Weather conditions have significant impacts on the solar concentration processes of the heliostat fields in solar tower power plants. The cloud shadow movements may cause varying solar irradiance levels received by each heliostat. Hence, fixed aiming strategies may not be able to guarantee the solar concentrating performance. Dynamic aiming strategies are able to optimize the aiming strategy based on real-time shadowing conditions and short-term forecast, and, therefore, provide much more robust solar concentration performance compared to fixed strategies. In this work, a model predictive control approach for s heliostat field power regulatory aiming strategy was proposed to regulate the total concentrated solar flux on the central receiver. The model predictive control method obtains the aiming strategy, leveraging real-time and forecast shadowing conditions based on the solar concentration model of the heliostat field. The allowable flux density of the receiver and the aiming angle a... [more]

The impact of the stray inductances originated from interconnects in power electronics becomes crucial with the next generation of SiC devices. This paper shows that the existing layout of a railway inverter, operating with Si IGBTs already exhibits a dynamic current imbalance between paralleled modules. This will not allow using this geometry with SiC MOSFETs. A complete investigation of the electromagnetic origin of this issue has been performed. A generic circuit model has been proposed to establish a cabling rule to design a Gate Distribution Printed Circuit Board (PCB) in such a way that it compensates the power dissymmetry. An optimization strategy has been used to obtain a new geometry of this PCB, which has been validated with a time domain simulation.

Sensor nodes have been assigned a lot of tasks in a connected environment that is growing rapidly. The power supply remains a challenge that is not answered convincingly. Energy harvesting is an emerging solution that is being studied to integrate in low power applications such as internet of things (IoT) and wireless sensor networks (WSN). In this work an interface circuit for a novel fluttering wind energy harvester is presented. The system consists of a switching converter controlled by a low power microcontroller. Optimization techniques on the hardware and software level have been implemented, and a prototype is developed for testing. Experiments have been done with generated input signals resulting in up to 67% efficiency for a constant voltage input. Other experiments were conducted in a wind tunnel that showed a transient output that is compatible with the target applications.

This paper assesses the potential environmental effects of the optimization of the kitchen waste management in Opole. The separate collection of kitchen waste is improved by distribution of separate collection kits consisting of an in-home bin and 10 L biodegradable bags. The surplus of collected kitchen waste is diverted from treatment in a mechanical-biological pretreatment (MBP) along with the residual waste to anaerobic digestion (AD) with the biowaste. This has positive effects on European and Polish goals, ambitions, and targets, such as (i) increasing the level of renewables in the primary energy supply, (ii) decreasing the level of greenhouse gas (GHG) emissions, (iii) increasing the level of preparation for reuse and recycling of municipal waste. The environmental effects of 1 ton additionally separately collected and treated kitchen waste are determined by using life cycle assessment. It was shown that in all selected impact categories (global warming potential, marine eutrop... [more]

The world’s demand for electrical energy is increasing rapidly while the use of fossil fuels is getting limited more and more by energy policies and the need for reducing the impact of climate change. New sources of energy are required to fulfill the world’s demand for electricity and they are currently found in renewable sources of energy, especially in solar and wind power. Choosing the optimal PV nominal power minimizes the unnecessary surplus of electrical energy that is exported to the grid and thus is not making any impact on the grid more than necessary. Oversizing the PV system according to the Croatian net-metering model results in switching the calculation of the costs to the prosumer model which results in a decrease of the project’s net present value (NPV) and an increase in the payback period (PP). This paper focuses on formulating and solving the optimization problem for determining the optimal nominal power of a grid-connected PV system with a case study for Croatia usin... [more]

This work presents an optimization framework based on mixed-integer programming techniques for a smart home’s optimal energy management. In particular, through a cost-minimization objective function, the developed approach determines the optimal day-ahead energy scheduling of all load types that can be either inelastic or can take part in demand response programs and the charging/discharging programs of an electric vehicle and energy storage. The underlying energy system can also interact with the power grid, exchanging electricity through sales and purchases. The smart home’s energy system also incorporates renewable energy sources in the form of wind and solar power, which generate electrical energy that can be either directly consumed for the home’s requirements, directed to the batteries for charging needs (storage, electric vehicles), or sold back to the power grid for acquiring revenues. Three short-term forecasting processes are implemented for real-time prices, photovoltaics, a... [more]

Internet of Things (IoT) is a new concept in the information and communication technology studies which indicates that any creature (human, animal, or object) can send and receive data through communication networks, such as the internet or intranet platform. Wireless sensors have limited energy resources due to the use of batteries to supply energy, and since it is usually not possible to replace the batteries of these sensors. In addition, the lifespan of the wireless sensor network is limited and short. Therefore, reducing the energy consumption of sensors in IoT networks for increasing network lifespan is one of the fundamental challenges and issues in these networks. In this paper, a routing protocol is proposed and simulated based on an ant colony optimization algorithm’s performance. The clustering is performed with a routing method based on energy level criteria, collision reduction, distance from the cluster-head to the destination, and neighborhood energy in the proposed meth... [more]

The aim of this study was to optimize biomass and docosahexaenoic acid (DHA) production by Schizochytrium sp. grown on waste glycerol as an organic carbon source. Parameters having a significant effect on biomass and DHA yields were screened using the fractional Plackett−Burman design and the response surface methodology (RSM). Schizochytrium sp. growth was most significantly influenced by crude glycerin concentration in the growth medium (150 g/dm3), process temperature (27 °C), oxygen in the bioreactor (49.99% v/v), and the concentration of peptone as a source of nitrogen (9.99 g/dm3). The process parameter values identified as optimal for producing high DHA concentrations in the biomass were as follows: glycerin concentration 149.99 g/dm3, temperature 26 °C, oxygen concentration 30% (v/v), and peptone concentration 2.21 g/dm3. The dry cell weight (DCW) obtained under actual laboratory conditions was 66.69 ± 0.66 g/dm3, i.e., 1.27% lower than the predicted value. The DHA concentratio... [more]

This paper presents a methodology to maximize the self-sufficiency or cost-effectiveness of grid-connected prosumers by optimizing the sizes of photovoltaic (PV) systems and electrochemical batteries. In the optimal sizing procedure, a limitation on the maximum injection in the grid can affect the energy flows, the economic effectiveness of the investments, and thus the sizing results. After the explanation of the procedure, a case study is presented, and a parametric analysis of the effect of possible injection limits is shown. The procedure is applied to size plants for an Italian domestic prosumer, whose electric load profile was measured for a year. A software program developed using the proposed methodology is also briefly presented. It is used for both research and educational purposes, both in laboratory classes and in remote lessons.

This article presents a method to adjust the elements of a small wind power plant to the wind speed characterized by the highest annual level of energy. Tests were carried out on the basis of annual wind distributions at three locations. The standard range of wind speeds was reduced to that resulting from the annual wind speed distributions in these locations. The construction of the generators and the method of their excitation were adapted to the characteristics of the turbines. The results obtained for the designed power plants were compared with those obtained for a power plant with a commercial turbine adapted to a wind speed of 10 mps. The generator structure and control method were optimized using a genetic algorithm in the MATLAB program (Mathworks, Natick, MA, USA); magnetostatic calculations were carried out using the FEMM program; the simulations were conducted using a proprietary simulation program. The simulation results were verified by measurement for a switched reluctan... [more]

Buildings in hot climate areas are responsible for high energy consumption due to high cooling load requirements which lead to high greenhouse gas emissions. In order to curtail the stress on the national grid and reduce the atmospheric emissions, it is of prime importance that buildings produce their own onsite electrical energy using renewable energy resources. Photovoltaic (PV) technology is the most favorable option to produce onsite electricity in buildings. Installation of PV modules on the roof of the buildings in hot climate areas has a twofold advantage of acting as a shading device for the roof to reduce the cooling energy requirement of the building while producing electricity. A high ground coverage ratio provides more shading, but it decreases the efficiency of the PV system because of self-shading of the PV modules. The aim of this paper was to determine the optimal value of the ground coverage ratio which gives maximum overall performance of the roof-mounted PV system by... [more]

Aalto New Campus Complex (ANCC) is a recently inaugurated educational facility at Aalto University, located in Otaniemi (Espoo), Finland. Within over 40,000 m2, it comprises two faculties, a shopping center, recreational areas, and a metro station. ANCC is also a large-scale application of Ground Source Heat Pump (GSHP)−Borehole Thermal Energy Storage (BTES) in Finland, comprising an irregular BTES field of 74 boreholes with an overall length of roughly 23 km and 4 million m3 of energy storage. Therefore, accurate monitoring of the GSHP−BTES energy system is crucial for sustainable and efficient long-term operation. Due to the fundamental issues affecting the accuracy of all thermal energy meters, a novel methodology adjusting for consistency of the measured data (in order to accomplish daily energy balance on both sides of the GSHP) is developed. The proposed methodology is used also in conjunction with reconstruction of missing relevant data before April/May 2020 by applying linear r... [more]

Effectively transporting drilled cuttings to the surface is a vital part of the well construction process. Usually, mechanistic models are used to estimate the cuttings concentration during drilling. Based on the results from these model, operational parameters are adjusted to mitigate any nonproductive time events such as pack-off or lost circulation. However, these models do not capture the underlying complex physics completely and frequently require updating the input parameters, which is usually performed manually. To address this, in this study, a data-driven modeling approach is taken and evaluated together with widely used mechanistic models. Artificial neural networks are selected after several trials. The experimental data collected at The University of Tulsa−Drilling Research Projects (in the last 40 years) are used to train and validate the model, which includes a wide range of wellbore and pipe sizes, inclinations, rate-of-penetration values, pipe rotation speeds, flow rate... [more]

This paper presents a comprehensive study of peak-to-peak and root-mean-square (RMS) values of AC current ripples with balanced and unbalanced fundamental currents in a generic case of three-phase four-leg converters with uncoupled AC interface inductors present in all three phases and in neutral. The AC current ripple characteristics were determined for both phase and neutral currents, considering the sinusoidal pulse-width modulation (SPWM) method. The derived expressions are simple, effective, and ready for accurate AC current ripple calculations in three- or four-leg converters. This is particularly handy in the converter design process, since there is no need for heavy numerical simulations to determine an optimal set of design parameters, such as switching frequency and line inductances, based on the grid code or load restrictions in terms of AC current ripple. Particular attention has been paid to the performance comparison between the conventional three-phase three-leg converte... [more]

Electronic devices usually operate in a variable loading condition and the power transfer efficiency of the accompanying wireless power transfer (WPT) method should be optimizable to a variable load. In this paper, a reconfigurable WPT technique is introduced to maximize power transfer efficiency in a weakly coupled, variable load wireless power transfer application. A series-series two-coil wireless power network with resonators at a frequency of 150 kHz is presented and, under a variable loading condition, a shunt capacitor element is added to compensate for a maximum efficiency state. The series capacitance element of the secondary resonator is tuned to form a resonance at 150 kHz for maximum power transfer. All the capacitive elements for the secondary resonators are equipped with reconfigurability. Regardless of the load resistance, this proposed approach is able to achieve maximum efficiency with constant power delivery and the power present at the load is only dependent on the i... [more]

An efficient cooling system for data centers can boost the working efficiency of servers and promote energy savings. In this study, a laboratory experiment and computational fluid dynamics (CFD) simulation were performed to explore the performance of a two-phase cooling system. The coefficient of performance (COP) and partial power usage effectiveness (pPUE) of the proposed system was evaluated under various IT (Information Technology) loads. The relationship between the interval of the two submerged servers and their surface temperatures was evaluated by CFD analysis, and the minimum intervals that could maintain the temperature of the server surfaces below 85 °C were obtained. Experimental results show that as server power increases, COP increases pPUE decreases. In one experiment, the COP increased from 19.0 to 26.7, whereas pPUE decreased from 1.053 to 1.037. The exergy efficiency of this system ranges from 12.65% to 18.96%, and the tank side accounts for most of the exergy destruc... [more]

This paper presents Nyström minimum kernel risk-sensitive loss (NysMKRSL) based control of a three-phase four-wire grid-tied dual-stage PV-hybrid energy storage system, under varying conditions such as irradiation variation, unbalanced load, and abnormal grid voltage. The Voltage Source Converter (VSC) control enables the system to perform multifunctional operations such as reactive power compensation, load balancing, power balancing, and harmonics elimination while maintaining Unity Power Factor (UPF). The proposed VSC control delivers more accurate weights with fewer oscillations, hence reducing overall losses and providing better stability to the system. The seamless control with the Hybrid Energy Storage System (HESS) facilitates the system’s grid-tied and isolated operation. The HESS includes the battery, fuel cell, and ultra-capacitor to accomplish the peak shaving, managing the disturbances of sudden and prolonged nature occurring due to load unbalancing and abnormal grid voltag... [more]

Quality of power supply in power distribution systems requires continuous measurement using power quality analyzers installed in the grid. The paper reviews the published methods for optimal location of metering points in distribution systems in the context of power quality metering and assessment. Three methods have been selected for detailed analysis and comparative tests. It has been found that utilization of the methods is possible, but their performance varies highly depending on the test grid’s topology. Since the methods rely on the state estimation approach, their performance is strictly related to observability analysis. It has been found that standard observability analysis used for typical state estimation problem yields ambiguous results when applied to power quality assessment. Inherited properties of the selected methods are also analyzed, which allows for the formulation of general recommendations about optimal selection of metering points in a distribution system.

The paper proposes a solution for the problem of optimizing medium voltage power systems which supply, among others, nonlinear loads. It is focused on decision tree (DT) application for the sizing and allocation of active power filters (APFs), which are the most effective means of power quality improvement. Propositions of some DT strategies followed by the results have been described in the paper. On the basis of an example of a medium-voltage network, an analysis of the selection of the number and allocation of active power filters was carried out in terms of minimizing losses and costs keeping under control voltage total harmonic distortion (THD) coefficients in the network nodes. The presented example shows that decision trees allow for the selection of the optimal solution, depending on assumed limitations, expected effects, and costs.

The microbial enhanced oil recovery (MEOR) method is an eco-friendly and economical alternative technology. The technology involves a variety of uncertainties, and its success depends on controlling microbial growth and metabolism. Though a few numerical studies have been carried out to reduce the uncertainties, no attempt has been made to consider temperature, pressure, and salinity in an integrated manner. In this study, a new modeling method incorporating these environmental impacts was proposed, and MEOR analysis was performed. As a result, accurate modeling was possible to prevent overestimating the performance of MEOR. In addition, oil recovery was maximized through sensitivity analysis and optimization based on an integrative model. Finally, applying MEOR to an actual reservoir model showed a 7% increase in oil recovery compared to waterflooding. This result proved the practical applicability of the method.

Buildings are responsible for over 30% of global final energy consumption and nearly 40% of total CO2 emissions. Thus, rapid penetration of renewable energy technologies (RETs) in this sector is required. Integration of renewable energy sources (RESs) into residential buildings should not only guarantee an overall neutral energy balance over long term horizon (nZEB concept), but also provide a higher flexibility, a real-time monitoring and a real time interaction with end-users (smart-building concept). Thus, increasing interest is being given to the concepts of Hybrid Renewable Energy Systems (HRES) and Multi-Energy Buildings, in which several renewable and nonrenewable energy systems, the energy networks and the energy demand optimally interact with each other at various levels, exploring all possible interactions between systems and vectors (electricity, heat, cooling, fuels, transport) without them being treated separately. In this context, the present paper gives an overview of fu... [more]

The scientific community is active in developing new models and methods to help reach the ambitious target set by UN SDGs7: universal access to electricity by 2030. Efficient planning of distribution networks is a complex and multivariate task, which is usually split into multiple subproblems to reduce the number of variables. The present work addresses the problem of optimal secondary substation siting, by means of different clustering techniques. In contrast with the majority of approaches found in the literature, which are devoted to the planning of MV grids in already electrified urban areas, this work focuses on greenfield planning in rural areas. K-means algorithm, hierarchical agglomerative clustering, and a method based on optimal weighted tree partitioning are adapted to the problem and run on two real case studies, with different population densities. The algorithms are compared in terms of different indicators useful to assess the feasibility of the solutions found. The algo... [more]

In this work, the aerodynamic performance and optimization of a vertical-axis wind turbine with a high tip-speed ratio are theoretically studied on the basis of the two-dimensional airfoil theory. By dividing the rotating plane of the airfoil into the upwind and downwind areas, the relationship among the angle of attack, azimuth, pitch angle, and tip-speed ratio is derived using the quasi-steady aerodynamic model, and aerodynamic loads on the airfoil are then obtained. By applying the polynomial approximation to functions of lift and drag coefficients with the angle of attack for symmetric and asymmetric airfoils, respectively, explicit expressions of aerodynamic loads as functions of the angle of attack are obtained. The performance of a fixed-pitch blade is studied by employing a NACA0012 model, and influences of the tip speed ratio, pitch angle, chord length, rotor radius, incoming wind speed and rotational speed on the performance of the blade are discussed. Furthermore, the optimi... [more]

With a rapid increase in the awareness of carbon reduction worldwide, the industry of electric vehicles (EVs) has started to flourish. However, the large number of EVs connected to a power grid with a large power demand and uncertainty may result in significant challenges for a power system. In this study, the optimal charging and discharging scheduling strategies of G2V/V2G and battery energy storage system (BESS) were proposed for EV charging stations. A distributed computation architecture was employed to streamline the complexity of an optimization problem. By considering EV charging/discharging conversion efficiencies for different load conditions, the proposed method was used to maximize the operational profits of each EV and BESS based on the related electricity tariff and demand response programs. Moreover, the behavior model of drivers and cost of BESS degradation caused by charging and discharging cycles were considered to improve the overall practical applicability. An EV ch... [more]

The method for preliminary powertrain design is presented in the paper. Performance of the EV is realized by motor torque−speed curve and gear ratio optimization. The typical two-zone mechanical characteristic of a PMSM traction motor is included in the optimization program. The longitudinal vehicle model is considered in the paper. Some examples try to show the calculation possibilities in application to existing vehicles: Tesla Model S and Mini Cooper SE.