This study presents a new Model Predictive Controller (MPC), built with algorithms based on Paraconsistent Annotated Logic (PAL), with application examples in the excitation control of a synchronous generator. PAL is a non-classical evidential and propositional logic that is associated with a Hasse lattice, and which presents the property of accepting the contradiction in its foundations. In this research, the algorithm was constructed with a version of the PAL that works with two information signals in the degrees of evidence format and, therefore, is called Paraconsistent Annotated Logic with annotation of two values (PAL2v). For the validation of the algorithmic structure, the computational tool MATLAB® Release 2012b, The MathWorks, Inc., Natick, MA, United States was used. Simulations were performed which compared the results obtained with PPC-PAL2v to those obtained in essays with the AVR (Automatic Voltage Regulator) controls in conjunction with the PSS (Power System Stabilizer)... [more]

In recent decades the power system has become a complex network, to design a load frequency control (LFC) requires solving a complex equation. Optimisation techniques are essentially required to optimise the parameters of different controllers used for LFC issues in the power system. In a unified power system, the LFC is examined from all angles using different optimisation strategies to optimise the conventional PI, PID, cascaded, and fuzzy controllers as well as recently designed controllers. This manuscript specifically reviews the use of soft computing techniques in the frequency regulation of the power system with single/multiple areas that include conventional, renewable, and combinations of both, with FACTS devices and certain energy storage devices such as superconductor magnetic energy storage (SMES) and battery sources. Furthermore, deregulated power systems and microgrids are also considered for the study. To regulate LFC under various disturbances such as generation rate co... [more]

Theft of electricity poses a significant risk to the public and is the most costly non-technical loss for an electrical supplier. In addition to affecting the quality of the energy supply and the strain on the power grid, fraudulent electricity use drives up prices for honest customers and creates a ripple effect on the economy. Using data-analysis tools, smart grids may drastically reduce this waste. Smart-grid technology produces much information, including consumers’ unique electricity-use patterns. By analyzing this information, machine-learning and deep-learning methods may successfully pinpoint those who engage in energy theft. This study presents an ensemble-learning-based system for detecting energy theft using a hybrid approach. The proposed approach uses a machine-learning-based ensemble model based on a majority voting strategy. This work aims to develop a smart-grid information-security decision support system. This study employed a theft-detection dataset to facilitate aut... [more]

The fast development of distributed generations enables the microgrid a popular solution for the construction of the modern power grid, where the control behaviors of power electronics converters play a crucial role. Under this scenario, the emulation of microgrid control behaviors is becoming an emerging need for the testing and teaching of the AC microgrid. However, conventional approaches, such as the dynamic simulation test and the Power-Hardware-In-Loop, are still costly or bulky to flexibly recreate the correct characteristics of microgrid including different layers of controls and the interactions among multiple converters. The dynamic simulation test is bulky and costly to emulate various types of control behaviors since all physical components in the test system may need to be adjusted. The high cost of Power-Hardware-In-Loop is mainly caused by the high-performance real-time simulator and power amplifier. In this paper, a novel emulation system is proposed for the testing of... [more]

The resistance−capacitance (RC) model is one of the most applicable circuits for modeling the charging and discharging processes of supercapacitors (SCs). Although this circuit is usually used in the electric and thermal investigation of the performance of SCs, it does not include leakage currents. This paper presents exact analytical formulas of leakage-current-based supercapacitor models that can be used in industrial applications, i.e., constant-power-based applications. In the proposed model, current and voltage are represented as a solution of nonlinear equations that are solved using the standard Newton method. The proposed expressions’ accuracy is compared with the results obtained using traditional numerical integration methods with leakage current formulation and other methods, found in the literature, with no leakage current formulation. The results confirm that including leakage current represents a more accurate and realistic manner of modeling SCs. The results show that th... [more]

Agriculture activities are completely dependent upon energy production worldwide. This research presents sensorless speed control of a three-phase induction motor aided with an extended Kalman filter (EKF). Although a proportional integral (PI) controller can ensure tracking of the rotor speed, a considerable magnitude of ripples is present in the torque generated by a motor. Adding a simple derivative to have a proportional integral derivative (PID) action can cause a further increase in ripple magnitude, as it allows the addition of high-frequency noise in the system. Therefore, a fractional-order-based PID control is presented. The proposed control scheme is applied in a closed loop with the system, and simulation results are compared with the PID controller. It is evident from the results that the fractional order control not only ensures 20 times faster tracking, but ripple magnitude in torque was also reduced by a factor of 50% compared to that while using PID and ensures the eff... [more]

In this paper, we present AWEbox, a Python toolbox for modeling and optimal control of multi-aircraft systems for airborne wind energy (AWE). AWEbox provides an implementation of optimization-friendly multi-aircraft AWE dynamics for a wide range of system architectures and modeling options. It automatically formulates typical AWE optimal control problems based on these models, and finds a numerical solution in a reliable and efficient fashion. To obtain a high level of reliability and efficiency, the toolbox implements different homotopy methods for initial guess refinement. The first type of method produces a feasible initial guess from an analytic initial guess based on user-provided parameters. The second type implements a warm-start procedure for parametric sweeps. We investigate the software performance in two different case studies. In the first case study, we solve a single-aircraft reference problem for a large number of different initial guesses. The homotopy methods reduce th... [more]

In order to give full play to the frequency regulation ability of multiple types of resources such as wind power, energy storage, and controllable load in a microgrid, this paper proposes a hierarchical cooperative frequency regulation control strategy of wind-storage-load in a microgrid based on model prediction. Firstly, according to the operation characteristics of each resource in the microgrid, a hierarchical cooperative frequency regulation architecture of wind-storage-load is constructed. On this basis, the frequency regulation control models of wind power, energy storage, and controllable load are established, respectively, and the calculation method of the characteristic index of the system frequency response is proposed. Then, taking the maximum frequency deviation as the stratification index, a hierarchical cooperative frequency regulation control strategy of wind-storage-load based on model prediction is proposed, and a power compensation strategy for connecting the wind tu... [more]

Fault diagnosis plays an important role in complex and safety-critical systems such as nuclear power plants (NPPs). With the development of artificial intelligence (AI), extensive research has been carried out for fast and efficient fault diagnosis based on intelligent methods. This paper presents a review of various AI-based system-level fault diagnosis methods for NPPs. We first discuss the development history of AI. Based on this exposition, AI-based fault diagnosis techniques are classified into knowledge-driven and data-driven approaches. For knowledge-driven methods, we discuss both the early if−then-based fault diagnosis techniques and the current new theory-based ones. The principles, application, and comparative analysis of the representative methods are systematically described. For data-driven strategies, we discuss single-algorithm-based techniques such as ANN, SVM, PCA, DT, and clustering, as well as hybrid techniques that combine algorithms together. The advantages and di... [more]

This study was carried out to estimate the relevance of biological supplementation in improving the economic efficiency of anaerobic digestion (AD). Three kinds of silages—maize, grass, and igniscum—were initially inoculated with digestate and then supplemented with one of four vaccines containing different bacteria species (APD®, PPT®, JENOR®) or a yeast and mold mixture (HAP®). In addition, each plant silage was fermented without any additives (control A—maize silage, B—grass silage, and C—igniscum silage). The biodegradability process was performed in batch tests at a mesophilic temperature (38 °C). To compare the energetic efficiency of AD, the process kinetics, biogas, and methane production were analyzed. We found that the applied supplementation measures improved biogas production in the case of maize and igniscum (7−62% higher than controls), but decreased the yield of AD when grass silage was fermented (2−34% lower than controls). The greatest increase in methane production (b... [more]

This paper presents the study and detailed analysis of converter losses at different stages together with the series-series (S-S) compensating coils in wireless power transfer (WPT) systems, via two distinct approaches to control the power converters. The two approaches towards wireless DC−DC power flow control are termed as the Single Active High-Frequency Wireless Power Transfer (SAHFWPT) system and the Dual Active High-Frequency Wireless Power Transfer (DAHFWPT) system. The operation of converters in SAHFWPT and DAHFWPT are controlled by the extended phase shift (EPS) and dual phase shift method respectively. The general schematic of the SAHFWPT system consists of an active bridge and a passive bridge, while the schematic of the DAHFWPT system consists of both active bridges. The efficiency evolutions of ideal SAHFWPT and DAHFWPT are far away from the real ones. Moreover, this article analyzes the operation and losses of the uni-directional power flow of the WPT system, i.e., from t... [more]

With the emergence of the electric vehicle (EV) era in which the vehicle’s embedded batteries can be exploited for grid support purposes, the role of EVs participating in ancillary services via vehicle-to-grid (V2G) technology cannot be disregarded. Although there are many forms of ancillary services, the most common services delivered by EVs are frequency regulation, frequency contingency, inertia, and voltage regulation. Numerous research studies have been conducted to propose the most effective control strategies for electric vehicle ancillary services (EVASs). In this paper, a comprehensive review is carried out on various control strategies for EVs with respect to their participation in ancillary services. The methodology applied for this review comprises a combination of thematic and historical reviews. The review explores the benefits and limitations of these control strategies and provides a clear understanding of the research gaps in the EVAS area. This review will provide a u... [more]

The article considers the actual problem of the ecology of urban areas associated with air pollution by industrial and energy enterprises. The study is aimed at substantiating the method of forming a plan for atmospheric air pollution observation using mobile laboratories. The quantitative characteristic of sites for different urban development zones is determined as a set of estimates. The air pollution index was chosen as a total sanitary and hygienic criterion for assessing pollution. The implementation of the decision-making problem using the analytic network process method is considered. Parameters of the city and environment that affect the assessment of atmospheric air quality were selected in the course of the study. A network structure of mutual influence of the studied parameters is formed. The architecture of the decision support system based on the proposed method is given. The created software makes it possible to automate the modeling of the distribution of pollutants in... [more]

The publication deals with the problem of the effect of interference with the movement of the “preceding” train on the movement of the “following” train in the case of efforts to reduce the distance between trains on a moving block interval. The paper presents results of the simulations for train of the ED250 type for a set of 135 traffic situations: for three contexts of reducing the speed of the “preceding” train, for five variants of the method of controlling the “following” train and for nine initial distances between these trains. The results confirmed the possibility of gaining time and energy benefits by implementing an appropriate method of controlling the “following” train, as well as providing insights into the area of shortening the gaps between trains, including the pursuit of synchronizing the speed of trains and possibly coupling them into a so-called virtual couples.

This paper describes the scheme and algorithm for controlling a laboratory setup that result in low uncertainty and high convergence with respect to the characteristics of electric discharges under the conditions of variable parameters of a reaction medium. The article presents current and voltage oscillograms when processing hydrocarbon raw materials. Methods for calculating the energy impact of electrical discharge are described. A comparison is made between the parameters of electric discharge with current pulse limitations and those without current pulse duration limitations. The proposed approach to controlling the characteristics of electric discharges provides the same parameters of nonthermal nonequilibrium plasma and, as a result, a regular composition of the products of plasma pyrolysis of hydrocarbon raw materials.

Availability of reliable and extended datasets of recorded power output from renewables is nowadays seen as one of the key drivers to improve the design and control of smart energy systems. In particular, these datasets are needed to train artificial intelligence methods. Very often, however, datasets can be corrupted due to lack of records connected to failures of the acquisition system, maintenance downtime periods, etc. Several recovery (imputation) methods have been used to guess and replace missing data. In this paper, we exploit the matrix completion approach. The available measures of several variables referring to a real onshore wind farm are organized into a matrix in a daily range and the Singular Value Thresholding method is used to carry out the matrix completion process. Numerical results show that matrix completion is a reliable and parameter-free tuning tool to impute missing data in these applications.

This paper presents a comparison of Isolated (Flyback) and non-Isolated (Buck) multiple input-single output (MISO) DC-DC converters. The analysis of DC-DC converters is based on pulsed voltage source cells (PVSC). The modeling of both converter types is detailed through their mathematical models and electrical simulations using Matlab/Simulink and PSIM. The comparison focuses on the sizing parameters, non-ideal output characteristics and efficiency. Results show that the output voltage of the MISO Buck converter exhibits a linear dependence on the duty cycles control signal and has slightly higher efficiency than the Flyback converter. To validate the operation of both converters, a scenario with two inputs (low-power hydroelectric and photovoltaic voltage sources) is considered. The modeling and control of both source systems are detailed and the MISO converter performance response is evaluated under sources changes and efficiency point of view.

For Brush-less DC motors to function better under various operating settings, such as constant load situations, variable loading situations, and variable set speed situations, speed controller design is essential. Conventional controllers including proportional integral controllers, frequently fall short of efficiency expectations and this is mostly because the characteristics of a Brush-less DC motor drive exhibit non linearity. This work proposes a hybrid gray wolf optimization and proportional integral controller for management of the speed in Brush-less DC motors to address this issue. For constant load conditions, varying load situations and varying set speed situations, the proposed controller’s efficiency is evaluated and contrasted with that of PID controller, PSO-PI controller, and ANFIS. In this study, two PI controller are used to get the more stability of the system based on tuning of their coefficients with meta heuristic method. The simulation findings show that Hybrid GW... [more]

Automated fault detection and diagnostics in building systems using machine learning (ML) can be applied to commercial buildings and can result in increased efficiency and savings. Using ML for FDD brings the benefit of advancing the analytics of a building. An automated process was developed to provide ML-based building analytics to building engineers and operators with minimal training. The process can be applied to buildings with a variety of configurations, which saves time and manual effort in a fault analysis. Classification analysis is used for fault detection and diagnostics. An ML analysis is defined which introduces advanced diagnostics with metrics to quantify a fault’s impact in the system and rank detected faults in order of impact severity. Explanations of the methodology used for the ML analysis include a description of the algorithms used. The analysis was applied to a building on the Texas A&M University campus where the results are shown to illustrate the performance... [more]

The Split-pi converter can suitably interface an energy storage system (ESS) with a DC microgrid when galvanic isolation is not needed. Usually, the ESS voltage is lower than the grid-side voltage. However, limitations in terms of the ESS current make the use of a high-voltage ESS unavoidable when high power levels are required. In such cases, the ESS voltage can be higher than the microgrid voltage, especially with low microgrid voltages such as 48 V. Despite its bidirectionality and symmetry, the Split-pi exhibits a completely different dynamic behavior if its input and output ports are exchanged. Thus, the present work aims to model the Split-pi converter operating with an ESS voltage higher than the grid-side voltage in three typical microgrid scenarios where the controlled variable is the converter’s output voltage. The devised state-space model considers the parasitic elements and the correct load model for each scenario. Furthermore, it is shown that the presence of the input LC... [more]

This paper describes a high-frequency soft-switching dc-dc converter with a simple energy recovery capacitor snubber on the secondary side. The presented dc-dc full-bridge converter with the energy recovery snubber removes the main drawbacks of the classic Phase Shifted PWM (PS-PWM) dc-dc converter, e.g., the circulating current flowing during the free-wheeling interval and dependency of the soft switching on the load current. The converter utilizes a full-bridge topology with pulse-width modulation and a centre-tapped full-wave controlled rectifier with one active switch. The zero-voltage switching on the primary side is ensured by utilising only the magnetizing current of the high-frequency transformer, and thus is load-independent. The proposed energy recovery snubber is described in detailed time waveforms of the converter and verified by simulation. The control algorithm also removes the circulating current, which is typical for PS-PWM converters. The soft-switching of the seconda... [more]

Modular multilevel converters (MMCs) have been conceived as an alternative in front-end converter applications to enhance the converter system’s reliability, minimize total harmonic distortion, and improve power quality. These converters utilize several DC-link capacitors and power electronic switches, along with switches operating with high switching frequencies, to attain the desired characteristics. Thereby, this paper systematically proposes a novel three-phase asymmetric hybrid modular multilevel converter (AHMMC) for front-end converters used in lower-medium-voltage applications. The AHMMC configuration is based on a three-phase converter connected to a per-phase series arrangement with a cascaded converter module (CCM). The study investigates the AHMMC and proposes a control scheme, which minimizes the voltage range on switches and maintains the current to its reference value. Furthermore, the study also introduces an active balancing of voltage across DC-link capacitors based o... [more]

The European Union obliged the member states to introduce monitoring and control tools in order to improve the quality of provided transmission services and to guarantee the contracted amount of energy to end users. However, the EU has left the member states the freedom to create and implement compensation tools, enabling customers to claim their rights arising from non-compliance by transmission companies with the provisions of distribution agreements. The introduction of quantitative energy monitoring and an appropriate compensation mechanism is of great importance not only for end users but also for distribution companies. For end users, this would be a tool to enforce their rights against transmission companies, while transmission companies would gain a tool to control and manage both legal and financial risks. The aim of this study is to analyze discount as an example of a guarantee instrument in the field of the consumer’s right to energy of an adequate quality based on the Polis... [more]

Following the International Maritime Organization (IMO), in order to safeguard the realization of the Paris Agreement on climate protection, greenhouse gas (GHG) emissions have to be reduced by 50% by the year 2050. This objective shall be reached by decarbonization of maritime traffic, which is why ship operators currently increasingly search for alternative fuels. Moreover, since the start of the Ukrainian war in February 2022, this issue of alternative fuels has gained central importance in political agendas. A promising candidate for clean shipping that meets the IMO goals is ammonia since it is a carbon-free fuel. Ammonia (NH3) shows good advantages in handling and storage, and it ensures long sea voyages without any significant loss in cargo space for a reasonable price. Hence, ammonia has the potential to improve the environmental footprint of global shipping enormously. Induced by the introduction of stricter regulations in the so-called emission control areas (ECAs) in Norther... [more]

A regulating valve is a key control element in the coal liquefaction industry, whose flow field distribution is related to the entropy production. In order to make a quantitative evaluation of the energy loss in the cavitation flow and calculate the magnitude and location of the hydraulic loss in the flow field more accurately, entropy production theory is employed to analyze the flow field in the regulating valve numerically. The entropy production under cavitation condition and its influence on steady-state flow force are also discussed. When the opening of the valve increases, the entropy production and energy loss change dramatically. The entropy production rate (EPR) is mainly distributed at the orifice and downstream of the regulating valve, the entropy production rate (EPR) reaches the maximum value at the orifice, and turbulent pulsation entropy production (TPEP) is the main part of the total entropy production for flow. When the valve’s opening increases from 40% to 70%, the t... [more]