\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 179 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 252 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\n'}],latestNews:[{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"}]},book:{item:{type:"book",id:"654",leadTitle:null,fullTitle:"Current Topics in Children's Learning and Cognition",title:"Current Topics in Children's Learning and Cognition",subtitle:null,reviewType:"peer-reviewed",abstract:"As a whole, the essays in this book address theoretical and empirical issues related to children's learning and cognition. 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He is a level-1 researcher of the National System of Researchers from Mexico. He also belongs to the Advanced Materials Applied to Engineering\nresearch group called and has PRODEP (Program for the Professional Development\nof Teachers) desirable profile. He has been a reviewer for journals for RSC, Elsevier, and IEEE. He has published thirtten articles in indexed journals and thirty\nbook chapters. 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He has published forty SCI&EI indexed papers, including ten IEEE conference papers, in IEEE Transactions on Components, Packaging and Manufacturing Technology, Journal of Materials Science: Materials in Electronics, Journal of Alloys and Compounds, and Advanced Materials. Dr. Zhang is the session chair of IEEE NANO 2019 and co-session chair of IEEE 3M NANO 2018 and 2019.",institutionString:"Harbin Institute of Technology",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Harbin Institute of Technology",institutionURL:null,country:{name:"China"}}},coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"17",title:"Nanotechnology and Nanomaterials",slug:"nanotechnology-and-nanomaterials"}],chapters:[{id:"71831",title:"Introductory Chapter: Hybrid Nanomaterials",slug:"introductory-chapter-hybrid-nanomaterials",totalDownloads:293,totalCrossrefCites:0,authors:[{id:"182114",title:"Dr.",name:"Rafael",surname:"Vargas-Bernal",slug:"rafael-vargas-bernal",fullName:"Rafael Vargas-Bernal"}]},{id:"69106",title:"Electronic Transport in Few-Layer Black 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"62117",title:"Additive Manufacturing Applied to the Design of Small Satellite Structure for Space Debris Reduction",doi:"10.5772/intechopen.78762",slug:"additive-manufacturing-applied-to-the-design-of-small-satellite-structure-for-space-debris-reduction",body:'\nAdditive manufacturing (AM) is changing the way of designing and manufacturing in multiple sectors. The possibilities that this fabrication method offers compared with the classical ones give it applicability in the space sector. Some advantages of using additive manufacturing technology are the following:
Possibility of building lots of pieces in short time.
Weight reduction can be easily achievable with new designs while ensuring structural properties.
Less environmental impact because of the decrease in time of fabrication and required material. Also, these factors reduce power consumption in fabrication.
Process speed optimization.
Part complexity has little impact on manufacturing time and cost plus fewer manufacturing constrains on part design allowing AM to manufacture complex parts. This enables “design for need” instead of “design for manufacturing”.
Creation of composites using printers with double extruder: one for the fiber and one for the matrix. This allows reinforcing selected parts of the components or including specific designs for embedding a bolt or other harness.
Possibility of embedding wiring or sensors to generate multifunctional structures.
Applicability to many materials such as metals, composites, polymers or ceramics.
Some indicate the possibility of in-orbit or on-planet manufacturing [1].
These advantages over classical manufacturing methods indicate that they can be applied in space for new applications or to improve the existing ones. Since the manufacture process with additive manufacturing offers new design possibilities, and also new geometries that are difficult to be obtained with classical methods, it is a priori expected that those characteristics can be used to improve the mechanical behavior of a system by establishing new requirements and boundary conditions.
\nIn this work, the use of additive manufacturing is analyzed along with other technologies that this manufacturing method enables. The objective is to implement space debris reduction measures in the design of small spacecraft.
\nTo achieve this objective, additive manufacturing in the space sector is reviewed and analyzed to find which components of spacecraft are susceptible of being manufactured with this methodology. Besides, the technologies enabled by additive manufacturing and applicable to the design of spacecraft are studied. Finally, a design of an 8 U CubeSat structure is proposed, and its impact in space debris reduction is analyzed.
\nConsidering the advantages of additive manufacturing defined in the introduction, the first objective is to identify which are the applications for additive manufacturing in space. In this section, the main applications of additive manufacturing in satellites are reviewed in order to identify which components of a satellite can be 3D printed and which of them can contribute to space debris reduction.
\nAdditive manufacturing has been applied to different components of spacecraft. Some of them are found to have potential to reduce space debris.
\nA major challenge in a satellite is the distribution of harness since it is not always easy to place. The design of the spacecraft is based on the payload and tries to minimize the volume of the structure. For that purpose, the components are strategically placed to reduce the internal volume, and harnessing a satellite becomes a major aspect. As a manner to reduce the harness into a satellite, additive manufacturing allows embedding wiring and even sensors into the panels of the structure. At least two options exist to embed electronics into the walls of satellite structures: (1) interrupting the 3D printer in the appropriate layer to place the component or (2) making use of a printer with dual extruder to print a circuit with a conductive material in just one process (see [2, 3]). In these works, the authors contemplate the possibility of embedding an antenna that can be directly printed into the walls of a spacecraft for space-to-ground links. The use of a wall as a backplane for addition of equipment provides multifunctionality to the structure. These applications, although they present some advantages, as for example the use of embedded wiring and sensors can contribute to reduce the debris generated in a catastrophic impact: in principle, the lower the number of components affected by a catastrophic impact, the lower the number of fragments generated. However, they also present major drawbacks such as difficulties to be repaired during the testing or qualification stages of a satellite if needed. This is analyzed in detail in Section 3.2.
\nProtecting sensitive circuitry from the damage caused by the exposure to space radiation is a current problem, which is overcome with the housing of sensitive components inside metal boxes. This, known as shielding, increases the volume and weight of the spacecraft, which are key parameters. The use of additive manufacturing offers an intriguing alternative because the protective metal could be selectively printed to enclose the part, minimizing volume and maximizing protection [4]. Shielding can highly contribute to the reduction of space debris if the satellite is shielded in order to resist impacts of debris particles. Most of these fragments are of size under 1 mm. By designing a shielding capable to resist in orbit the impact of projectiles of this size, the number of generated fragments would be highly reduced and, for instance, the number of space debris particles.
\nAdditive manufacturing can provide new advances in thermal management; for example, in the fabrication of surface topologies into radiating panels. This solution increases the surface area of the panel and heat pipes embedded into the structure of the spacecraft [3].
\nThe application of additive manufacturing to the functional structure of the spacecraft can potentially reduce its weight and manufacturing time with respect to classical approaches, such as computer numerical control (CNC) milling. The use of this technology provides more freedom to the designers, who can make use of more complex geometries to improve the structural efficiency without bearing in mind the complexity of manufacturing a part. Small satellites can be benefited with the use of this technology. In The CubeSat Challenge [5], several designs that could be manufactured with additive manufacturing technology were presented. In this case, when designing the structure, the designer shall bear in mind that the structure and all the components of the spacecraft shall be integrated: the reduction of joints can be a major advantage, for example, but it will also make more difficult the integration tasks of the spacecraft components inside the volume of the structure.
\nHowever, for large satellites, the use of 3D printing to be part of the functional structure has limitations, mainly because of the reduced 3D printing volume of the metal 3D printers. Then, the use of additive manufacturing for the functional structure of large satellites is nowadays limited to the manufacture of specific components or parts. Otherwise, the advantages of using this technology would be reduced.
\nA potential use of additive manufacturing in the functional structure of a spacecraft is the manufacture of metal brackets. The current generation of satellites includes specific brackets used as mechanical interface between the main frame of the satellite and some components such as star trackers, GPS receivers, reflectors and reaction wheels, among others. The main benefits are the weight reduction and the design for need. These advantages have motivated the introduction of additive manufacturing in the manufacture of brackets for satellites, for example the swiss company RUAG optimized the antenna bracket of Sentinel-1A by using this technology [6].
\nIn the space propulsion area, the improvements that come from the application of additive manufacturing are not only focused on mass reduction through new designs of propellant tanks but also on the improvement of the performance. In this case, the possibility of building rocket injectors serves as example of a complex component easily built with a 3D printer with same or even better performances and tolerances than manufactured with classical approaches. One example is the injector for RL-10 upper-stage rocket engine by Aerojet Rocketdyne [7]. This company also used additive manufacturing in the fabrication of a titanium piston, the propellant tank and the pressurant tank of a propulsion system for CubeSat [8].
\nNASA’s Goddard Space Flight Center analyzed the possibility of assembling a space imaging telescope made almost exclusively from 3D printed components [9].
\nSome antenna reflectors have complex geometries. This makes their manufacture a complex issue. Additive manufacturing can facilitate the manufacture of antenna reflectors for space applications and satellites, making possible the manufacture of the whole antenna in a single piece, independently of the complexity that its geometry can have. The European Space Agency (ESA) developed a 3D printed antenna for satellites in a single piece to be tested in [10]. NASA and Stratasys also developed antennas by using additive manufacturing in [11]. In this last study, in which they validated the technology for space, they claimed that the use of additive manufacturing saved time and money. However, it shall be considered that plastic materials are highly reactive to oxygen atoms present at the operating height of the satellite. This can produce degradation in the component. They solved this problem by painting the components with a high emissivity protective paint to form a glass-like layer on the plastic structure. With this solution, the component can reflect a high percentage of solar radiation and optimize thermal control of the antenna operating conditions.
\nLockheed Martin used additive manufacturing in the prototyping of fuel tanks, commonly made of titanium, which along with reaction wheels are also a major problem for space debris and which also have a high casualty risk since titanium is very resistant to the effect of the atmosphere in the reentry. They analyzed the design and the manufacture process to develop this component [12]. In that publication, they claimed that additive manufacturing reduced mass, cycle time and material waste.
\nAs described in the previous section, additive manufacturing can be applied itself in several components of a satellite. However, the characteristics of this technology apart from the generally claimed mass reduction, waste reduction, manufacturing time and prototyping, what seems to be really interesting is the (i) design for need, which changes the whole design paradigm previously established in the design for manufacturability and (ii) independence of the complexity of the geometry to manufacture. These two factors facilitate the appearance of new technologies which before additive manufacturing were very difficult to apply, or even impossible, at least in the way they can be applied with additive manufacturing. Two technologies that can highly contribute to the design of satellites to reduce the space debris were identified.
\nAdditive manufacturing independence of geometry complexity facilitates the manufacturing of metallic lattices, which without this technology were very difficult to manufacture, they being reduced to the creation of foams and other irregular similar structures. However, the capability to generate a lattice with complex although with regular geometry guarantees that the mechanical behavior of such a structure is the same across the whole section. Besides, the lattice can be designed for a specific need to improve or maximize the performance of specific mechanical behaviors. In addition, lattice structures can also reach negative Poisson rates, which increase the resistance of the structure, fracture thoroughness and shear resistance [13].
\nBoeing created the microlattice variant to lattice, which is the lightest material ever made (microlattice variant is about 99% air) [14].
\nAs reviewed in [15], the most commonly used debris shields for spacecraft rely on several layers with a large standoff distance between them to dissipate the impact energy. However, proven effective, this type of solution is difficult to suit in small satellites in which volume is even more important than mass.
\nCurrent solutions are based on structures such as the honeycomb panels. They have poor impact mitigation and may be difficult to integrate in small satellites satisfying, for example, the envelope limits of the CubeSat standard deployment pods. However, lattices can be used to replace the core of the panels and be manufactured integrated with the structure requiring little extra space and at the same time increasing the impact mitigation. For this concept, the energy of the impact is dissipated through plastic deformation and generation of break surfaces; thus, the design can be easily miniaturized. This performance increase was analyzed by NASA through testing [16] by comparing honeycomb panels with open cell foam core sandwich panels (open cell foam has similar mechanical behavior than lattice) concluding that for equivalent panels the impact mitigation was always better for foam core panels.
\nThe other set of technologies enabled by additive manufacturing are those linked to embedded wiring and sensors into the 3D printed structure. Some of them can be directly printed or perfectly placed in strategic locations of the structure. Besides, as indicated before, this can reduce the number of fragments if a catastrophic impact occurs in orbit. These technologies were divided into three main groups: embedded devices (such as sensors, electronics and antennas), embedded batteries and embedded wiring. The main limitation of this set of technologies is that it can only be used over not electrically conductive or very well isolated materials. They are reviewed in the following section.
\nThere are three different approaches to embedded sensors:
An off-the-shelf device made by traditional methods introduced in the structure during the printing process. In this case, the provided device must be prepared to survive to the printing environment with no damage. In [17], three accelerometers and other electronic devices were embedded in a polymeric matrix with a combination of Fused Deposition Modeling (FDM) and Stereolithography (SLA) additive manufacturing methods.
An offline 3D printed device introduced in a 3D printed structure. This is similar to the previous case, but instead of embedding an off-the-shelf device, a 3D printed one is embedded instead. An example is the 3D Hall Effect displacement sensor introduced in [18].
A device printed in the structure. This can be done with the same process or intercalating two or more manufacturing methods. In this case, if a single process is used, the process needs to provide at least two different materials in the same print. Examples of sensors printed in the structure are the 3D printed strain sensors. These consist of injecting a conductive resin in an elastomeric uncured matrix. The final result is a part with an embedded flexible strain sensor [19]. Other application that was included in this classification is that of the antennas that can be printed in a structure or surface: in [20], the authors used Inkjet technology to print a metallic ink (silver based) on convex and concave surfaces. They used conductive meander lines with connected feed lines (printed separately) obtaining performance levels comparable to theoretical results. These 3D printed and miniaturized antennas have multiple applications in addition to classical communication uses.
A review of 3D printing methods in the sensor industry can be found in [21]. It is remarkable that none of the examples described there uses a metallic substrate (structure material) and most of them use printing methods based on polymerization not melting.
\nConsidering the advantage of additive manufacturing referred to the independence of geometry stated above, this technology can be applied to print batteries of any shape. This can be an advantage in satellites because empty spaces in the structure or in the volume of the spacecraft can be used to create a battery that perfectly fits in.
\nSeveral Li-Ion battery designs were developed by using additive manufacturing. For example, the authors in [22] used graphene oxide-based ink to print miniaturized batteries, which could be potentially embedded within a spacecraft structure. The capacity of these cells (called 3D-IMA) was 1.2 mAh·cm−2 normalized with the area of the current collector.
\nEmbedded wiring for space applications mostly relies on recent conductive inks developed for Inkjet technologies. As stated by Kief et al. in [3], these materials were successfully proven to produce conductive inks for electronics in complex geometries. But low limits in curing temperature led to poor performance in terms of conductivity and carrying capacity which are required for high-power high-frequency applications.
\nAdditionally embedding metallic meshes into polymeric structures were tested, this meshes can act as back planes for electronic components like antennas or as ground planes. Even more meshes can work as support points to weld metallic parts and plastic ones together.
\nThis analysis shows that although all these 3DP embedded technologies seemed to be promising, they have relevant technical implementation drawbacks. The advantages of using 3D printed embedded technologies, in general terms are associated to the perfect positioning of sensors, elimination of wiring, optimization of space, and reduction of debris fragments but their integrability in a critical system, such as a satellite is still risky: first, any 3D printed conductive element shall be printed on isolated surfaces such as polymers. This obliges satellite manufacturers to come up with new fabrication methods, materials, or additional surface treatment. Second, these technologies present difficulties in any repairing process that can appear during testing or qualification stages. It would be critical that a main sensor or circuit, embedded in a structural element, fails at any stage of the manufacturing or testing processes, obliging manufacturers to create additional parts. The installation of individual sensors that can be repaired or changed with accessibility seems more applicable. Third, the use of multiple extruders should be used in most of cases, with the exception of printing surfaces with conductive inks, as the cases with strain sensors and printed antennas, which could be printed after the metallic part is complete. The printing with different materials is complex and not viable when the thermal properties of the materials being printed substantially differ, as it is the case of many polymers and metals that can be used in space.
\nHowever, some of the previous technologies can provide benefits for specific applications:
3D printed embedded strain sensors. This solution would provide a perfect positioning of the strain in the surface to be monitored. Furthermore, the surface can be covered, for example with thermal isolation or shielding without affecting the functionality since it is a measure of an intrinsic parameter of the surface in which the strain is placed. Nevertheless, additional analysis and testing should be done in the process of isolation of metallic surfaces and adhesion of the sensor because there are different materials under critical mechanical and thermal loads. This technology would reduce harness and electromechanical components that can be fragmented in case of collision, potentially reducing the space debris of future systems.
3D printed embedded antennas. This technology, as described in the analysis, requires an unused area to be printed on. Furthermore, that area cannot be covered with thermal isolation, radiators or shielding. This is difficult to provide in a satellite. However, in some cases, it would be beneficial to manufacture an antenna through an additive manufacturing process that optimizes its shape and performance and then it is installed in the spacecraft as a component afterwards.
3D printed batteries. They present the same drawbacks of embedded devices into the satellite structure (if they are embedded in the structure); however, they can be separately printed and integrated in the satellite afterwards. This presents many advantages because they can be printed with any shape, which would be beneficial to make use of any available volume available in the spacecraft or in the structure.
Thus, this analysis indicates that more research and development is needed for 3D printed embedded technologies to reduce the risk of implementation in operative missions.
\nConsidering the analysis carried out in the previous sections, an 8 U CubeSat satellite structure was designed to reduce space debris. Notice that there is no mission defined as the design was done to demonstrate the use of different technologies that contribute to space debris reduction, which is the objective of this work. The reasons of selecting an 8 U CubeSat instead of other type were the following:
To apply additive manufacturing to the whole functional structure of the satellite for demonstration purposes was intended. The 8 U CubeSat is small enough to be fully printed in a typical SLM metal printer such the ConceptLaser M2. This metal printer has a printing volume of 238 × 238 × 230 mm (length × width × height). The 8 U CubeSat has a volume of 200 × 200 × 200 mm, which fits in the 3D printer.
The 8 U CubeSat follows the CubeSat standard so the analysis carried out in this work can be applied to a large number of satellites (smaller than 1, 1, 1.5, 2, 3 and 6 U), not only to a specific satellite with a specific design.
The 8 U will facilitate further work on additional analysis of casualty risk of propulsion titanium tanks and reaction wheels.
The technologies implemented in the design of the 8 U CubeSat were additive manufacturing and lattice structures, applied in the structure to improve the shielding. Embedded devices technologies were not considered in this work because of the high risk of implementation in operative mission. Future improvements on those technologies would lead to additional solutions with the benefits already described. Furthermore, the research was focused in the design of the structure, so the implementation of additive manufacturing to other components of the satellite was not addressed, such as metal brackets, harness, propulsion subsystems including propellant tanks, telescopes and antennas. The AlSi10Mg aluminum alloy was selected as the reference material for the structure. The mechanical properties of the material can be funded in [23].
\nThis work does not enter into details of the structural design of the 8 U CubeSat by following the CubeSat standard. This can be found in [24]. It is focused on the design of the lattice core panels.
\nFollowing the work carried out by NASA in [25], the geometry of the lattice core panel was defined to provide the best impact efficiency possible. The panel was designed as a sandwich panel concept. It was divided into three parts: (1) an inner panel, (2) lattice core and (3) shear panel. Because of the benefits of using additive manufacturing, the inner panel and the lattice core can be printed together. The shear panel can be assembled afterwards with bolted unions. The three parts were not printed together because the SLM printer used metal powder. If the volume to be printed was closed, the residual powder could not be extracted from the part, remaining inside and changing the mechanical properties of the part. Figure 1 shows the concept of the panel with lattice core. For instance, the structure was constituted by six independent faces with lattice core panel.
\nLattice core panel concept.
A common CubeSat usually has the maximum thickness of 7.7 mm and with 1 mm to assemble shear panels. Thus, the total margin to increase the shielding and width of the structure was 8.7 mm. Increasing this margin would limit the incorporation of standard COTS components in the satellite and would also difficult the integration of the spacecraft in a POD, which is the common interface with the launcher for CubeSats. So excluding the shear panel, the lattice thickness plus the inner wall added could not be wider than 7.7 mm.
\nTo design the panel, a three-dimensional cost function is generated by relating (1) the impact area efficiency when a projectile of aluminum alloy impacts the surface with an angle of 0° (i.e., perpendicular to the impact surface and a velocity of 8 km/s magnitude) with (2) lattice relative density and with (3) lattice thickness. Eq. (1) was adapted from [25]:
\nwhere dc is the critical projectile diameter at shield failure in cm, tw is the rear wall thickness in cm, ADlatt is the area density of the lattice core in g/cm2, ρw is the density of the rear wall in g/cm3, tlatt is the thickness of the lattice in cm, σ is the rear wall at 0.2% offset tensile yield stress in ksi (kilopound per square inch), ρp is the density of the projectile in g/cm3, ρf is the density of the shear panel in g/cm3, V is the impact velocity in km/s and θ is the impact angle from the target normal vector.
\nwhere ρAlSi10Mg is the AlSi10Mg aluminum alloy density in g/cm3, and ρLRel is the relative density of the lattice from 0 to 1.
\nρA stands for the area density of the lattice core panel in g/cm2 and ts is the shear panel thickness in centimetre.
\nwhere μI is the impact area efficiency in cm3/g.
\nFigure 2 depicts the results of the optimization region. From this region it was concluded that the optimal solution was a lattice of 10% relative density. Ideally, a higher reduction of the lattice relative density would increase the efficiency, but there is a physical limit as the printer has limited resolution and the model used to calculate the critical projectile diameter is not valid since the mechanic behavior changes for lower relative densities.
\nLattice core sandwich impact areal efficiency [cm3/g].
Figures 3 and 4 depict the lattice thickness in function of the impact aerial efficiency defined in Eq. (4) and the critical projectile diameter defined in Eq. (1) with a lattice relative density of 10%. The design point was chosen to have a lattice thickness of 0.35 mm, a relative lattice density of 10%, and an inner panel with 0.42 mm thickness. This point is not the maximum of the curve but by having moved the design point slightly to the left, although there is lower impact aerial efficiency, there is higher resistance to impacts of projectiles of larger size. The decision of maximizing the impact resistance instead of the efficiency was taken due to the fact that the majority of the space debris has a size lower than 1 mm. In addition, these fragments cannot be tracked so impact avoidance maneuvers cannot be done [26, 27]. Consequently, the Impact Areal Efficiency for the design point was \n
Impact areal efficiency vs. lattice thickness for a relative density of 10%.
Critical projectile diameter vs. lattice thickness for a relative density of 10%.
In this section, the shielding performance of the lattice core panel designed is compared with three cases:
A classical shear panel of 1 mm thickness. This solution weights 0.11 kg.
An IsoMass panel: it keeps the same mass than the lattice core panel. It has larger thickness than the 1 mm shear panel and generates an equivalent solid plate to that of the lattice core panel. This solution measures the benefit of making a more complex geometry which cannot be made with traditional methods. For a 20 × 20 cm plate, this solution weights 0.60 kg.
IsoVolume panel: CubeSats are restricted in volume to take advantage of COTS pods so a second variant is presented, instead of keeping the same mass now a solid plate with the same volume as the panel with lattice is defined. This approach evaluates how volume efficient the lattice core solution is compared to a heavier solution with its same volume. For a 20 × 20 cm plate, this solution weights 0.94 kg.
The different plates and the lattice core critical projectile diameters, dc, for a span of impact velocities can be obtained by implementing the equations introduced in [16] for the single plates and in [25] for the lattice core panel. The relative impact mitigation (RIM) of the plates compared with the lattice can be obtained with the following equation:
\nwhere \n
Figure 5 shows the critical projectile diameter at shield failure for all the four panels. For velocities of the projectile lower than 4.6 km/s both the IsoMass and the IsoVolume panels resist to projectiles with higher diameters than the lattice core panel. At this speed both the IsoMass and the lattice core panels can resist impacts of projectiles with 0.13 cm size, while the IsoVolume panel can resist impacts with projectiles of 0.20 cm size. However, from 4.5 km/s, the lattice core panel resists to larger size impacts than the IsoMass panel, and from velocities higher than 6.4 km/s (at which both lattice and IsoVolume panels resist impacts of projectiles with 0.1 cm size), the lattice panel has more resistance than the IsoVolume panel to impacts of projectiles with larger size. This result is notorious since the IsoVolume panel having more mass than lattice has lower resistance to impacts. In addition, the classical panel with 1 mm width has lower resistance than the lattice core panels in all conditions, as could be expected.
\nPlates vs. lattice core critical projectile.
Figure 6 shows the relative impact mitigation in percentage of the plates with regard to the lattice core panel. Even though an optimized lattice impact mitigation of only 0.089 cm at 8 km/s may seem too low, when compared to solid plates results are remarkable. A simple shear panel shields an 80% less than the lattice core panel for the hypersonic regime while the mass is only a 55% higher; compared then with the solution with the same mass the lattice core panel performs better for high speed impacts which are the impacts potentially more dangerous: 7 km/h or higher. The lattice core for these impacts outperforms the IsoVolume plate, which is an 80% heavier solution.
\nRelative impact mitigation.
Finally, the designed 8 U CubeSat structure can be seen in Figure 7.
\nIsometric view of the small satellite structure with and without shear panels (left and right views).
In this chapter, a review of the additive manufacturing technology applied to satellites was done. Besides, the applicability of other technologies that can be enabled by this manufacturing method was also analyzed. As a consequence of the study, it was found that the application of additive manufacturing and lattice structures could be applied to improve the behavior of a satellite to reduce space debris when these technologies were incorporated in the functional structure of small satellites and in the impacts shielding of the system. Then the structure of an 8 U CubeSat was proposed and designed incorporating a sandwich panel with lattice core. The design was analyzed and compared with classical CubeSat panels of 1 mm thickness, with an IsoMass panel (i.e., same mass than the lattice core panel) and with an IsoVolume panel (i.e., an aluminum panel with the same volume than the lattice core panel but with 56.7% more mass). It was found that the lattice core panel in impacts with particles at velocities higher than 4.6 km/s provides more shielding than the IsoMass panel and in impacts with higher velocity than 6.4 km/s provides more shielding than with the IsoVolume panel.
\nFor instance, the improvement in the impact shielding of a spacecraft can dramatically reduce the space debris by designing the future satellites accordingly. If they resist to a larger number of impacts, new fragments of space debris will not be generated. According to National Research Council [26], the highest population of space debris within 1600 km of the Earth surface is constituted of small size fragments lower than 1 mm diameter. The authors estimate that hundreds of trillions of fragments under this size are orbiting and impact at velocities with magnitudes between 6 and 8 km/s. They can be potentially destructive since objects of this size cannot be tracked. On the other hand, they estimate that approximately the order of magnitude of larger fragments is 10 millions. However, objects with size between 1 and 5 cm and higher can be tracked, so collision avoidance maneuvers could be done to avoid impacts [27]. This indicates that the proposed design can resist impacts of hundreds of trillions of debris fragments, in the order of magnitude of 10,000 fragments can be tracked so collision avoidance manoeuvers could be executed (most destructive ones) and that the design would be exposed to approximately 1–10 million fragments of size between 1 mm and 1 cm sizes.
\nThe research leading to these results has received funding from the Horizon 2020 Program of the European Union’s Framework Programme for Research and Innovation (H2020-PROTEC-2015) under REA grant agreement number 687500 – ReDSHIFT (
The authors want to acknowledge Irene Vázquez and Gerardo González for their support to identify the applications of additive manufacturing in space.
\nThis publication reflects only the author’s views and the European Commission is not liable for any use that may be made of the information contained therein.
Nowadays, due to the increased operation and maintenance cost and issues related to transportation of fuels, conventional ways of power generation are no longer an optimal solution. With more concerns about environmental footprints and global warming together with the steady progress in green technologies, renewable energy resources (RESs) are deemed to be key enablers for sustainable energy development, cost-effective operations, and pollutant emission prevention. The use of RESs in an integrated framework with different energy sources not only enhances the system efficiency at different levels (e.g., energy generation, transmission, and distribution) but also improves the energy supply reliability and allows empowering of consumers in the different locations (such as suburban districts, countrysides, and remote/islanded areas). Additionally, with the complementary characteristics of energy storage systems (ESSs) and hybridization of energy systems, it is possible to offer more affordable and reliable source of power and introduce more controllability to the generation mix. More importantly, with the application of ESSs, the issues related to unpredictable nature of RESs (mainly solar and wind energy sources) can be resolved, and a smooth-running power supply can be guaranteed. On the other hand, implementation of an integrated energy system supported with ESSs allows energy saving at different scales. By proper charging/discharging of the ESSs, we can economically benefit from dispatching cheaper energy sources during peak load hours and saving excess energy during low-demand periods. It is noteworthy that the term “ESS” could have different definitions; however, in this chapter we are talking about a “commercially available technology that is capable of absorbing energy, storing it for a period of time, and thereafter dispatching the energy” [1]. It should be also noted that the system operation can be further improved if demand response programs (DRPs) are considered in energy management portfolio. DRPs will incentivize the users to reduce their energy consumption over peak times or to shift part of their consumptions to other time intervals for matching energy supply [2]. However, a good DRP should have two primary features: the first feature is defined as the adaptability to different consumers with different dispositions toward the DRP, and the second one is defined as the adjustability to time preferences of consumers. This means that each consumer should be able to easily shift his/her demand from the high-price hours to the favorite hours according to his/her lifestyle [3]. With this introduction on advantages of renewable energy integration and reliable backup through energy storage options, this chapter discusses different battery-based ESS (BESS) technologies and presents potentials of BESS in distribution systems. Moreover, different design criteria and methodologies for ESS sizing and planning are proposed, and a general framework for optimal operation management and control of BESSs in energy networks is developed.
This section provides an overview of criteria and methods that should be used to optimally size and use a battery energy storage system (BESS) for different applications.
A battery is constituted of electrochemical cells connected in series, parallel, or both in order to obtain the desired capacity and voltage output. A cell consists of a set of two electrodes (oxidizer and reducer) in contact with an electrolyte and converts chemical energy into electric energy (and vice versa for rechargeable cells) [3, 4, 5]. Since the end of the eighteenth century with the development of the Volta pile, “voltaic pile,” numerous designs of batteries have been invented (with different electrode materials, electrolytes, casings, separators, management systems, etc.). Hundreds of systems have been created, but almost 20 of them are currently commercialized (mainly derived from lead, zinc, nickel, or lithium materials) [6]. As presented in Figure 1, electrochemical cells can be classified into three main families:
Flow batteries (also called redox flow batteries) are based on two electrolytes stored in external tanks. The electrolytes are pumped into an electrochemical cell in order to produce electricity. The energy density depends on the size of the tanks, and the power density depends on the rate of chemical reactions occurring in the electrochemical cell. These batteries can be fast to recharge by changing the electrolytes. In general, the chemical reactions are reversible.
Primary batteries cannot be easily and efficiently recharged so they are usually only discharged once and discarded. They are often used in portable electric devices such as lighting, cameras, toys, and also in-home automation sensors (e.g., smoke and movement detectors). They offer a good energy density and a good shelf life.
Secondary batteries are rechargeable and can perform a large number of cycle charge/discharge (100–1000). The market of rechargeable batteries comprises a very wide range of applications such as powering portable electronic devices, electric vehicles, storing surplus of energy from photovoltaic systems, etc. Since 1990, the average growth rate of rechargeable battery pack market is 5% per year [7]. For decades, lead-acid batteries (such as valve regulated and sealed) have been leading, by far, the global market of rechargeable batteries. Since the end of the 1990s, lithium-ion batteries have been gradually preferred to nickel-cadmium (Ni-Cd) and nickel-metal hydride (Ni-MH) batteries in portable devices [7]. The historical development of the main battery chemistries and the key issues to create sustainable batteries with always higher performances are well presented in Ref. [8].
Main different electrochemical technologies.
In this chapter, the analysis will be focused on secondary batteries, especially on lead-acid and lithium-ion batteries, the most popular technologies (because of an attractive price for the first cited and because of high performances in terms of energy and power densities for the latter). The main useful characteristics of a BESS, when selecting a technology, are listed below:
Response time: a BESS has to charge/discharge in a given period (e.g., fast response time from milliseconds to seconds is needed to remove power fluctuations inherited from renewable source production).
Capital cost: depending on the application, different costs are useful to be considered such as the cost of rated power (€/kW), the cost of rated capacity (€/kWh), and the cost on the long run (€/(cycle kWh)).
Operation and maintenance (O&M) cost: every BESS has its proper O&M requirements. It is difficult to find a clear trend in the literature because it is highly dependent on the location (labor costs) and on the age of the facility.
Specific energy (Wh/kg) and specific power (W/kg): enables to know the BESS weight that achieves power and energy requirements of the application. Energy and power densities, respectively, in Wh/l and W/l, are other metric representative of the volume aspect.
Cycling lifetime (number of cycles): maximum number of cycles that the BESS can perform.
Calendar lifetime (years): maximum shelf life of the BESS.
Cycle efficiency (%): also named round-trip efficiency, the energy discharged by the BESS is lower than the energy initially charged into it. This parameter can be measured by calculating the ratio between energies discharged to the energy charged Eout/Ein. This calculation should not take into account self-discharge.
Self-discharge: due to parasitic chemical reactions, the charges stored in the BESS decrease. This process can be accelerated or slowed not only by external conditions (e.g., temperature, humidity) but also by operating conditions (e.g., state of charge (SOC) of the battery, previous rate of charge, etc.).
Operating temperature (°C): some parameters such as the efficiency, the available capacity, and the lifetime depend on the operating temperature range of the BESS.
Environmental impact and safety: the extraction of the main components and manufacturing processes of batteries have different impacts on the environment from a technology to another. These impacts can be expressed as an energy consumption or a mass of GHG emissions [9]. The toxicity of some materials and the stability of the battery (e.g., thermal runaway of lithium batteries with cobalt-based cathode) can be a crucial issue depending on the application.
Maturity: a strong scientific background is behind mature technologies which benefit from numerous user experiences. Only incremental improvements are expected. In comparison, a new technology is evolving fast thanks to breakthrough advances.
Grid-scale storage facilities through the world have been gathered in a large database from the US DOE [10]. A full description is given for most of them such as the date of creation, the location, the technology, the rated capacity, the rated power, the use cases, a picture of the project, etc. It appears that the global storage resource is small (the operational maximum power storage is around 170–180 GW, corresponding to less than 1% of our energy production). The main storage technology (in terms of rated power) is by far pumped hydro (~96%), but electrochemical projects are the most numerous (nearly 1000) and represent nearly 2% of the total rated power. As listed in [10, 11, 12], a BESS can provide numerous benefits such as:
Environmental: integration of renewable sources (the variability of these sources threatens the grid stability), replacement of diesel generators (in off-grid sites), pollution reduction (by reducing peak demand often met with harmful and costly plants), etc.
Societal: electricity supply in remote areas, reliability improvement (possibility to maintain the grid stability or operate separately from the utility in a so-called islanded mode), duration of outages decreased (ESS can perform a black start), etc.
Economic: energy cost decrease (due to electric energy time-shift that enables to buy cheap energy and then sell and/or use it when it is expensive), the use of expensive thermal power plant diminution (with advanced energy management strategies), electric peak demand flattening, power factor correction, transmission and distribution (T&D) investment deferral, etc.
Every actor of electricity from the end user to the utility operator may find one or more benefits to install a BESS facility [12]. Indeed, potential synergies might be achieved, for example, by charging batteries during off-peak demand and discharging during peak; energy cost may decrease (because energy is bought cheap and sold expensive); energy losses (I2R) can be reduced (less power in transmission lines during on-peak demand); pollution may be reduced (because in general cleaner power plants are used for the supply of baseload demand), and T&D deferral or life extension of the utility can be fulfilled because it mainly depends on the level of the peak demand. Two typical use cases are illustrated in Figure 2, where (a) represents the use of energy storage in order to reduce the peak demand. In this case, the power plant responsible for the baseload generation will increase its production in order to charge the BESS (in general the cost and the pollution related to this plant are the lowest compared to the other plants that are used to meet the peak demand). During peak demand, the energy comes from the BESS which replaces costly and high-pollutant power plants. Case (b) represents a typical power production from a solar photovoltaic (PV) plant during a sunny day which is not correlated with the demand profile. The BESS is charging when there is a surplus of energy in order to ensure the stability of the grid (unintentional injection of renewable power is not allowed), and it is discharging when the cost of energy is high (i.e., flattening the energy peak demand in the morning and in late afternoon).
Typical use cases of a BESS, (A) peak shaving and load leveling and (B) integration of renewable sources.
The following criteria help to quantify the benefits brought by a BESS associated to renewable sources such as solar PV panels and wind turbines (WT).
First of all, the reliability of the distribution system can be assessed by Eqs. (1) and (2):
Loss of power supply probability (LPSP) is defined as the ratio of energy deficit to the load demand for a given period [13]:
Level of autonomy (LA) is derived from the ratio of the hours that exhibit a loss of load (HLOL) to the total hours of operation (HTOT) [13]:
Concerning the economic issue, the BESS can be analyzed by calculating the annualized cost of system (ACS). The formulation (3) is derived from [14, 15] in which the annual cost of a renewable plant (PV or WT) with batteries is calculated. In these studies a replacement cost is added in the calculation of ACS because the duration of the project is often based on the lifetime expectancy of renewable sources which is longer than battery lifetime:
where Ccap is the initial capital cost of the BESS (€), CRF is the capital recovery factor defined in Eq. (4) to calculate annual equal payments over the lifetime of the BESS based on the initial capital cost, and CO & M is the annual cost of operation and maintenance (€):
where ir is the interest rate (between 5% and 10% for such projects [16]) and n is the BESS lifetime (years).
Another popular metric used in renewable plants is the levelized cost of energy (LCOE) which indicates the total cost of energy (generally per kilowatt-hour) by taking into account the cost of all equipment involved in energy production over their entire lifetime. It can be adapted to BESS by using the annualized discharged energy Edis, as proposed in Eq. (5):
A good criterion to take into account the environmental aspect is the PV self-consumption Eq. (6) that can be highly improved by the integration of a BESS. A high PV self-consumption implies a good use of the PV source and a local use of produced energy (transmission losses are reduced). In case of grid-connected system, some energy is exchanged with the grid, EDU is the energy directly used from the PV installation to the load, EBC is the PV energy used to charge the BESS, and EPV is the total energy produced by the PV installation:
Other criteria can be taken into account such as the life cycle analysis (LCA) which aims at assessing the environmental impact of a device by taking into account four life stages that are manufacturing, transportation, use, and end of life. A life cycle inventory (LCI) analysis, only focused on the manufacturing of different batteries, is presented in Ref. [9]. In such studies, some data are difficult to obtain and are often estimated (especially those concerning the manufacturing processes which are fast evolving due to improvements of technologies).
Several optimization techniques are available for the sizing and the planning of renewable energy-based systems [17]. Some popular software tools such as Hybrid Optimization Model for Electric Renewables (HOMER) and Hybrid Power System Simulation Model (HYBRID2) both developed by the National Renewable Energy Laboratory (NREL), United States, and Hybrid Optimization using Genetic Algorithm (HOGA) developed in the University of Zaragoza, Spain, are presented in Ref. [17] to simulate and optimize any microgrid configuration. Nevertheless, in order to have the highest flexibility in terms of modeling and optimization, other classical tools are commonly used such as MATLAB and General Algebraic Modeling System (GAMS).
In optimization problem, the objective function can be mono-objective (e.g., cost of the entire installation during 20 years) or multi-objective (e.g., a combination of reliability, cost, and environmental impact). Very often, the cost function of a multi-objective problem is defined as a weighted sum of multiple criteria that can be expressed in different quantities. In this case, some arbitrary weighting coefficients are necessarily introduced, and the difficulty is to determine their right value. For example, if the cost function, expressed in euros per year, evaluates the yearly cost of a BESS in a microgrid, what equivalent cost (in euros per kilogram) should be associated to the greenhouse gas (GHG) emissions induced by the production, use, and end of life of batteries? This cost depends on environmental and social impacts that are not globally standardized and are fluctuating from a year to another, whereas the mass of GHG emissions is a fixed value. In this sense, the Pareto representation is very practical because each objective is expressed in the most appropriate quantity and defines its own axis.
In Ref. [18], a robust mixed-integer linear programming (RMILP) is proposed to minimize the cost of the system. In order to take into account uncertainties such as renewable production, load demand, or costs, a stochastic simulation can be achieved through the generation of multiple Monte Carlo scenarios. Heuristic and meta-heuristic optimization techniques are very popular to find the optimal solution among a large number of solutions while using the least computational resources. Two multi-objective problems combining genetic algorithms and Pareto representation are presented in [19, 20]. This method is very promising because a large number of feasible solutions are analyzed and a set of optimal solutions, best trade-off between all criteria, are obtained.
In order to simulate the system, a model of BESS has to be defined. In the literature, BESS models developed for the sizing and the scheduling are simple with a few parameters (e.g., nominal capacity, cycle efficiency, maximum number of cycles, etc.) in order to limit the complexity of the problem.
The state of charge (SOC) of the BESS is the parameter related to the number of charges stored in the battery (a SOC of 100% means that the BESS is fully charged, whereas it is considered to be empty at 0%). In [21, 22, 23], the online estimation of SOC named “coulomb counting” is proposed. This method is based on the measurement of current and takes into account the coulombic efficiency (ampere-hour efficiency):
where ηCh and ηDis are, respectively, the charge and discharge coulombic efficiencies of the BESS (in Ref. [21], the coulombic efficiency is considered equal to 1 during the discharge and smaller than 1 during the charge, due to unwanted side reactions). ICh(t) and IDis(t) are the current level at the charge and discharge, respectively. Cn(t) is the nominal capacity of the BESS. It is to notice that the nominal capacity of the BESS is decreasing all along the lifetime of the BESS; this point will be explained in the next section.
Another variable widely used in the literature is the depth of discharge (DOD) which describes the emptiness of battery (complement of the SOC). Battery manufacturers often provide the maximum number of cycles that a battery can perform for different DODs, as depicted in Figure 3:
Calendar and cycling lifetime model of the BESS derived from [27].
In order to model the effect of other operating conditions (e.g., C-rate and temperature) on the BESS behavior, the SOC can be formulated by introducing the concept of equivalent current. Three technologies of batteries have been tested in Ref. [24], exhibiting both the effect of the C-rate and the temperature on the available discharged capacity. Indeed, it has been empirically formulated by Peukert for lead-acid batteries at the end of the nineteenth century that the discharged capacity is related to the C-rate. The main issue is that this relation is given for a constant level of current during all the discharge conditions (not representative of real conditions). In [25], an improved method is proposed for management of lithium-ion batteries, but the model is difficult to parameterize because it needs a lot of experimental tests to be adapted to the BESS. Usually, a BESS operates at low C-rate in renewable power plants, and the temperature can be assumed to be constant. This is why the state of health (SOH) is the main parameter taken into account in sizing and planning studies.
Due to irreversible reactions, the active material is decreasing, and the electrode interfaces are deteriorated. Thus, the capacity decreases, and the internal resistance increases (power capability fade). In order to know when to replace a BESS, a common criterion is to consider the end of life (EOL) of a battery when its capacity drops to less than 20% of the initial nominal capacity [26]. This limit of 20% has been initially set because of the behavior of lead-acid batteries: the capacity fade is quite linear until 20%, and then there was a sudden drop of capacity. Of course all the batteries do not exhibit this large decrease of capacity; this is why some projects such as the second life of batteries have been created (old batteries that do not fulfill the automotive requirements are reused in stationary projects).
Usually, the aging of batteries is monitored by measuring the nominal capacity and comparing it to the initial nominal capacity Cn(t0). In this case, the battery reaches its EOL when the state of health (SOH) goes below 80%:
The lifetime of batteries is related to calendar aging (shelf life) and cycle aging. In renewable microgrids, a BESS is subjected to variable cycling conditions. The lifetime of a BESS depends on the cycle depth and the SOC level (mean of SOC during the cycle). As shown in Ref. [27], the degradation of the nominal capacity can be considered linear for both calendar and cycling lifetime. As presented in Figure 3, experimental studies performed on lithium-ion batteries [27] revealed that the maximum number of cycles performed by the BESS is higher for low cycle depths and medium SOC levels (close to 50%). Assuming that the BESS will perform at least 1 cycle per day, a limit can be set on the maximum number of cycles that is defined by the calendar aging.
Two main methods are used to estimate the aging of a BESS. In Ref. [28], a simple method called “ampere hour throughput” is based on the assumption that the exchangeable energy of a battery is fixed (because nearly constant) whatever the cycle depth performed by the BESS. In this case, the maximum energy that can be exchanged is calculated as follows:
in which the initial nominal capacity is expressed in Wh. Another method is called the rainflow counting. A very popular algorithm of rainflow counting has been presented by Downing and Socie [29]. Initially developed to estimate the effect of mechanical stress in automotive and building industries, the rainflow counting is often employed to describe the aging of batteries, as in Ref. [30]. Given a battery SOC time series, it is possible to extract the number of cycles with their associated cycle depth and SOC level and then update the value of nominal capacity.
For optimal operation of an energy system equipped with BESSs in different working modes (i.e., grid-connected or islanded), it is crucial to properly design and implement energy management systems (EMSs). These system optimizers normally determine the best possible operating scheme at supply and demand sides in terms of optimized set points for controllable units such as energy storage devices and send them as the control signals into the dedicated control system of interfacing converters. Generally, there are two types of energy/power management strategies used in energy system applications. These are named as interactive schemes based on information sharing mechanisms and passive schemes based on self-autonomy [31].
In a given interactive power/energy management system (IP/EMS), local and global system information (such as line currents, nodal voltages, frequency, and powers) is communicated in the system and exchanged between corresponding nodes in order to determine operation point of each controllable ESS or distributed generation (DG) unit. These strategies also benefit from a sort of intelligence in the integration of the computing and communications technologies which help them to define and develop the communication structure based on the computation burden of each node and other related system’s objectives and constraints [32]. In this regard, three different communication schemes can be realized for an IP/EMS: centralized, decentralized, and hybrid. In each of the mentioned schemes, different communication technologies such as microwave (μW), power line carrier (PLC), fiber optics, infrared, and/or wireless radio networks (such as global system for mobile (GSM) communications and code division multiple access (CDMA)) can be effectively used and integrated into the existing infrastructures [33, 34].
In a centralized P/EMS, also known as a supervisory scheme, there is a centralized entity or a control center that monitors the system’s behavior, collects information from different parts of the network, makes decisions based on the observations, and accordingly updates set points for the controllable units in supply/demand sides [35, 36, 37]. In other words, a centralized P/EMS acts as a master unit, while other local controllers within the system are treated as slaves to follow the reference signals coming from the master unit as shown in Figure 4. To improve the effectiveness of a P/EMS, it is also very important to clearly define system’s objectives and constraints. These objectives (such as operating cost minimization, emission mitigation, power loss reduction, SOC equalization, etc.) together with the constraints might be conflicting in some cases which in turn make the optimal decision-making process a difficult or even an impossible task. Different examples of centralized P/EMS for microgrids can be found in the literature [38, 39, 40]. The advantages of a centralized scheme mainly lie within the simplicity of implementation and globality of optimal solution; however, it brings two disadvantages: single point of failure which implies that a centralized P/EMS has to be securely designed with appropriate built-in redundancy and massive communication expenditure. The latter is not a challenging problem in small-scale networks, but it could be problematic for larger systems as the complexity of the centralized optimization grows exponentially with the number of units (control variables) in the system.
Block diagram of a centralized P/EMS.
Distributed P/EMS is the second interactive scheme for management of a given system in which there is no central supervisory unit, but all the local controllers are connected and communicate with each other through a communication bus [41]. In this sense, each controller not only captures local measurements but also receives information from neighboring nodes which helps in decision-making process according to different optimization objectives [42, 43]. In this scheme, intelligent algorithms are often used for better exploration/exploitation of the environment in order to find optimal operation point. Figure 5 shows the block diagram of a decentralized P/EMS. A distributed scheme has some advantages over a centralized one. First, it supports a scalable structure with Plug-and-Play (PnP) feature for newly added/removed energy sources or load blocks. Second, computation burden of each local controller is mitigated which in turn reduces the required communication bandwidth. Finally, a distributed P/EMS could improve the redundancy and modularity of the system where it is needed. However, there is still a problem if a communication link fails in the system. This failure would not end to a total system collapse, but the performance of the system would not be optimal any longer. Also, a distributed P/EMS suffers from degradation of performance on small/medium networks, increased use of database space, and complex use and administration. Multi-agent system (MAS) is one of the best illustrations for a distributed scheme [44].
Block diagram of a decentralized P/EMS.
Hybrid scheme for power/energy management can be realized as another interactive structure that is mainly based on a combination of centralized and distributed schemes. In a hybrid structure, local controllers which are used for operation management of different energy sources are divided into groups [45]. Within each group, a centralized scheme is used to control and optimize the performance of local controllers. On a higher level, a distributed scheme is utilized to coordinate the operation of centralized controllers in different clusters for global optimization. Such a hybrid strategy can be seen in Figure 6.
Block diagram of a hybrid P/EMS.
It is notable that a hybrid P/EMS scheme is normally implemented for large-scale networks such as interconnected energy systems or microgrids, where the optimal operation of the entire system depends on cooperation and coordination of different control layers over time. By doing this hybridization, it is very possible to improve the system reliability and resiliency for long-run operations due to the unique features that inherently exist in centralized/decentralized schemes [46].
Self-autonomy of operation for a local controller without having information from neighboring nodes is the main idea of a passive power/energy management scheme (PP/EMS). In this structure, it is assumed that making an information sharing mechanism is too costly or not viable; thus, independent operation of energy sources is required. Moreover, it is needed to clearly define the control objective of each energy source to assure reliable operation of the system. Block diagram for such a power/energy management scheme is shown in Figure 7.
Block diagram of a PP/EMS.
Among the existing methods for PP/EMS, droop-based control strategy is regarded as a dominant method [47, 48, 49]. This control methodology adopts the behavior of synchronous machines in responding to the changes in voltage and frequency and applies similar rules in operation management of converters in ac/dc sides. The droop-based control strategy works based on the assumption that the output impedance of a controllable unit (such as a micro-source) is mainly inductive, and it utilizes droop characteristics of voltage amplitude and frequency of each controllable unit to control its output. In case of a dc microgrid, bus voltages and in case of an ac microgrid the system voltage and frequency are the information sensed by each local droop controller and used subsequently to adjust output active (and/or reactive) power of a BESS or a generation unit. Figure 8 shows such control strategy for a given dc microgrid. As can be seen in the same figure, either output power or output current can be selected as the feedback signal in droop control. For dc microgrids with power-type load, output power can be used as droop feedback, as shown in Eq. (11).
Droop control for dc microgrids.
On the other hand, when current signal is used, as shown in Eq. (12), droop coefficient mc can be regarded as a virtual internal resistance. In that case, the implementation and design of the parallel converter system in a dc microgrid can be simplified to some extent as the control law is linear:
where v*DCi is the output of the droop controller, i.e., the reference value of dc output voltage of converter #i; v*DC is the rated value of dc voltage; and mp and mc are the droop coefficients in power-based and current-based droop controllers, while Poi and ioi are the output power and current of converter #i, respectively. Since there is no communication requirement to fulfill the control objectives, this control strategy is highly reliable. Moreover, this control structure could be easily extended to different energy sources while enabling true PnP features. Apart from the benefits, there are several issues in such power/energy management strategy. First, low-voltage regulation and proportional current sharing cannot be addressed directly by this method. Instead, nonlinear and adaptive droop techniques are proposed as key solutions for achieving acceptable voltage regulation at full load and ensuring proportional current sharing. Second, low X/R line impedance ratio may result in active and reactive power coupling and instability issues in low-voltage microgrid systems and cause power sharing errors for generation units [50]. Recently, several works have been done to improve the performance of a conventional droop-based control method by implementing the droop in virtual frames [51], adding virtual impedance in control loops [52], or adjusting the output voltage bandwidth [50]. However, without a coordinating unit such as a central controller or a system optimizer, it would be a challenging task to optimally manage the operation of a microgrid system with PP/EMS.
As another type of PP/EMS, maximum power point tracking (MPPT) control methodology is also applied in microgrids to maximize power extraction from RESs (mainly WTs and PVs) under all conditions [53]. In such power management technique, unit’s voltage and current are sampled frequently, and the duty ratio of the interfaced converter is adjusted accordingly. However, it should be noted that in islanded renewable-based microgrids which are controlled based on MPPT principles, ESSs must also be dispatched to provide voltage and frequency regulation services [54]. Considering the drawbacks of IP/EMS and PP/EMS, it seems that a combined P/EMS structure (e.g., a consensus-based droop framework [55] or a droop-based distributed cooperative control [56]) could not only address reliability issues but also enhance control performance of the system both in grid-connected and stand-alone modes.
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