—Model predictive control (MPC) for multilevel converter has a multi-term cost function that requires high computation burden. In this paper, the deviation terms considered are classified into two categories according to their dependency on the voltage vector or the switching states of the multilevel converter. Subsequently, two approaches to reduce the computation burden are proposed. Mathematical models for the proposed MPC approaches are discussed and analyzed. An experimental platform for a fivelevel T-type multilevel induction drive is used to validate the proposed study. The experimental results show that the proposed approaches have substantially reduced the MPC computation burden compared to the conventional MPC techniques.

This paper proposes a voltage sag estimation approach based on linear machine learning models. The proposed approach estimates the voltage sag profile on distributions systems with limited monitored buses. The approach takes advantage of the priory knowledge about the linearity of the problem to train and compare three linear models: Least Squares (LS), Ridge Regression (RR), and Absolute Shrinkage and Selection Operator (LASSO). The approach is tested on the IEEE-34-bus distribution system, and the performance of models is validated through the Mean Square Error (MSE). The results show that the proposed linear machine learning models capture the internal relationships of the problem and estimate the voltage sag with high accuracy on test data.

One of the main goals of building design is indoor comfort, regardless of its use (residential, educational, institutional, etc…). However, to achieve indoor comfort, buildings require a significant amount of energy. In the last decades, designers and researchers have been studying new strategies to improve buildings’ energy efficiency, with the purpose of mitigating the negative environmental impact caused by heavy energy consumption. Green roofs have been one of the most investigated solutions because of the many thermal benefits they can offer, and amongst these, hydroponic green roofs gained momentum. This study aims to analyse the rooftop temperature reduction provided during the hot months by a hydroponic green roof, compared to a traditional roof slab and an extensive green roof, in order to assess the different performances of these systems. In situ experiments were conducted to collect surface temperature of the roof slab during summer, with and without the hydroponic system, in order to assess the potential temperature reduction, which subsequently affects the heat flow through the roof and therefore the indoor air temperature. The results show a significant decrease in the external surface temperature of the roof compared to the bare roof, but also slightly better performance compared to the extensive green roof. Despite first promising results, the knowledge on hydroponic green roofs performance remains limited and some drawbacks need to be assessed. For these reasons, further in situ testing should be carried out, under different climatic conditions and experimental setups.

Solar thermal energy is a type of non-conventional renewable energy (NCRE) that takes advantage of the sun's heat to heat a fluid called heat carrier, then in a heat exchanger it produces steam at high pressure and temperature that generates electricity in a conventional thermal process, this process being of crucial importance since the production of electrical energy on a large scale depends on its efficiency. The technology chosen here is that of parabolic cylinder thermosolar (PCT), that reflect solar radiation and concentrate it in a tube located in its focal line. Inside it is a thermal fluid heated up to almost 400 ºC. The objective of the present investigation was the thermodynamic modelling of the power cycle of PCT plant that works under a modified Rankin cycle. The research is quantitative in nature since it allowed us to assess how the different thermodynamic processes occur, and it is also non-experimental, descriptive, explanatory and propositional, establishing causal relationships based on secondary sources. The result was a real temperatureentropy diagram (T-S) in which the thermodynamic modelling of the power cycle is represented.

This document describes the application of multiobjective genetic algorithms as techniques and tools to optimize generation and distribution in small microgrids. In this way, genetic algorithms have been used for the allocation of distributed generation to reduce losses and improve the voltage profile. The IEEE14 network has been taken as a study and analysis model. This smart grid has 14 nodes and integrates several generation units, both conventional and renewable, transformers, and multiple loads. In this way, a multi-objective metaheuristic algorithm is proposed with the purpose of planning the power distribution grid based on a series of conditions such as the optimal generation configuration, the minimization of power losses in the lines, power transfer capacity, the reduction of CO2 emissions, and the optimization of the benefits obtained in renewable generation. The overall purpose is the development of an intelligent microgrid management system that is capable of determining the optimal configuration, by estimating demand, energy costs, and operating costs.

In order to smooth the wind power output, a wavelet packet-double fuzzy control for hybrid energy storage is proposed to smooth the wind power fluctuation. Firstly, the wavelet packet decomposition is used to decompose the wind power output to obtain the grid-connected power signal and the power signal allocated to the hybrid energy storage. Then, the double fuzzy control algorithm is used to optimise the hybrid energy storage SOC to maintain it within a reasonable range, and to make a secondary correction to the hybrid energy storage power allocation, taking into account the charge states of lithium batteries and super capacitors. The results of the analysis show that the proposed method can smooth out the wind power fluctuations while keeping the energy storage SOC within a reasonable range.

This paper describes the design of low-cost variablespeed wind turbines by recycling small electrical machines. In this way, electrical machines such as automobile claw-pole alternators, induction motors for domestic applications, or simply electric motors for some industrial applications are studied, considering their reuse as permanent magnet synchronous generators (PMSG) in small wind turbines or hydro-power turbines. The main purpose is the integration of hybrid energy conversion systems (wind and hydraulic turbines) in small stand-alone microgrids within the rural environment. Likewise, in order to optimize the design, the arrangement of the permanent magnets in the rotor is analyzed. The analysis has been carried out using the FluxMotor simulation software, which is based on the 2D finite element method. At the same time, the FEM software provides a lot of information about the optimization of the electrical machine and its multiple design options and topologies. Suggested designs have similar performance as well as a similar size and weight. The purpose has been to explore different topologies and select the most efficient designs. In this way, it is shown that it is possible to reuse an electrical generator easily, without losing much of the general performance.

Tenerife is one of the main islands of the Canary Islands, which, due to its characteristics as outermost region, has a high energy dependence as well as a limitation on available territory; in addition, as it has been designated as a Remote Area, the elimination of Animal By-Products (ABPs) in landfills is permitted. This treatment does not contribute to the current trend of a circular economy and negatively harms the environment. The energy recovery of this waste through anaerobic digestion to produce biogas would enhance the use of renewable energies, contributing to the meat industry's energy independence and better management of the waste generated by this industry in Tenerife, promoting an energy transition towards cleaner energies. The study of the potential for biomethanization has been carried out both separately and in co-digestion in search of the best biogas production. Of the samples studied, only biogas was obtained in the anaerobic digestion of the rumen content, sewage sludge and for the co-digestion of viscera (cattle, pigs, goats, sheep, and rabbits) with raw blood and sewage sludge. The latter produces 128 mL of biogas per gram of volatile solids (VS) of the mixture, resulting in a total of 4,800 kWhe of electrical energy for Tenerife's estimated waste in 2019.

A linear time-invariant (LTI) system is usually characterized by its gains, which are ratios of various output and input signal magnitudes. When the main function of the system is energy conversion, one is more interested in the power or energy gain or loss between input and output terminals. Such a "gain" represents the efficiency of the system as an energy conversion device. In this paper, we show that the power or energy "gain" of an LTI system can be determined as a nonlinear function of three signal gains of the system. This results in an explicit formula for the power (energy) gain in terms of the system parameters. This can then be optimized over the design parameters to maximize the gain and thus the system energy efficiency. A detailed DC circuit example is included for illustration. The energy efficiency of an LTI system operating in a steady state in response to a sinusoidal signal is also determined.

Ground Thermal Response (TRT) tests are employed to calculate ground thermal characteristics for Ground Heat Exchanger (GHE) design and optimization purposes. There are plenty of 3D models to increase the accuracy of the calculated characteristics, with which the fluid outlet temperature is obtained based on the experimental inlet temperature. To simulate other behaviours not tested in the GHE, it is necessary to correctly simulate the conduct of the fluid inside the test equipment. For this reason, a simple model has been obtained which considers the absorption of heat by the elements of the equipment during an initial time through a variable equivalent heat capacity term and a load factor.

A packed-bed catalytic configuration reactor using pumice granules loaded with lithium (Li/Pumice) as a heterogeneous catalyst was developed for the continuous biodiesel production. For this purpose, Jatropha curcas oil was used as an alternative feedstock to edible oils and diethyl ether was used as a cosolvent to improve the mass transfer between the phases present in the transesterification reaction. The solid catalyst was characterized, and its catalytic activity was evaluated for the biodiesel production. Fatty acid methyl esters (FAME) yield of 100% was achieved under the conditions of 1.4 mL min-1, 20.0 methanol/oil molar ratio, 0.57:1 cosolvent/methanol molar ratio and 40ºC. Moreover, Li/Pumice catalyst shows high stability for the continuous biodiesel production.

This paper addresses state estimation as one of the most essential mechanisms in real-time operation and control of modern power systems, and proposes a novel solution to the issue of poor network observability, commonly faced in distribution system state estimation (DSSE) characterized by an ever-increasing penetration of renewable generation. The ongoing transformation from conventional passive, onedirectional power systems to active smart grids necessitates more accurate and reliable system state estimation to achieve optimal system performance. Real-time grid monitoring and control has been a routine task in transmission networks, but distribution grids cannot successfully utilize these capabilities due to different topologies, specific electrical characteristics, the low amount of available real-time measurements, as well as substantial communication effort needed to handle the data. Furthermore, with the advent of distributed generation, new types of loads and the vast surge of prosumers, a substantial amount of data is required to maintain system stability and controllability. For these reasons, reliable state estimation requires a high-quality creation process of pseudo-measurement, in addition to an efficient algorithm and an extremely accurate estimator. Thus, this paper proposes a novel framework of dynamic estimation methodology that includes the use of Artificial Neural Networks (ANN) in the pseudo-measurements generation process, utilizes Iteratively Reweighted Least Squares (IRWLS) algorithm and Schweppe-Huber Generalized Maximum Likelihood (SHGM) estimator. The efficiency and accuracy of the proposed methodology were assessed and verified on a benchmark network model.

This paper is focused on the input current in a Switched Mode Power Supply (SMPS) in which the power inductor is exploited up to the saturation showing a non-linear behaviour. The input current exhibits a distortion due to the nonlinearity. The electromagnetic interference (EMI) caused by the ripple at switching frequency, superimposed to the DC value of the input current, requires a suitable design of the input differential mode (DM) filter. The input current is analyzed both in the time and frequency domain for different operating conditions, and it is compared to a SMPS equipped with a traditional linear inductor.

A photovoltaic system consists of several components that are interconnected into a grid network or standalone system. The overall efficiency of a photovoltaic system is the result of component selection, accurate implementation, and stable operation. Therefore, if these factors are not in harmony during the design and execution of the system, optimal efficiency will not be achieved. This paper summarizes the technological trend of photovoltaic cells which lead to the development of multijunction photovoltaic cells based on III-V elements. Additionally, the challenges within the implementation of multijunction cells based on III-V elements into terrestrial applications will also be discussed, followed by a potential solution to counter the efficiency loss of these cells caused by the atmospheric gases filtering the solar irradiance across the optical band length of absorption. The implementation of Adaptive-Perturbation-Frequency (APF) in a Perturb and Observe (P&O) algorithm, instead of a linear step size variation, combined with several hardware optimizations on the Maximum Power Point Tracker (MPPT), maybe an ideal approach to reduce the impacts of having a multijunction photovoltaic cell based on elements III-V operating at terrestrial conditions.

Renewable Energy Sources (RES) use at local scale reduces the environmental impact, maximizing the effect as production and consumption are carried out in the same place. Therefore, this limits the losses associated with distribution networks, and minimizes the impact on the landscape in areas of special interest, including touristic beaches and other natural sites, where there are high-value natural environments, and where the citizens’ comfort must be considered. Implementation of an intra-urban transport ecosystem, based on fleets of light electric vehicles charged from RES, is proposed for these natural touristic areas. In this context, Urban Touristic Transport at Sustainable Environments (TTUES) project aims to promote the implementation of a transport ecosystem, using specifically designed and tested light and small-sized electric vehicles (EVs), and suitable charging stations based solely on RES. This paper presents a development of an Energy Storage System (ESS) based on Hybrid Supercapacitors (HSC) for their application in light EVs recharging points. It details the main equipment and capabilities of the testing facilities, and the tests performed by INTA, the Spanish National Institute for Aerospace Technology, in the framework of the project TTUES, as well as the experimental results validating the HSC system for its application.

The dual unified power quality conditioner (iUPQC) is an active filter that has been studied to be applied as utility interface in microgrid applications. It regulates the voltage of the microgrid side and controls the power flow between the grid and microgrid side. Besides that, ancillary functions to grid side has been proposed to extend its power quality compensation. This paper presents a detailed analytical and numerical analysis of the power flow of an iUPQC, which operates as an utility interface in microgrid applications with the extended function of STATCOM. It can compensate not only the disturbances at the load or microgrid side but also provides a RMS voltage regulation at the Point of Common Coupling (PCC), thus, providing reactive power to the grid. Moreover, the iUPQC power flow is evaluated considering the implementation of the power angle control (PAC), a technique used to share and equalize the power processed by each converter allowing the optimization of this conditioner. Therefore, this study can support the understanding of the power flow of the iUPQC operating as STATCOM, in order to share and optimize the available power in the iUPQC converters using PAC.

In a bid of facilitating the increasing penetration of intermittent and random renewable energies, microgrids along with their management algorithms are becoming crucial assets. To prove their effectiveness, these algorithms need to be tested in real environments and/or laboratories, which can be very difficult in many cases, especially at the initial development stages. To solve this issue, this article proposes the use of a laboratory digital twin, i.e., a virtual laboratory with a behaviour that is similar to that of real installations, aimed at facilitating the development, testing and debugging of microgrids management algorithms. The proposed solution is demonstrated to be safe and complete when it comes to test these algorithms.

This paper evaluates the impact of a modular Static Synchronous Series Compensator (m-SSSC) on the operation of communication-assisted line distance and differential protection relays. The m-SSSC system incorporates an over-current protection feature to trigger the bypass mode of operation during grid faults. A case study is analyzed for a 220 kV transmission line and an m-SSSC with a reactive power rating of 80 MVAr per phase using a Hardware-In-the-Loop configuration. The obtained results show the impact of the m-SSSC system on the distance protection operation during some cases of high resistive faults. The differential protection operation was not affected by the mSSSC.

Race to Zero challenge is a world-wide activity for the universities and colleges to foster the climate goals. This paper analyses the potential of Riga Technical University (RTU) for this action. Different renewable energy sources (PV, wind generators) have been discussed to be installed around the RTU campus. The profiles of electric power consumption are analysed for one faculty and sport centre. The consumption profiles show the amount of power demanded during the working hours, weekends and at night. Energy yield assessment on the roofs is made for two buildings where the configuration of PV panel placement and orientation are analysed that in turn is reflected in the energy generation profile. SCADA system is considered as a monitoring and control tool to visualize power generation and control of the power flow within the system elements.

One of the main industries in Spain and other Mediterranean countries are oil mills. Although the specific energy consumption of oil mills depends on the capacity and other characteristics, some studies have highlighted the high energy consumption of these industries. In the case of olive mills, previous studies have shown that energy consumption is mainly supported by electricity, with low contribution from gas, diesel or biomass. Considering the importance of reducing the electricity consumption in oil mills, it is necessary to analyse the power consumption in order to take actions focused to reduce the contracted power and the energy required in its operation. Moreover, since these industries may require stable power supply, it is appropriate to analyse the power quality in order to detect possible adverse effects derived from a poor power quality. This paper presents the analysis of data collected by the Circutor MYeBOX 1500 portable meter installed in an olive oil mill. It is shown how monitoring these facilities during several weeks can provide relevant information regarding the energy assessment and policies.

The paper deals with optimisation of passive solar systems installed on family and office buildings in central Europe locations. In these territories, in contrast to more southern countries, it is not typical to utilize passive solar systems on public or private buildings. Although these systems can significantly influence thermal comfort inside the buildings, many controversions and myths reduce wider utilisation. It could be expected, that new European legislative tending to common energy savings will cause also wider usage of these systems. In contrast of classic countries utilizing passive solar systems, the benefits can be expected either in hot season or in cold season. If we focus on systems that can supplement existing buildings – roller blinds and slats, significant energy and economy benefits can be easily reached. These systems can either decrease or avoid overheating during hot summer days or to limit thermal loses in cold winter days and nights. This paper compares various roller blind and slat systems installed on office building and family house. Exact measurements explains the influence on thermal gains, thermal loses and thermal comfort in particular storeys during constituent seasons. The main results of these experiments and calculations are principles of operational charts for particular locations in the buildings leading to provable energy savings and economy profits. The measurements also serve as verification of computer simulations.

This paper presents a decision tool for the optimisation of wind turbine technical parameters, using a multiphysical model of the power system. This includes a multiphysical modelling of aerodynamical, mechanical and electromechanical system behaviours. The aerodynamics is based on a blade element momentum model. A mass model of wind turbines components is also used in this paper. The optimisation is performed with NSGA-II algorithm which may choose technical parameters (blade length, transmission ratio or electro-mechanical coefficient in this example) to maximise performances indicators (in this example the output electrical power and the wind turbine mass). The results provide a wide range of solutions that are the best compromises between the performances indicators chosen. The diversity in terms of parameters allows great latitude in the design of wind turbine.

In analysing power flows, computational strategies and tools are used to study electrical networks considered illconditioned by characteristics such as radial topology, load unbalance, and distributed generation. However, these techniques do not consider harmonic distortion that power electronics devices recently injected into electrical networks. For this reason, this work presents a comparison of the results of three strategies for solving harmonic power flows, where each one of them uses a specific load model in the frequency domain to represent nonlinear loads and a photovoltaic system installed in a distribution network. The traditional Backward/Forward algorithm is adjusted to meet the characteristic conditions of the network. It applies the Norton equivalent coupled admittance matrix model. The other strategies model the electrical network in specialised software; the analysis in Simulink considers the Norton decoupled admittance matrix model, while PowerFactory uses the current source model to represent the loads and the PV system. All three strategies successfully determined the waveforms of the voltage signals; however, the results showed differences for the current signals and power parameters.

Marine renewable energies are being implemented as basic energy sources of the Spanish energy system for various reasons, the first because the planet Earth is made up of 70% water, which makes marine resources very important when programming the production, the second because they are clean energies that do not emit greenhouse gases, necessary to comply with the European Green Deal and the third because this type of energy provides us with energy independence from third countries. But, despite the social benefits mentioned above, we also have to take into account economic factors that can make the economic profitability of this type of equipment less viable. For this, the wind resource, platform costs, etc. are analyzed. Within these factors, this research focuses on seeing how the variation in the price of steel (the main material used in this equipment) caused by the increase in the cost of electricity causes the main economic parameters to vary for a park made up of W2Power hybrid platforms. of 300 MW located on the Atlantic coast of the Iberian Peninsula.

Z‐source inverters have attracted considerable attention in renewable energy systems like photovoltaic (PV) systems due to advantages such as buck–boost power conversion in single stage, shoot-through capability, and wide range of input voltage regulation. Transformer-Based Z-source inverters (TransZSI) based on magnetically coupled inductors and reduced number of passive components can be used to improve the boost capacity of these inverters, and to increase the voltage levels. Medium voltage DC (MVDC) is being used more and more in distribution grids and renewable energy systems. This paper presents a transZ-source inverter with MVDC link where renewable energy systems and energy storage systems can be integrated. The active and reactive powers and DC voltage are controlled by acting on the modulation index and shoot-through duty cycle of the converter. The trans-Z-source inverter is evaluated under different operating conditions to illustrate its suitable operation.

The development of technology and science is decisive in the development of social welfare. We are experiencing the fourth revolution in technological development –after the invention of the steam engine; electricity and process automation; and then computer / IT technology – characterized by an interconnected information network. This revolution will affect all related industries, including the energy sector. New solutions, sensors, devices are available, but the main issue is the use of these devices. So-called smart grid technologies have many advantages, but they also present challenges, whether technologically, economically or sociologically and socially [1]. The answers to these challenges are often not traditional, but creative solutions can mean a breakthrough, changing and accelerating the current progress trends. Such solutions and methods can change and advance all segments and areas, from energy to medicine to the beauty industry. The digital transformation and its implications will significantly change the support for the basic functions of energy distribution. Nowadays, it is almost impossible to solve any task or complete a simple work phase without a computer or IT tool, location data, work schedule description, parameters, and so on. Long-term operation and design, proper architecture and design framework are crucial for efficient operation. Enterprise architecture management within large companies usually involves a very complex range of activities [2]: business, IT and organizational information infrastructure. The role of enterprise architecture is becoming increasingly important for developing and growing companies [3]. In our article, we show how recent decades have helped improve the efficiency of network management and how digitalization is becoming an indispensable player in a sustainable, renewablebased vision.

Supervision and monitoring are mandatory for large PhotoVoltaic (PV) plants, because failures can cause high power loss, due to the large number of PV modules. InfraRed (IR) analysis is effective and reliable to detect anomalies or failures in PV modules, but it is time consuming and then expensive, when the infrared inspection of large PV plants is manual. The diffusion of Unmanned Aerial Vehicle (UAV) equipped by infrared camera can support the fast supervision of PV plants, but the use of UAVs is regulated by international and national rules and its utilization is limited, based on geographic areas and/or authorizations. This article discusses these critical issues, directs the reader to official, national, geographic maps for the drones, and suggests technical solutions for some specific issues not considered in the technical specification for outdoor infrared thermography of PV modules

The present work aims to study the influence of using different methods for wind speed extrapolation in energy production calculations. A dataset of 21 meteorological masts from several landscape characteristics and locations, with at least one year of 10-minute wind speed/direction data, was used as the basis for calculations. Both the power law through estimation of wind shear coefficients, and the logarithmic-based profile using WAsP, were used as mathematical models for predicting wind shear. Wind speed extrapolation was performed either from the top-most height, using a distance method that incorporated all measurement heights, or using the function for wind shear coefficient prediction. It was found that using the logarithmicbased profile was the less reliable of all studied methods. The study showed that the most accurate method was the power law with wind shear coefficients estimated from the two upper heights closest to the extrapolation height, by wind direction sector of 30º, and the wind speeds extrapolation from the topmost height of the two. It is suggested that the use of this method reduces uncertainty in AEP estimates.

In this study, a solar photovoltaic microgrid, to sustainable energy and system efficiency, is being studied under different configurations. Solar modules, energy storage devices (battery), power electronics converters are used to validate the desired results. The study of stand-alone to grid-connected systems will be analyzed and tuned for a stable system performance. In the stand-alone tuning, the voltage and the frequency are the key driving parameters to be controlled and evaluated for proper operation of the microgrid. Also, the grid connected configuration will be studied and then both systems will be compiled together using a switching mechanism. The aim is developing a control system that enables the transition between the two configurations. The microgrid is simulated and tested using MATLAB/Simulink platform. The objective is to create a smooth transition of system with control mechanisms in different modes of the microgrid

The concerning growth of energy and water demand worldwide presents two major issues that can both be tackled by using renewable energy sources to oppose the energy consumption of wastewater treatment plants (WWTP), while taking advantage of their energy production potentialities. This work deals with the sizing of a photovoltaic system of a mediumsized Portuguese WWTP designed to meet the energy consumption needs, benefitting from the higher levels of irradiance in the country. The goal is to act as a model for future similar projects. The potentiality of producing electricity through cogeneration of biogas, in WWTP’s of activated sludge, needs to be taken into account. In the study case, 70% of the energy consumption needs were covered via cogeneration. This led to the conception of two different scenarios concerning the PV System: the first one covers the total electric needs of the WWTP and the other covers 30%, taking into account that the cogeneration system ensures 70%. During the 25 year-life of the PV System, an average annual performance ratio of 0.805 for scenario 1 and 0.789 for scenario 2 was achieved. Furthermore, the average energy contribution of scenario 1 and 2 was 36.5% and 32.8%, respectively, ensuring 100% of self-sufficiency, when adding the cogeneration contribution.

Modelling the operation of energy storage systems such as batteries in an energy model is challenging as it requires estimation of current and future imbalances between supply and demand and the value of energy stored and later returned to the system. Here, an approach is developed which optimally prioritises the provision of stored energy to the system according to a specified criterion such as time-of-use tariff. At this stage, the model assumes perfect knowledge of future supply and demand as well as a hierarchy of utility to the system operator. Such an operator would specify a ranked list of times of need from the energy storage. The model will then allocate available energy from earlier times while reserving necessary space in the available storage. By progressing through the times of need in ranked order, the model ensures best optimum use of the stored energy. The results show that the proposed method is very robust and can calculate reliably the potential of an energy storage system in any energy model based on time steps of balancing generation and demand with the mediation of storage.

Overall, the intervention on buildings on university facilities presents a lack of design criteria oriented to the rational use of energy (RUE), which can reduce electricity consumption between 20% and 40%. In particular, the selection of lighting and air conditioning systems in buildings is limited to the choice of efficient equipment. A process of classification of control and automation techniques have developed as a base for the computing of the electrical load associated with lighting and air conditioning systems. This article presents an interface based on Microsoft Excel® for evaluation, classification, and validation criteria for the control and automation of RUE-oriented applications. In particular, the results of the implementation of the software are set to evaluate different inner spaces like classrooms, offices, and auditoriums, among others. As a case study, several techniques of control and automation for lighting and refrigeration are analyzed for a classroom and an office considering specific warm tropical microclimate, physical characteristics, operation schedules, and operation characteristics.

Anaerobic digestion is a method of agricultural residue transformation used in bioenergy, making these activities energy efficient. However, it can be limited on a larger scale by the availability and diversity of organic residues related to carbon-nitrogen (C/N). Therefore, the anaerobic co-digestion of bovine manure and Jatropha seed cake (Jatropha curcas) were evaluated, with three different C/N ratios, under two conditions: mesophilic (30ºC) and thermophilic (50ºC). Biodigesters were mounted with three replicates for each C/N ratio. The highest production of CH4 was registered after 30 days of processing in the thermophilic condition (C/N 25:1) with 633.95 ± 5.59 mL of CH4 g-1 VS. In contrast, the lowest production was in the mesophilic condition (C/N 20:1) with 208.66 ± 2.61 mL of CH4 g-1 VS. The feasibility of co-digestion of agricultural residues in the production of CH4 as a possible bioenergetic alternative in short periods was demonstrated.

Digitalization process experienced by traditional power networks towards smart grids extend the challenges faced by power grid operators to the field of cybersecurity. False data injection attacks, one of the most common cyberattacks in smart grids, could lead the power grid to sabotage itself. In this paper, an event detection algorithm for cyberattack in smart grids is developed based on a decision tree. In order to find the most accurate algorithm, two different decision trees with two different goals have been trained: one classifies the status of the network, corresponding to an event, and the other will classify the location where the event is detected. To train the decision trees, a dataset made by co-simulating a power network and a communication network has been used. The decision trees are going to be compared in different settings by changing the division criteria, the dataset used to train them and the misclassification cost. After looking at their performance independently, the best way to combine them into a single algorithm is presented.

The increased participation of renewable variable energy sources (RVS) in the Brazilian electricity matrix brings several challenges to the planning and operation of the Brazilian Electricity System (BES) due to the stochasticity present in RVS. Such challenges involve the modeling and simulation of intermittent generation processes. In this context, this work aims to simulate power generation scenarios of three Brazilian plants, each based on three distinct renewable sources: wind power, solar, and biomass. The methodology used is based on the modeling of historical time series by Markov Chains, and the generation of scenarios is performed by Monte Carlo simulation. The results obtained are promising: the simulated scenarios satisfactorily reproduced the characteristics of the historical generation data of the plants.

Natural gas and diesel currently are the main fuel for electrical power generation in Oman. Decreasing the dependence on national gas and diesel is one of the main goals for Oman’s vision of 2040. This paper discusses the optimum design of a hybrid stand-alone power generation system for the power station of Al-Mazyouna located west of Dhofar governorate using HOMER Pro Software. Real load data and solar radiation of Al-Mazyouna were utilized in the modelling approach. Different scenarios of power systems were investigated, using mainly, diesel generators, PV solar panels, and storage batteries to reach an optimal solution. The main factors that were considered to decide the wining setup of a power system are the net present cost, cost of energy and the amount of emissions. The optimum scenario resulted in a net present cost of $84.8 M and a cost of energy of $0.161/kWh compared to a net present cost of $99.4M and a cost of energy of $0.188/kWh for the current system. Additionally, the optimum scenario system limits toxic emissions significantly compared to the base system. The results of the winning scenario showed that the emitted quantities of harmful gases are all reduced by about 28% compared to the base system.

A not stable mechanical movement transmission between systems produces equilibrium losses, such as a rotor of motors that are coupled in rotating machines. This can be studied as a disturbance “vibration” either as characteristic of the movement transmission due to controlled displacement over rotors, which transmits the movement. Therefore, in this research is presented an analysis for an optimal control of the rotor axis displacement that includes “vibration” as the part of the movement transmission. It implies mathematical modelling and specific sensors selections to correlate the vibration in this control task. Furthermore, in order to verify the proposed analysis, it was simulated and tested in a hybrid magnetic bearing system.

Renewable energy sources are continually increasing their share in the energy system. The introduction of Hybrid Renewable Energy Sources (H.R.E.S.) in the electrical power system has gained momentum. The increased share of Renewable sources has resulted in an increase in Power Quality (P.Q.) disturbances at the user and consumer levels. This research will engineers dedicate the P.Q. disturbances produced in the electrical system due to Hybrid Renewable energy sources, especially solar and wind. The research will predict what type of P.Q. disturbances are introduced during power production. The study will focus on a stand-alone Hybrid Renewable Energy System (H.R.E.S.). The energy system data will be collected and used to produce a Fuzzy Logic (F.L.) algorithm to improve the mitigating techniques to reduce P.Q. disturbances. The suggested algorithm analyzes the stored and continuous data from different sources. The data will be collected and used to drive the hardware to take appropriate actions at the mitigation level. The hardware used in the system consists of a Multiplexer (MUX) and different types of filters. The output of the multiplexer chooses the filters. The algorithm will improve the system's efficiency and help the designers improve the system's design capabilities. The monitoring system will help predict what type of P.Q. disturbances are produced when different energy sources are used to produce power. The proposed system monitors these P.Q. disturbances and classifies them according to their severity.

The aim of this paper is to study the suitability of different floating offshore energy technologies in a particular location in economic terms. In this context, their main initial investments and expenses have been taken into account in order to calculate the economic indicators of the economic feasibility study. These indicators are Internal Rate of Return, Net Present Value and Levelized Cost Of Energy. The case study has evaluated the Canary Islands (Spain) and three types of floating offshore renewable energies: offshore wind, wave energy and hybrid systems. The method created generates economic maps, which facilitates the election of the best area where install offshore renewable energy farms in the location selected. In addition, it also allows to select what is the best marine technology to be exploited in this area.

The distributed generation (DG) allows electricity production to be closer to consumers, relieving the burden on distribution grid feeders. Interest in DG has increased in recent years due to its close relationship with smart grids and the development of carbon-free generation technologies. The Ciudad del Sol feeder in the city of Machala in Ecuador is one of the feeders with the highest electricity demand. This study evaluates the incorporation of DG in several consumers connected to this feeder. Depending on the range of energy consumption of each customer, different PV systems are proposed to meet their demands. The results of the study show that the installation of PV generation systems allows considerable savings on the electricity bill. In addition, the reduction of grid demand reduces Joule effect losses and improves voltage profiles. The results suggest that the massive incorporation of correctly dimensioned PV systems does not affect the operating conditions of a distribution power grid.

A PWM power conversion system connected to a grid through parallel-combined LCL filter is proposed in this paper. The system has four inverters paralleled and operates with PWM using 4-phase carrier for powering up and performance improvement. Four LCL filters have four separate filter inductors connected to individual inverters and one common LC filter which is composed of a filter capacitor and a grid inductor. The differential mode current circulates only through four inverters and four filter inductors. The differential mode current is completely eliminated from the filter capacitor and the connected power grid. Accordingly, performance improvement can be achieved since the current in the filter capacitor is reduced and the harmonic current into a grid is reduced. An 1.3kW single phase prototype system has been constructed and tested, and the proposed system has been verified.

In this work we introduce the concept and method of so-called cooperative solar generation forecasting, where geographically close data sources are utilized in order to improve forecasting accuracy. We devised and examined various largescale one-hour-ahead artificial neural networks based solar generation forecasting scenarios to prove the benefits of cooperation. The introduced cooperative solar generation forecasting method showed significant improvement in forecasting accuracy, especially when combined with previous generation data, where a root mean square error reduction of at least 50% could be achieved in the majority of cases. We believe these results point to a scientific and economical benefit of international cooperation in solar generation forecasting.

New control strategies based on Grid-Forming converters make possible the operation of isolated microgrids without the support of synchronous generation. This paper proposes an Energy Management System algorithm that optimizes the operation of a microgrid, maximizing the integration of renewable energy and considering the possibility of disconnecting all synchronous generators. The algorithm is applied to a microgrid modelled with real data and two economic dispatch strategies are analysed: the first requires keeping at least one synchronous generator connected to provide frequency regulation following standard practice; and the second considers the disconnection of all conventional generation relying on the capabilities of Grid-Forming converters when sufficient reserve is available. The results show that the proposed strategy reduces the operational cost of the system, as well as solar PV curtailment and diesel consumption.

The current energy model requires a transformation based on a sustainable model that is accessible to all, focused on the needs of citizens and committed to climate change. Moreover, the rising cost of non-renewable energy sources, and the growing presence of distributed renewable generation, has a major impact on the electricity sector, creating the need to develop mechanisms to help manage energy demand in order to converge towards an efficient, emission-free electricity system that is responsible for the environment and future generations. The main motivation is the recent change in the regulation of electricity tariff systems and the introduction of time discriminations in the residential sector. Based on the previous need and supported by a survey to find out society's predisposition and sensitivity to demand management, this paper presents the methodology developed as an active demand-side management mechanism for residential consumers, considering their load shifting priorities and prioritising the use of renewable energy if possible, reducing grid energy consumption. In a nutshell, the use of a tool capable of helping consumers to regulate their energy consumption, analyse their consumption pattern and plan their domestic loads to obtain the lowest energy and economic impact is developed. Key words. Active demand-side management, Load shedding, Energy optimisation, Renewable energy, Load prioritisation

Wave energy has much more potential and benefits than other forms of renewable energy. It is more predictable, consistent, and controllable than wind or solar energy. In this way, an adequate infrastructure can be an alternative and also sustainable system for power supply. In this paper, different wave energy conversion mechanisms (buoys, Pelamis, and oysters) have been described. These models are implemented and simulated using the Design Modeller, ANSYS-AQWA, and WEC-SIM applications. The purpose has been to develop a complete simulation of the wave energy converter and discuss its operation. The analysis has been developed in Matlab-Simulink and both regular and irregular waves have been considered. For this, an approximation to the linear waves theory has been used. The results obtained indicate the energy absorbed from the sea waves and also the energy supplied to the power grid. The simulation results estimated with the different WEC models are comparable to the results shown by other research papers.

. This paper aimed to develop a model to estimate the generation of electrical energy through human muscular effort, using a generator bicycle, connected to the electrical grid. The motivation resulted from the author's experience in distributed electrical energy generation, which identified a difficulty in installing photovoltaic solar generation systems on the top of buildings. As a research methodology, this study used multiple linear regression using time, weight, height, and body mass index (BMI) as independent variables. The model showed promising results, presenting a high adjusted R-squared, respecting the assumptions associated with a linear regression model. The simulations based on the model showed a considerable energy generation potential for Brazil. In conclusion, although the estimated regression model presented a high predictive capability, further studies are recommended before any financial investment.

The aim of this work is to describe the behavior of three-phase inverters connected to a faulty grid by means of a parametric approach which gives rise to limaçon of Pascal curves and 3D figures formed by the injected currents during the fault. The analytical study is given in the complex form of the transformed Park variables, and the simulation results are obtained by means of MATLABTM. The results show that the parametric analysis can be an easy and useful tool to predict the behavior of three-phase inverters operating under voltage sags, with the aim of achieving fault ride-through (FRT) capability.

The hemp flower has gained relevance in the agroindustrial and medical field worldwide due to the analgesic, antiinflammatory, and antiepileptic benefits that cannabidiol offers. A critical process in post-harvest is drying, as this allows to maintain the intrinsic properties of the flower. This operation requires a constant heat supply that involves high energy consumption. Therefore, a dryer was designed that uses a hybrid heat supply system based on solar thermal and electric energy. For this, a design of the chamber with a dome cover capable of taking advantage of solar radiation was made together with a system of collectors, supported by an electrical resist for periods of low irradiance. A theoretical analysis of the process was carried out considering the speed and temperature as study parameters and was validated by simulation and dynamic fluid modeling (CFD), obtaining that the thermal power to dry 120kg of the flower is 8.52kW, supplied by 4 solar collectors in series, the dome-type cover, and a tubular resistance of 2kW. The proposed design meets the requirements for maintaining a temperature of 50 ° C within the chamber during the drying time and a speed of 0.5m/s, which guarantees that the product is dehydrated without affecting its organoleptic properties and quality. Furthermore, the project will contribute as a benchmark for technological innovation in the use of renewable energy sources in Ecuador.

In recent years several efforts have being made in bringing smart network connectivity to the Renewable Energy Plant (REP) environment. On the other hand, REP is extending in scale from specialized points where the energy provider acts as a supplier to home REP (self-energy producers). This enables new important features such as: process automation, monitoring, control and optimizations. On the other hand, and in particular during and after the Covid19 pandemics the cybersecurity menace is a massive concern. The digital literacy of a worker of such an infrastructure is relevant to the correct implementation of adequate security policies. This article describes the threats and challenges on the field and conducts an enquire for perceiving the awareness of Automation and Mechanics Engineering students for this relevant problem, as future player in the field.