ALBERT

Description / Table of Contents: The reversible elimination of hydrogen from metal hydrides serves as the basis for unique methods of energy transformation. This technology has found widespread practical utilization in applications such as hydrogen compressors, storage, and sensors, as well as batteries. Moreover, it is plausible that metal hydride technology could be utilized to provide practically viable solutions to the challenges of energy storage. For nearly two decades, an extensive, worldwide research effort has been devoted to complex metal hydrides possessing high volumetric and/or gravimetric hydrogen densities with the goal of their practical utilization as onboard hydrogen storage materials. Additionally, a significant and growing number of efforts have been devoted to developing metal hydrides as advanced sensors and ionic conductors, and for electrochemical and stationary energy storage. This Special Issue will provide a sampling of on-going, state-of-art research on metal hydrides, ranging from fundamental investigations to practical applications with a concentration on topics which are currently of high interest.

Description / Table of Contents: Biopolymers, as natural polysaccharides, are considered benign polymers for what concerns the environment. This is not a new invention, but at best a renaissance: the first type of polymers used by human kind were animal hides, cellulose, silk, wool. Among benefits of natural occurring biopolymers there are potential biocompatibility, renewable resources, low processing costs, tailoring of structure by genetic manipulation, and, as said, environmentally compatibility. Limits are, sometimes, premature degradation and high production costs due to the very high purity required for medical uses. Polysaccharides are not drugs by themselves, but their use in pharmaceutical field, for example as drug carriers or antimicrobial, anti-inflammatory or anticoagulant agents, is increasingly promising. Marine polysaccharides include chitin, chitosan, alginate, agar and carrageenans. Chitosan is a cationic carbohydrate biopolymer derived from chitin, the second most abundant polysaccharides present in nature after cellulose. The main sources of chitin are the shell wastes of shrimps, lobsters and crabs. For its characteristics, chitosan founds particular application as non viral vector in gene delivery. Films from chitosan are very tough and long lasting. Alginates derive from seaweed extraction (pheophyceae), and are mainly used in drug delivery and as hydrogels for immobilizing cells and enzymes, due to the mild conditions of cross-linking through bivalent cations (Ca2+). Agar (or agar-agar) and carrageenans are linear polysaccharides from red seaweeds. They are highly reactive chemically and are peculiar for thermoreversible gel formation. Exopolysaccharides (EPS), substantial components of the extracellular matrix of many cells of marine origin, also have to be mentioned for their potential interest in pharmaceuticals, and new EPS producing bacteria, particularly from extreme marine environments, are being isolated. The possibility of chemical modification, blending and addition of biodegradable additives allows to tailor the final properties of polysaccharides and opens the doors to wider applications, particularly in pharmaceutical area. This issue is intended to explore any new potentiality of marine polysaccharides, as those above mentioned, deriving from chemical or chemical-physical modifications, and the scaling-up of their pharmaceutical applications.

Description / Table of Contents: Biopolymers, as natural polysaccharides, are considered benign polymers for what concerns the environment. This is not a new invention, but at best a renaissance: the first type of polymers used by human kind were animal hides, cellulose, silk, wool. Among benefits of natural occurring biopolymers there are potential biocompatibility, renewable resources, low processing costs, tailoring of structure by genetic manipulation, and, as said, environmentally compatibility. Limits are, sometimes, premature degradation and high production costs due to the very high purity required for medical uses. Polysaccharides are not drugs by themselves, but their use in pharmaceutical field, for example as drug carriers or antimicrobial, anti-inflammatory or anticoagulant agents, is increasingly promising. Marine polysaccharides include chitin, chitosan, alginate, agar and carrageenans. Chitosan is a cationic carbohydrate biopolymer derived from chitin, the second most abundant polysaccharides present in nature after cellulose. The main sources of chitin are the shell wastes of shrimps, lobsters and crabs. For its characteristics, chitosan founds particular application as non viral vector in gene delivery. Films from chitosan are very tough and long lasting. Alginates derive from seaweed extraction (pheophyceae), and are mainly used in drug delivery and as hydrogels for immobilizing cells and enzymes, due to the mild conditions of cross-linking through bivalent cations (Ca2 ). Agar (or agar-agar) and carrageenans are linear polysaccharides from red seaweeds. They are highly reactive chemically and are peculiar for thermoreversible gel formation. Exopolysaccharides (EPS), substantial components of the extracellular matrix of many cells of marine origin, also have to be mentioned for their potential interest in pharmaceuticals, and new EPS producing bacteria, particularly from extreme marine environments, are being isolated.The possibility of chemical modification, blending and addition of biodegradable additives allows to tailor the final properties of polysaccharides and opens the doors to wider applications, particularly in pharmaceutical area. This issue is intended to explore any new potentiality of marine polysaccharides, as those above mentioned, deriving from chemical or chemical-physical modifications, and the scaling-up of their pharmaceutical applications.

Description / Table of Contents: Preface: Morphology and Internal Mixing of Atmospheric Particles / Atmosphere 2018, 9(7), 249; https://doi.org/10.3390/atmos9070249 --- PDF Full-text (692 KB) | HTML Full-text | XML Full-text / Immersion Freezing of Total Ambient Aerosols and Ice Residuals / Atmosphere 2018, 9(2), 55; https://doi.org/10.3390/atmos9020055 --- Influence of Common Assumptions Regarding Aerosol Composition and Mixing State on Predicted CCN Concentration / Atmosphere 2018, 9(2), 54; https://doi.org/10.3390/atmos9020054 --- Physicochemical Characteristics of Individual Aerosol Particles during the 2015 China Victory Day Parade in Beijing / Atmosphere 2018, 9(2), 40; https://doi.org/10.3390/atmos9020040 --- Quantifying Impacts of Aerosol Mixing State on Nucleation-Scavenging of Black Carbon Aerosol Particles / Atmosphere 2018, 9(1), 17; https://doi.org/10.3390/atmos9010017 --- Machine Learning to Predict the Global Distribution of Aerosol Mixing State Metrics / Atmosphere 2018, 9(1), 15; https://doi.org/10.3390/atmos9010015 --- Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15 / Atmosphere 2017, 8(9), 173; https://doi.org/10.3390/atmos8090173 --- Effect of Thermodenuding on the Structure of Nascent Flame Soot Aggregates / Atmosphere 2017, 8(9), 166; https://doi.org/10.3390/atmos8090166 --- The Impact of Sampling Medium and Environment on Particle Morphology / Atmosphere 2017, 8(9), 162; https://doi.org/10.3390/atmos8090162 --- Temperature-Dependent Diffusion of H2SO4 in Air at Atmospherically Relevant Conditions: Laboratory Measurements Using Laminar Flow Technique / Atmosphere 2017, 8(7), 132; https://doi.org/10.3390/atmos8070132 --- Monthly and Diurnal Variation of the Concentrations of Aerosol Surface Area in Fukuoka, Japan, Measured by Diffusion Charging Method / Atmosphere 2017, 8(7), 114; https://doi.org/10.3390/atmos8070114 --- Q-Space Analysis of the Light Scattering Phase Function of Particles with Any Shape / Atmosphere 2017, 8(4), 68; https://doi.org/10.3390/atmos8040068 --- Morphology, Composition, and Mixing State of Individual Aerosol Particles in Northeast China during Wintertime / Atmosphere 2017, 8(3), 47; https://doi.org/10.3390/atmos8030047

Description / Table of Contents: Zambon, I.; Colosimo, F.; Monarca, D.; Cecchini, M.; Gallucci, F.; Proto, A.; Lord, R.; Colantoni, A. An Innovative Agro-Forestry Supply Chain for Residual Biomass: Physicochemical Characterisation of Biochar from Olive and Hazelnut Pellets. Energies 2016, 9(7), 526; doi:10.3390/en9070526. http://www.mdpi.com/1996-1073/9/7/526 --- Liu, P.; Wang, Q.; Yan, D.; Fang, W.; Mao, L.; Wang, D.; Li, Y.; Ouyang, C.; Guo, M.; Cao, A. Effects of Biochar Amendment on Chloropicrin Adsorption and Degradation in Soil. Energies 2016, 9(11), 869; doi:10.3390/en9110869. http://www.mdpi.com/1996-1073/9/11/869 --- Fang, W.; Cao, A.; Yan, D.; Han, D.; Huang, B.; Li, J.; Liu, X.; Guo, M.; Wang, Q. The Effect of Two Types of Biochars on the Efficacy, Emission, Degradation, and Adsorption of the Fumigant Methyl Isothiocyanate. Energies 2017, 10(1), 16; doi:10.3390/en10010016. http://www.mdpi.com/1996-1073/10/1/16 --- Long, J.; Boyette, M. Analysis of Micronized Charcoal for Use in a Liquid Fuel Slurry. Energies 2017, 10(1), 25; doi:10.3390/en10010025. http://www.mdpi.com/1996-1073/10/1/25 --- Fuente-Hernández, A.; Lee, R.; Béland, N.; Zamboni, I.; Lavoie, J. Reduction of Furfural to Furfuryl Alcohol in Liquid Phase over a Biochar-Supported Platinum Catalyst. Energies 2017, 10(3), 286; doi:10.3390/en10030286. http://www.mdpi.com/1996-1073/10/3/286 --- Brassard, P.; Godbout, S.; Raghavan, V.; Palacios, J.; Grenier, M.; Zegan, D. The Production of Engineered Biochars in a Vertical Auger Pyrolysis Reactor for Carbon Sequestration. Energies 2017, 10(3), 288; doi:10.3390/en10030288. http://www.mdpi.com/1996-1073/10/3/288 --- González-Vázquez, M.; García, R.; Pevida, C.; Rubiera, F. Optimization of a Bubbling Fluidized Bed Plant for Low-Temperature Gasification of Biomass. Energies 2017, 10(3), 306; doi:10.3390/en10030306. http://www.mdpi.com/1996-1073/10/3/306 --- Yang, X.; Wang, H.; Strong, P.; Xu, S.; Liu, S.; Lu, K.; Sheng, K.; Guo, J.; Che, L.; He, L.; Ok, Y.; Yuan, G.; Shen, Y.; Chen, X. Thermal Properties of Biochars Derived from Waste Biomass Generated by Agricultural and Forestry Sectors. Energies 2017, 10(4), 469; doi:10.3390/en10040469. http://www.mdpi.com/1996-1073/10/4/469 --- Ellison, C.; McKeown, M.; Trabelsi, S.; Boldor, D. Dielectric Properties of Biomass/Biochar Mixtures at Microwave Frequencies. Energies 2017, 10(4), 502; doi:10.3390/en10040502. http://www.mdpi.com/1996-1073/10/4/502 --- Kang, S.; Sim, B.; Kim, J. Volume and Mass Measurement of a Burning Wood Pellet by Image Processing. Energies 2017, 10(5), 603; doi:10.3390/en10050603. http://www.mdpi.com/1996-1073/10/5/603 --- Tamošiūnas, A.; Chouchène, A.; Valatkevičius, P.; Gimžauskaitė, D.; Aikas, M.; Uscila, R.; Ghorbel, M.; Jeguirim, M. The Potential of Thermal Plasma Gasification of Olive Pomace Charcoal. Energies 2017, 10(5), 710; doi:10.3390/en10050710. http://www.mdpi.com/1996-1073/10/5/710 --- Guizani, C.; Jeguirim, M.; Valin, S.; Limousy, L.; Salvador, S. Biomass Chars: The Effects of Pyrolysis Conditions on Their Morphology, Structure, Chemical Properties and Reactivity. Energies 2017, 10(6), 796; doi:10.3390/en10060796. http://www.mdpi.com/1996-1073/10/6/796 --- Zhao, S.; Ta, N.; Wang, X. Effect of Temperature on the Structural and Physicochemical Properties of Biochar with Apple Tree Branches as Feedstock Material. Energies 2017, 10(9), 1293; doi:10.3390/en10091293. http://www.mdpi.com/1996-1073/10/9/1293 --- Wanassi, B.; Hariz, I.; Ghimbeu, C.; Vaulot, C.; Jeguirim, M. Green Carbon Composite-Derived Polymer Resin and Waste Cotton Fibers for the Removal of Alizarin Red S Dye. Energies 2017, 10(9), 1321; doi:10.3390/en10091321. http://www.mdpi.com/1996-1073/10/9/1321 --- Ghouma, I.; Jeguirim, M.; Sager, U.; Limousy, L.; Bennici, S.; Däuber, E.; Asbach, C.; Ligotski, R.; Schmidt, F.; Ouederni, A. The Potential of Activated Carbon Made of Agro-Industrial Residues in NOx Immissions Abatement. Energies 2017, 10(10), 1508; doi:10.3390/en10101508. http://www.mdpi.com/1996-1073/10/10/1508 --- Jeguirim, M.; Limousy, L. Biomass Chars: Elaboration, Characterization and Applications. Energies 2017, 10(12), 2040; doi:10.3390/en10122040. http://www.mdpi.com/1996-1073/10/12/2040

Description / Table of Contents: Belle, J.; Liu, Y. Evaluation of Aqua MODIS Collection 6 AOD Parameters for Air Quality Research over the Continental United States. Remote Sens. 2016, 8(10), 815; doi:10.3390/rs8100815. http://www.mdpi.com/2072-4292/8/10/815 --- Sun, K.; Chen, X.; Zhu, Z.; Zhang, T. High Resolution Aerosol Optical Depth Retrieval Using Gaofen-1 WFV Camera Data. Remote Sens. 2017, 9(1), 89; doi:10.3390/rs9010089. http://www.mdpi.com/2072-4292/9/1/89 --- Chen, X.; Yang, D.; Cai, Z.; Liu, Y.; Spurr, R. Aerosol Retrieval Sensitivity and Error Analysis for the Cloud and Aerosol Polarimetric Imager on Board TanSat: The Effect of Multi-Angle Measurement. Remote Sens. 2017, 9(2), 183; doi:10.3390/rs9020183. http://www.mdpi.com/2072-4292/9/2/183 --- Jiang, M.; Sun, W.; Yang, G.; Zhang, D. Modelling Seasonal GWR of Daily PM2.5 with Proper Auxiliary Variables for the Yangtze River Delta. Remote Sens. 2017, 9(4), 346; doi:10.3390/rs9040346. http://www.mdpi.com/2072-4292/9/4/346 --- Wang, Y.; Chen, L.; Li, S.; Wang, X.; Yu, C.; Si, Y.; Zhang, Z. Interference of Heavy Aerosol Loading on the VIIRS Aerosol Optical Depth (AOD) Retrieval Algorithm. Remote Sens. 2017, 9(4), 397; doi:10.3390/rs9040397. http://www.mdpi.com/2072-4292/9/4/397 --- Wang, W.; Mao, F.; Pan, Z.; Du, L.; Gong, W. Validation of VIIRS AOD through a Comparison with a Sun Photometer and MODIS AODs over Wuhan. Remote Sens. 2017, 9(5), 403; doi:10.3390/rs9050403. http://www.mdpi.com/2072-4292/9/5/403 --- Zhu, J.; Xia, X.; Wang, J.; Che, H.; Chen, H.; Zhang, J.; Xu, X.; Levy, R.; Oo, M.; Holz, R.; Ayoub, M. Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain. Remote Sens. 2017, 9(5), 432; doi:10.3390/rs9050432. http://www.mdpi.com/2072-4292/9/5/432 --- Dolgii, S.; Nevzorov, A.; Nevzorov, A.; Romanovskii, O.; Kharchenko, O. Intercomparison of Ozone Vertical Profile Measurements by Differential Absorption Lidar and IASI/MetOp Satellite in the Upper Troposphere–Lower Stratosphere. Remote Sens. 2017, 9(5), 447; doi:10.3390/rs9050447. http://www.mdpi.com/2072-4292/9/5/447 --- Liu, L.; Zhang, X.; Xu, W.; Liu, X.; Lu, X.; Wang, S.; Zhang, W.; Zhao, L. Ground Ammonia Concentrations over China Derived from Satellite and Atmospheric Transport Modeling. Remote Sens. 2017, 9(5), 467; doi:10.3390/rs9050467. http://www.mdpi.com/2072-4292/9/5/467 --- Chen, W.; Fan, A.; Yan, L. Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing. Remote Sens. 2017, 9(5), 496; doi:10.3390/rs9050496. http://www.mdpi.com/2072-4292/9/5/496 --- Osorio, M.; Casaballe, N.; Belsterli, G.; Barreto, M.; Gómez, Á.; Ferrari, J.; Frins, E. Plume Segmentation from UV Camera Images for SO2 Emission Rate Quantification on Cloud Days. Remote Sens. 2017, 9(6), 517; doi:10.3390/rs9060517. http://www.mdpi.com/2072-4292/9/6/517 --- Gu, J.; Chen, L.; Yu, C.; Li, S.; Tao, J.; Fan, M.; Xiong, X.; Wang, Z.; Shang, H.; Su, L. Ground-Level NO2 Concentrations over China Inferred from the Satellite OMI and CMAQ Model Simulations. Remote Sens. 2017, 9(6), 519; doi:10.3390/rs9060519. http://www.mdpi.com/2072-4292/9/6/519 --- Wang, Y.; Wang, J.; Levy, R.; Xu, X.; Reid, J. MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water. Remote Sens. 2017, 9(6), 595; doi:10.3390/rs9060595. http://www.mdpi.com/2072-4292/9/6/595 --- Kim, D.; Lee, H.; Hong, H.; Choi, W.; Lee, Y.; Park, J. Estimation of Surface NO2 Volume Mixing Ratio in Four Metropolitan Cities in Korea Using Multiple Regression Models with OMI and AIRS Data. Remote Sens. 2017, 9(6), 627; doi:10.3390/rs9060627. http://www.mdpi.com/2072-4292/9/6/627 --- Qu, Y.; Han, Y.; Wu, Y.; Gao, P.; Wang, T. Study of PBLH and Its Correlation with Particulate Matter from One-Year Observation over Nanjing, Southeast China. Remote Sens. 2017, 9(7), 668; doi:10.3390/rs9070668. http://www.mdpi.com/2072-4292/9/7/668 --- Tosca, M.; Campbell, J.; Garay, M.; Lolli, S.; Seidel, F.; Marquis, J.; Kalashnikova, O. Attributing Accelerated Summertime Warming in the Southeast United States to Recent Reductions in Aerosol Burden: Indications from Vertically-Resolved Observations. Remote Sens. 2017, 9(7), 674; doi:10.3390/rs9070674. http://www.mdpi.com/2072-4292/9/7/674 --- Tao, M.; Wang, Z.; Tao, J.; Chen, L.; Wang, J.; Hou, C.; Wang, L.; Xu, X.; Zhu, H. How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China?. Remote Sens. 2017, 9(8), 800; doi:10.3390/rs9080800. http://www.mdpi.com/2072-4292/9/8/800 --- Wang, W.; Mao, F.; Du, L.; Pan, Z.; Gong, W.; Fang, S. Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China. Remote Sens. 2017, 9(8), 858; doi:10.3390/rs9080858. http://www.mdpi.com/2072-4292/9/8/858 --- Yuchechen, A.; Lakkis, S.; Canziani, P. Linear and Non-Linear Trends for Seasonal NO2 and SO2 Concentrations in the Southern Hemisphere (2004−2016). Remote Sens. 2017, 9(9), 891; doi:10.3390/rs9090891. http://www.mdpi.com/2072-4292/9/9/891 --- Qin, K.; Rao, L.; Xu, J.; Bai, Y.; Zou, J.; Hao, N.; Li, S.; Yu, C. Estimating Ground Level NO2 Concentrations over Central-Eastern China Using a Satellite-Based Geographically and Temporally Weighted Regression Model. Remote Sens. 2017, 9(9), 950; doi:10.3390/rs9090950. http://www.mdpi.com/2072-4292/9/9/950

Description / Table of Contents: The use of agent-based models (ABMs) and modelling for understanding landscape change and dynamics continues to grow. One reason for the popularity of ABMs is that they provide a framework to represent multiple, discrete, multi-faceted, heterogeneous actors (human or otherwise) and their relationships and interactions between one another and their environment, through time and across space. This special issue seeks to showcase innovative uses of ABMs for investigating and explaining landscape change and dynamics and to explore and identify how researchers in different disciplines can learn from one another to further innovate. Thus, this special issue will emphasise multidisciplinary dialogue between researchers using ABM in physical geography, hydrology, ecology, land change science, economics, alternative histories, archaeology, sociology, psychology and others. Innovation may come in the form of computational, conceptual, analytical, participatory or epistemological advances in the use of ABM for a range of aims and motivations associated with landscape change and dynamics. Modelling advances may include new ways of representing agent decisions and/or interactions, establishing and evaluating model structures and rules, presenting and visualising change, multi-scale analysis, comparative techniques, narrative methods, and more. The presentation of innovative agent-based modelling from diverse research backgrounds and perspectives will demonstrate opportunities for learning and enable dialogue to enhance future use of ABMs for understanding landscape change.

Description / Table of Contents: As the fields of organometallic and coordination chemistry of the transition metals has grown more mature, the under-explored chemistry of the rare-earths and actinides has drawn the attention of research groups from across the globe looking for new fundamental discoveries and access to compounds with unique properties. The rare earths – the group 3 metals and the 4f lanthanide series – have long shown many interesting properties in the solid state which exploit their unique electronic configurations. However, it is the molecular chemistry of these metals that has expanded dramatically in recent years as researchers identify the differences between – and unique features of – their molecular compounds. Recent highlights include the identification of new oxidation states and patterns of reactivity as well as applications in medical imaging and health care which represent new and exciting areas of research. The actinides show a wide range of different properties as a consequence of their radioactivity and radiochemistry, but this has not stopped recent rapid progress into the exploration of their unique chemistry. Uranium, in particular, shows huge potential with its transition metal like range of oxidation states (+2 to +6), and in specialised laboratories, the heavier actinides are also beginning to show their unique chemistry as well. This Special Issue aims to bring together these strands of research in an openly-accessible way to allow better communication of these advances to a wider audience. This is necessary as despite these exciting advances, the rare earths and actinides are still much neglected topics in both school and undergraduate curriculums.

Description / Table of Contents: The success of the Suomi National Polar-orbiting Partnership (NPP) brings us into a new era of global daily Earth observations, ranging from the faintest light of human settlements and air glows to the dramatic events of hurricanes and forest fires, as well as the subtle changes in the planet Earth which we call home. At the heart of all satellite applications, calibration/validation of the measurements and derived products is the key. Satellite product calibration and validation have become increasingly more important and challenging in order to meet the stringent requirements for accurate quantitative data for climate change detection, numerical weather prediction, and environmental intelligence. Validation is required not only for the satellite measurements, but also for all geophysical retrievals, including aerosols, cloud properties, radiation budget, sea surface temperature, ocean color, active fire, albedo, snow and ice, vegetation, as well as nightlights from human settlements. Active validation research includes but not limited to, comparisons with similar products from other satellites, with in situ, aircraft measurements, or observations from other platforms. Validation results not only help users and decision makers but also serve as feedback to calibration, which in turn improves the products. This Special Issue of Remote Sensing aims at exploring recent results in the calibration and validation of the Suomi National Polar-orbiting Partnership satellite (Suomi NPP)/JPSS radiometers.

Description / Table of Contents: Fu, R.; Wu, Y.; Wang, H.; Xie, J. A Distributed Control Strategy for Frequency Regulation in Smart Grids Based on the Consensus Protocol. Energies 2015, 8(8), 7930-7944; doi:10.3390/en8087930. http://www.mdpi.com/1996-1073/8/8/7930 --- Chae, W.; Lee, H.; Won, J.; Park, J.; Kim, J. Design and Field Tests of an Inverted Based Remote MicroGrid on a Korean Island. Energies 2015, 8(8), 8193-8210; doi:10.3390/en8088193. http://www.mdpi.com/1996-1073/8/8/8193 --- Nguyen, T.; Yoo, H.; Kim, H. Application of Model Predictive Control to BESS for Microgrid Control. Energies 2015, 8(8), 8798-8813; doi:10.3390/en8088798. http://www.mdpi.com/1996-1073/8/8/8798 --- Jung, S.; Jang, G. Development of an Optimal Power Control Scheme for Wave-Offshore Hybrid Generation Systems. Energies 2015, 8(9), 9009-9028; doi:10.3390/en8099009. http://www.mdpi.com/1996-1073/8/9/9009 --- Yang, Y.; Zhang, W.; Jiang, J.; Huang, M.; Niu, L. Optimal Scheduling of a Battery Energy Storage System with Electric Vehicles’ Auxiliary for a Distribution Network with Renewable Energy Integration. Energies 2015, 8(10), 10718-10735; doi:10.3390/en81010718. http://www.mdpi.com/1996-1073/8/10/10718 --- Xia, H.; Chen, H.; Yang, Z.; Lin, F.; Wang, B. Optimal Energy Management, Location and Size for Stationary Energy Storage System in a Metro Line Based on Genetic Algorithm. Energies 2015, 8(10), 11618-11640; doi:10.3390/en81011618. http://www.mdpi.com/1996-1073/8/10/11618 --- Telaretti, E.; Ippolito, M.; Dusonchet, L. A Simple Operating Strategy of Small-Scale Battery Energy Storages for Energy Arbitrage under Dynamic Pricing Tariffs. Energies 2016, 9(1), 12; doi:10.3390/en9010012. http://www.mdpi.com/1996-1073/9/1/12 --- Gelažanskas, L.; Gamage, K. Distributed Energy Storage Using Residential Hot Water Heaters. Energies 2016, 9(3), 127; doi:10.3390/en9030127. http://www.mdpi.com/1996-1073/9/3/127 --- Pietrosanti, S.; Holderbaum, W.; Becerra, V. Optimal Power Management Strategy for Energy Storage with Stochastic Loads. Energies 2016, 9(3), 175; doi:10.3390/en9030175. http://www.mdpi.com/1996-1073/9/3/175 --- Lin, F.; Li, X.; Zhao, Y.; Yang, Z. Control Strategies with Dynamic Threshold Adjustment for Supercapacitor Energy Storage System Considering the Train and Substation Characteristics in Urban Rail Transit. Energies 2016, 9(4), 257; doi:10.3390/en9040257. http://www.mdpi.com/1996-1073/9/4/257 --- Bruen, T.; Hooper, J.; Marco, J.; Gama, M.; Chouchelamane, G. Analysis of a Battery Management System (BMS) Control Strategy for Vibration Aged Nickel Manganese Cobalt Oxide (NMC) Lithium-Ion 18650 Battery Cells. Energies 2016, 9(4), 255; doi:10.3390/en9040255. http://www.mdpi.com/1996-1073/9/4/255 --- Chung, Y. A Novel Power-Saving Transmission Scheme for Multiple-Component-Carrier Cellular Systems. Energies 2016, 9(4), 265; doi:10.3390/en9040265. http://www.mdpi.com/1996-1073/9/4/265 --- Zangs, M.; Adams, P.; Yunusov, T.; Holderbaum, W.; Potter, B. Distributed Energy Storage Control for Dynamic Load Impact Mitigation. Energies 2016, 9(8), 647; doi:10.3390/en9080647. http://www.mdpi.com/1996-1073/9/8/647 --- Zhao, Z.; Sun, Y.; Hu, A.; Dai, X.; Tang, C. Energy Link Optimization in a Wireless Power Transfer Grid under Energy Autonomy Based on the Improved Genetic Algorithm. Energies 2016, 9(9), 682; doi:10.3390/en9090682. http://www.mdpi.com/1996-1073/9/9/682 --- Gatta, F.; Geri, A.; Lamedica, R.; Lauria, S.; Maccioni, M.; Palone, F.; Rebolini, M.; Ruvio, A. Application of a LiFePO4 Battery Energy Storage System to Primary Frequency Control: Simulations and Experimental Results. Energies 2016, 9(11), 887; doi:10.3390/en9110887. http://www.mdpi.com/1996-1073/9/11/887 --- Kies, A.; Schyska, B.; von Bremen, L. The Demand Side Management Potential to Balance a Highly Renewable European Power System. Energies 2016, 9(11), 955; doi:10.3390/en9110955. http://www.mdpi.com/1996-1073/9/11/955 --- Yang, J.; Choi, J.; An, G.; Choi, Y.; Kim, M.; Won, D. Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation. Energies 2016, 9(12), 1010; doi:10.3390/en9121010. http://www.mdpi.com/1996-1073/9/12/1010 --- Gao, Z.; Chin, C.; Woo, W.; Jia, J. Integrated Equivalent Circuit and Thermal Model for Simulation of Temperature-Dependent LiFePO4 Battery in Actual Embedded Application. Energies 2017, 10(1), 85; doi:10.3390/en10010085. http://www.mdpi.com/1996-1073/10/1/85 --- Yunusov, T.; Zangs, M.; Holderbaum, W. Control of Energy Storage. Energies 2017, 10(7), 1010; doi:10.3390/en10071010. http://www.mdpi.com/1996-1073/10/7/1010