Energies

14 pages, 3682 KiB

Open AccessArticle

Load Prediction Algorithm Applied with Indoor Environment Sensing in University Buildings

by Yunho Kim, Yunha Park, Hyuncheol Seo and Jungha Hwang

Energies 2023, 16(2), 999; https://doi.org/10.3390/en16020999 - 16 Jan 2023

Cited by 3 | Viewed by 1498

Recently, building automation system (BAS) and building energy management system (BEMS) technologies have been applied to efficiently reduce the energy consumption of buildings. In addition, studies on utilizing large quantities of building data have been actively conducted using artificial intelligence and machine learning. [...] Read more.

Recently, building automation system (BAS) and building energy management system (BEMS) technologies have been applied to efficiently reduce the energy consumption of buildings. In addition, studies on utilizing large quantities of building data have been actively conducted using artificial intelligence and machine learning. However, the high cost and installation difficulties limit the use of measuring devices to sense the indoor environment of all buildings. Therefore, this study developed a comprehensive indoor environment sensor module with relatively inexpensive sensors to measure the indoor environment of a university building. In addition, an algorithm for predicting the load in real time through machine learning based on indoor environment measurement is proposed. When the reliability of the algorithm for predicting the number of occupants and load according to the indoor CO₂ concentration was quantitatively assessed, the mean squared error (MSE), root mean square deviation (RMSD), and mean absolute error (MAE) were calculated to be 23.1, 4.8, and 2.5, respectively, indicating the high accuracy of the algorithm. Since the sensor used in this study is economical and can be easily applied to existing buildings, it is expected to be favorable for the dissemination of load prediction technology. Full article

(This article belongs to the Special Issue Energy Evaluation and Energy-Savings for Sustainable Buildings)

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19 pages, 1987 KiB

Open AccessArticle

Convergence of Energy Policies between the EU and Ukraine under the Green Deal Policy

by Yevheniia Ziabina, Aleksy Kwilinski, Oleksii Lyulyov, Tetyana Pimonenko and Yana Us

Energies 2023, 16(2), 998; https://doi.org/10.3390/en16020998 - 16 Jan 2023

Cited by 46 | Viewed by 1982

Abstract

EU countries declared the strategic goal to achieve energy independence and increase energy efficiency. In this case, EU countries have provided a vast range of incentives, mechanisms, and directives to promote energy efficiency. Ukraine as a potential candidate should provide a convergent policy [...] Read more.

EU countries declared the strategic goal to achieve energy independence and increase energy efficiency. In this case, EU countries have provided a vast range of incentives, mechanisms, and directives to promote energy efficiency. Ukraine as a potential candidate should provide a convergent policy with EU countries to increase energy efficiency. The paper aims to estimate energy efficiency based on the revealed convergent and divergent determinants of energy policies among the EU and Ukraine. The data are compiled from the World Energy Statistics Yearbook, the European Statistical Office, the International Energy Agency, SolAbility agencies, and State Statistics Service of Ukraine. The study applies σ- i β-convergence theory to determine the convergent and divergent determinants of the country’s energy efficiency. The empirical results allow concluding that Ukraine has an average level in the integrated energy efficiency index of the national economy, and the highest value of this index was in 2008. The highest values of energy efficiency were in Sweden and Denmark among EU countries. Besides, the findings confirm that the Ukrainian government should pay attention to divergent determinants (expenditure for environmental protection, pricing for energy resources, etc.) to improve the country’s energy efficiency. Full article

(This article belongs to the Section C: Energy Economics and Policy)

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12 pages, 5911 KiB

Open AccessArticle

Grating Spectrum Design and Optimization of GMM-FBG Current Sensor

by Fei Jiao, Yuqing Lei, Guozheng Peng, Funing Dong, Qing Yang and Wei Liao

Energies 2023, 16(2), 997; https://doi.org/10.3390/en16020997 - 16 Jan 2023

Cited by 2 | Viewed by 1338

Abstract

In this study, the performance of a current sensor based on giant magnetostrictive materials (GMM) and fiber Bragg grating (FBG) has been improved by optimizing the spectral characteristics of gratings. By analyzing the influence of FBG on the current sensor characteristics, three key [...] Read more.

In this study, the performance of a current sensor based on giant magnetostrictive materials (GMM) and fiber Bragg grating (FBG) has been improved by optimizing the spectral characteristics of gratings. By analyzing the influence of FBG on the current sensor characteristics, three key parameters (gate region length, refractive index modulation depth, and toe cutting system) are selected for optimization. The optimal grating parameters are determined to improve the linearity and sensitivity of sensor output. Experimental tests reveal that after grating optimization, the current sensor shows excellent performance parameters, including a linearity of 0.9942, sensitivity of 249.75 mV/A, and good stability in the temperature range of 0–60 °C. This research can provide a reference for improving the grating design and performance of existing GMM-FBG current sensors. Full article

(This article belongs to the Topic High Voltage Systems and Smart Technologies)

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14 pages, 3627 KiB

Open AccessArticle

A New Cloud-Based IoT Solution for Soiling Ratio Measurement of PV Systems Using Artificial Neural Network

by Mussawir Ul Mehmood, Abasin Ulasyar, Waleed Ali, Kamran Zeb, Haris Sheh Zad, Waqar Uddin and Hee-Je Kim

Energies 2023, 16(2), 996; https://doi.org/10.3390/en16020996 - 16 Jan 2023

Cited by 7 | Viewed by 2385

Abstract

Solar energy is considered the most abundant form of energy available on earth. However, the efficiency of photovoltaic (PV) panels is greatly reduced due to the accumulation of dust particles on the surface of PV panels. The optimization of the cleaning cycles of [...] Read more.

Solar energy is considered the most abundant form of energy available on earth. However, the efficiency of photovoltaic (PV) panels is greatly reduced due to the accumulation of dust particles on the surface of PV panels. The optimization of the cleaning cycles of a PV power plant through condition monitoring of PV panels is crucial for its optimal performance. Specialized equipment and weather stations are deployed for large-scale PV plants to monitor the amount of soil accumulated on panel surface. However, not much focus is given to small- and medium-scale PV plants, where the costs associated with specialized weather stations cannot be justified. To overcome this hurdle, a cost-effective and scalable solution is required. Therefore, a new centralized cloud-based solar conversion recovery system (SCRS) is proposed in this research work. The proposed system utilizes the Internet of Things (IoT) and cloud-based centralized architecture, which allows users to remotely monitor the amount of soiling on PV panels, regardless of the scale. To improve scalability and cost-effectiveness, the proposed system uses low-cost sensors and an artificial neural network (ANN) to reduce the amount of hardware required for a soiling station. Multiple ANN models with different numbers of neurons in hidden layers were tested and compared to determine the most suitable model. The selected ANN model was trained using the data collected from an experimental setup. After training the ANN model, the mean squared error (MSE) value of 0.0117 was achieved. Additionally, the adjusted R-squared (

R^{2}

) value of 0.905 was attained on the test data. Furthermore, data is transmitted from soiling station to the cloud server wirelessly using a message queuing telemetry transport (MQTT) lightweight communication protocol over Wi-Fi network. Therefore, SCRS depicts a complete wireless sensor network eliminating the need for extra wiring. The average percentage error in the soiling ratio estimation was found to be 4.33%. Full article

(This article belongs to the Special Issue Optimizing, Forecasting, Modeling and Applications of New Energy Microgrid/Grid)

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18 pages, 1139 KiB

Open AccessArticle

On the Minimum and Maximum Variable Cost of Heating of the Flat in Multifamily Building

by Tomasz Cholewa, Alicja Siuta-Olcha, Anna Życzyńska, Aleksandra Specjał and Paweł Michnikowski

Energies 2023, 16(2), 995; https://doi.org/10.3390/en16020995 - 16 Jan 2023

Cited by 1 | Viewed by 1068

Abstract

Heat cost allocation is commonly used in existing buildings supplied by centralized sources of heating/cooling and provided with individual metering systems. However, this process is not always fair for the users, since “fairness” strongly depends on the methods established to allocate variable and [...] Read more.

Heat cost allocation is commonly used in existing buildings supplied by centralized sources of heating/cooling and provided with individual metering systems. However, this process is not always fair for the users, since “fairness” strongly depends on the methods established to allocate variable and fixed costs among the dwellings. That is why unrealistic cost for heating may be allocated for specific flats. However, there is a lack of evidence about procedures as to how maximum and minimum variable cost of heating may be calculated for specific flats in multifamily building for a specific heating season. This paper presents different methods for estimation of maximum and minimum variable cost of heating of flat in multifamily buildings, the use of which depends of the availability of input data for specific buildings. Evaluation of the proposed methods is made on the example of a case study multifamily building located in Poland. It was shown that the maximum variable costs of heat purchase for specific flats in the analyzed building were in the range from 169% to 256% of the average unit cost of heat, depending on the method used. The recommendation about the accuracy of proposed methods is also provided by the authors. Full article

(This article belongs to the Special Issue Individual Heat Metering in Smart Buildings for Improving Energy Efficiency in the Residential Sector)

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13 pages, 774 KiB

Open AccessPerspective

The Cost of Using Gas as a Transition Fuel in the Transition to Low-Carbon Energy: The Case Study of Poland and Selected European Countries

by Grzegorz Zych, Jakub Bronicki, Marzena Czarnecka, Grzegorz Kinelski and Jacek Kamiński

Energies 2023, 16(2), 994; https://doi.org/10.3390/en16020994 - 16 Jan 2023

Cited by 6 | Viewed by 1506

Abstract

The purpose of this article is to answer the question of whether it is economically justified to use natural gas as an interim fuel on the way to creating a low-emission energy sector from the perspective of Poland in comparison to other countries [...] Read more.

The purpose of this article is to answer the question of whether it is economically justified to use natural gas as an interim fuel on the way to creating a low-emission energy sector from the perspective of Poland in comparison to other countries in the European Community. Despite the existence of numerous scientific studies concerning natural gas as a ‘bridge’ fuel, there is a lack of precise references to the situation of Poland in this respect, especially considering its specific situation in the historical development of energy, as well as the ongoing energy crisis caused by the Russia–Ukraine war. The study suggests that from Poland’s point of view, given the changes in natural gas prices resulting from a series of events of an international nature, gas investments are not economically justified in the economic climate (NPV of −891 million EUR) at present and will not be justified in the event of their anticipated changes (NPV of −691 million EUR), having its justification only in the presence of unlikely global changes (NPV of 2.37 billion EUR). Full article

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11 pages, 2161 KiB

Open AccessArticle

Multiple Exciton Generation Solar Cells: Numerical Approaches of Quantum Yield Extraction and Its Limiting Efficiencies

by Jongwon Lee and Chi-Hyung Ahn

Energies 2023, 16(2), 993; https://doi.org/10.3390/en16020993 - 16 Jan 2023

Cited by 1 | Viewed by 1472

Abstract

Multiple exciton generation solar cells exhibit low power conversion efficiency owing to non-radiative recombination, even after the generation of numerous electron and hole pairs per incident photon. This paper elucidates the non-idealities of multiple exciton generation solar cells. Accordingly, we present mathematical approaches [...] Read more.

Multiple exciton generation solar cells exhibit low power conversion efficiency owing to non-radiative recombination, even after the generation of numerous electron and hole pairs per incident photon. This paper elucidates the non-idealities of multiple exciton generation solar cells. Accordingly, we present mathematical approaches for determining the quantum yield to discuss the non-idealities of multiple exciton generation solar cells by adjusting the delta function. We present the use of the Gaussian distribution function to present the occupancy status of carriers at each energy state using the Dirac delta function. Further, we obtained ideal and non-ideal quantum yields by modifying the Gaussian distribution function for each energy state. On the basis of this approach, we discuss the material imperfections of multiple exciton generations by analyzing the mathematically obtained quantum yields. Then, we discuss the status of radiative recombination calculated from the ratio of radiative to non-radiative recombination. Finally, we present the application of this approach to the detailed balance limit of the multiple exciton generation solar cell to evaluate the practical limit of multiple exciton generation solar cells. Full article

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21 pages, 1618 KiB

Open AccessArticle

Comparison of Willingness to Pay for Quality Air and Renewable Energy Considering Urban Living Experience

by Rui Zhou, Hiroatsu Fukuda, You Li and Yafei Wang

Energies 2023, 16(2), 992; https://doi.org/10.3390/en16020992 - 16 Jan 2023

Cited by 1 | Viewed by 1542

Abstract

Currently, quality air and renewable energy are main concerns in protecting the environment. Comparing willingness to pay for quality air and renewable energy is rare in the existing literature. However, the public faces these issues simultaneously. In addition, population mobility under China’s household [...] Read more.

Currently, quality air and renewable energy are main concerns in protecting the environment. Comparing willingness to pay for quality air and renewable energy is rare in the existing literature. However, the public faces these issues simultaneously. In addition, population mobility under China’s household registration system, i.e., urban living experience, may affect the willingness to pay for environmental protection. Consequently, the difference between people’s willingness to pay for quality air and renewable energy in China is discussed. Binary logistic regression is adopted to analyze the correlation factors based on data from the China General Social Survey. The results show that willingness to pay is influenced by environmental attitudes, awareness of energy use, government responsibilities, age, household income level, and trust. The effects of urban living experience on willingness to pay weakens as age decreases. Thus, improving environmental awareness and specialized knowledge remain important means of promoting willingness to pay. Our findings can help marketers and policy designers develop balanced or targeted measures when taking joint actions. Full article

(This article belongs to the Special Issue Willingness to Pay Studies and Energy Use)

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22 pages, 938 KiB

Open AccessReview

Neural Load Disaggregation: Meta-Analysis, Federated Learning and Beyond

by Hafsa Bousbiat, Yassine Himeur, Iraklis Varlamis, Faycal Bensaali and Abbes Amira

Energies 2023, 16(2), 991; https://doi.org/10.3390/en16020991 - 16 Jan 2023

Cited by 5 | Viewed by 2597

Abstract

Non-intrusive load monitoring (NILM) techniques are central techniques to achieve the energy sustainability goals through the identification of operating appliances in the residential and industrial sectors, potentially leading to increased rates of energy savings. NILM received significant attention in the last decade, reflected [...] Read more.

Non-intrusive load monitoring (NILM) techniques are central techniques to achieve the energy sustainability goals through the identification of operating appliances in the residential and industrial sectors, potentially leading to increased rates of energy savings. NILM received significant attention in the last decade, reflected by the number of contributions and systematic reviews published yearly. In this regard, the current paper provides a meta-analysis summarising existing NILM reviews to identify widely acknowledged findings concerning NILM scholarship in general and neural NILM algorithms in particular. In addition, this paper emphasizes federated neural NILM, receiving increasing attention due to its ability to preserve end-users’ privacy. Typically, by combining several locally trained models, federated learning has excellent potential to train NILM models locally without communicating sensitive data with cloud servers. Thus, the second part of the current paper provides a summary of recent federated NILM frameworks with a focus on the main contributions of each framework and the achieved performance. Furthermore, we identify the non-availability of proper toolkits enabling easy experimentation with federated neural NILM as a primary barrier in the field. Thus, we extend existing toolkits with a federated component, made publicly available and conduct experiments on the REFIT energy dataset considering four different scenarios. Full article

(This article belongs to the Special Issue Internet of Energy and Artificial Intelligence for Sustainable Cities)

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15 pages, 3170 KiB

Open AccessArticle

Power Grid Structure Performance Evaluation Based on Complex Network Cascade Failure Analysis

by Di Zhang, Limin Jia, Jin Ning, Yujiang Ye, Hao Sun and Ruifeng Shi

Energies 2023, 16(2), 990; https://doi.org/10.3390/en16020990 - 16 Jan 2023

Cited by 7 | Viewed by 1600

Abstract

A safe and stable operation power system is very important for the maintenance of national industrial security and social economy. However, with the increasing complexity of the power grid topology and its operation, new challenges in estimating and evaluating the grid structure performance [...] Read more.

A safe and stable operation power system is very important for the maintenance of national industrial security and social economy. However, with the increasing complexity of the power grid topology and its operation, new challenges in estimating and evaluating the grid structure performance have received significant attention. Complex network theory transfers the power grid to a network with nodes and links, which helps evaluate the system conveniently with a global view. In this paper, we employ the complex network method to address the cascade failure process and grid structure performance assessment simultaneously. Firstly, a grid cascade failure model based on network topology and power system characteristics is constructed. Then, a set of performance evaluation indicators, including invulnerability, reliability, and vulnerability, is proposed based on the actual functional properties of the grid by renewing the power-weighted degree, medium, and clustering coefficients according to the network cascade failure. Finally, a comprehensive network performance evaluation index, which combines the invulnerability, reliability, and vulnerability indicators with an entropy-based objective weighting method, is put forward in this study. In order to confirm the approach’s efficacy, an IEEE-30 bus system is employed for a case study. Numerical results show that the weighted integrated index with a functional network could better evaluate the power grid performance than the unweighted index with a topology network, which demonstrates and validates the effectiveness of the method proposed in this paper. Full article

(This article belongs to the Special Issue Research on Operation Optimization of Energy Systems)

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19 pages, 25449 KiB

Open AccessArticle

Thermal Performance and Durability Evaluation of Arundo Donax towards an Improvement in the Knowledge of Sustainable Building Materials

by Raphaele Malheiro, Aurora Morillas, Adriana Ansolin, Jorge Fernandes, Aires Camões, Maria Teresa Amorim, Sandra Monteiro Silva and Ricardo Mateus

Energies 2023, 16(2), 989; https://doi.org/10.3390/en16020989 - 16 Jan 2023

Viewed by 1306

Abstract

Bio-based and natural building materials can support the building sector to reduce its environmental impact. In this study, experimental research was developed to evaluate the performance of giant reed when used as a building thermal insulation. Reed was chosen due to its high [...] Read more.

Bio-based and natural building materials can support the building sector to reduce its environmental impact. In this study, experimental research was developed to evaluate the performance of giant reed when used as a building thermal insulation. Reed was chosen due to its high availability and close relationship to Portuguese vernacular architecture. The role of the reed’s origin in this context, its physical characteristics and its durability aspects were evaluated. The results showed that the performance of the reed boards was compatible with their use as a thermal insulation material, regardless of the reed’s origin. Denser boards showed better results. Under the favourable conditions related to the reed’s water content, mould growth could occur. Full article

(This article belongs to the Section G: Energy and Buildings)

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21 pages, 2216 KiB

Open AccessArticle

Stability and Control for Buck–Boost Converter for Aeronautic Power Management

by Antonio Russo and Alberto Cavallo

Energies 2023, 16(2), 988; https://doi.org/10.3390/en16020988 - 16 Jan 2023

Cited by 11 | Viewed by 1544

Abstract

The need for greener and cleaner aviation has accelerated the transition towards more electric systems on the More Electric Aircraft. One of the key challenges related to the increasing number of electrical devices onboard is the control of bidirectional power converters. In this [...] Read more.

The need for greener and cleaner aviation has accelerated the transition towards more electric systems on the More Electric Aircraft. One of the key challenges related to the increasing number of electrical devices onboard is the control of bidirectional power converters. In this work, stability analysis and control of a buck–boost converter for aeronautic applications are presented. Firstly, stability of the buck–boost converter in the Lyapunov sense is proven by resorting to input-to-state stability notions. Then, a novel control design based on second order sliding mode control and uniting control, aimed at overcoming the difficulties generated by the nonlinear input gain function of the system not being sign definite, is presented. Extensive and detailed simulations, designed to emulate one of the possible energy management policies onboard a More Electric Aircraft, confirm the correctness of the theoretical analysis both in buck and in boost mode. Full article

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13 pages, 5698 KiB

Open AccessArticle

On the Sublimation of Dry-Ice: Experimental Investigation and Thermal Modelling of Low-Temperatures on a Sandy Soil

by Matteo Vitali, Giovanni Biancini, Barbara Marchetti and Francesco Corvaro

Energies 2023, 16(2), 987; https://doi.org/10.3390/en16020987 - 16 Jan 2023

Cited by 1 | Viewed by 1766

Abstract

In the last decade, growing awareness about CO₂ emissions is supporting the authorities in a more sustainable society. The proposed solutions embrace different topics, such as renewable energy implementation, lower waste production, and carbon capture and storage technologies (CCS). The latter is [...] Read more.

In the last decade, growing awareness about CO₂ emissions is supporting the authorities in a more sustainable society. The proposed solutions embrace different topics, such as renewable energy implementation, lower waste production, and carbon capture and storage technologies (CCS). The latter is based upon the best available knowledge about the thermophysical properties of CO₂, which are not always satisfactory for its complete characterization. In this work, it is investigated the interaction of the CO₂ in solid phase (dry-ice) with sandy soil, a phenomenon that can potentially occur following pipeline ruptures. An experimental setup and a numerical model have been developed to measure and validate the temperature profiles beneath the dry-ice bank at steady-state conditions. The model has been validated with the experimental data by defining a suitable range of the thermal conductivity at the solid phase (0.25–0.30 W m⁻¹ K⁻¹) that led to the best match (deviation of 7.81%). Finally, the overall heat transfer coefficient (85.56–86.35 W m⁻² K⁻¹) has been numerically calculated. Full article

(This article belongs to the Special Issue Challenges and Development on Carbon Capture and Storage)

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13 pages, 835 KiB

Open AccessArticle

Ensuring the Reliability of Gas Supply Systems by Optimizing the Overhaul Planning

by Volodymyr Grudz, Yaroslav Grudz, Ivan Pavlenko, Oleksandr Liaposhchenko, Marek Ochowiak, Vasyl Pidluskiy, Oleksandr Portechyn, Mykola Iakymiv, Sylwia Włodarczak, Andżelika Krupińska, Magdalena Matuszak and Krystian Czernek

Energies 2023, 16(2), 986; https://doi.org/10.3390/en16020986 - 16 Jan 2023

Viewed by 1277

Abstract

The aim of the article is the development of methods for optimal overhaul planning of compressor station equipment. Nowadays, due to uncertainties in the forecast of gas supply flow rates, increasing the reliability and energy efficiency of main gas pipelines is an urgent [...] Read more.

The aim of the article is the development of methods for optimal overhaul planning of compressor station equipment. Nowadays, due to uncertainties in the forecast of gas supply flow rates, increasing the reliability and energy efficiency of main gas pipelines is an urgent problem. The dependence of operating costs for major repairs on the maintenance periodicity is extreme. Reducing equipment’s maintenance period leads to an increase in repair costs. It also increases the reliability of equipment operation. Overall, all these facts reduce the probability of emergency failures and related expenses for emergency recovery, gas losses, and undersupply to consumers. Therefore, an optimal maintenance frequency exists, at which the total operating costs will be minimal. A procedure for optimizing the periodicity of repairs and equipment replacement is proposed. It was realized by constructing an objective function as a dependence of exploitation costs on the inter-repair period of major repairs. A probabilistic approach was applied to assess the aging process. The characteristics of the equipment’s state are described by distribution densities (i.e., pre-repair, inter-repair, and full-service life), which vary depending on product initialization time. The main characteristics of major repairs are their duration and intensity, which are evaluated by the quality factor related to repair costs. The extremum of the objective function is sought by the method of competing options. It was determined that the optimal management of the frequency of equipment replacement can be realized by choosing the optimal values of the average service life, average operation time of units until the first planned and preventive repair, and quality factor. As a result, the required technical condition for the technological equipment is ensured under minimum operating costs without reducing the system’s reliability. Full article

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14 pages, 1529 KiB

Open AccessArticle

Comparison of Wavelet Artificial Neural Network, Wavelet Support Vector Machine, and Adaptive Neuro-Fuzzy Inference System Methods in Estimating Total Solar Radiation in Iraq

by Wongchai Anupong, Muhsin Jaber Jweeg, Sameer Alani, Ibrahim H. Al-Kharsan, Aníbal Alviz-Meza and Yulineth Cárdenas-Escrocia

Energies 2023, 16(2), 985; https://doi.org/10.3390/en16020985 - 16 Jan 2023

Cited by 5 | Viewed by 1682

Abstract

Estimating the amount of solar radiation is very important in evaluating the amount of energy that can be received from the sun for the construction of solar power plants. Using machine learning tools to estimate solar energy can be a helpful method. With [...] Read more.

Estimating the amount of solar radiation is very important in evaluating the amount of energy that can be received from the sun for the construction of solar power plants. Using machine learning tools to estimate solar energy can be a helpful method. With a high number of sunny days, Iraq has a high potential for using solar energy. This study used the Wavelet Artificial Neural Network (WANN), Wavelet Support Vector Machine (WSVM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) techniques to estimate solar energy at Wasit and Dhi Qar stations in Iraq. RMSE, EMA, R², and IA criteria were used to evaluate the performance of the techniques and compare the results with the actual measured value. The results showed that the WANN and WSVM methods had similar results in solar energy modeling. However, the results of the WANN technique were slightly better than the WSVM technique. In Wasit and Dhi Qar stations, the value of R² for the WANN and WSVM methods was 0.89 and 0.86, respectively. The value of R² in the WANN and WSVM methods in Wasit and Dhi Qar stations was 0.88 and 0.87, respectively. The ANFIS technique also obtained acceptable results. However, compared to the other two techniques, the ANFIS results were lower, and the R² value was 0.84 and 0.83 in Wasit and Dhi Qar stations, respectively. Full article

(This article belongs to the Special Issue Performance Analysis of Novel Solar Energy Systems)

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9 pages, 2251 KiB

Open AccessArticle

Prediction Model for the DC Flashover Voltage of a Composite Insulator Based on a BP Neural Network

by Zhenan Zhou, Haowei Li, Silun Wen and Chuyan Zhang

Energies 2023, 16(2), 984; https://doi.org/10.3390/en16020984 - 16 Jan 2023

Cited by 2 | Viewed by 1276

Abstract

To be able to predict the DC flashover characteristics of composite insulators, a four-layer BP neural network model is established with composite insulator shed structure parameters as the input. Three algorithms (gradient descent with momentum, RMSProp gradient descent, and Adam gradient descent) are [...] Read more.

To be able to predict the DC flashover characteristics of composite insulators, a four-layer BP neural network model is established with composite insulator shed structure parameters as the input. Three algorithms (gradient descent with momentum, RMSProp gradient descent, and Adam gradient descent) are applied, and the DC pollution flashover experimental data of composite insulators are used as training data. The results show that all three algorithms have good prediction capabilities. Among them, the Adam gradient descent model has the best prediction result, which can make the average prediction with an error of less than 4% and a maximum error of less than 8%, so these results can provide a reference for the design of composite insulators in DC voltage and product performance verifications. Full article

(This article belongs to the Section F6: High Voltage)

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17 pages, 1303 KiB

Open AccessArticle

Electric Vehicle Charging Station Layout for Tourist Attractions Based on Improved Two-Population Genetic PSO

by Shuang Che, Yan Chen and Longda Wang

Energies 2023, 16(2), 983; https://doi.org/10.3390/en16020983 - 16 Jan 2023

Cited by 4 | Viewed by 1348

Abstract

In this paper, the optimization issue of electric vehicle charging station layout (EVCSL) for tourist attractions is addressed, and an improved PSO is used to solve the optimization issue. Specifically, the improved particle swarm optimization (PSO) is proposed to obtain an appreciative planning [...] Read more.

In this paper, the optimization issue of electric vehicle charging station layout (EVCSL) for tourist attractions is addressed, and an improved PSO is used to solve the optimization issue. Specifically, the improved particle swarm optimization (PSO) is proposed to obtain an appreciative planning solution of EVCSL, and dynamic weight adjustment strategy and integration into the two-population genetic mode are proposed to improve the optimization quality for PSO. Simulation results show that the proposed improvement strategies can increase the optimization quality for PSO effectively so that a more appreciative planning solution of EVCSL can be obtained. Full article

(This article belongs to the Special Issue Internet of Vehicles for Intelligent Transportation System)

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25 pages, 24954 KiB

Open AccessArticle

Characterization of the Operation of a BESS with a Photovoltaic System as a Regular Source for the Auxiliary Systems of a High-Voltage Substation in Brazil

by Washington de Araujo Silva Júnior, Andrea Vasconcelos, Ayrlw Carvalho Arcanjo, Tatiane Costa, Rafaela Nascimento, Alex Pereira, Eduardo Jatobá, José Bione Filho, Elisabete Barreto, Roberto Dias and Manoel Marinho

Energies 2023, 16(2), 1012; https://doi.org/10.3390/en16021012 - 16 Jan 2023

Cited by 10 | Viewed by 2610

Abstract

Substation (SS) auxiliary systems (SAux) are facilities responsible for hosting the alternating (AC) and direct current (DC) busbar to serve the equipment and systems that perform the substation’s protection, control, and supervision. External and internal power supplies typically ensure the continuity of such [...] Read more.

Substation (SS) auxiliary systems (SAux) are facilities responsible for hosting the alternating (AC) and direct current (DC) busbar to serve the equipment and systems that perform the substation’s protection, control, and supervision. External and internal power supplies typically ensure the continuity of such a facility. The electricity support will be restricted to diesel emergency generators (DG) if the external power supply is unavailable due to a contingency. The DG present a slower response time and are susceptible to starting failures. Microgrids with Battery Energy Storage Systems (BESS) paired with photovoltaic systems (PV) are presented as an innovative and reliable solution for powering the SAux. In this article, tests were carried out on the microgrid of the Edson Mororó Moura Institute of Technology (ITEMM) in Brazil to support the use of microgrids BESS/PV in the SAux of a transmission SS of the São Francisco Hydroelectric Company (Chesf). Without an external power supply, BESS commands the action of islanded operation, maintaining both voltage and frequency requirements of the microgrid without load shedding. It was possible to observe all operations of the microgrid. The experimental results showed that the solution proposed in the paper implements a dependable self-dispatchable autonomous power supply. Full article

(This article belongs to the Special Issue Applications of Battery Energy Storage Systems (BESS))

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23 pages, 430 KiB

Open AccessArticle

A Surrogate-Assisted Adaptive Bat Algorithm for Large-Scale Economic Dispatch

by Aokang Pang, Huijun Liang, Chenhao Lin and Lei Yao

Energies 2023, 16(2), 1011; https://doi.org/10.3390/en16021011 - 16 Jan 2023

Cited by 8 | Viewed by 1657

Abstract

Large-scale grids have gradually become the dominant trend in power systems, which has increased the importance of solving the challenges associated with large-scale economic dispatch (LED). An increase in the number of decision variables enlarges the search-space scale in LED. In addition to [...] Read more.

Large-scale grids have gradually become the dominant trend in power systems, which has increased the importance of solving the challenges associated with large-scale economic dispatch (LED). An increase in the number of decision variables enlarges the search-space scale in LED. In addition to increasing the difficulty of solving algorithms, huge amounts of computing resources are consumed. To overcome this problem, we proposed a surrogate-assisted adaptive bat algorithm (GARCBA). On the one hand, to reduce the execution time of LED problems, we proposed a generalized regression neural network surrogate model based on a self-adaptive “minimizing the predictor” sampling strategy, which replaces the original fuel cost functions with a shorter computing time. On the other hand, we also proposed an improved hybrid bat algorithm (RCBA) named GARCBA to execute LED optimization problems. Specifically, we developed an evolutionary state evaluation (ESE) method to increase the performance of the original RCBA. Moreover, we introduced the ESE to analyze the population distribution, fitness, and effective radius of the random black hole in the original RCBA. We achieved a substantial improvement in computational time, accuracy, and convergence when using the GARCBA to solve LED problems, and we demonstrated this method’s effectiveness with three sets of simulations. Full article

(This article belongs to the Topic Energy Economics and Sustainable Development)

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23 pages, 6396 KiB

Open AccessArticle

PV Powered High Voltage Pulse Converter with Switching Cells for Food Processing Application

by P. Sumathy, J. Divya Navamani, A. Lavanya, Jagabar Sathik, R. Zahira and Fadl A. Essa

Energies 2023, 16(2), 1010; https://doi.org/10.3390/en16021010 - 16 Jan 2023

Cited by 5 | Viewed by 1701

Abstract

In recent years, industries in the suburb have retrofitted their power supply units with solar power supply systems. Using solar power supply systems for various applications, such as food processing, enables energy expense saving. A promising opportunity in the food industry is solar-powered [...] Read more.

In recent years, industries in the suburb have retrofitted their power supply units with solar power supply systems. Using solar power supply systems for various applications, such as food processing, enables energy expense saving. A promising opportunity in the food industry is solar-powered Pulsed Electric Field (PEF) used in the treatment of fruits and their by-products. For this application, a converter is proposed in this paper with a combination of a passive switched inductor cell and a switched capacitor cell. Furthermore, the derived topology possesses an extendable feature. This topology generates high voltage repetitive pulses with a single semiconductor switch and a reduced component count. Dynamic study of the converter is also performed with the derivation of the transfer function. Cost effective, reliable, and simple circuitry are the critical features of this topology. The circuit topology can generate high voltage pulses by increasing the number of switched inductors and switched capacitor cells. A correlation study on the impact of the switched inductor/capacitor cell is also performed and analyzed, which is not usually performed. A 50 W prototype is designed and tested to validate the performance of the converter Full article

(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)

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19 pages, 2178 KiB

Open AccessArticle

Application of an Independent Temporary Spent Fuel Storage Pool Cooling System for Decommissioning of Pressurized Water Reactor Kori Units 3 and 4

by Wonjune Mah and Chang-Lak Kim

Energies 2023, 16(2), 1009; https://doi.org/10.3390/en16021009 - 16 Jan 2023

Cited by 1 | Viewed by 1230

Abstract

The operating license of Kori units 3 and 4 are to be expired in 2024 and 2025. If the plants are decided to be decommissioned, the spent nuclear fuels in the spent fuel storage pool (SFP) have to be removed from the site. [...] Read more.

The operating license of Kori units 3 and 4 are to be expired in 2024 and 2025. If the plants are decided to be decommissioned, the spent nuclear fuels in the spent fuel storage pool (SFP) have to be removed from the site. However, no proper storage facility is currently available in Korea. To overcome the difficulty, this study proposes application of an independent temporary SFP cooling system. It is expected to safely isolate the SFP from the plant. The case study conducted showed this concept is achievable and technically mature. Moreover, the installation cost per unit is USD 9.51 million obtained from an analogous estimating. This is much lower cost than the dry cask options. Then, system requirements and applicable design are developed. Maximum heat generation of unit 4 is estimated as 1.67 MW, through fuel characteristics categorizations and ORIGEN calculations. To remove the decay heat, installation of an indirect air-cooled method is selected by evaluating three cooling methods. The modification includes new heat exchanger, secondary cooling pumps, and chillers. Furthermore, two single failures are considered; cooling pump and normal power. This can be covered by two redundant trains and a back-up diesel generator provided. Full article

(This article belongs to the Special Issue The Future of Nuclear Power for Clean Energy Systems)

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27 pages, 8835 KiB

Open AccessArticle

Secondary Atomization of Fuel Oil and Fuel Oil/Water Emulsion through Droplet-Droplet Collisions and Impingement on a Solid Wall

by Anastasia Islamova, Pavel Tkachenko, Nikita Shlegel and Genii Kuznetsov

Energies 2023, 16(2), 1008; https://doi.org/10.3390/en16021008 - 16 Jan 2023

Cited by 3 | Viewed by 1878

Abstract

This paper presents findings from an experimental study investigating the secondary atomization of liquid fuel droplets widely used in the heat and power industry exemplified by fuel oil and environmentally promising fuel oil/water emulsion. The scientific novelty comes from the comparative analysis of [...] Read more.

This paper presents findings from an experimental study investigating the secondary atomization of liquid fuel droplets widely used in the heat and power industry exemplified by fuel oil and environmentally promising fuel oil/water emulsion. The scientific novelty comes from the comparative analysis of the critical conditions and integral characteristics of the secondary atomization of the liquid and composite fuels with the greatest potential for power plants. Here, we used two fuel atomization schemes: droplet–droplet collisions in a gas and droplets impinging on a heated solid wall. The temperature of the liquids under study was 80 °C. The velocities before collision ranged from 0.1 m/s to 7 m/s, while the initial droplet sizes varied from 0.3 mm to 2.7 mm. A copper substrate served as a solid wall; its temperature was varied from 20 °C to 300 °C. The main characteristics of droplet interaction were recorded by a high-speed camera. Regime maps were constructed using the experimental findings. It was established that the critical Weber number was several times lower when water and fuel oil droplets collided than during the collision of fuel oil droplets with 10 vol% of water. The secondary atomization of fuel oil/water emulsion droplets by their impingement on a heated solid wall was found to reduce the typical sizes of liquid fragments by a factor of 40–50. As shown in the paper, even highly viscous fuels can be effectively sprayed using primary and secondary droplet atomization schemes. It was established that the optimal temperature of the fuel oil to be supplied to the droplet collision zone is 80 °C, while the optimal substrate temperature for the atomization of fuel oil/water emulsion droplets approximates 300 °C. Full article

(This article belongs to the Collection Board Members’ Collection Series: Clean Coal Extraction and Using)

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18 pages, 4880 KiB

Open AccessArticle

Investigation of the Splashing Characteristics of Lead Slag in Side-Blown Bath Melting Process

by Quan Zou, Jianhang Hu, Shiliang Yang, Hua Wang and Ge Deng

Energies 2023, 16(2), 1007; https://doi.org/10.3390/en16021007 - 16 Jan 2023

Cited by 4 | Viewed by 1573

Abstract

Aiming at the melt splashing behavior in the smelting process of an oxygen-enriched side-blowing furnace, the volume of fluid model and the realizable

k

−

ε

turbulence model are coupled and simulated. The effects of different operating parameters (injection velocity, immersion depth, liquid [...] Read more.

Aiming at the melt splashing behavior in the smelting process of an oxygen-enriched side-blowing furnace, the volume of fluid model and the realizable

k

−

ε

turbulence model are coupled and simulated. The effects of different operating parameters (injection velocity, immersion depth, liquid level) on splash height are explored, and the simulation results are verified by water model experiments. The results show that the bubbles with residual kinetic energy escape to the slag surface and cause slag splashing. The slag splashing height gradually increases with the increase in injection velocity, and the time-averaged splashing height reaches 1.01 m when the injection speed is 160 m/s. Increasing the immersion depth of the lance, and the slag splashing height gradually decreases. When the immersion depth is 0.12 m, the time-averaged splashing height is 0.85 m. Increasing the liquid level is beneficial to reduce the splash height, when the liquid level is 2.7 m, the splash height reduces to 0.77 m. With the increase in the liquid level, the slag splashing height gradually decreases, and the time-averaged splashing height is 0.77 m when the initial liquid level is 2.7 m. Full article

(This article belongs to the Topic Energy-Saving and Emission Reduction in Metallurgy)

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23 pages, 2694 KiB

Open AccessArticle

Measuring and Analyzing Operational Efficiency and Returns to Scale in a Time Horizon: Assessment of China’s Electricity Generation & Transmission at Provincial Levels

by Toshiyuki Sueyoshi, Ruchuan Zhang and Aijun Li

Energies 2023, 16(2), 1006; https://doi.org/10.3390/en16021006 - 16 Jan 2023

Cited by 2 | Viewed by 1472

Abstract

This study discusses the assessment of OE (operational efficiency) and RTS (returns to scale) over a time horizon. Many previous DEA (Data Envelopment Analysis) studies have discussed how to measure OE/RTS. However, their works did not consider the measurement over time. The important [...] Read more.

This study discusses the assessment of OE (operational efficiency) and RTS (returns to scale) over a time horizon. Many previous DEA (Data Envelopment Analysis) studies have discussed how to measure OE/RTS. However, their works did not consider the measurement over time. The important feature of the proposed approach is that our models are different from standard ones in terms of factor (inputs and outputs) unification. A problem with standard models is that they produce different efficiency measures for input and output orientations. Consequently, they yield different OE and RTS estimates depending upon which production factor is used for measurement. To handle the difficulty, we develop a new DEA formulation whose efficiency measure is determined after combining inputs and outputs, and then we discuss how to measure the types of RTS. The other methodological feature is that the proposed model incorporates a time horizon. As an empirical application, this study considers electricity generation and transmission across Chinese provinces from 2006 to 2019. The first key outcome is that the performance of China’s electricity generation and transmission system tends to improve with an annual growth rate of 0.45% across time. The second outcome is that, during the observed periods, China has more occurrences of decreasing rather than increasing RTS. As an implication, some provinces (e.g., Jiangxi and Hainan) need to increase their generation sizes to enhance their OE measures, while other provinces (e.g., Jiangsu and Zhejiang) should decrease their generation sizes. Finally, this study confirms significant technological heterogeneity across Chinese provinces and groups. Full article

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Graphical abstract

11 pages, 2334 KiB

Open AccessArticle

Influence of Dielectric Liquid Type on Partial-Discharge Inception Voltage in Oil-Wedge-Type Insulating System under AC Stress

by Bartlomiej Pasternak and Pawel Rozga

Energies 2023, 16(2), 1005; https://doi.org/10.3390/en16021005 - 16 Jan 2023

Cited by 4 | Viewed by 1689 | Correction

Abstract

This article describes the results of laboratory tests on an oil-wedge-type electrode system, which were supplemented by FEM (finite element method) simulations. The studies were focused on the comparison of the partial-discharge inception voltage (PDIV) in the abovementioned system when immersed in different [...] Read more.

This article describes the results of laboratory tests on an oil-wedge-type electrode system, which were supplemented by FEM (finite element method) simulations. The studies were focused on the comparison of the partial-discharge inception voltage (PDIV) in the abovementioned system when immersed in different liquid dielectrics, namely inhibited mineral oil, uninhibited mineral oil, synthetic ester, and natural ester. In addition, the electric field stress obtained from the simulations was used in each case to determine the safe level for the actual transformer insulation. The studies were performed under AC voltage. Both electrical and optical detection methods were applied in order to properly determine the discharge inception. The statistical analysis of the results obtained from the laboratory measurements was carried out using Weibull distribution. We found that both mineral oils demonstrated better properties than the ester liquids in terms of resistance against partial-discharge appearance under the conditions of the oil-wedge-type electrode model. Therefore, for all considered cases, the inception electric field stress obtained from the FEM-based simulations corresponding to the partial-discharge inception voltage was found to be significantly higher than the commonly accepted safe design level, which is in the range of 10–12 kV/mm. This proved the good electrical strength of all liquids under test. Full article

(This article belongs to the Special Issue High Voltage Insulating Materials-Current State and Prospects 2022)

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24 pages, 1011 KiB

Open AccessArticle

The Influence of Digital Transformation and Supply Chain Integration on Overall Sustainable Supply Chain Performance: An Empirical Analysis from Manufacturing Companies in Morocco

by Imadeddine Oubrahim, Naoufal Sefiani and Ari Happonen

Energies 2023, 16(2), 1004; https://doi.org/10.3390/en16021004 - 16 Jan 2023

Cited by 16 | Viewed by 6134

Abstract

This study examined the association between digital transformation (DT), supply chain integration (SCI), and overall sustainable supply chain performance (OSSCP). The current literature has preliminarily explored the concepts of DT and SCI and their relationship with sustainable supply chain performance. However, real empirical [...] Read more.

This study examined the association between digital transformation (DT), supply chain integration (SCI), and overall sustainable supply chain performance (OSSCP). The current literature has preliminarily explored the concepts of DT and SCI and their relationship with sustainable supply chain performance. However, real empirical evidence of the direct impact of DT and SCI on OSSCP has been missing so far. To fill this gap, data were collected from 134 professionals working in international manufacturing companies operating in Morocco through a questionnaire-based survey from August 2022 to November 2022. A conceptual framework was developed based on DT, SCI, and OSSCP and analyzed by partial least squares structural equation modeling (PLS-SEM) with the assistance of SmartPLS 4.0 software. The findings revealed that DT has a significant positive influence on SCI and OSSCP. Furthermore, SCI directly and positively impacts OSSCP with a partial mediation effect on the relationship between DT and OSSCP. Further, this research provides insights for practitioners into enhancing sustainable supply chain performance by adopting digital technologies and integrating SC functions. In particular, this study revealed that DT adoption drives a higher ethical supply chain level from the perspective of sustainability and efficiency in operations. This study is the first to analyze the influence of digital transformation and supply chain integration on sustainable supply chain performance in a manufacturing context. Full article

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18 pages, 3440 KiB

Open AccessArticle

An Experimental Investigation on the Characteristics of a Compression Ignition Engine Fuelled by Diesel-Palm Biodiesel–Ethanol/Propanol Based Ternary Blends

by Navaneetha Krishnan Balakrishnan, Yew Heng Teoh, Heoy Geok How, Thanh Danh Le and Huu Tho Nguyen

Energies 2023, 16(2), 1003; https://doi.org/10.3390/en16021003 - 16 Jan 2023

Cited by 2 | Viewed by 1495

Abstract

Issues such as rising fuel prices, fuel costs, and lowering reserves highlight the importance of research into sustainable fuels derived from biological sources. This study is focused on experiments on a CI engine using ethanol and propanol-based ternary blends. Palm biodiesel is kept [...] Read more.

Issues such as rising fuel prices, fuel costs, and lowering reserves highlight the importance of research into sustainable fuels derived from biological sources. This study is focused on experiments on a CI engine using ethanol and propanol-based ternary blends. Palm biodiesel is kept constant at 40% volumetric concentration, while diesel and ethanol/propanol are varied in different batches. The results obtained with ternary blends were compared with reference fuel diesel, pure palm biodiesel, and a palm biodiesel–diesel binary blend. The ternary blends exhibit lower brake thermal efficiency and higher brake specific energy consumption than diesel and binary blends due to their lower calorific value. Despite in-fuel oxygen presence, lower brake specific oxides of nitrogen and smoke opacity were observed for engine operation with a ternary blend due to the predominant role of higher latent heat of vaporization and volatility of alcohols, but unburned hydrocarbon and carbon monoxide emissions increased due to the interactive effect of a lower cetane number, higher latent heat of vaporization, and lower kinematic viscosity of alcohols when compared to reference fuels. Among the tested fuels, in-cylinder pressure was observed to decrease with ternary blends due to their lower calorific value, but a raised heat release rate was attributed to lower viscosity and faster burning of alcohols. Full article

(This article belongs to the Special Issue Advances in Biodiesel for Application in Diesel Engines)

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14 pages, 465 KiB

Open AccessArticle

The Role of Energy Transition and International Tourism in Mitigating Environmental Degradation: Evidence from SEE Countries

by Elma Satrovic and Festus Fatai Adedoyin

Energies 2023, 16(2), 1002; https://doi.org/10.3390/en16021002 - 16 Jan 2023

Cited by 19 | Viewed by 1932

Abstract

Since curbing the upward trend of energy consumption has become a global pursuit in achieving environmental sustainability, macroeconomic factors such as energy transition and international tourism may be of crucial importance in mitigating environmental degradation. However, the combined role of economic welfare, population, [...] Read more.

Since curbing the upward trend of energy consumption has become a global pursuit in achieving environmental sustainability, macroeconomic factors such as energy transition and international tourism may be of crucial importance in mitigating environmental degradation. However, the combined role of economic welfare, population, international tourism, and energy transition towards mitigating environmental degradation has not been investigated extensively. In this regard, this study looks at the combined interplay between these variables for a panel of ten southeastern Europe (SEE) countries, covering the period of 1997–2018 under the umbrella of the environmental Kuznets curve (EKC) phenomenon. Two indicators of environmental degradation, namely, ecological footprint and carbon intensity, were used in this study. The ordinary least squares (OLS) regression with Driscoll–Kraay (DK) and the panel Method of Moments Quantile Regression (MMQR) with fixed effects were used to disclose the following outcomes: firstly, the environmental degradation–economic welfare nexus firmly established an inverted U-shaped relationship, thereby depicting the validity of the EKC hypothesis. Secondly, energy transition and international tourism manifest negative effects: they induce environmental degradation. Thirdly, the impact of the population is positive but not significant. Given the empirical outcomes, energy transition and international tourism are proposed as critical to mitigating the environmental degradation of the inspected sample of countries. Full article

(This article belongs to the Section C: Energy Economics and Policy)

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13 pages, 3859 KiB

Open AccessArticle

Research on Laboratory Test Method of Wave Energy Converter Wave-Wire Conversion Ratio in Irregular Waves

by Liang Shangguan, Kuan Lu and Huamei Wang

Energies 2023, 16(2), 1001; https://doi.org/10.3390/en16021001 - 16 Jan 2023

Cited by 3 | Viewed by 1487

Abstract

The laboratory test of the wave energy converter model is an important means to evaluate the performance of the device. At present, there are few performance tests for complete specifications under the irregular wave. Referring to the test methods and standards at home [...] Read more.

The laboratory test of the wave energy converter model is an important means to evaluate the performance of the device. At present, there are few performance tests for complete specifications under the irregular wave. Referring to the test methods and standards at home and abroad, combined with the actual test work experience in the laboratory, using the irregular wave power calculation formula with the effective wave height and the spectral peak period as parameters, then the wave-wire conversion ratio test method of the wave energy converter physical model under irregular waves in the laboratory is proposed. The method is applied to the basin test experiment of the physical model of the horn-shaped backward bent duct buoy (BBDB) wave energy converter. The research results show that the established test method and process of wave-wire conversion performance have achieved good application results in the irregular waves laboratory test, and can better reflect the device operating characteristics in real sea conditions. The test results provide data support for the model design of the wave energy converter in the next test stage, the demonstration test of the prototype, and the prediction of power generation in real sea conditions. Full article

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17 pages, 3561 KiB

Open AccessArticle

Optimal Management of a Virtual Power Plant Consisting of Renewable Energy Resources and Electric Vehicles Using Mixed-Integer Linear Programming and Deep Learning

by Ali Ahmadian, Kumaraswamy Ponnambalam, Ali Almansoori and Ali Elkamel

Energies 2023, 16(2), 1000; https://doi.org/10.3390/en16021000 - 16 Jan 2023

Cited by 7 | Viewed by 2071

Abstract

Recently, renewable energy resources (RESs) and electric vehicles (EVs), in addition to other distributed energy resources (DERs), have gained high popularity in power systems applications. These resources bring quite a few advantages for power systems—reducing carbon emission, increasing efficiency, and reducing power loss. [...] Read more.

Recently, renewable energy resources (RESs) and electric vehicles (EVs), in addition to other distributed energy resources (DERs), have gained high popularity in power systems applications. These resources bring quite a few advantages for power systems—reducing carbon emission, increasing efficiency, and reducing power loss. However, they also bring some disadvantages for the network because of their intermittent behavior and their high number in the grid which makes the optimal management of the system a tough task. Virtual power plants (VPPs) are introduced as a promising solution to make the most out of these resources by aggregating them as a single entity. On the other hand, VPP’s optimal management depends on its accuracy in modeling stochastic parameters in the VPP body. In this regard, an efficient approach for a VPP is a method that can overcome these intermittent resources. In this paper, a comprehensive study has been investigated for the optimal management of a VPP by modeling different resources—RESs, energy storages, EVs, and distributed generations. In addition, a method based on bi-directional long short-term memory networks is investigated for forecasting various stochastic parameters, wind speed, electricity price, load demand, and EVs’ behavior. The results of this study show the superiority of BLSTM methods for modeling these parameters with an error of 1.47% in comparison with real data. Furthermore, to show the performance of BLSTMs, its results are compared with other benchmark methods such as shallow neural networks, support vector machines, and long short-term memory networks. Full article

(This article belongs to the Special Issue Advanced Machine Learning Applications in Modern Energy Systems)

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