Microalgal biomass is a promising alternative and renewable substrate for bioenergy production. The main problem for its commercial application is to obtain and keep a high level of production by providing microalgae with appropriate conditions for growth. The aim of this study was to determine optimal culture conditions such as temperature, photoperiod, and pH. The amount of biomass by gravimetry, optical density by spectrophotometry, and productivity were analyzed. Suitable values of cultivation parameters allowed for the increased growth and biomass productivity of Arthrospira platensis (4.24 g·L−1), Chlamydomonas reinchardtii (1.19 g·L−1), Chlorella vulgaris (2.37 g·L−1), and Dunaliella salina (4.50 g·L−1) and optical density for Ch. reinchardtii and C. vulgaris. These species had maximum biomass productivity of 0.72, 0.12, 0.36, and 0.77 g·L−1·d−1, respectively. Productivity was determined by cultivation temperature and for Ch. reinchardtii also by pH.

Biomass gasification is a relevant option to produce a gaseous fuel, it faces, however, several barriers regarding its quality for energetic applications. Therefore, in this study, air-steam and O2-enriched air mixtures were used as gasification agents during the gasification of residual biomass from eucalyptus to improve the producer gas quality. The steam addition promoted an increase in CO2 and H2 concentrations, whilst decreasing the CO and CH4 concentrations. The steam addition had no evident impact on the lower heating value of the dry producer gas and a positive effect on gas yield and the H2:CO molar ratio, attaining the later values up to 1.6 molH2∙mol−1CO. The increase in O2 concentration in the gasification agent (φ) promoted an increase in all combustible species and CO2 concentrations. The lower heating value of the dry producer gas underwent an increase of 57%, reaching a value of 7.5 MJ∙Nm−3dry gas, when the φ increased from 20 to 40 %vol.O2, dry GA. The gas yield had a... [more]

Fibrous materials are often used in the manufacturing of fire protection devices such as fire curtains. Their optimization and improved performance is still a topic of interest. The present work aims to develop and test a new combination of fibers arranged in various 2D and 3D patterns with coatings. For this purpose, basalt fibers were added into a glass fiber fabric, and wires of a shape memory material (SMM) were inserted into the fabric to create air pockets induced by temperature. In fire curtains, the base structure is a 2D basket pattern, and all combinations were tested with and without a waterborne polyurethane (WPU) coating with inorganic materials. Three different tests were selected to characterize the thermal behavior: fire resistance, ignitability, and smoke production. Fiberglass proved to be the best material to provide thermal resistance in fire curtains, with the outer surface temperature of the fabric below 650 °C at the end of the tests. The SMM wires provided good... [more]

Given the fundamental role of renewable energy assets in achieving global temperature control targets, new energy management methods are required to efficiently match intermittent renewable generation and demand. Based on analysing various designed cases, this paper explores a number of heuristics for a smart battery scheduling algorithm that efficiently matches available power supply and demand. The core of improvement of the proposed smart battery scheduling algorithm is exploiting future knowledge, which can be realized by current state-of-the-art forecasting techniques, to effectively store and trade energy. The performance of the developed heuristic battery scheduling algorithm using forecast data of demands, generation, and energy prices is compared to a heuristic baseline algorithm, where decisions are made solely on the current state of the battery, demand, and generation. The battery scheduling algorithms are tested using real data from two large-scale smart energy trials in t... [more]

Electromobility is generally seen as an efficient means of decarbonizing the transport sector. Ensuring both a broad propagation of electric vehicles and a stable energy system requires intelligent charging strategies in the form of use cases. Most use cases do not combine both the prospect of profit and systemic advantages. This paper analyzes combinations of use cases that merge different use cases to combine profitability and systemic benefits. We present a novel methodological approach for analyzing and comparing the synergies of different use case combinations. The focus is on evaluating the potential for reducing the technical implementation effort resulting from the simultaneous implementation of two to three different use cases. Our findings show that the simultaneous implementation of complex use cases, often involving in-front-of-meter pooling of vehicles, produces the greatest synergies. Combinations that include ancillary services and spot market trading lead to considerabl... [more]

Earth−rock dams are typical soil−rock mixtures with high heterogeneity. Mastering the effect of dam heterogeneity on seismic wavefields is the premise of accurately detecting hidden risks in dams. In this paper, based on the soil−rock mixture characteristics of actual dams, a soil−rock mixture model that can reflect the heterogeneity of dams is established through local segmentation and reassignment of random disturbances. The influence of local area size on model heterogeneity is described. The seismic wavefield in a soil−rock mixture dam is numerically simulated through a staggered-grid finite-difference algorithm with second-order accuracy in time and sixth-order accuracy in space. Then, the effect of dam heterogeneity on effective wavefields is analyzed. The results show that the heterogeneity of the earth−rock dam can lead to scattered waves in the seismic wavefield, and the scattered waves are mainly generated by Rayleigh surface waves. In the seismic record, scattered waves with... [more]

Fossil fuels are associated with problems such as resource depletion and pollution, necessitating the exploration of alternatives. Giant miscanthus (Miscanthus × giganteus Greef et Deu), a perennial that can be harvested yearly, requires a low production energy input. It has less ash content and high heat efficiency and has attracted attention as an energy source. An on-site processing equipment, powered via a tractor and equipped with a chipper and a two-stage compression roller, was developed that can harvest 1000 kg of giant miscanthus per hour and simultaneously produce compressed pellets eliminating unnecessary processes such as transportation and processing. With its use, 33−74.5 kWh/t of electrical energy can be saved by producing pellets. The changes in moisture content between the produced compressed pellets and two samples of the ground product were measured immediately before compression for 24 h at relative humidity ranging from 65% to 80%. The moisture content was 6% initi... [more]

The use of solar photovoltaic (PV) generation and battery energy storage (BES) systems in commercial buildings has been increasing significantly in recent years. Most of these systems, however, are designed to solely minimize the investment and operation costs. With the increasing concerns about high-impact low-probability (HILP) events, such as natural disasters, and their impact on power system resilience, there is a substantial need to integrate outage risks in power system infrastructure planning problems. This paper examines the impact of various electricity rates on the feasibility of PV and BES systems in commercial buildings for financial and resilience purposes. Simulation studies are conducted using the Renewable Energy Integration & Optimization (REopt) decision support software to optimize the size of solar PV and BES systems for both financial and resilience purposes, considering different combinations of geographic locations, load profiles, electricity rates, and outage d... [more]

To reduce greenhouse gas emissions from natural gas use, utilities are investigating the potential of adding hydrogen to their distribution grids. This will reduce the carbon dioxide emissions from grid-connected engines used for stationary power generation, and it may also impact their power output and efficiency. Promisingly, hydrogen and natural gas mixtures have shown encouraging results regarding engine power output, pollutant emissions, and thermal efficiency in well-controlled on-road vehicle applications. This work investigates the effects of adding hydrogen to the natural gas fuel for a lean-burn spark-ignited four-stroke, 8.9 liter eight-cylinder naturally aspirated engine used in a commercial stationary power generation application via an engine model developed in the GT-SUITETM modelling environment. The model was validated for fuel consumption, air flow, and exhaust temperature at two operating modes. The focus of the work was to assess the sensitivity of the engine’s powe... [more]

Since P.O. Fanger proposed PMV, it has been the most widely used index to estimate thermal comfort. However, in some cases, it is challenging to measure all six parameters within indoor spaces, which are essential for PMV estimation; a couple of parameters, such as Clo or Met, tend to show a large deviation in accuracy. For these reasons, several studies have suggested methods to estimate PMV but their accuracies were significantly compromised. In this vein, this study proposed a way to reduce the dimensions of parameters for PMV prediction utilizing the machine learning method, in order to provide fast PMV calculations without compromising its prediction accuracy. Throughout this study, the most influential features for PMV were pinpointed using PCA, Best Subset, and the Gini Importance, with each model compared to the others. The results showed that PCA and ANN achieved the highest accuracy of 89.70%, and the combination of Best Subset and Random Forest showed the fastest prediction... [more]

The automotive sector has been experiencing a rapid development in recent times. Modern trends aim at the progress of so-called sustainable, eco-friendly vehicles, in many cases associated with advanced technologies and assistance systems. It is increasingly common to see cars with electric, hybrid, gas or hydrogen propulsion systems. Such approaches can create a transformation of manufacturing processes towards the growth of new types and fields of technologies and systems in the automotive industry. The manuscript discusses the subject of vehicles with various types of power supply, i.e., propulsion system. The investigation was executed with different respondent groups whereby the analysis was performed predominantly by using two merging criteria such as place of residence and gender of respondents. Following the research conducted, we state that given a variety of variables, the majority of the respondents are convinced that, prospectively, electric and hybrid vehicles in all proba... [more]

Outdoor air conditioning systems (ACS) are used as autonomic systems as well as in combined outdoor and indoor ACS of the variable refrigerant flow (VRF) type, with variable speed compressors (VSC) as their advanced version. Methods for determining the optimal value of refrigeration capacity and providing the maximum rate of the summarized annual refrigeration energy generation increment, according to its needs at minimum compressor sizes and rational values, are applied to reveal the reserves for reducing the designed (installed) refrigeration capacity, thus enabling us to practically achieve maximum annual refrigeration energy generation as the primary criterion at the second stage of the general design methodology previously developed by the authors. The principle of sharing the total thermal load on the ACS between the ranges of changeable loads for outdoor air precooling, and a relatively stable load range for further processing air are used as its basis. According to this princip... [more]

A chilled water system transports cooling functionality from refrigerators to users via heating, ventilation, and air conditioning (HVAC) systems. This paper investigated an optimal control strategy to regulate the volume flow rate of each user branch in a chilled water system, considering the minimum resistance operation to reduce energy consumption. An artificial neural network (ANN) was adopted to establish the nonlinear relationship between the volume flow rate of each user branch, pump frequency, and valve opening of each user branch. An optimal control strategy for a chilled water HVAC system is proposed in this article, according to the pump-valve combined control (PVCC) principle and an ANN model, i.e., pump-valve combined control using an artificial neural network model (PVCC-ANN). A series of tests were conducted to collect data to train the ANN model and analyze the performance of the PVCC-ANN in an experimental chilled water system. The results show that the trained ANN mod... [more]

This article presents the results of a study on metallurgical slag reduction using biomass such as Spent Coffee Grounds (SCGs). The proposed solution is a new aspect of searching for alternatives to standard reducers used in pyrometallurgical processes of metal production. Its gasification yields significant amounts of hydrocarbons, which are excellent reducing agents in such processes. The research results of copper slag reduction with the use of SCG biomass indicate this process is characterised by lower carbon dioxide emissions compared with the process using solid fuels such as coke and coke breeze. The addition of SCG as the reducer ensures the decrease in copper content in the slag to 0.32 wt.%, which corresponds to the increase of so-called relative decopperisation degree even up to 96.9%. As the decopperisation degree of slag increases, significantly more intense reduction in lead oxides during the reduction process is observed. The smallest lead content in waste slag of 0.91 w... [more]

During the trial production of marine gas hydrate in the former Soviet Union, Canada, North Slope of Alaska, South Sea Trough of Japan and Shenhu Sea of South China Sea, the problem of sand and water production cannot be avoided. The problems of sand production and water production in the process of natural gas hydrate depressurization exploitation have seriously restricted the exploitation efficiency and production of natural gas hydrate. The problems of sand production and water production are some of the main factors that prevent natural gas hydrate being commercially exploited. Therefore, it is urgent to carry out useful, relevant and cutting-edge research on the efficient drainage of sand and water from the wellbore in the process of natural gas hydrate mining. This paper innovatively proposes liquid-carrying and solid-carrying technology under foam circulation purging to address the existing problems of sand removal and drainage technology in hydrate mining. At present, no schola... [more]

Aiming at the influence of wind power and load uncertainty on the transient stability of a power system under low carbon mode, this paper first proposes a collaborative preventive and emergency control model of transient stability by distribution preserving graph representation learning (DPG). Second, the uncertainty set of wind power output and load demand is studied, and the mathematical form of the two-stage robust transient stability collaborative control model is proposed. Then, the latest artificial intelligence technology is embedded into the global optimization algorithm of the model so as to further improve the solving efficiency of the algorithm. Finally, based on the developed improved two-stage robust optimization framework, an effective collaborative control method for transient stability is developed. The transient stability prediction and control system developed in this project is not only conducive to large-scale wind power grid connection but also expected to make aca... [more]

Oxygen lances are key equipment for copper converters. The effect of the lance arrangement on the mixing of a gas−slag two−phase is discussed using numerical simulation and experimental verification with a water model, and the stirring characteristics enhanced by variable−velocity blowing are explored. The results showed that the single−row lance arrangement (SA) increased the average velocity in the slag phase by 17.93% and reduced the disturbance to the metal phase by 27.78% compared to the double−row lance arrangement (DA). Compared to the constant−velocity blowing system (CSB), the sine−wave blowing system (SWB) and rectangular−wave blowing system (RWB) increased the average velocity in the slag phase by 24.03% and 13.96%, respectively, and reduced the proportion of the low−velocity area by more than 46.2%. The velocity imbalance in the SA local area enhances the mixing of the gas−slag two−phase. The variable−speed blowing improves the mass transfer and mixing effect.

Sustainable energy development requires environment-friendly energy-generating methods. Pricing system constraints influence the efficient use of energy resources. Real-Time Pricing (RTP) is theoretically superior to previous pricing systems for allowing demand response (DR) activities. The DR approach has been useful for correcting supply−demand imbalances as technology has evolved. There are several systems for determining and controlling the DR. However, most of these solutions are unable to control rising demand or forecast prices for future time slots. This research provides a Real-Time Pricing DR model for energy management based on deep learning, where the learning framework is trained on demand response and real-time pricing. The study data in this article were taken from the Australian Energy Market Operator (AEMO), and the learning framework was trained over 17 years of data to forecast the real future energy price and demand. To investigate the suggested deep learning-based... [more]

Due to stringent emission regulations, it is of practical significance to understand cycle-to-cycle variations in the combustion of fossil or renewable fuels to reach future emission regulations. The present study aims to conduct a parametric investigation to analyse the influence of the valve lift and different mass flows of an inlet valve of the test engine “Flex-OeCoS” on the flow structures. To gain a deeper understanding of the flow behaviour, an optical test bench for 2D Particle Image Velocimetry (PIV) and a Large Eddy Simulation (LES) are used. Turbulence phenomena are investigated using Proper Orthogonal Decomposition (POD) with a quadruple decomposition and the Reynolds stress transport equation. The results show good agreement between the PIV and LES. Moreover, the main flow structures are primarily affected by valve lift while being unaffected by mass flow variation. The turbulent kinetic energy within the flow field increases quadratically to the mass flow and to the decre... [more]

Shared energy storage systems (SESS) have been gradually developed and applied to distribution networks (DN). There are electrical connections between SESSs and multiple DN nodes; SESSs could significantly improve the power restoration potential and reduce the power interruption cost during fault periods. Currently, a major challenge exists in terms of how to consider both the efficiency of the operation and the reliability cost when formulating the SESS scheduling scheme. A SESS optimal scheduling method that considers the DN operation risk is proposed in this paper. First, a multi-objective day-ahead scheduling model for SESS is developed, where the user’s interruption cost is regarded as the reliability cost and it is the product of the occurrence probability of the expected accident and the loss of power outage. Then, an island partition model with SESS was established in order to accurately calculate the reliability cost. Via the maximum island partition and island optimal rectifi... [more]

The shape design of the Tubular Linear Synchronous Motor (TLSM) is a critical engineeri ng optimization problem which was handled as single- and multi-objective optimization frameworks. However, the different practical constraints for the TLSM design must be efficiently guaranteed. This paper proposes a developed multi-objective shape design of the TLSM to maximize the operating force and minimize the flux saturation. In this regard, a Multi-objective Grey Wolf Optimizer (MGWO) is developed, including an outside archive with a predetermined size that is integrated for storing and retrieving Pareto optimal solutions. Using this knowledge, the grey wolf social structure would then be established, and, in the multi-objective searching environments, grey wolf hunting behavior would then be replicated. The superiority and effectiveness of the developed MGWO is assessed in comparison to the Multi-objective Flower Pollination Algorithm (MFPA), Multi-objective Lichtenberg Algorithm (MOLA), and... [more]

A large part of the European building stock was built before implementing the recent energy and structural codes, resulting in buildings characterized by deficiencies in terms of comfort, energy savings and structural safety. The retrofitting and rehabilitation of the existing building stock need to be adequately performed, aiming to improve the seismic and energy performance simultaneously. The work summarized here is dedicated to defining priority scenarios for buildings’ retrofitting to improve the seismic safety and energy efficiency of the European Union (EU) building stock. First, the state of the EU building stock is analysed in terms of buildings’ age, types of structures, energy efficiency, energy consumption and energy poverty. Then, the EU climate demands are presented, namely the regions with higher temperature variations, i.e., heating or cooling degree days. The EU seismic risk is also presented and discussed in terms of average annual losses, average annual economic loss... [more]

A single sensible thermal storage system has the disadvantage of poor system efficiency, and a sensible-latent graded thermal storage system can effectively solve this problem. Moreover, the graded thermal storage system has the virtue of being adjustable, which can be adapted to many power generation systems. Therefore, this paper first analyzes the influence factors of the graded thermal storage system’s exergy and thermal efficiency. Subsequently, each factor’s significance was analyzed using the response surface method, and the prediction model for system exergy efficiency and cost was established using the support vector machine method. Finally, the second-generation nondominated sorting genetic algorithm (NSGA-II) was used to globally optimize the graded thermal storage system’s exergy efficiency and cost by Matlab software. As a result, the exergy efficiency was increased by 11.01%, and the cost was reduced by RMB 5.85 million. In general, the effect of multi-objective optimizat... [more]

Increasing access to power, enhancing clean cooking fuels, decreasing wasteful energy subsidies, and limiting fatal air pollution are just a few of the sustainable development goals that all revolve around energy (E). Energy-specific sustainable development objectives were a turning point in the global shift towards a more sustainable and just system. By understanding energy resources, markets, regulations, and scientific studies, the country can progress more quickly towards a sustainable economy (SE). Investment in renewable energy industries is hampered by institutional obstacles such as market-controlled procedures and inconsistent supporting policies. Power plant building is currently incompatible with existing transmission and distribution networks, posing significant risks to investors. Deep neural networks (DNN) are specifically investigated in this article for energy demand forecasting at the individual building level. Other relevant information is supplied into fully connecte... [more]

Widely employed in hydrate exploitation, the single well method is utilized to broaden the scope of hydrate decomposition. Optimizing the well structure and production strategy is necessary to enhance gas recovery efficiency. Complex wells represented by the multilateral wells have great application potential in hydrate mining. This study focused on the impact of multilateral well production methods on productivity, taking the Nankai Trough in Japan as the study area. The spatial distribution of physical parameters such as porosity, permeability, and hydrate saturation in the Nankai Trough has significant heterogeneity. For model accuracy, the Sklearn machine learning and Kriging interpolation methods were used to construct a three-dimensional heterogeneous geological model to describe the structure and physical property parameters in the study area of the hydrate reservoir. The numerical simulation model was solved using the TOUGH + Hydrate program and fitted with the measured data of... [more]