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20 pages, 1257 KiB

Open AccessArticle

Solar Business in an Oil-Rich Country? A Socio-Technical Investigation of Solar PV Businesses in Iran

by Leila Aghlimoghadam

Sustainability 2023, 15(11), 8973; https://doi.org/10.3390/su15118973 - 1 Jun 2023

Cited by 1 | Viewed by 1599

Abstract

Market acceptance of renewable energy technologies involves both the demand and supply sides, though the main empirical literature has focused on the demand side under the titles like public, communities, users’, market or even social acceptance. In this study, I focus on solar [...] Read more.

Market acceptance of renewable energy technologies involves both the demand and supply sides, though the main empirical literature has focused on the demand side under the titles like public, communities, users’, market or even social acceptance. In this study, I focus on solar businesses (niche actors) as the suppliers of solar PV services in Iran. My main research questions are: (i) which factors drive solar businesses to establish and do business in the solar PV field despite the fossil-based economy and energy policies in Iran? (ii) what are the practical barriers to solar business in Iran? and (iii) which roles do Iranian solar businesses play in bringing solar PV development forward? I collected the data via 20 semi-structured interviews with solar businesspeople in diverse Provinces in Iran. Taking an inductive approach (Grounded Theory) toward the data, my results lead to significant insights: the dominance of intrinsic behavioural drivers over the major extrinsic barriers among Iranian solar businesspeople, moreover to their key roles in educating people and driving the innovative deployment of solar PV. This research helps to inform first, policymakers about the existing potential among solar businesses, and second the solar businesses themselves about adopting better business strategies. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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26 pages, 8870 KiB

Open AccessArticle

Comparative Performance Analysis of a Grid-Connected Photovoltaic Plant in Central Greece after Several Years of Operation Using Neural Networks

by Elias Roumpakias and Tassos Stamatelos

Sustainability 2023, 15(10), 8326; https://doi.org/10.3390/su15108326 - 19 May 2023

Cited by 2 | Viewed by 1362

Abstract

The increasing installed volume of grid-connected PV systems in modern electricity networks induces variability and uncertainty factors which must be addressed from several different viewpoints, including systems’ protection and management. This study aims to estimate the actual performance and degradation of photovoltaic (PV) [...] Read more.

The increasing installed volume of grid-connected PV systems in modern electricity networks induces variability and uncertainty factors which must be addressed from several different viewpoints, including systems’ protection and management. This study aims to estimate the actual performance and degradation of photovoltaic (PV) parks in Central Greece after several years of operation. Monitoring data over several years are analyzed and filtered, the performance ratio and normalized efficiency are computed, and five different ANNs are employed: (i) a feed-forward network (one hidden layer); (ii) a deep feed-forward network (two hidden layers); (iii) a recurrent neural network; (iv) a cascade-forward network; and (v) a nonlinear autoregressive network. The following inputs are employed: in-plane irradiance; backsheet panel temperature; airmass; clearness index; and DC voltage of the inverter. Monitoring data from an 8-year operation of a grid-connected PV system are employed for training, testing, and validation of these networks. They act as a baseline, built from the first year, and the computed metrics act as indicators of faults or degradation. Best accuracy is reached with the DFFNN. The ANNs are trained with data from the first year of operation, and output prediction is carried out for the remaining years. Annual electricity generation exceeds 1600 kWh /kWp, and MAPE values show an increasing trend over the years. This fact indicates a possible change in PV performance. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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16 pages, 8314 KiB

Open AccessArticle

Classification Method of Photovoltaic Array Operating State Based on Nonparametric Estimation and 3σ Method

by Qiang Tong, Donghui Li, Xin Ren, Hua Wang, Qing Wu, Li Zhou, Jiaqi Li and Honglu Zhu

Sustainability 2023, 15(10), 7769; https://doi.org/10.3390/su15107769 - 9 May 2023

Viewed by 1400

Abstract

Photovoltaic (PV) array, as the key component of large-scale PV power stations, is prone to frequent failure that directly affects the efficiency of PV power stations. Therefore, accurate classification of the operating state of PV arrays is the basis for fault location. Thus, [...] Read more.

Photovoltaic (PV) array, as the key component of large-scale PV power stations, is prone to frequent failure that directly affects the efficiency of PV power stations. Therefore, accurate classification of the operating state of PV arrays is the basis for fault location. Thus, a novel classification method for PV array operating state was designed based on nonparametric estimation and a 3σ method. The actual data analysis proves the hypothesis that performance ratio (PR) distribution characteristics of PV arrays can characterize the operating state of PV arrays. The modeling curve of the PV array with an excellent performance has only one peak and the peak value is large, while the distribution curve of the PV array with a poor performance has a small peak. In this paper, the distribution characteristics of PV arrays are modeled, the peak value is used to classify the operating state of PV arrays, and finally the effectiveness of the proposed method is compared. Overall, this paper makes a valuable contribution by proposing a novel method for accurately classifying the operating state of PV arrays. The proposed method can help improve the efficiency and fault diagnosis of PV power stations. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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16 pages, 10363 KiB

Open AccessArticle

A Novel Operating State Evaluation Method for Photovoltaic Strings Based on TOPSIS and Its Application

by Xiaofei Li, Zhao Wang, Yinnan Liu, Haifeng Wang, Liusheng Pei, An Wu, Shuang Sun, Yongjun Lian and Honglu Zhu

Sustainability 2023, 15(9), 7268; https://doi.org/10.3390/su15097268 - 27 Apr 2023

Cited by 1 | Viewed by 1256

Abstract

PV strings are essential for energy conversion in large-scale photovoltaic (PV) power plants. The operating state of PV strings directly affects the power generation efficiency and economic benefits of PV power plants. In the process of evaluating PV arrays, a reference array needs [...] Read more.

PV strings are essential for energy conversion in large-scale photovoltaic (PV) power plants. The operating state of PV strings directly affects the power generation efficiency and economic benefits of PV power plants. In the process of evaluating PV arrays, a reference array needs to be identified. By comparing PV arrays with the reference array, the operational status of the PV arrays can be evaluated. However, in the actual operation of PV power stations, it is difficult to directly determine the reference state of a PV array due to random fluctuations in the PV power output. In order to solve the problems mentioned above, this paper proposes a method to select the reference state and perform a grading evaluation of PV strings. Additionally, the proposed method is based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm, which is used to rank the performance of PV arrays to determine their status. In order to solve the problem of random fluctuations in PV power generation, a probability distribution model of the PV string conversion efficiency was built by using the kernel density estimation method. Then, the characteristic indicator of the PV string’s operating state was described by the output power of the PV string and its probability distribution model. Then, based on the operating characteristic indicator, the reference state of the PV string was determined using the TOPSIS method, and the grading evaluation of the operating state of the PV string was realized. Finally, the effectiveness of the proposed method was verified using the actual data of a PV power station. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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18 pages, 7351 KiB

Open AccessArticle

CFD Analysis of the Heat Transfer and Fluid Flow Characteristics Using the Rectangular Rib Attached to the Fin Surface in a Solar Air Heater

by Hwi-Ung Choi, Kwang-Am Moon, Seong-Bhin Kim and Kwang-Hwan Choi

Sustainability 2023, 15(6), 5382; https://doi.org/10.3390/su15065382 - 17 Mar 2023

Cited by 3 | Viewed by 1815

Abstract

This study discussed the effect of ribbed fin, which was suggested by the authors, on the enhancement of heat transfer and flow characteristics of fluid in a solar air heater. The ribbed fin has a rectangular rib at the base and side surfaces [...] Read more.

This study discussed the effect of ribbed fin, which was suggested by the authors, on the enhancement of heat transfer and flow characteristics of fluid in a solar air heater. The ribbed fin has a rectangular rib at the base and side surfaces of the fin. Thus, it can increase the heat transfer coefficient in the fluid field of a solar air heater as well as extend the heat transfer area. The simulation was performed with various Reynolds numbers, relative heights, and pitches of the rib. The presence of the rib enhances the heat transfer performance by 3.497 times over a smooth fin. However, the addition of the rib also increases pressure drop. Thus, the thermo-hydraulic performance, which considers both heat transfer enhancement and pressure drop increase, was also discussed. Furthermore, this study developed correlations for the Nusselt number and friction factor as a function of geometric condition of the rib and Reynolds number. The correlations accurately predicted the Nusselt number for the base and side surfaces of the fin and friction factor with mean absolute percent errors of 4.24%, 4.53%, and 7.33%, respectively. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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14 pages, 7022 KiB

Open AccessArticle

Measurement and Analysis of Light Leakage in Plastic Optical Fiber Daylighting System

by Kunhao Liu, Lianglin Zou, Yuanlong Li, Kai Wang, Haiyu Wang and Jifeng Song

Sustainability 2023, 15(4), 3155; https://doi.org/10.3390/su15043155 - 9 Feb 2023

Cited by 4 | Viewed by 2390

Abstract

The daylighting systems via polymethylmethacrylate (PMMA) plastic optical fibers have obvious cost advantages and have been widely studied. However, there is light leakage when PMMA optical fibers transmit concentrated sunlight, resulting in a transmission efficiency lower than the theoretical value. This research aims [...] Read more.

The daylighting systems via polymethylmethacrylate (PMMA) plastic optical fibers have obvious cost advantages and have been widely studied. However, there is light leakage when PMMA optical fibers transmit concentrated sunlight, resulting in a transmission efficiency lower than the theoretical value. This research aims to quantitatively study the light leakage effect of PMMA optical fibers. Concentrated sunlight was used as the sunlight source instead of a monochromatic laser. An adjustable diaphragm was used to adjust the angle of the incident light, and the infrared filter and heat-absorbing glass were used to solve the overheating problem of PMMA fibers. The results show that when the incident angle is greater than 13°, the relative transmission efficiency of the fibers drops rapidly, which means that the light leakage deteriorates. The data also show that the angle of the output beam of PMMA optical fibers is ±30°, which is independent of the angle of the incident beam. Based on this conclusion, a PMMA optical fiber daylighting system with an incident angle of 13° was developed, which has higher transmission efficiency than previously developed systems. This study indicates that the angle effect of light leakage should be considered in the design of a plastic optical fiber daylighting system. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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11 pages, 3315 KiB

Open AccessArticle

Analysis of Laser Cell Response Characteristics under Different Irradiation Conditions

by Xudong Wang, Jinmao Chen, Chunhua Xiong, Shizhan Li and Wanli Xu

Sustainability 2023, 15(4), 3082; https://doi.org/10.3390/su15043082 - 8 Feb 2023

Viewed by 1503

Abstract

Although the application of laser wireless energy transmission technology in many fields such as UAV power supply is increasing, the laser incidence angle and beam shift remain the key factors limiting the efficiency of long-range laser wireless energy transmission. In this study, a [...] Read more.

Although the application of laser wireless energy transmission technology in many fields such as UAV power supply is increasing, the laser incidence angle and beam shift remain the key factors limiting the efficiency of long-range laser wireless energy transmission. In this study, a laser cell response test platform was built to measure and analyze the response characteristics of a laser cell under different laser incidence angles and beam shifts. The results show that the increase in the incident angle intensifies the reflection on the irradiated surface, resulting in a linear decrease in the power density received by the laser cell, which eventually leads to a significant decrease in the output power, and the output power tends to be close to 0 when the incident angle exceeds 75°. The increase in the beam offset distance increases the reverse bias of the cell, which is the main reason for the significant decrease in the output power. The local irradiation also leads to an increase in the heat generation power; when the beam coverage is below 50%, the overall output power tends to be close to 0. This study provides a reference for improving the laser wireless energy transmission efficiency and laser cell optimization. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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19 pages, 4770 KiB

Open AccessArticle

Effects of Double-Diffusive Convection on Calculation Time and Accuracy Results of a Salt Gradient Solar Pond: Numerical Investigation and Experimental Validation

by Yassmine Rghif, Daniele Colarossi and Paolo Principi

Sustainability 2023, 15(2), 1479; https://doi.org/10.3390/su15021479 - 12 Jan 2023

Cited by 7 | Viewed by 1623

Abstract

The main aim of this study is to investigate numerically and experimentally the effects of double-diffusive convection on calculation time and accuracy results of a Salt Gradient Solar Pond (SGSP). To this end, two-numerical models are developed based on the Fortran programming language. [...] Read more.

The main aim of this study is to investigate numerically and experimentally the effects of double-diffusive convection on calculation time and accuracy results of a Salt Gradient Solar Pond (SGSP). To this end, two-numerical models are developed based on the Fortran programming language. The first one is based on energy balance neglecting the development of double-diffusive convection, while the second is two-dimensional and is based on Navier-Stokes, heat, and mass transfer equations considering the development of double-diffusive convection. The heat losses via the upper part, bottom, and vertical walls, as well as the internal heating of saltwater, are considered. In order to validate and compare both numerical models, a laboratory-scale SGSP is designed, built, and tested indoors for 82 h. Results indicate that the two numerical models developed can predict the SGSP thermal behavior with good accuracy. Furthermore, the average relative error between experimental and numerical results is around 9.39% for Upper Convective Zone (UCZ) and 2.92% for Lower Convective Zone (LCZ) based on the first model. This error reduces to about 5.98% for UCZ and 3.74% for LCZ by using the second model. Consequently, the neglect of double-diffusive convection in the SGSP modeling tends to overestimate the thermal energy stored in the storage zone by about 4.3%. Based on the calculation time analysis, results show that the second model returns a calculation time hundreds of times larger than the first one and, accordingly, an increase in computational cost. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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20 pages, 7341 KiB

Open AccessArticle

A New Regional Distributed Photovoltaic Power Calculation Method Based on FCM-mRMR and nELM Model

by Honglu Zhu, Tingting Jiang, Yahui Sun and Shuang Sun

Sustainability 2022, 14(21), 13880; https://doi.org/10.3390/su142113880 - 26 Oct 2022

Cited by 2 | Viewed by 1508

Abstract

As the proportion of distributed photovoltaic (DP) increases, improving the accuracy of regional distributed photovoltaic power calculation is crucial to making full use of PV and ensuring the safety of the power system. The calculation of regional power generation is the key to [...] Read more.

As the proportion of distributed photovoltaic (DP) increases, improving the accuracy of regional distributed photovoltaic power calculation is crucial to making full use of PV and ensuring the safety of the power system. The calculation of regional power generation is the key to power prediction, performance evaluation, and fault diagnosis. Distributed photovoltaic plants (DPP) are characterized by scattered distribution and small installed capacity, lots of DPPs are not fully monitored, and their real-time output power is difficult to obtain. Therefore, to improve the observability of DPPs and increase the accuracy of calculation, a new method that combines with fuzzy c-means (FCM), Max-Relevance and Min-Redundancy (mRMR) and Extreme Learning Machine(ELM), which can calculate the regional DPP output power without meteorological data is proposed, and validated using actual operational data of regional DPPs in China. The calculations results show good robustness in different months. The innovation of this study is the combination of the benchmark DPP selection method FCM-mRMR and the power calculation method nELM, and the mean absolute error (MAPE) of the proposed method is 0.198 and the coefficient of determination (R2) is 0.996. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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16 pages, 4714 KiB

Open AccessArticle

Method of Predicting SOH and RUL of Lithium-Ion Battery Based on the Combination of LSTM and GPR

by Jiahui Zhao, Yong Zhu, Bin Zhang, Mingyi Liu, Jianxing Wang, Chenghao Liu and Yuanyuan Zhang

Sustainability 2022, 14(19), 11865; https://doi.org/10.3390/su141911865 - 21 Sep 2022

Cited by 26 | Viewed by 3705

Abstract

The state of health and remaining useful life of lithium-ion batteries are important indicators to ensure the reliable operation of these batteries. However, because they cannot be directly measured and are affected by many factors, they are difficult to predict. This paper presents [...] Read more.

The state of health and remaining useful life of lithium-ion batteries are important indicators to ensure the reliable operation of these batteries. However, because they cannot be directly measured and are affected by many factors, they are difficult to predict. This paper presents method of jointly predicting state of health and RUL based on the long short-term memory neural network and Gaussian process regression. This method extracts the batteries’ health factors from the charging curve, selects health factors with more relevance than the setting standard as the characteristic of capacity by the maximum information coefficient method, and establishes the battery aging and remaining useful life prediction models with Gaussian process regression. On this basis, the long short-term memory neural network is used to predict the trend of the change in health factors with the increase in cycles, and the results are input into a Gaussian process regression aging model to predict the state of health. Taking the health factors and state of health as the characteristics of remaining useful battery life, a battery remaining useful life model based on Gaussian process regression is established, and the change trend in the remaining useful life can be obtained by inputting the predicted health factors and state of health. In this study, four battery data sets with different depths of charge were used to verify the accuracy and adaptability of the algorithm. The results show that the proposed algorithm has high accuracy and reliability. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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16 pages, 15355 KiB

Open AccessArticle

Highly Concentrated Solar Flux of Large Fresnel Lens Using CCD Camera-Based Method

by Kexin Zhang, Ying Su, Haiyu Wang, Qian Wang, Kai Wang, Yisen Niu and Jifeng Song

Sustainability 2022, 14(17), 11062; https://doi.org/10.3390/su141711062 - 5 Sep 2022

Cited by 6 | Viewed by 3002

Abstract

Fresnel lens is a kind of lens that can concentrate sunlight up to a level of thousands of suns with small space occupation which is widely used in the research of sunlight concentration and transmission systems via optical fiber. Most studies on the [...] Read more.

Fresnel lens is a kind of lens that can concentrate sunlight up to a level of thousands of suns with small space occupation which is widely used in the research of sunlight concentration and transmission systems via optical fiber. Most studies on the concentrated flux of lenses use experimental methods to measure the flux distribution on the receiver of parabolic trough solar concentrators, solar power towers, and parabolic dish concentrators, while for Fresnel lenses, especially large-aperture Fresnel lenses such as the one in this manuscript, the simulation approach was mostly used. In response to this problem, this study has developed an experimental system for measuring the concentrated flux density of Fresnel lenses. A charge-coupled device (CCD) camera was used to capture the image of spot of large-aperture (968 mm) Fresnel lenses in the CCD camera-based method, and a heat flow meter was used to calibrate the spot brightness image obtained by the CCD camera. Experimental data show that the peak flux of concentrated spot can reach 4.06 MW/m². This method confirms the simulation results of previous studies that using the rays tracing method, that is, the flux level of the Fresnel lenses can reach 5000 suns. The experimental results demonstrated the CCD camera-based method combined with a heat flow meter is competent in measuring the intensity of flux with a level of 5000 suns. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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14 pages, 3000 KiB

Open AccessArticle

Potential Failure Prediction of Lithium-ion Battery Energy Storage System by Isolation Density Method

by Yong Zhu, Mingyi Liu, Lin Wang and Jianxing Wang

Sustainability 2022, 14(12), 7048; https://doi.org/10.3390/su14127048 - 9 Jun 2022

Cited by 3 | Viewed by 2318

Abstract

Lithium-ion battery energy storage systems have achieved rapid development and are a key part of the achievement of renewable energy transition and the 2030 “Carbon Peak” strategy of China. However, due to the complexity of this electrochemical equipment, the large-scale use of lithium-ion [...] Read more.

Lithium-ion battery energy storage systems have achieved rapid development and are a key part of the achievement of renewable energy transition and the 2030 “Carbon Peak” strategy of China. However, due to the complexity of this electrochemical equipment, the large-scale use of lithium-ion batteries brings severe challenges to the safety of the energy storage system. In this paper, a new method, based simultaneously on the concepts of statistics and density, is proposed for the potential failure prediction of lithium-ion batteries. As there are no strong assumptions about feature independence and sample distribution, and the estimation of the anomaly scores is conducted by integrating several trees on the isolation path, the algorithm has strong adaptability and robustness, simultaneously. For validation, the proposed method was first applied to two artificial datasets, and the results showed that the method was effective in dealing with different types of anomalies. Then, a comprehensive evaluation was carried out on six public datasets, and the proposed method showed a better performance with different criteria when compared to the conventional algorithms. Finally, the potential failure prediction of lithium-ion batteries of a real energy storage system was conducted in this paper. In order to make full use of the time series characteristics, voltage variation during a whole discharge cycle was taken as the representation of the operation condition of the lithium-ion batteries, and three different types of voltage deviation anomalies were successfully detected. The proposed method can be effectively used for the predictive maintenance of energy storage systems. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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Review

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22 pages, 3690 KiB

Open AccessReview

Review of State Estimation and Remaining Useful Life Prediction Methods for Lithium–Ion Batteries

by Jiahui Zhao, Yong Zhu, Bin Zhang, Mingyi Liu, Jianxing Wang, Chenghao Liu and Xiaowei Hao

Sustainability 2023, 15(6), 5014; https://doi.org/10.3390/su15065014 - 11 Mar 2023

Cited by 38 | Viewed by 5563

Abstract

The accurate estimation of the state of charge, the state of health and the prediction of remaining useful life of lithium–ion batteries is an important component of battery management. It is of great significance to prolong battery life and ensure the reliability of [...] Read more.

The accurate estimation of the state of charge, the state of health and the prediction of remaining useful life of lithium–ion batteries is an important component of battery management. It is of great significance to prolong battery life and ensure the reliability of the battery system. Many researchers have completed a large amount of work on battery state evaluation and RUL prediction methods and proposed a variety of methods. This paper first introduces the definition of the SOC, the SOH and the existing estimation methods. Then, the definition of RUL is introduced, and the main methods are classified and compared. Finally, the challenges of lithium–ion battery state estimation and RUL prediction are summarized, and the direction for future development is proposed. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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15 pages, 1684 KiB

Open AccessReview

Progress and Applications of Seawater-Activated Batteries

by Jinmao Chen, Wanli Xu, Xudong Wang, Shasha Yang and Chunhua Xiong

Sustainability 2023, 15(2), 1635; https://doi.org/10.3390/su15021635 - 13 Jan 2023

Cited by 12 | Viewed by 12486

Abstract

Obtaining energy from renewable natural resources has attracted substantial attention owing to their abundance and sustainability. Seawater is a naturally available, abundant, and renewable resource that covers >70% of the Earth’s surface. Reserve batteries may be activated by using seawater as a source [...] Read more.

Obtaining energy from renewable natural resources has attracted substantial attention owing to their abundance and sustainability. Seawater is a naturally available, abundant, and renewable resource that covers >70% of the Earth’s surface. Reserve batteries may be activated by using seawater as a source of electrolytes. These batteries are very safe and offer a high power density, stable discharge voltage, high specific energy, and long dry storage life and are widely used in marine exploration instruments, life-saving equipment, and underwater weaponry. This review provides a comprehensive introduction to seawater-activated batteries. Here, we classify seawater-activated batteries into metal semi-fuel, high-power, and rechargeable batteries according to the different functions of seawater within them. The working principles and characteristics of these batteries are then introduced, and we describe their research statuses and practical applications. Finally, we provide an outlook on the development of seawater-activated batteries and highlight practical issues to drive further progress. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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23 pages, 6555 KiB

Open AccessReview

Issues Concerning Interfaces with Inorganic Solid Electrolytes in All-Solid-State Lithium Metal Batteries

by Zhouting Sun, Mingyi Liu, Yong Zhu, Ruochen Xu, Zhiqiang Chen, Peng Zhang, Zeyu Lu, Pengcheng Wang and Chengrui Wang

Sustainability 2022, 14(15), 9090; https://doi.org/10.3390/su14159090 - 25 Jul 2022

Cited by 11 | Viewed by 4178

Abstract

All-solid-state batteries have attracted wide attention for high-performance and safe batteries. The combination of solid electrolytes and lithium metal anodes makes high-energy batteries practical for next-generation high-performance devices. However, when a solid electrolyte replaces the liquid electrolyte, many different interface/interphase issues have arisen [...] Read more.

All-solid-state batteries have attracted wide attention for high-performance and safe batteries. The combination of solid electrolytes and lithium metal anodes makes high-energy batteries practical for next-generation high-performance devices. However, when a solid electrolyte replaces the liquid electrolyte, many different interface/interphase issues have arisen from the contact with electrodes. Poor wettability and unstable chemical/electrochemical reaction at the interfaces with lithium metal anodes will lead to poor lithium diffusion kinetics and combustion of fresh lithium and active materials in the electrolyte. Element cross-diffusion and charge layer formation at the interfaces with cathodes also impede the lithium ionic conductivity and increase the charge transfer resistance. The abovementioned interface issues hinder the electrochemical performance of all-solid-state lithium metal batteries. This review demonstrates the formation and mechanism of these interface issues between solid electrolytes and anodes/cathodes. Aiming to address the problems, we review and propose modification strategies to weaken interface resistance and improve the electrochemical performance of all-solid-state lithium metal batteries. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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Other

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17 pages, 2098 KiB

Open AccessViewpoint

Research on Integrated Customer-Side Energy System Planning Method Considering Carbon Emission Reduction

by Cong Liu and Yongjie Zhang

Sustainability 2022, 14(17), 10868; https://doi.org/10.3390/su141710868 - 31 Aug 2022

Viewed by 1118

Abstract

With the improvement of the urbanization level, the energy demand of users continues to increase, which also brings a series of problems. Therefore, in order to effectively solve these problems, energy transformation has begun, and the traditional energy supply model is gradually changing [...] Read more.

With the improvement of the urbanization level, the energy demand of users continues to increase, which also brings a series of problems. Therefore, in order to effectively solve these problems, energy transformation has begun, and the traditional energy supply model is gradually changing to a diversified and coordinated supply of cold, heat, electricity, and gas. The integrated energy system is not only one of the important means for China to realize the energy revolution, but also one of the important carriers to realize China’s dual carbon goal, because it can realize the coupling and synergy between different energy subsystems and reduce carbon, while also saving costs. Integrated energy system planning is one of the core technologies of integrated energy. Because the load demand of the community will change with time, as a result, this paper studies the typical scenario use frequency of different types of equipment, combined with the energy-pricing method, considering the energy factors such as carbon and energy prices and investment capacity; building area, power supply; equipment operation; and construction-cost factors such as natural gas network and reliability. In order to minimize the total life-cycle cost and total carbon emissions, a dual-objective expansion planning optimization model of integrated energy system was established, and an energy pricing model was added to the capacity optimization of equipment planning. Finally, through the determination of typical scenarios, the economic performance and environmental performance of the three scenarios were compared and analyzed to verify the effectiveness and superiority of the planning model. Full article

(This article belongs to the Special Issue Climate Change and Sustainability: Collective Wisdom in the Solar Energy Sector)

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