bluuebunny/crossref_metadata_2025 huggingface dataset:
Weather Forecast Based on Color Cloud Image Recognition under the Combination of Local Image Descriptor and Histogram Selection
Authors: Tran-Trung Kiet , Duong Thi Hong Ha , Truong Hoang Vinh
Published: October 2022

Numerous researchers have used machine vision in recent years to identify and categorize clouds according to their volume, shape, thickness, height, and coverage. Due to the significant variations in illumination, climate, and distortion that frequently characterize cloud images as a type of naturally striated structure, the Local Binary Patterns (LBP) descriptor and its variants have been proposed as feature extraction methods for characterizing natural texture images. Rotation invariance, low processing complexity, and resistance to monotonous brightness variations are characteristics of LBP. The disadvantage of LBP is that it produces binary data that are extremely noise-sensitive and it struggles on regions of the image that are “flat” because it depends on intensity differences. This paper considers the Local Ternary Patterns (LTP) feature to overcome the drawbacks of the LBP feature. We also propose the fusion of color characteristics, LBP features, and LTP features for the classification of cloud/sky images. Morover, this study proposes to apply the Intra-Class Similarity (ICS) technique, a histogram selection approach, with the goal of minimizing the number of histograms for characterizing images. The proposed approach achieves better performance of recognition with less features in use by fusing LBP and LTP features and using the ICS technique to choose potential histograms.
A Novel Multistrategy-Based Differential Evolution Algorithm and Its Application
Authors: Wang Jinyin , Shang Shifan , Jing Huanyu , Zhu Jiahui , Song Yingjie , Li Yuangang , Deng Wu
Published: October 2022

To address the poor searchability, population diversity, and slow convergence speed of the differential evolution (DE) algorithm in solving capacitated vehicle routing problems (CVRP), a new multistrategy-based differential evolution algorithm with the saving mileage algorithm, sequential encoding, and gravitational search algorithm, namely SEGDE, is proposed to solve CVRP in this paper. Firstly, an optimization model of CVRP with the shortest total vehicle routing is established. Then, the saving mileage algorithm is employed to initialize the population of the DE to improve the initial solution quality and the search efficiency. The sequential encoding approach is used to adjust the differential mutation strategy to legalize the current solution and ensure its effectiveness. Finally, the gravitational search algorithm is applied to calculate the gravitational relationship between points to effectively adjust the evolutionary search direction and further improve the search efficiency. Four CVRPs are selected to verify the effectiveness of the proposed SEGDE algorithm. The experimental results show that the proposed SEGDE algorithm can effectively solve the CVRPs and obtain the ideal vehicle routing. It adopts better search speed, global optimization ability, routing length, and stability.
A 0.00426 mm2 77.6-dB Dynamic Range VCO-Based CTDSM for Multi-Channel Neural Recording
Authors: Wang Shiwei , Yang Xiaolin , Wang Chaohan , Vilouras Anastasios , Lopez Carolina Mora
Published: October 2022

Driven by needs in neuroscientific research, future neural interface technologies demand integrated circuits that can record a large number of channels of neural signals in parallel while maintaining a miniaturized physical form factor. Using conventional methods, it is challenging to reduce circuit area while maintaining the high dynamic range, low noise, and low power consumption required in the neural application. This paper proposes to address this challenge using a VCO-based continuous-time delta-sigma modulator (CTDSM) circuit, which can record and digitize neural signals directly without the need for front-end instrumentation amplifiers and anti-aliasing filters, which are limited by the abovementioned circuit-area performance tradeoff. Thanks to the multi-level quantization and intrinsic mismatch-shaping capabilities of the VCO-based approach, the proposed first-order CTDSM can achieve comparable electrical performance to a higher-order CTDSM while offering further area and power reductions. We prototyped the circuit in a 22-channel test chip and demonstrate, based on the chip measurement results, that the proposed modulator occupies an area of 0.00426 mm2 while achieving input-referred noise levels of 6.26 and 3.54 µVrms in the action potential (AP) and local field potential (LFP) bands, respectively. With a 77.6 dB wide-dynamic range, the noise and total harmonic distortion meet the requirements of a neural interface with up to 149 mVpp input AC amplitude or up to ±68 mV DC offsets. We also validated the feasibility of the circuit for multi-channel recording applications by examining the impact of cross-channel VCO oscillation interferences on the circuit noise performance. The experimental results demonstrate the proposed architecture is an excellent candidate to implement future multi-channel neural-recording interfaces.
EBR: Routing Protocol to Detect Blackhole Attacks in Mobile Ad Hoc Networks
Authors: Kancharakuntla Deepika , El-Ocla Hosam
Published: October 2022

The presence of malevolent nodes in mobile ad hoc networks (MANETs) would lead to genuine security concerns. These nodes may disturb the routing process or deform the pattern of the data packets passing through the network. The MANET is extremely liable to attacks, owing to its characteristics of the network framework, such as the absence of infrastructure, moveable topology, and a centralized control unit. One of the most common attacks in MANETs is the blackhole attack. MANET nodes are susceptible to spectacular degradation of network performance in the presence of such attacks. In this regard, detecting or preventing deceitful nodes that will launch blackhole attacks is a challenge in MANETs. In this paper, we propose an Enhanced Blackhole Resistance (EBR) protocol to identify and resist nodes that are responsible for blackhole attacks. EBR can avoid congested traffic by passing the data packets through a safe route with the minimum RTT. The EBR protocol uses a combination of time to live (TTL) and round trip time (RTT), which is also called a TR mechanism, to detect the blackhole attacks. Our algorithm does not require any cryptographic or authentication mechanisms. Simulation results prove that EBR behaves better than other protocols in terms of throughput, end-to-end delay, packet delivery ratio, energy, and routing overhead.
Performance of Cooperative Relay NOMA with Large Antenna Transmitters
Authors: Tweneboah-Koduah Samuel , Affum Emmanuel Ampoma , Agyemang-Prempeh Agyekum Kwame , Ajagbe Sunday Adeola , Adigun Matthew O.
Published: October 2022

The potential of the Non-Orthogonal Multiple Access (NOMA) approach for wireless communications in the fifth generation (5G) and beyond can not be underestimated. This is because users with favorable channel conditions can serve as relays to improve system performance by employing Successive Interference Cancellation (SIC). Lately, the combination of NOMA and the cooperative relay has attracted the interest of researchers. The analysis of cooperative relay NOMA (CR-NOMA) with a massive multiple-input multiple-output (mMIMO) system is mainly based on theoretical channel models such as the correlated-based stochastic channel model (CBSM) even though the geometric-based stochastic channel model (GBSM) has been found to provide better, practical and realistic channel properties. This, in our view, is due to computational challenges. Again, the performance of CR-NOMA systems using the GBSM channel model with large antenna transmitters and network coding schemes has attracted little attention in academia. Therefore, the need to study mMIMO CR-NOMA that considers channel properties such as path-loss, delay profile and tilt angle has become vital. Furthermore, the co-existing of large antenna transmitters with coding schemes needs further investigation. In this paper, we study the performance of a two-stage mMIMO CR-NOMA network where the transmitter is represented as a uniform rectangular array (URA) or cylindrical array (CA). The communication channel from the transmitter (TX) to the user equipment (UE) through a relay station (RS) is modeled with a 3GPP’s three-dimensional (3D) GBSM mMIMO channel model. To improve the analytical tractability of 3D GBSM, we defined the antenna element location vectors using the physical dimension of the antenna array and incorporated them into the 3D channel model. Bit-error rates, achievable rates and outage probabilities (OP) are examined using amplify-and-forward (AF) and decode-and-forward (DF) coding schemes. Results obtained show with fixed power allocation and SNR of 20 dB, far or weak users can attain a high achievable rate using DF and URA. Again, from the results, the combination of AF and CA presents better outage probabilities. Finally, the results indicate that the performance difference between CBSM and GBSM is marginal, even though the proposed 3D GBSM channel model has a higher degree of random parameters and computational complexities.
Study on Heat and Mass Transfer Performance during Heating, Pressurization and Expansion Stage in Explosion Puffing at Low Temperature and High-Pressure
Authors: Ruan Shijie , Su Lei , Ou Haoyu , Lin Wei , Jiang Shuiquan , Sun Fang
Published: October 2022

China is a large agricultural country that is leading worldwide in the annual number of agricultural products and exports. However, the growth and harvest of fruits and vegetables are greatly affected by geographical conditions, climate and other factors, which will lead to their rotting in peak season and shortages in the off-season. Therefore, it is necessary to vigorously promote the development of drying technology. The explosion puffing technology at low temperature and high pressure is a kind of compound drying technology which can enable the puffed product to obtain the advantages of honeycomb, good rehydration, a short running time, etc. With the guidance of the theory of heat and mass transfer and relevant thermodynamics laws, this study has established high-pressure extruding technology in low-temperature heating; expanded the two-phase theoretical model, using mass conservation and the law of the conservation of energy to analyze the coupled heat and mass transfer process and influencing factors; and researched the influence of the operation temperature, pressure and time on the properties of dried fruit.
Parametric Investigation on the Electrical-Thermal Performance of Battery Modules with a Pumped Two-Phase Cooling System
Authors: Wang Jun , Ruan Lin , Li Ruiwei
Published: October 2022

The pumped two-phase cooling method is a practical way to dissipate heat from the battery module. The operating parameters of the cooling system should be investigated thoroughly to improve the performance of the battery thermal management system (BTMS). However, the previous BTMS designs only explored the thermal performance and ignored the electrical performance in the battery module. This study designed a pumped two-phase cooling BTMS with the refrigerant of R1233zd. An electrothermal coupled model was established for a series-connected battery module to predict thermal and electrical behavior. The results showed that the pumped two-phase cooling system could obtain excellent cooling performance with low system pressure under 2C discharging condition. The average temperature of the module and the temperature difference among cells could be maintained under 40 °C and 5 K under a 2C discharging rate. A lower saturation temperature, higher mass flux, and higher subcooling degree could enhance heat dissipation for the cooling system based on R1233zd. An increase in the saturation temperature and a decrease in the subcooling degree could enhance the temperature uniformity within the module. The battery consistency was mainly dominated by the temperature difference and deteriorated with a lower average temperature in the pack. The research outcome of this paper can guide the design and optimization of the pumped two-phase cooling BTMS.
A Divide and Conquer Strategy for Sweeping Coverage Path Planning
Authors: Vasquez Juan Irving , Merchán-Cruz Emmanuel Alejandro
Published: October 2022

One of the main challenges faced by floor treatment service robots is to compute optimal paths that completely cover a set of target areas. Short paths are of noticeable importance because their length is directly proportional to the energy used by the robot. Such a problem is known to be NP-hard; therefore, efficient algorithms are needed. In particular, computation efficiency is important for mobile robots with limited onboard computation capability. The general problem is known as coverage path planning (CPP). The CPP has several variants for single regions and for disjoint regions. In this research, we are investigating the solutions for disjoint target regions (rooms) that have fixed connection points (doors). In particular, we have found effective simplifications for the cases of rooms with one and two doors, while the challenging case of an unbounded number of rooms can be solved by approximation. As a result, this work presents a divide and conquer strategy (DnCS) to address the problem of finding a path for a sweeping robot that needs to sweep a set of disjoint rooms that are connected by fixed doors and corridors. The strategy divides the problem into computing the sweeping paths for the target rooms and then merges those paths into one solution by optimising the room visiting order. In this strategy, a geometrical approach for room coverage and an undirected rural postman problem optimisation are strategically combined to solve the coverage of the entire area of interest. The strategy has been tested in several synthetic maps and a real scenario showing short computation times and complete coverage.
Analysis of the Thermal Processes in an Electromagnetic Mill
Authors: Całus Dariusz
Published: October 2022

The purpose of this research is to develop effective methods for the thermal calculation of an electromagnetic mill. The article deals with the structural features of the liquid cooling system of such a device, with direct channel cooling of the induction coils. By analysing the recent research in this area, I have revealed that in order to achieve this goal it is expedient to use the finite element method (FEM). I have also suggested the input data for the boundary values to calculate a three-dimensional thermal field of an electromagnetic mill with an internal diameter of the working chamber of 200 mm. I have also graphically shown the results of calculating this problem using FEM analysis. Based on the analysis of the temperature field and gradient, I have also synthesized and substantiated the structure of the thermal equivalent circuit, which approximates the active part of the mill with a complex of five bodies with internal heat release and enables an approximate estimation of its thermal state at the initial stages of design to be held. I have suggested the formulae to calculate the parameters of this equivalent circuit and the principle to form a system of equations for the further determination of unknown temperatures. In addition, I have performed a comparative analysis of the methods for calculating the thermal state.
Strategic Planning and Management in Energy
Authors: Karaszewski Robert
Published: October 2022

The proposal for this Special Issue of Energies, devoted to Strategic Planning and Management in Energy, was developed at the end of 2021 [...]
Geomechanical and Petrophysical Assessment of the Lower Turonian Tight Carbonates, Southeastern Constantine Basin, Algeria: Implications for Unconventional Reservoir Development and Fracture Reactivation Potential
Authors: Baouche Rafik , Sen Souvik , Radwan Ahmed E.
Published: October 2022

In this study, we assessed the unconventional reservoir characteristics of the Lower Turonian carbonates from the southeastern Constantine Basin. We integrated petrography, petrophysical, and rock-mechanical assessments to infer formation properties and unconventional reservoir development strategies. The studied fossiliferous argillaceous limestones are rich in planktonic foraminifera, deposited in a calm and low energy depositional condition, i.e., deep marine basinal environment. Routine core analysis exhibits very poor porosity (mostly < 5%) and permeability (<0.1 mD), implying the dominance of nano and microporosity. Micritization and calcite cementation are inferred as the major reservoir quality-destroying diagenetic factors. Based on the wireline log-based elastic properties, the upper part of the studied interval exhibits higher brittleness (BI > 0.48) and fracability (FI > 0.5) indices compared to the lower interval. Borehole breakouts indicate ~N-S SHmax orientation and a normal to strike-slip transitional stress state has been constrained based on a geomechanical assessment. We analyzed safe wellbore trajectory and minimum mud weight requirements to ensure stability in the deviated and horizontal wells required for field development. At the present stress state, none of the fracture orientations are critically stressed. We inferred the fracture reactivation potential during hydraulic stimulation required to bring the tight Turonian limestones into production. Additional pore pressure build-up required to reactivate optimally oriented natural fractures has also been inferred to ensure success of hydraulic fracturing.
Heat Pump Installation in Public Buildings: Savings and Environmental Benefits in Underserved Rural Areas
Authors: Gradziuk Piotr , Siudek Aleksandra , Klepacka Anna M. , Florkowski Wojciech J. , Trocewicz Anna , Skorokhod Iryna
Published: October 2022

Heat pump technology offers a path towards reducing the use of fossil fuels to heat space, providing energy bill savings and reducing air pollution and GHG emissions. The choice of heating method is based on costs; hence, this study examines the gains from operating heat pump systems in public buildings as well as alternative systems using electricity, LPG, and heating oil. The study focuses on the Ruda-Huta municipality in Poland that, as is common in rural areas, lacks access to a district heating system or piped gas. The empirical analysis includes heat pump installations in eight municipal buildings. The study found that the use of ground source heat pumps proved competitive with existing heating systems in terms of payback time. Calculations for three heating energy source scenarios, i.e., electricity, LPG, and heating oil, used the Simple Pay Back Time (SPBT) and the Levelized Cost of Heat (LCOH) methods and the average prices of the three energy types for the period 2012–2021. The payback period calculations disregarded the EU subsidies for heating systems utilizing renewable energy sources (RES). The payback time for electric, LPG, and heating oil were, respectively, 6.7–7.8 years, 4.1–6.1 years, and 6.7–6.9 years. Much larger spreads favoring heat pumps were calculated using the LCOH, and the costs in the case of electric heating were nearly three times higher and doubled when using heating oil and LPG. The gains from investing in heat pump systems have been offset by the increase in electricity, LPH, and heating oil prices, which have been predicted to continue to increase in the foreseeable future supporting the use of heat pumps in rural areas lacking access to, for example, district heating systems. The switch to heat pumps reduced local air pollution by eliminating the burning of fossil fuels to heat space in public buildings.
Energy M&A Market in the Baltic States Analyzed through the Lens of Sustainable Development
Authors: Andriuškevičius Karolis , Štreimikienė Dalia
Published: October 2022

Mergers and acquisitions (M&A) may serve as a catalyst in energy transition by accelerating this trend and “greenwashing” the deals. M&A are often used by large energy companies as a tool to explore potential synergy benefits. Recently, M&A strategies in the energy industry have been pursued to transform traditional business models into more “sustainable” models. On the one hand, it may be observed that companies are taking a proactive rather than reactive approach towards environmental-, social-, and governance (ESG)-related M&A deals. On the other hand, sustainable M&A deals do not interest activist shareholders and regulatory authorities only anymore. Inclusion of a sustainability framework and managing ESG-related risks have become part of the overall strategy of most companies within the energy industry. This research addresses the problem of how energy M&A are contributing to sustainable development on the one hand and reflecting sustainable developments on the other hand. The current research focuses on the systematic literature on the M&A deals in the energy industry through the lens of sustainability by applying the SALSA methodology. Further, we applied a SWOT analysis of M&A in the energy industry from the perspective of sustainable development. Thomson Reuters DataStream 5.1 database was used for developing a case study. A sample of Lithuanian, Latvian, and Estonian energy companies that were involved as acquirers or targets in the M&A events from 1995 to 2020 was developed. Establishing a methodological approach construed of SALSA, SWOT, and case study analyses allowed us to bridge a gap in the existing literature and provoke further discussion in regards to market developments through the lens of sustainable development. The research results showed that there are relatively few M&A of renewable companies as the M&A market is dominated by traditional energy companies within Baltic states. However, companies in the Baltic states are pursuing energy security, have set targets for emission reductions, renewables and energy efficiency, are supporting EU climate neutrality, and put great emphasis on climate change mitigation.
An Econometric Model of the Operation of the Steel Industry in POLAND in the Context of Process Heat and Energy Consumption
Authors: Gajdzik Bożena , Wolniak Radosław , Grebski Wieslaw Wes
Published: October 2022

The analyses presented in the publication allowed, on the basis of the data collected, development of an econometric model for the Polish steel industry from the point of view of the relationship between heat and energy management in the steel production process. The developed model is the main novelty of the paper. The main objective of the study was to develop an econometric model of Poland’s heat and energy economy. The following research questions were raised: Is there an econometric model describing heat consumption (intensity) in the steel industry in Poland in relation to steel production and the energy economy? What are the relations between heat intensity and energy prices and steel production in Poland? How might the current energy crisis affect steel production? In the analysis we used data of energy and heat management in the Polish steel industry. An econometric model was developed of the dependence of heat consumption (Yt) on electricity prices (X1t) and steel production (X2t) in Poland. The authors took advantage of open access to data. Annual volumes of heat consumption in steel production processes in Poland were analysed as a function of the annual volume of steel production and the prices of electricity, which are consumed in technological processes in steel mills. We analyzed data for years 2004–2020. The analyses carried out showed that there is an inversely proportional relationship between electricity prices and the intensity of heat consumption by the steel industry. Research shows that rising energy prices lead to lower steel production. This is a dangerous phenomenon for the steel industry in the context of the current energy crisis caused by the pandemic and war in Ukraine. We think that the significance of our results is connected with the fact that the developed model is a useful analytical tool, as it not only allows the analysis of historical data, but can also be used to predict how steel industry parameters will change in the future under the influence of changes in external factors, such as energy prices. This gives a wide range of analytical possibilities for the use of the model.
Ship Energy Efficiency and Maritime Sector Initiatives to Reduce Carbon Emissions
Authors: Issa Mohamad , Ilinca Adrian , Martini Fahed
Published: October 2022

With stricter IMO regulations on CO2 taking effect in 2023 and ambitious goals to reduce carbon intensity by 2030, the maritime industry is scrambling to clean up its act. Conventional methods and equipment are now being reevaluated, upgraded or completely replaced. The difference between a short-term fix and a long-term sustainable option is how flexible vessels will be to use new energy sources or technology as they become viable. The review discusses the recent literature on renewable energy sources, technical and operational strategies for new and existing ships, technology maturity, and alternative fuels. It is found that the IMO’s targets can be met by combining two or three technologies, or via a radical technology shift which can provide innovative, high-efficiency solutions from an environmental and economic standpoint. It has also been noted that policies and enforcement are essential management instruments for mitigating the unfavourable environmental effects of marine transportation and directing the maritime industry toward sustainability on a regional, national, and international scale.
Production Concepts for Inductive Power Transfer Systems for Vehicles
Authors: Kuehl Alexander , Kneidl Maximilian , Seefried Johannes , Masuch Michael , Weigelt Michael , Franke Joerg
Published: October 2022

The option of wireless energy transmission in electric vehicles can become the main market driver for electric vehicles due to its distinct advantages, such as range, weight, or costs, over conventional conductive charging solutions. In addition to the great potential, which different research work and realized systems have already shown, there are new requirements for the associated production networks in the automotive industry which must be addressed at an early stage. Furthermore, no solutions currently exist for the industrial production of these components. This paper presents the main components for the feasibility of wireless power transmission in electric vehicles. In addition, the required value chains and processes for the new components of the inductive power transfer systems, and the final assembly for induction coils, which has been developed at the FAU, will be presented. These include the developing of a winding process on a 15-axis special machine, ultrasonic crimping of the litz wire ends, and vacuum potting.
Waste Heat Recovery in a Compression Ignition Engine for Marine Application Using a Rankine Cycle Operating with an Innovative Organic Working Fluid
Authors: Mariani Antonio , Morrone Biagio , Laiso Davide , Prati Maria Vittoria , Unich Andrea
Published: October 2022

The exhaust heat of energy conversion systems can be usefully recovered by Organic Rankine Cycles (ORC) instead of wasting it into the environment, with benefits in terms of system efficiency and environmental impact. Rankine cycle technology, consolidated in stationary power plants, has not yet spread out into transport applications due to the layout limitations and to the necessity of containing the size and weight of the ORC system. The authors investigated an ORC system bottoming a compression ignition engine for marine application. The exhaust mass flow rate and temperature, measured at different engine loads, have been used as inputs for modeling the ORC plant in a Simulink environment. An energy and exergy analysis of the ORC was performed, as well as the evaluation of the ORC power at different engine loads. Two different working fluids were considered: R1233zd(e), an innovative fluid belonging to the class of hydrofluoroolefin, still in development but interesting due to its low flammability, health hazard, and environmental impact, and R601, a hydrocarbon showing a benchmark thermodynamic performance but highly flammable, considered as a reference for comparison. Three plant configurations were investigated: single-pressure, dual-pressure, and reheating. The results demonstrated that the dual-pressure configuration achieves the highest exploitation of exhaust heat. R1233zd(e) produced an additional mechanical power of 8.0% with respect to the engine power output, while, for R601, the relative contribution of the ORC power was 8.7%.
Influence of Temperature and Residence Time on Torrefaction Coupled to Fast Pyrolysis for Valorizing Agricultural Waste
Authors: Alcazar-Ruiz Angel , Dorado Fernando , Sanchez-Silva Luz
Published: October 2022

Torrefaction is a promising pretreatment technology for valorizing biomass and upgrading pyrolysis products. This study sets out an original procedure consisting of subjecting the biomass to torrefaction before fast pyrolysis to increased value-added compounds based on agricultural waste biomasses production. This study uses a combined biomass treatment consisting of torrefaction (280–320 °C) and subsequent fast pyrolysis (500 °C) using the same reactor. Under different torrefaction temperatures and residence times, olive pomace (OP) and almond shell (AS) have been evaluated. The study demonstrated OP rather than AS was thermally unstable. The highest total yield of carboxylic acids (mainly acetic acid) was obtained by means of torrefaction at 280 °C with a residence time of 20 s for OP, and at 300 °C and 20 s for AS. Higher torrefaction temperature and residence time promoted phenolic compounds production for OP. However, OP had a higher lignin content and inherent metals that promoted a catalytic reaction during the procedure. The highest yield (47.7%) was obtained using torrefaction at 320 °C with a residence time of 240 s. Overall, the torrefaction of biomass combined with fast pyrolysis constituted a very simple and efficient strategy for valorizing the conversion of agricultural waste biomass into value-added chemicals.
Improving Pumped Hydro Storage Flexibility in China: Scenarios for Advanced Solutions Adoption and Policy Recommendations
Authors: Nibbi Leonardo , Sospiro Paolo , De Lucia Maurizio , Wu Cheng-Cheng
Published: October 2022

The decarbonisation targets of the People’s Republic of China are ambitious. Their achievement relies on the large-scale deployment of variable renewable energy sources (VRES), such as wind and solar. High penetration of VRES may lead to balancing problems on the grid, which can be compensated by increasing the shifting flexibility capacity of the system by integration with energy storage, e.g., by installing additional electricity storage. Pumped Hydro Storage (PHS) is the most diffused electricity storage technology at the global level and the only fully mature solution for long-term electricity storage. China already has the highest PHS capacity installed worldwide and plans to increase it strongly before 2030. The present study, based on the data from the “Pumped Storage Tracking Tool” of the International Hydropower Association, investigates the potential for technological improvement of the existing and future PHS fleet in China. The aims of adopting advanced PHS solutions allow China to better cope with the task of balancing the VRES production. The potential for adopting advanced PHS solutions is evaluated through five different intervention possibilities (here referred to as scenarios). These scenarios consider revamping part of the operational Pumped Storage Plant (PSP) fleet and redesigning future installations that are already planned. As a result, considering all the major technical and authorisation process constraints, 4.0% (5.2 GW) of the 132 GW fleet expected to be commissioned before 2035 could additionally adopt advanced PHS in a high-potential scenario. Meanwhile in the medium and low potential scenarios, the quota can reach 11.1% (14.6 GW) and 26.2% (34.5 GW), respectively. Furthermore, policy recommendations are elaborated to promote, facilitate, and support the adoption of these advanced PHS solutions.
Exact Feedback Linearization of a Multi-Variable Controller for a Bi-Directional DC-DC Converter as Interface of an Energy Storage System
Authors: Broday Gabriel R. , Lopes Luiz A. C. , Damm Gilney
Published: October 2022

DC microgrids have shown to be a good approach for better accommodating stochastic renewable energy sources (RES) and for the charging of electric vehicles (EVs) at the distribution level. For this, fast-acting energy storage units (ESSs) are essential. This requires that both the bi-directional power converter topology and the control scheme present the right set of features. The ESS discussed in this paper consists of a new DC-DC converter based on a tapped inductor (TI) for a higher voltage gain at moderate duty cycles. The direction of the current in its intermediate inductor does not need to be reversed for power flow reversal, leading to a faster action. Moreover, it can employ a multi-state and multi-variable modulation scheme that eliminates the right half-plane (RHP) zero, common in boost-type converters. In order to achieve good dynamic performance across a wide range of operating points, a control scheme based on feedback linearization is developed. This paper presents the modeling of the five-switch DC-DC converter operating in the tri-state buck–boost mode. A systematic approach for deriving control laws for the TI current and output voltage based on exact state feedback linearization is discussed. The performance of the proposed control scheme is verified by simulation for a supercapacitor (SC)-based ESS. It is compared to that of a conventional control scheme for a dual-state buck–boost mode with cascaded PI controllers designed based on small-signal models. The results show that both control schemes work similarly well at the operating point that the conventional control scheme was designed for. However, only the proposed scheme allows the SC-based ESS to control the current injected into the DC microgrid with the voltage of the SC varying between the expected range of rated to half-rated.
Novel Cloud-Edge Collaborative Detection Technique for Detecting Defects in PV Components, Based on Transfer Learning
Authors: Wang Hongxi , Li Fei , Mo Wenhao , Tao Peng , Shen Hongtao , Wu Yidi , Zhang Yushuai , Deng Fangming
Published: October 2022

The existing techniques for detecting defects in photovoltaic (PV) components have some drawbacks, such as few samples, low detection accuracy, and poor real-time performance. This paper presents a cloud-edge collaborative technique for detecting the defects in PV components, based on transfer learning. The proposed cloud model is based on the YOLO v3-tiny algorithm. To increase the detection effect of small targets, we produced a third prediction layer by fusing the shallow feature information with the stitching layer in the second detection scale and introducing a residual module to achieve improvement of the YOLO v3-tiny algorithm. In order to further increase the ability of the network model to extract target features, the residual module was introduced in the YOLO v3-tiny backbone network to increase network depth and learning ability. Finally, through the model’s transfer learning and edge collaboration, the adaptability of the defect-detection algorithm to personalized applications and real-time defect detection was enhanced. The experimental results showed that the average accuracy and recall rates of the improved YOLO v3-tiny for detecting defects in PV components were 95.5% and 93.7%, respectively. The time-consumption of single panoramic image detection is 6.3 ms, whereas the consumption of the model’s memory is 64 MB. After cloud-edge learning migration, the training time for a local sample model was improved by 66%, and the accuracy reached 99.78%.
The Initial Boiling Point of Lubricating Oil as an Indicator for the Assessment of the Possible Contamination of Lubricating Oil with Diesel Oil
Authors: Chybowski Leszek
Published: October 2022

This article provides a brief introduction to the indicators of the volatility and flammability of lubricating oils and fuels. It is proposed that the initial boiling point be used as an indicator of the contamination of lubricating oil with distillate fuel (i.e., diesel biofuel oil) in the context of the rapid detection of explosion risks in the crankcase. Detailed tests were carried out on lubricating oil samples (SAE 30 and SAE 40 grades, which are most commonly used in the lubrication systems of marine trunk engines) diluted with diesel oil at selected mass concentrations (0, 1, 2, 5, 10, 20, 50, and 100%). The oils were tested to determine their relevant properties: the flash point temperature and the initial boiling temperature. The flash point was determined in a closed crucible using the Pensky–Martens method, which is in accordance with PN-EN ISO 2719. The differences between the initial boiling point and the flash point of the tested lubricating oils were determined for different dilution levels of lubricating oil in diesel fuel. An approximate method for the calculation of the flash point of the oil based on the initial boiling point is proposed. The results of oil flash point measurements are compared with values calculated as a function of the boiling point for both lubricating oils tested. An evaluation of how well models fit the experimental results is reported. Conclusions are presented on the applicability of the proposed method during operational practice.
Optimized Data-Driven Models for Short-Term Electricity Price Forecasting Based on Signal Decomposition and Clustering Techniques
Authors: Arvanitidis Athanasios Ioannis , Bargiotas Dimitrios , Kontogiannis Dimitrios , Fevgas Athanasios , Alamaniotis Miltiadis
Published: October 2022

In recent decades, the traditional monopolistic energy exchange market has been replaced by deregulated, competitive marketplaces in which electricity may be purchased and sold at market prices like any other commodity. As a result, the deregulation of the electricity industry has produced a demand for wholesale organized marketplaces. Price predictions, which are primarily meant to establish the market clearing price, have become a significant factor to an energy company’s decision making and strategic development. Recently, the fast development of deep learning algorithms, as well as the deployment of front-end metaheuristic optimization approaches, have resulted in the efficient development of enhanced prediction models that are used for electricity price forecasting. In this paper, the development of six highly accurate, robust and optimized data-driven forecasting models in conjunction with an optimized Variational Mode Decomposition method and the K-Means clustering algorithm for short-term electricity price forecasting is proposed. In this work, we also establish an Inverted and Discrete Particle Swarm Optimization approach that is implemented for the optimization of the Variational Mode Decomposition method. The prediction of the day-ahead electricity prices is based on historical weather and price data of the deregulated Greek electricity market. The resulting forecasting outcomes are thoroughly compared in order to address which of the two proposed divide-and-conquer preprocessing approaches results in more accuracy concerning the issue of short-term electricity price forecasting. Finally, the proposed technique that produces the smallest error in the electricity price forecasting is based on Variational Mode Decomposition, which is optimized through the proposed variation of Particle Swarm Optimization, with a mean absolute percentage error value of 6.15%.
Thermal Electrical Tests for Battery Safety Standardization
Authors: Stein Annika , Kehl Daniel , Jackmann Cedric , Essmann Stefan , Lienesch Frank , Kurrat Michael
Published: October 2022

Battery safety tests are defined by several international standards in different ways and with heterogenous termination and failure criteria. In this work, lithium-ion cells were examined regarding their behavior in the event of overcharging and also in the event of an external short circuit with varied parameters specified by standards. The voltage, current, and temperature curves were evaluated. In addition, the changes in the cells were analyzed using electrochemical impedance spectroscopy (EIS). It is shown that the cells exhibit reproducible behavior in a clamped state. Further, it could be determined that the position of the cell opening during an overcharge has an influence on the further behavior of the cell. EIS data showed that the cells have a significantly higher internal resistance after an overcharge. The short-circuit tests at different ambient temperatures indicated that the internal resistance of the cell decreases with increasing temperature. However, no reproducible effects in impedance spectra were present after the short-circuit test. This work illustrates that the choice of test parameters and termination criteria undoubtedly influence the test results and thus may change the classification of cells as either safe or unsafe. Thus, cells may be classified as safe regarding a certain standard but unsafe regarding another.
Potential of the Synthetic Fuel Oxymethylene Ether (OME) for the Usage in a Single-Cylinder Non-Road Diesel Engine: Thermodynamics and Emissions
Authors: Zacherl Florian , Wopper Christoph , Schwanzer Peter , Rabl Hans-Peter
Published: October 2022

Non-road sectors, such as agriculture and construction machinery, require high energy densities and flexibility in use, which is why diesel engines are mainly used. The use of climate-neutral fuels, produced from renewable energies, such as Oxymethylene Ether (OME) as a diesel substitute, can significantly reduce CO2 and pollutant emissions in these sectors. In addition to CO2 neutrality, OME also offers improved combustion characteristics compared to diesel fuel, eliminating the soot–NOx trade-off and thus enabling new opportunities in engine design and calibration. In this paper, the combustion of pure OME on a close-to-production, single-cylinder non-road diesel engine with a pump–line–nozzle injection system is analyzed. A variation of the center of combustion at constant power output was performed for diesel and OME at different operating points. Two injectors were investigated with OME. A study on ignition delay and a detailed thermodynamic analysis was carried out. In addition, the exhaust emissions CO, NOx, VOC, as well as particulate-matter, -number and -size distributions were measured. With OME, a significantly shorter ignition delay as well as a shortened combustion duration could be observed, despite a longer injection duration. In addition, the maximum injection pressure increases. VOC and CO emissions are reduced. Particulate matter was reduced by more than 99% and particle number (>10 nm) was reduced by multiple orders of magnitude. The median of the particle size distribution shifts from 60 to 85 nm (diesel) into a diameter range of sub 23 nm (OME). A significant reduction of NOx emissions with OME enables new degrees of freedom in engine calibration and an efficiency advantage without hardware adaption.
Determination of Carbonyls Compound, Ketones and Aldehydes Emissions from CI Diesel Engines Fueled with Pure Diesel/Diesel Methanol Blends
Authors: Al-Rawashdeh Hani , Hasan Ahmad O. , Gomaa Mohamed R. , Abu-jrai Ahmad , Shalby Mohammad
Published: October 2022

Quantitative and qualitative analyses of chemical species out of CI engine tailpipe emissions fueled with pure diesel and diesel methanol blends, trapped in dinitro phenylhydrazine (DNPH) solutions, were performed. The formed hydrazine was studied using high-performance liquid chromatography (HPLC) accompanied by a detector for ultraviolet (UV). A set of carbonyl-DNPH derivative standards was developed and compared with engine tailpipe gases produced by both fuel modes. An understanding of carbonyl chemical compounds such as formaldehyde, acetaldehyde, and acrolein (HCHO, CH3CHO, and H2 = CHCHO, respectively) is essential for researchers to know how these chemicals affect human health and the environment. In both fuel modes, acetaldehyde was the main combustible product 25 ppm followed by formaldehyde 17 ppm, croton aldehydes 16 ppm, acrolein 12 ppm, and iso-valerdyhyde 10 ppm. In addition to these species, only a few other chemical species were detected in the exhaust gas. According to this study, carbonyl compounds from blended fuel contribute 15–22% of pure diesel fuel emissions. As shown by the results, engine operating conditions and fuel mode have a strong impact on the total amount of carbonyls released by the engine. Engine performance was highly influenced by different fuel modes and engine speeds. Using pure diesel, the regulated emissions, HC, CO, and NOx, registered high concentrations at a lower speed (1500 rpm) and NOx presented with the highest concentration of 4 g/kWh followed by CO with 1 g/kWh and HC with 0.5 g/kWh.
Modeling and Finite-Horizon MPC for a Boiler-Turbine System Using Minimal Realization State-Space Model
Authors: Wang Jun , Ding Baocang , Wang Ping
Published: October 2022

This paper aims to address a finite-horizon model predictive control (MPC) for non-linear drum-type boiler-turbine system using a system-identification method. Considering that the strong state coupling of a non-linear mechanism model, the subspace identification method is first utilized to obtain a linear state-space model, and transformed into an input–output model. By taking the inputs and outputs of the input–output model as system states, an augmented non-minimal state-space (NMSS) model of state measurable is constructed. In order to reduce the computation burden, the augmented NMSS model is further transformed into a canonical formulation by adopting a Kalman decomposition. Based on the minimal realization state-space model, the MPC controller is parameterized as a finite-horizon optimization problem. Finally, simulations are performed and evaluated the performance of the proposed method, and the simulation results show that: the linear model approximate the non-linear system accurately; the proposed MPC method can achieve a satisfactory stable control performance; and the computation time 18.388 s for the overall optimization problem also illustrates the real-time performance effectively.