the design of mini-cars and the correlation of identical interests of the self-movement of several people and the integration of this coincidence in a single concurrent mobility formula is already functional through the ride sharing system. Along with intelligent mobility management and the transition to electric and autonomous mobility, streamlining the occupancy of moving cars is seen as a great potential of the mobility revolution. Within the limits of the methodology of data collection in economic statistics, this study proposes a complex technique associated with a convincing tactic of empirical measurement of specific indices of urban traffic issues. The special method is characterized by the simultaneity and plurality of observation points followed by the correlation of the values obtained from the measurement thus performed, with the results from the video recordings taken at the same time. This method will increase the methodological accuracy of data collection in economic statistics. By advancing this method, this study aims to capture the occupancy rates of people in urban vehicle traffic, in different cities, using a combined method. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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13 pages, 2437 KiB

Open AccessArticle

Energy and Resource Efficiency in Apatite-Nepheline Ore Waste Processing Using the Digital Twin Approach

by Maksim Dli, Andrei Puchkov, Valery Meshalkin, Ildar Abdeev, Rail Saitov and Rinat Abdeev

Energies 2020, 13(21), 5829; https://doi.org/10.3390/en13215829 - 8 Nov 2020

Cited by 16 | Viewed by 3014

Abstract

The paper presents a structure of the digital environment as an integral part of the “digital twin” technology, and stipulates the research to be carried out towards an energy and recourse efficiency technology assessment of phosphorus production from apatite-nepheline ore waste. The problem [...] Read more.

The paper presents a structure of the digital environment as an integral part of the “digital twin” technology, and stipulates the research to be carried out towards an energy and recourse efficiency technology assessment of phosphorus production from apatite-nepheline ore waste. The problem with their processing is acute in the regions of the Russian Arctic shelf, where a large number of mining and processing plants are concentrated; therefore, the study and creation of energy-efficient systems for ore waste disposal is an urgent scientific problem. The subject of the study is the infoware for monitoring phosphorus production. The applied study methods are based on systems theory and system analysis, technical cybernetics, machine learning technologies as well as numerical experiments. The usage of “digital twin” elements to increase the energy and resource efficiency of phosphorus production is determined by the desire to minimize the costs of production modernization by introducing advanced algorithms and computer architectures. The algorithmic part of the proposed tools for energy and resource efficiency optimization is based on the deep neural network apparatus and a previously developed mathematical description of the thermophysical, thermodynamic, chemical, and hydrodynamic processes occurring in the phosphorus production system. The ensemble application of deep neural networks allows for multichannel control over the phosphorus technology process and the implementation of continuous additional training for the networks during the technological system operation, creating a high-precision digital copy, which is used to determine control actions and optimize energy and resource consumption. Algorithmic and software elements are developed for the digital environment, and the results of simulation experiments are presented. The main contribution of the conducted research consists of the proposed structure for technological information processing to optimize the phosphorus production system according to the criteria of energy and resource efficiency, as well as the developed software that implements the optimization parameters of this system. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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17 pages, 3039 KiB

Open AccessArticle

A New Virtual Synchronous Generator Design Based on the SMES System for Frequency Stability of Low-Inertia Power Grids

by Gaber Magdy, Abualkasim Bakeer, Morsy Nour and Eduard Petlenkov

Energies 2020, 13(21), 5641; https://doi.org/10.3390/en13215641 - 28 Oct 2020

Cited by 62 | Viewed by 4838

Abstract

In light of the challenges of integrating more renewable energy sources (RESs) into the utility grid, the virtual synchronous generator (VSG) will become an indispensable configuration of modern power systems. RESs are gradually replacing the conventional synchronous generators that are responsible for supplying [...] Read more.

In light of the challenges of integrating more renewable energy sources (RESs) into the utility grid, the virtual synchronous generator (VSG) will become an indispensable configuration of modern power systems. RESs are gradually replacing the conventional synchronous generators that are responsible for supplying the utility grid with the inertia damping properties, thus renewable power grids are more vulnerable to disruption than traditional power grids. Therefore, the VSG is presented to mimic the behavior of a real synchronous generator in the power grid through the virtual rotor concept (i.e., which emulates the properties of inertia and damping) and virtual primary and secondary controls (i.e., which emulate the conventional frequency control loops). However, inadequate imitation of the inertia power owing to the low and short-term power of the energy storage systems (ESSs) may cause system instability and fail dramatically. To overcome this issue, this paper proposes a VSG based on superconducting magnetic energy storage (SMES) technology to emulate the needed inertia power in a short time and thus stabilizing the system frequency at different disturbances. The proposed VSG based on SMES is applied to improve the frequency stability of a real hybrid power grid, Egyptian Power System (EPS), with high renewables penetration levels, nonlinearities, and uncertainties. The performance superiority of the proposed VSG-based SMES is validated by comparing it with the traditional VSG approach based on battery ESSs. The simulation results demonstrated that the proposed VSG based on the SMES system could significantly promote ultra-low-inertia renewable power systems for several contingencies. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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18 pages, 6955 KiB

Open AccessArticle

A Fuzzy-PID Scheme for Low Speed Control of a Vehicle While Going on a Downhill Road

by Liqiang Jin, Ronglin Zhang, Binghao Tang and Hao Guo

Energies 2020, 13(11), 2795; https://doi.org/10.3390/en13112795 - 1 Jun 2020

Cited by 12 | Viewed by 3598

Abstract

We explored a vehicle hill descent control (HDC) system based on an electronic stability program (ESP) and applied this system to brake cars. The experimental results reveal that our system can effectively reduce the workload of a driver during a downhill journey. In [...] Read more.

We explored a vehicle hill descent control (HDC) system based on an electronic stability program (ESP) and applied this system to brake cars. The experimental results reveal that our system can effectively reduce the workload of a driver during a downhill journey. In the first phase of our work, the control strategy of the HDC system based on fuzzy-PID (Proportion Integral Differential) was built by MATLAB/Simulink. Then, the co-simulation based on MATLAB/Simulink, CarSim and AMESim was carried out. Finally, a real vehicle test was conducted to further verify the feasibility of the strategy. A series of simulation experiments and real vehicle tests show that the HDC system can assist the driver to control the vehicle while driving downhill at low speed, thus effectively improving the safety of the vehicle and reducing the workload of driver. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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5 pages, 221 KiB

Open AccessComment

Comment on Rogalev et al. Structural and Parametric Optimization of S-CO₂ Thermal Power Plants with a Pulverized Coal-Fired Boiler Operating in Russia. Energies 2021, 14, 7136

by Miroslav Variny

Energies 2022, 15(5), 1640; https://doi.org/10.3390/en15051640 - 23 Feb 2022

Viewed by 1613

Abstract

The reconstruction of ageing thermal power plants with the possibility of their increased efficiency, prolonged service and decreased environmental impact is an intensely debated and researched topic nowadays. Among various concepts, the replacement of the steam cycle by a supercritical CO₂ cycle [...] Read more.

The reconstruction of ageing thermal power plants with the possibility of their increased efficiency, prolonged service and decreased environmental impact is an intensely debated and researched topic nowadays. Among various concepts, the replacement of the steam cycle by a supercritical CO₂ cycle is proposed with the prospect of reaching higher efficiencies at the same working fluid inlet parameters as the ultra-supercritical steam cycles. A paper published previously by Rogalev et al. (2021) analyzed the variants of supercritical coal power plant reconstruction to a supercritical CO₂ cycle and ranked them according to the cycle efficiency. This contribution comments on the scope and applied method in that paper aiming to provide additional input relevant to the decision-making process on thermal power plant reconstruction to such a cycle. Full article

(This article belongs to the Special Issue Intelligent Control for Future Systems)

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