Global optimization of industrial plant configurations using organic Rankine cycles (ORC) to recover heat is becoming attractive nowadays. This kind of optimization requires structural and parametric decisions to be made; the number of variables is usually high, and some of them generate disruptive responses. Surrogate models can be developed to replace the main components of the complex models reducing the computational requirements. This paper aims to create, evaluate, and compare surrogates built to replace a complex thermodynamic-economic code used to indicate the specific cost (US$/kWe) and efficiency of optimized ORCs. The ORCs are optimized under different heat sources conditions in respect to their operational state, configuration, working fluid and thermal fluid, aiming at a minimal specific cost. The costs of 1449.05, 1045.24, and 638.80 US$/kWe and energy efficiencies of 11.1%, 10.9%, and 10.4% were found for 100, 1000, and 50,000 kWt of heat transfer rate at average tempera... [more]

This paper is a research article for finding the optimal control of smart power substations for improving the network parameters and reliability. The included papers are the most essential and main studies in the field, which propose a different approach to reach the best performance in electrical power systems. The parameters for improvement are the ability for tracking of the reference signal, stabilizing the system, reducing the error in steady state and controlling the behavior in transient state. The research focuses with the reaching a better transient stability considering voltage and frequency dynamic parameters. The optimal model for the control is focused on minimizing energy consumption but maintaining the controllable parameters, exploring some optimization techniques to find the optimal control, with of aim of minimizing the response time, the energy consumption, and maximizing the reliability by means of improving the controller to be more robust.

Optimization of the sizing and operation strategy of a complex energy system requires a large computational burden because of the non-linear nature of the mathematical problem. Accordingly, using a conventional numerical method with only a physics-based model for complete optimization is impractical. To resolve this problem, this paper adopted an optimization method of using an artificial intelligence scheme that combines an artificial neural network (ANN) and a genetic algorithm (GA). Especially, the ANN was constructed based on results from a physics-based model to obtain a large amount of accurate simulation data in a short time frame. A distributed generation (DG) system based on a gas turbine (GT) and renewable energy (RE) was simulated to demonstrate the usefulness of the optimization method. In consideration of the capacity and partial load performance of the GT, the optimization of the sizing and operation strategy of the DG system was performed for three system design scenario... [more]

This article presents studies related to the driving and control of the switched reluctance generator in order to enhance its efficiency. This type of electrical machine is an option for wind energy conversion systems, favoring the generation of electricity in distributed generation systems and contributing positively to loads without access to the main grid. The studies developed in this paper verify the possibility of controlling the output voltage of the switched reluctance generator in parallel with an efficiency tracking technique acting on the switching angles of the power converter. Simulation and experimental results are presented in order to verify the feasibility of implementing this technique to enhance the efficiency of the generator.

This paper presents an open architecture for a sensor platform for the processing, collection, and image reconstruction from measurement data. This paper focuses on ultrasound tomography in block-wise-transform-reduction image reconstruction. The advantage of the presented solution, which is part of the project “Next-generation industrial tomography platform for process diagnostics and control”, is the ability to analyze spatial data and process it quickly. The developed solution includes industrial tomography, big data, smart sensors, computational intelligence algorithms, and cloud computing. Along with the measurement platform, we validate the methods that incorporate image compression into the reconstruction process, speeding up computation and simplifying the regularisation of solving the inverse tomography problem. The algorithm is based on discrete transformation. This method uses compression on each block of the image separately. According to the experiments, this solution is m... [more]

(1) Background: considering multiple, and somehow conflicting, design objectives can potentially make achieving a high-performance design a complex task to perform. For instance, shading devices can dramatically affect the building performance in various ways, such as energy consumption and daylight. This paper introduces a novel procedure for designing shading devices as an integral part of daylightophil architecture for office buildings by considering daylight and energy performance as objectives to be optimal. (2) Methods: to address the topic, a three-step research method was used. Firstly, three different window shades (fixed and dynamic) were modeled, one of which was inspired by traditional Iranian structures, as the main options for evaluation. Secondly, each option was evaluated for energy performance and daylight-related variables in critical days throughout the year in terms of climatic conditions and daylight situations (equinoxes and solstices including 20 March, 21 June,... [more]

In the power and heat sectors, the uncertainty of energy and carbon prices plays a decisive role in the rationale for decommissioning/repurposing coal-fired CHP (combined heat and power) systems and on investment decisions of energy storage units. Therefore, there is a growing need for advanced methods that incorporate the stochastic disturbances of energy and carbon emission prices into the optimization process of an energy system. In this context, this paper proposes an integrated method for investigating the effects of uncertain energy and carbon prices on the operational patterns and financial results of CHP systems with thermal energy storage units. The approach combines mathematical programming and Monte Carlo simulation. The computational process generates feasible solutions for profit maximization considering the technical constraints of the CHP system and the variation of energy and carbon emission prices. Four scenarios are established to compare the operational patterns and... [more]

Due to the growing demand for new ecological, low-emission heat sources, there is a need to develop new tools for simulating the operating parameters and costs of the implemented solutions. The article analyses the existing solutions for the simulation of heat pump operation parameters, describes the requirements for a modern building—nZEB and proposes a simulation tool based on thermodynamic parameters of the refrigerant. The script allows for deriving simple linear equations that can be used for the overall simulation of a system in which the heat pump is a key part and the efficiency of the entire system depends on its performance. The developed numerical script allows for reproducing the Linde refrigeration cycle and the parameters of its characteristic points. To calibrate the simulation, historical data obtained from the SOPSAR system were used. These data were pre-cleaned (peaks and other obvious measurement errors were removed). The obtained numerical model in combination with... [more]

Multi-microgrids have gained interest in academics and industry in recent years. Multi-microgrid (MG) allows the integration of different distributed energy resources (DERs), including intermittent renewables and controllable local generators, and provides a more flexible, reliable, and efficient power grid. This research formulates and proposes a solution for finding optimal location and operation of mobile energy storage (MES) in multi-MG power distribution systems (PDS) with different resources during extreme events to maximize system resiliency. For this purpose, a multi-stage event-based system resiliency index is defined and the impact of the Internet of things (IoT) application in MES operation in multi-MG systems is investigated. Moreover, the demand and price uncertainty impact on multi-MG operational performance indices is presented. This research uses a popular PG & E 69-bus multi-MG power distribution network for simulation and case studies. A new hybrid PSO-TS optimization... [more]

This article presents approximating relations defining energy-optimal structures of the HVAC (Heating, Ventilation, Air Conditioning) system for cleanrooms as a function of key constant parameters and energy-optimal control algorithms for various options of heat recovery and external climates. The annual unit primary energy demand of the HVAC system for thermodynamic air treatment was adopted as the objective function. Research was performed for wide representative variability ranges of key constant parameters: cleanliness class—Cs (ISO5÷ISO8), unit cooling loads—q˙j (100 ÷ 500) W/m2 and percentage of outdoor air—αo (5 ÷ 100)%. HVAC systems are described with vectors x¯ with coordinates defined by constant parameters and decision variables, and the results are presented in the form of approximating functions illustrating zones of energy-optimal structures of the HVAC system x¯* = f (Cs, q˙j, αo). In the optimization procedure, the type of heat recovery as an element of optimal structur... [more]

The displacement and eventual replacement of fossil-derived fuel gases with biomass-derived alternatives can help the energy sector to achieve net zero by 2050. Decarboxylation of butyric acid, which can be obtained from biomass, can produce high yields of propane, a component of liquefied petroleum gases. The use of different gaseous reaction atmospheres of nitrogen, hydrogen, and compressed air during the catalytic hydrothermal conversion of butyric acid to propane have been investigated in a batch reactor within a temperature range of 200−350 °C. The experimental results were statistically evaluated to find the optimum conditions to produce propane via decarboxylation while minimizing other potential side reactions. The results revealed that nitrogen gas was the most appropriate atmosphere to control propane production under the test conditions between 250 °C and 300 °C, during which the highest hydrocarbon selectivity for propane of up to 97% was achieved. Below this temperature ra... [more]

In this work, a 3D computational model based on computational fluid dynamics (CFD) is built to simulate the aerodynamic behavior of a Savonius-type vertical axis wind turbine with a semi-elliptical profile. This computational model is used to evaluate the performance of the wind turbine in terms of its power coefficient (Cp). Subsequently, a full factorial design of experiments (DOE) is defined to obtain a representative sample of the search space on the geometry of the wind turbine. A dataset is built on the performance of each geometry proposed in the DOE. This process is carried out in an automated way through a scheme of integrated computational platforms. Later, a surrogate model of the wind turbine is fitted to estimate its performance using machine learning algorithms. Finally, a process of optimization of the geometry of the wind turbine is carried out employing metaheuristic optimization algorithms to maximize its Cp; the final optimized designs are evaluated using the computa... [more]

The present work performed a comprehensive investigation to find the effects of a dual-bleeding port recirculation channel on the aerodynamic performance of a single-stage transonic axial compressor, NASA Stage 37, and optimized the channel’s configuration to enhance the operating stability of the compressor. The compressor’s performance was examined using three parameters: The stall margin, adiabatic efficiency, and pressure ratio. Steady-state three-dimensional Reynolds-averaged Navier−Stokes analyses were performed to find the flow field and aerodynamic performance. The results showed that the addition of a bleeding channel increased the recirculation channel’s stabilizing effect compared to the single-bleeding channel. Three design variables were selected for optimization through a parametric study, which was carried out to examine the influences of six geometric parameters on the channel’s effectiveness. Surrogate-based design optimization was performed using the particle swarm op... [more]

The main aim of the paper was to develop an innovative approach to the preliminary estimation possibility of train energy cooperation based on data from timetables, without traction calculations. The article points out the need to strive for sustainable and environmentally friendly transport. It was pointed out that rail transport using electric traction is one of the more ecological branches of transport. It also offers a number of possibilities for improving energy efficiency and reducing energy consumption, one of which is the recovery and reuse of energy lost in the electrodynamic braking process. The main ways in which such energy can be used are listed, but the focus is mainly on the aspect of the so-called “energy cooperation” of trains. Then, the current state of the research and knowledge on the narrowed scope of rail traffic management and recuperative braking in rail transportation is presented; an innovative approach to the indirect optimization of the amount of recuperated... [more]

Since the automotive industry is shifting towards electrification, brake-by-wire technologies are becoming more prevalent. However, there has been little research comparing and optimizing brake-by-wire actuators in terms of their energy expenditure and response time. This paper investigates the comparison of three different smart brake-by-wire actuators, Electro-Hydraulic Brakes (EHB), Electro-Mechanical Brakes (EMB), and Electronic Wedge Brakes (EWB), first by defining an objective metric and then using both linear and nonlinear optimization techniques. Modeling of the actuators is performed using the bond graph method. Then, the controllers are designed using a robust control strategy, Youla parameterization. After designing the controllers, two types of optimization are performed on the actuators. Optimizations are performed in two ways: 1. by linearizing the plants and optimizing using their transfer functions and 2. by nonlinear optimization of the plants in the closed-loop follow... [more]

Europe stated the ambitious target of becoming carbon neutral by 2050 to combat climate change and meet the requirements imposed by the Paris Agreement, and renewable energy has proved to be a promising solution for the decarbonization of many sectors. Nonetheless, their aleatory nature leads to grid unbalances due to the difference between supply and demand. Storage solutions are needed, and electrofuels become a key factor in this context: they are fuels produced from electricity, which leads to carbon-neutral fuels if it originates from renewable sources. These can constitute a key solution to store the surplus energy and to decarbonize the so-called hard-to-abate sectors. Electrofuel production technologies have not yet been fully developed, and, in this context, extensive study of the state-of-the-art of existing projects can be very useful for researchers and developers. This work researches the European projects funded by the Horizon 2020 Programme regarding electrofuel producti... [more]

Nowadays, learning-based modeling methods are utilized to build a precise forecast model for renewable power sources. Computational Intelligence (CI) techniques have been recognized as effective methods in generating and optimizing renewable tools. The complexity of this variety of energy depends on its coverage of large sizes of data and parameters, which have to be investigated thoroughly. This paper covered the most resent and important researchers in the domain of renewable problems using the learning-based methods. Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. The performance of the given methods in the literature is assessed by a new taxonomy. This paper focus on conducting comprehensive state-of-the-art methods heading to performance evaluation of the given techniques and discusses vital difficulties and possibilities for extensive research. Based on the results, variations in efficiency, robustness... [more]

Fast charging is an attractive way of charging batteries; however, it may result in an undesired degradation of battery performance and lifetime because of the increase in battery temperature during fast charge. In this paper we propose a simple optimized fuzzy controller that is responsible for the regulation of the charging current of a battery charging system. The basis of the method is a simple dynamic equivalent circuit type model of the Li-ion battery that takes into account the temperature dependency of the model parameters, too. Since there is a tradeoff between the charging speed determined by the value of the charging current and the increase in temperature of the battery, the proposed fuzzy controller is applied for controlling the charging current as a function of the temperature. The controller is optimized using a genetic algorithm to ensure a jointly minimal charging time and battery temperature increase during the charging. The control method is adaptive in the sense th... [more]

Automation and electrification are changing vehicles and mobility. Whereas electrification is mainly changing the powertrain, automation enables the rethinking of the vehicle and its applications. The actual driving range is an important requirement for the design of automated and electric vehicles, especially if they are part of a fleet. To size the battery accordingly, not only the consumption of the powertrain has to be estimated, but also that of the auxiliary users. Heating Ventilation and Air Conditioning (HVAC) is one of the biggest auxiliary consumers. Thus, a variable HVAC model for vehicles with electric powertrain was developed to estimate the consumption depending on vehicle size and weather scenario. After integrating the model into a tool for autonomous and electric vehicle concept development, various vehicle concepts were simulated in different weather scenarios and driving cycles with the HVAC consumption considered for battery sizing. The results indicate that the bat... [more]

Energy consumption in residential, commercial and industrial buildings is one of the major contributors to global warming. Due to the increase in the latter, and growing global energy crisis, more attention is being paid to renewable energy resources (RES). The use of innovative concepts in existing buildings is gaining popularity to provide reduction in energy requirements for electricity, heating and cooling. In this paper, an electricity, heating and cooling cooperation mechanism among neighboring buildings with RES is proposed. It relies on adjusting the RES tariff with a mutual agreement between the neighboring buildings, with an aim to minimize the operational costs. For this purpose, a mathematical model is developed for joint energy cooperation, where surplus energy in one of the buildings is shared with others, thereby reducing dependency on the grid. The optimization structure of the environment friendly energy cooperation is nonlinear, which is linearized using the McCormick... [more]

The progressive use of renewable energy sources to ensure a continuous and abundant energy supply is the significant target towards a sustainable and secure energy system. Previously, the countries that had relied on fossil fuel as a dominating energy source are now endorsing energy system transition towards renewable energy sources. In this study, a comparative assessment of the energy problems of South Asian countries is summarized. Nevertheless, there are many similarities and differences in the electricity supply system of these countries. Long-term planning for renewable energy development is suggested for a diverse population and dispersed geographical location considering all the significant challenges. However, appropriate schemes are imperative for integrating significant renewable energy sources. This study introduces a foresight plan of the electricity model according to the demand and supply balance for extensive technical analysis. The EnergyPLAN modeling tool was employed... [more]

Nowadays, energy policymakers are asked to develop strategies to ensure an affordable clean energy supply as well as minimizing investment risks. In addition, the rise of several community engagement schemes and the uptake of user-scale technologies introduce uncertainties that may result in a disruptive factor for energy systems evolution. This paper introduces a novel scenario analysis approach for local energy planning that supports policymakers and investors in prioritizing new renewable power plant investments, addressing the risks deriving from citizens’ choices. Specifically, a combined analysis is performed on the adoption trends of distributed photovoltaic systems and electric vehicles that are expected to heavily influence the evolution of energy systems. For this reason, an energy model is developed for Pantelleria island, and its transition from an oil-based energy supply to a renewable one up to 2050 is investigated. It is demonstrated how optimal-cost renewable-based scen... [more]

The microgrid has two main steady-state modes: grid-connected mode and islanded mode. The microgrid needs a high-performance controller to reduce the overshoot value that affects the efficiency of the network. However, the high voltage value causes the inverter to stop. Thus, an improved power-sharing response to the transfer between these two modes must be insured. More important points to study in a microgrid are the current sharing and power (active or reactive) sharing, besides the match percentage of power sharing among parallel inverters and the overshoot of both active and reactive power. This article aims to optimize the power response in addition to voltage and frequency stability, in order to make this network’s performance more robust against external disturbance. This can be achieved through a self-tuning control method using an optimization algorithm. Here, the optimized droop control is provided by the H-infinity (H∞) method improved with the artificial bee colony algorit... [more]

In the present study, the laminar flow and heat transfer of water jet impingement enhanced with nano-encapsulated phase change material (NEPCM) slurry on a hot plate is analytically investigated for the first time. A similarity solution approach is applied to momentum and energy equations in order to determine the flow velocity and heat transfer fields. The effect of different physical parameters such as jet velocity, Reynolds number, jet inlet temperature, and the NEPCM concentration on the cooling performance of the impinging jet are investigated. The volume fraction of NEPCM particles plays an essential role in the flow and heat transfer fields. The results show that NEPCM slurry can significantly enhance the cooling performance of the system as it improves the latent heat storage capacity of the liquid jet. However, the maximum cooling performance of the system is achieved under an optimum NEPCM concentration (15%). A further increase in NEPCM volume fraction has an unfavorable eff... [more]

In this work, a design optimization study was conducted to improve the performance of a membraneless microfluidic fuel cell with a double-bridge cross-section of the flow channel. Governing equations including Navier−Stokes, mass-transport, and Butler−Volmer equations were solved numerically to analyze the electrochemical phenomena and evaluate the performance of the fuel cells. Optimization was performed to maximize the peak power density using a genetic algorithm combined with a surrogate model constructed by radial basis neural network. Two sub-channel widths of the flow channel were selected as design variables for the optimization. As a result, a large increase in the inner channel width and a small decrease in the outer channel width effectively increased the peak power density of the MMFC. The optimal design increased the peak power density by 57.6% compared to the reference design.