Global Energy Efficiency Research Articles

Cost- and Energy-Efficient Aerial Communication Networks With Interleaved Hovering and Flying

This work proposes a methodology for the energy-and cost-efficient 3-D deployment of an unmanned aerial vehicle (UAV)-based aerial access point (AAP), that exchanges a given amount of independent data with a set of ground user equipment (UE). Considering a fly-hover-communicate transmission scheme, the most energy-efficient 3-D hovering points (HPs) of the AAP are determined by decoupling the problem in the horizontal and vertical dimensions. First, we derive analytically the optimal hovering altitude that jointly maximizes the downlink and uplink global energy efficiency (GEE) of the system. Next, we propose the multilevel circle packing (MCP) algorithm to determine the minimal number of HPs and their associated horizontal coordinates, such that the AAP covers all the UEs in the given geographical area. A cost analysis is carried out to observe the variation of both fixed and variable costs; these are then minimized by suitably selecting the AAP's battery parameters, like the depth of discharge (DOD), defined as the portion of battery capacity that is consumed during a discharge cycle, and the velocity of the UAV. Simulation results show that: the UAV energy consumption has a significant impact on the 3-D HPs of the AAP; the time spent during the substitution swap of an out of power AAP has a major influence on the operational cost; the cost of the system can be optimized by suitably selecting the onboard battery and the UAV flight parameters.

Properties and Performance of Eco-Friendly Hydro-Fluoro-Olefin (HFO) Refrigerant-R1234yf: Part I

The creation of new age refrigerants might be the answer to the issue of an Earth-wide rise in temperature. Hence, while choosing new refrigerants a careful process is required. The general effect of any refrigerant substance on global warming, energy efficiency, ozone depletion, cost-effectiveness, chemical stability, and safety ought to be assessed. This paper sums up the experimental and numerical investigations directed with the globally accepted R1234yf refrigerant. The paper’s principal points are to assess the capability of the hydro-fluoro-olefin (HFO) refrigerant mainly R1234yf utilized in the refrigeration system (vapor compression systems, domestic refrigeration system) and to explore its utilization as an eco-friendly refrigerant. In the vapor compression refrigeration system, the cooling capacity and coefficient of performance of R1234yf are found to be less, 9% and 11%, respectively compared to that of R134a. But the power consumption of the system with R1234yf increased between 1.6% and 6.7% when compared to R134a. This paper likewise assists with recognizing the gap in the past research works and explores the possibilities for additional works.

Combined vehicle to building (V2B) and vehicle to home (V2H) strategy to increase electric vehicle market share

Buildings are one of the most important energy consumers in modern economy countries. The massive use of electrical vehicles could help decarbonizing the economy by using electricity produced using renewable energy. Combined use of Vehicle to Grid (V2G), Vehicle to Home (V2H) and Vehicle to Building (V2B) is one of the strategies to increase the number of electrical vehicles, ensure a better coupling between energy generation and consumption, reducing peak demand and increasing global energy efficiency. This research presents a novel approach of combined use of V2H and V2B that can be applied in different scenarios such as when the building workers own EVs, company shared car fleets or leasing, among others. Recharged energy at workers homes during night hours is delivered in the building during daily working hours lowering peak demand, reducing carbon intensity and energy cost savings. The results show that the methodology is feasible and can be extended to other cases and greatly contribute to better energy efficiency, reduces peak demand in buildings and increase electric vehicles penetration in transport to workplaces.

Biomass direct gasification for electricity generation and natural gas replacement in the lime kilns of the pulp and paper industry: A techno-economic analysis

This study shows a comparative techno-economic analysis of the integration of biomass gasification for generation of producer gas to be used in electricity production and to replace natural gas in the lime kilns of the pulp and paper industry. Three study cases with alternative configurations of the energy system integrating biomass gasification were analysed, including or not the co-generation of electricity and thermal energy, namely: i) Case I, for generation of electricity from residual forest biomass (RFB) in an integrated gasification combined cycle system, ii) Case II, generation of producer gas by RFB gasification for replacement of natural gas in the burners of a lime kiln, and iii) Case III, as an integration of Cases I and II for combined production of electricity and heat. Residual forest biomass from eucalyptus logging activities for feedstock processing for the pulp and paper industry was considered as fuel for direct (air) gasification in bubbling fluidized bed. The analysis made is supported on review reports, namely, the evaluation of the existing literature on investment projects in biomass power plants, and on experimental investigation for determining the composition of the producer gas from gasification of the selected feedstock. An economic model was developed that combines the net present value, internal rate of return and payback period. The main results of the energy system analysis show that the net electricity generation is between 72 and 83 GWh/year, while the production of CaO in the lime kiln supported by combustion of producer gas, is 82.12 kt/year, and a global energy efficiency between 21.70 and 34.17 % is achieved for the analysed configurations of the energy system. The results of the economic analysis show a positive NPV, an IRR greater than the discount rate and a PBP less than the useful life of the plant. The sensitivity analysis shows quite favorable investment projections given the low probability that the NPV will reach negative values and compromise the economic viability of the project.

Does Energy Efficiency Affect Ambient PM2.5? The Moderating Role of Energy Investment

The difficulty of balance between environment and energy consumption makes countries and enterprises face a dilemma, and improving energy efficiency has become one of the ways to solve this dilemma. Based on the data of 158 countries from 1980 to 2018, the dynamic TFP of different countries is calculated by means of the Super-SBM-GML model. The TFP is decomposed into indexes of EC (Technical Efficiency Change), TC (Technological Change) and EC has been extended to PEC (Pure Efficiency Change) and SEC (Scale Efficiency Change). Then the fixed effect model and the fixed effect panel quantile model are used to analyze the moderating effect and the exogenous effect of energy efficiency on PM2.5 concentration on the basis of verifying that energy efficiency can reduce PM2.5 concentration. We conclude, first, the global energy efficiency has been continuously improved during the sample period, and both technological progress and technical efficiency have been improved. Second, the impact of energy efficiency on PM2.5 is heterogeneous which is reflected in the various elements of energy efficiency decomposition. The increase in energy efficiency can inhibit PM2.5 concentration and the inhibition effect mainly comes from TC and PEC, but SEC promotes PM2.5 emission. Third, energy investment plays a moderating role in the environmental protection effect of energy efficiency. Fourth, the impact of energy efficiency on PM2.5 concentration is heterogeneous in terms of national attribute, which is embodied in the differences of national development, science and technology development level, new energy utilization ratio, and the role of international energy trade.

Optimization and digitization of wind farms using internet of things : A review

Utilizing every available technology in improving the effectiveness of sustainable energy schemes is an important tool that should be harnessed in the war against fossil fuel and other problems associated with global warming. Enhancing sustainable energy schemes is fundamental to improving the rate of global energy efficiency coupled with decreasing the share of carbon systems in the global energy mix. With the integration of modern technologies like the internet of things (IoT), machine learning, and artificial intelligence, energy systems are generally smarter, more efficient, reliable and also possess the potential to mitigate global energy problems. This paper reviews the application of IoT in wind farms and the energy sector at large. It establishes that integrating IoT into wind farms has the potential to save about 50 million to 230 million US dollars of its operation expenses, improve the current 743 GW global wind power capacity to an amount substantial to enable it supply 20% of the world's electricity by 2030 and also allow wind energy technology to hold a good share in the 100 billion objects that is expected to be connected to the internet by 2025. In addition to this, it reviews the challenges associated with the deployment of IoT in wind farms and the future of block-chain technology and green IoT in energy systems.

Non-Orthogonal Multiple Access for Unicast and Multicast D2D: Channel Assignment, Power Allocation and Energy Efficiency.

Non-orthogonal multiple access (NOMA) techniques have emerged in the past years as a solution to approximate the throughput performance of wireless communications systems to their theoretical capacity region. We consider in this paper an optimization-based model for multicast device-to-device (MD2D) communications where the channels are not orthogonal and may be (partially or fully) shared among the transmitters in each cluster. This setting leads naturally to the introduction of NOMA transmitters and receivers who use successive interference cancellation (SIC) to separate the superposed signals. To analyze the role of NOMA in MD2D, its performance impact, potential performance gains and possible shortcomings, we formulate a model that includes SIC operations in the decoders, so that higher rates can be attained when several sources transmit on the same channel(s). We also investigate the energy efficiency of the network (global and max-min) through a dynamic power control algorithm and present a centralized and a semi-distributed solution to these optimization problems. Through numerical simulations, we show that NOMA is able to improve both the sum-rate and the max-min rate of a MD2D network even from a small degree of resource sharing. Furthermore, these gains also improve the global energy efficiency on the network, but not always the max-min energy efficiency of the devices.

Energy‐efficient radio resource allocation for dual‐hop relay‐assisted orthogonal frequency division multiple access systems with quality of service provisioning

AbstractBesides the conventional spectral efficiency metric, energy efficiency (EE) has been adopted as one of the new mandatory performance metrics for green future mobile networks. In this sense, in this article we study energy‐efficient radio resource allocation for dual‐hop orthogonal frequency division multiple access relay networks considering multiple relays and users. Resource allocation in our scenario is comprised of relay selection, subcarrier pairing, subcarrier assignment, and transmit power allocation. Particularly, in the context of EE with quality of service constraints, three different problems, namely, power consumption minimization, global EE maximization, and minimum individual EE maximization are addressed. For tackling them, first, we demonstrate a property that exploits the use of the decode and forward protocol employed in the relays and we show how it can be applied to simplify the investigated problems. Although some of these problems are nonconvex due to the fractional objective functions and integer optimization domain, optimal solutions are provided using generalized fractional programming theory to transform the fractional objective functions to the subtractive forms. Then, by employing Dinkelbach or bisection methods, we propose iterative algorithms where a parametric problem is solved in each iteration until reaching convergence. By introducing a penalty function to handle integer variables and applying majorization‐minimization approach, we make the parametric problem convex and we propose suboptimal iterative solutions with reduced computational cost. Regarding obtained simulation results, we discuss the performance of the involved solutions in terms of global EE and fairness with respect to different parameters of the system.

Secrecy Energy Efficiency in Cognitive Radio Networks With Untrusted Secondary Users

The information security and energy efficiency in cognitive radio (CR) networks have been extensively studied. However, the practical scenario involving multiple untrusted secondary users (SUs) in CR networks under the underlay spectrum sharing mechanism has not been studied so far. This article considers the downlink secrecy energy efficient coordinated beamforming design for multiple inputs single output CR networks under this scenario. Our goal is to maximize the global secrecy energy efficiency (GSEE), defined as the ratio of the sum of secrecy rates of all the primary users (PUs) to the total power consumption, under requirements on quality of service of PUs and SUs as well as constraints on power budget at the primary transmitter (PTx) and the secondary transmitter (STx). To tackle the non-convex GSEE maximization (GSEEM) problem, an algorithm is proposed based on Dinkelbach method and successive convex approximation to jointly optimize beamforming vectors of the PTx and the STx. The convergence behavior and the computational complexity of the proposed GSEEM algorithm are analyzed, followed by the connection with the secrecy rate maximization design and the power minimization (PM) design in terms of GSEE. In view of significantly higher computational complexity of the proposed GSEEM algorithm than that of the PM design, a 2-step searching scheme is further designed to efficiently search for an approximate solution to the considered GSEEM problem based on the PM design and the golden search method. Simulation results demonstrate the efficacy of the proposed GSEEM algorithm and the searching scheme, and show that the spatial degrees of freedom (primarily determined by the antenna numbers of PTx and STx) is the key factor to the performance of the proposed GSEEM algorithm.

Joint Mobility, Communication and Computation Optimization for UAVs in Air-Ground Cooperative Networks

Unmanned aerial vehicles (UAVs) play a significant role in various 5G or Beyond-5G (B5G)-enabled Internet-of-Things (IoT) applications. However, the UAV performance in an air-ground cooperative network is significantly affected by its mobility and air-to-ground (A2G) communication and computation behaviors. In this paper, a UAV-oriented computation offloading system is investigated, where the UAV desires to complete its onboard computation demands with the assistance of a ground edge-computing infrastructure, i.e., a road-side unit (RSU). The objective is to maximize the energy efficiency of the UAV. Specifically, a non-convex constrained optimal control problem is formulated to optimize the overall energy efficiency of UAV by jointly considering the coupled effects of UAV's longitudinal mobility, A2G communication, and computation dynamics. To address the coupled complexity and non-convexity of the original problem, a primal decomposition approach is developed to transform the problem into a convex subproblem and a primary problem, and then a closed-form optimal transmission power control is derived by solving the subproblem, which is dependent on mobility information. By embedding the closed-form optimal power control into the primary problem, a gradient projection-based iterative algorithm is proposed to obtain a joint optimal solution for both the longitudinal acceleration control and the power control, the feasibility and convergence of which is also theoretically proven. Extensive simulations have been conducted to validate the effectiveness of the proposed method in terms of constraint satisfaction and convergence speed, and comparative results also demonstrate that it can outperform other benchmark methods in terms of global energy efficiency.

Global energy efficiency improvement of redundant hydraulic manipulator with dynamic programming

Open-loop controlled hydraulic manipulators are still dominating in construction sites and forest fields thanks to little reliance on the expertise of human operators in manipulator control, which however exist large inlet/outlet and other energy losses during working cycles. And the situation further deteriorates with the increasing number of joints. This paper discusses the problem of global energy optimization of three-degrees-of-freedom (3-DOF) hydraulic manipulator in case of plane motion where exists an exceeding DOF for motion redundancy. Different from conventional energy optimization methods applied to electric driven manipulators, the proposed global energy-optimized dynamic programming (DP) algorithm models the whole system at the hydraulic level, which contains the dynamic characteristics of pressure-flow coupling between cylinders. The energy consumption models of constant pressure (CP), load-sensing (LS) and electrohydraulic load-sensing (ELS) systems are built in terms of cost functions formulated in the proposed algorithm together with penalty function containing physical actuator constraints at position, velocity and acceleration level. The DP algorithm is tested in various cases, and the convergence is proved consistent. To highlight the effectiveness of the proposed algorithm, the gradient projection (GP) method and the actuator velocity minimum norm (MA) method are introduced as a contrast. The results of the numerical examples of end-effector paths using the mechanical-hydraulic coupling AMESim model demonstrate that the DP algorithm saves around 10.49% hydraulic energy consumption in the CP system while saving around 76.55% in the LS system. Experiments performed on a typical-structured hydraulic manipulator further validate the effectiveness of the proposed algorithm, with approximately 4.61% energy saving in the CP system and 29.89% in the LS system. The energy-saving ratio is even larger in the ELS system, with around 80.03% comparing the max value. These contribute to the energy optimization resolution of redundant hydraulic manipulators to a degree.

Global Energy Efficiency Optimization of a Ka-Band Multi-Beam LEO Satellite Communication System

We investigate the issue of global energy efficiency optimization in a multi-beam low Earth orbit (LEO) satellite communication system. Current terrestrial networks provide high-quality and low cost communication mainly in densely populated areas. However, the cost of extending wideband coverage to remote areas is unaffordable. LEO satellites provide a low cost solution for offering global coverage by supporting terrestrial networks. We consider downlink transmissions in Ka-band, where a LEO satellite transmits to access points or users directly. Impairments due to Ka-band channels, inter-beam interference as well as Doppler effects are taken into account in our mathematical model. We formulate the problem of jointly optimizing beam assignment and power allocation for maximizing global energy efficiency. Given the intractability of this problem, we propose to divide it into two subproblems: first, beam assignment optimization under fixed power per beam, and second, power allocation optimization under fixed beam assignment. We devise two algorithms, beam-wise power optimization and equal power optimization. These two algorithms solve the subproblems, beam assignment and power allocation, in a different way. Numerical results show that our proposed methods can greatly improve the global energy efficiency compared to the baseline method with a fixed power per beam.

Distributed Algorithms for Spectral and Energy-Efficiency Maximization of K-User Interference Channels

In this paper, we propose a cooperative distributed framework to optimize a variety of rate and energy-efficiency (EE) utility functions, such as the minimum-weighted rate or the global EE, for the K-user interference channel. We focus on the single-input multiple-output (SIMO) case, where each user, based solely on local channel state information (CSI) and limited exchange information from other users, optimizes its transmit power and receive beamformer, although the framework can also be extended to the multiple-output multiple-input (MIMO) case. The distributed framework combines an alternating optimization approach with majorization-minimization (MM) techniques, thus ensuring convergence to a stationary point of the centralized cost function. Closed-form power update rules are obtained for some utility functions, thus obtaining very fast convergence algorithms. The receivers treat interference as noise (TIN) and apply the beamformers that maximize the signal-to-interference-plus-noise (SINR). The proposed cooperative distributed algorithms are robust against channel variations and network topology changes and, as our simulation results suggest, they perform close to the centralized solution that requires global CSI. As a benchmark, we also study a non-cooperative distributed framework based on the so-called “signal-to-leakage-plus-noise ratio” (SNLR) that further reduces the overhead of the cooperative version.

Local and Global Energy Efficiency Analysis for Energy Production Based on Multi-Plant Generalized Production Technology

Power plants plays an important role in term of economic and social affect in all societies. Most of economic sectors and manufacturers are depended in the outcome of power plants in one side and electricity is a vital need of all households and entire society. Therefore, the performance of power plants and consequently their sustainability is crucial concept in the current century. This article proposes a generalized efficiency measurement model for multi-plant firms in terms of returns to scale and number of outputs. This yields to some new indicators for efficiency measurement in an un-communal and communal environment for the local and global analysis. The idea is explained by providing a graphical illustration and numerical example. Proposed models are used for energy efficiency analysis of 46 power plants of 19 provinces in Iran. Local and global aspect of energy efficiency are investigated by using proposed models for aforementioned case study. Primary results are shown that, higher potential energy saving in the communal global environment compared with the local analysis. This highlight the corporation of production electricity units, namely, power plants in this study is a requirement for sustainable energy supply.

Energy-Efficient Spatially-Correlated Hardware Impaired Massive MIMO FD Relaying

Most of the existing massive multi-input-multi-output (mMIMO) relaying works assume ideal transceiver hardware and spatially uncorrelated channels. A practical mMIMO relay, however, due to limited antenna spacing and the use of cost-effective equipment, usually experiences spatially-correlated channels and hardware impairments, respectively. We consider a hardware-impaired two-way full-duplex (FD) spatially-correlated mMIMO relaying with multiple MIMO FD user-pairs, and derive a closed-form spectral efficiency (SE) expression which is valid for a practical number of finite relay antennas. We use this expression to develop a quadratic transformation approach to optimize the non-convex global energy efficiency (GEE) and weighted sum energy efficiency (WSEE) metrics, which are fractional functions of optimization variables. The proposed approach first converts the fractional problem into its equivalent fraction-free counterpart, and then uses novel transformations to make the problem concave, and solve it using an iterative algorithm. We use this optimization to i) investigate the impact of spatial correlation and hardware impairments on GEE; ii) decide hardware impairment values for a tolerable reduction in GEE; and iii) investigate the impact of weights in WSEE on the users energy efficiency.

Robust Cooperative Communication Optimization for Multi-UAV-Aided Vehicular Networks

Aerial-ground cooperative vehicular networks are envisioned as a novel paradigm in B5G/6G visions. In this letter, the challenge of optimizing the global energy-efficiency (EE) of multi-UAV-aided vehicular networks in the presence of uncertain air-to-ground (A2G) channels is addressed. Specifically, we propose a maximin paradigm to characterize the system, which aims to maximize its global EE meanwhile satisfying Quality-of-Service (QoS)-oriented data rate requirements in the worst-case situation. We theoretically derive a closed-form optimal solution for an embedded minimization subproblem under a parametric channel uncertainty set and thus develop a computationally tractable robust counterpart, which leads to a robust EE optimization design. Simulation results show that the proposed method significantly outperforms conventional EE schemes in terms of achieving higher global system performance and better robustness under random uncertain environments.

Early hemodynamic changes after transcatheter aortic valve implantation in patients with severe aortic stenosis measured by invasive pressure volume loop analysis

Replacement of a stenotic aortic valve reduces immediately the ventricular to aortic gradient and is expected to improve diastolic and systolic left ventricular function over the long term. However, the hemodynamic changes immediately after valve implantation are so far poorly understood. Within this pilot study, we performed an invasive pressure volume loop analysis to describe the early hemodynamic changes after transcatheter aortic valve implantation (TAVI) with self-expandable prostheses. Invasive left ventricular pressure volume loop analysis was performed in 8 patients with aortic stenosis (mean 81.3 years) prior and immediately after transfemoral TAVI with a self-expandable valve system (St. Jude Medical Portico Valve). Parameters for global hemodynamics, afterload, contractility and the interaction of the cardiovascular system were analyzed. Left ventricular ejection fraction, (53.9% vs. 44.8%, p = 0.018), preload recruitable stroke work (68.5 vs. 44.8 mmHg, p = 0.012) and end-systolic elastance (3.55 vs. 2.17, p = 0.036) both marker for myocardial contractility declined significantly compared to baseline. As sign of impaired diastolic function, TAU, a preload-independent measure of isovolumic relaxation (37.3 vs. 41.8 ms, p = 0.018) and end-diastolic pressure (13.1 vs. 16.4 mmHg, p = 0.015) raised after valve implantation. Contrarily, a smaller ratio of end-systolic to arterial elastance (ventricular-arterial coupling) indicates an improvement of global cardiovascular energy efficiency (1.40 vs. 0.97 p = 0.036). Arterial elastance had a strong correlation with the number of conducted rapid ventricular pacings (Pearson correlation coefficient, r = 0.772, p = 0.025). Invasive left ventricular pressure volume loop analysis revealed impaired systolic and diastolic function in the early phase after TAVI with self-expandable valve for the treatment of severe aortic stenosis. Contrarily, we found indications for early improvement of global cardiovascular energy efficiency.

Techno-economic modeling of an integrated biomethane-biomethanol production process via biomass gasification, electrolysis, biomethanation, and catalytic methanol synthesis

Biological methanation (biomethanation) of syngas obtained from biomass gasification offers the opportunity to employ a low-pressure, low-temperature process to produce storable bio-derived substitute natural gas (bSNG), although its economic viability is limited by high energy and biomass costs. Research on syngas biomethanation techno-economic performance is limited and novel biomass-to-biomethane process configurations are required in order to assess opportunities for the enhancement of its efficiency and economic feasibility. In this study, we carried out the techno-economic modeling of two processes comprising integrated biomass gasification, electrolysis, and syngas biomethanation with combined heat and power recovery in order to assess and compare their fuel yields, energy efficiency, carbon efficiency, and bSNG minimum selling price (MSP). The first process operates standalone biomethanation (SAB) of syngas and can produce approximately 38,000 Nm3 of bSNG per day, with a total plant efficiency of 50.6%. The second process (integrated biomethane-biomethanol, IBB) exploits the unconverted carbon stream from the biomethanation process to recover energy and synthesize methanol via direct catalytic CO2 hydrogenation. In addition to the same bSNG output, the IBB process can produce 10 t/day of biomethanol, at a 99% purity. The IBB process shows little global energy efficiency gains in comparison with SAB (51.7%) due to the large increase in electrolytic hydrogen demand, but it shows a substantial improvement in biomass-to-fuel carbon efficiency (33 vs. 26%). The SAB and IBB processes generate a bSNG MSP of 2.38 €/Nm3 and 3.68 €/Nm3, respectively. Hydrogenation of unconverted carbon in biomass-to-biomethane processes comes with high additional capital and operating costs due to the large-scale electrolysis plants required. Consequently, in both processes, the market price gap of the bSNG produced is 0.13 €/kWhbSNG (SAB) and 0.25 €/kWhbSNG (IBB) even under the most optimistic cost scenarios considered, and it is primarily influenced by the cost of surplus electricity utilized in electrolysis, while the selling price of biomethanol exerts a very limited influence on process economics. Intensive subsidization would be required in order to sustain the decentralized production of bSNG through both processes. Despite their limited economic competitiveness, both processes have a size comparable with existing renewable gas production plants in terms of bSNG production capacity and the IBB process is of a size adequate for the supply of biomethanol to a decentralized biorenewable supply chain.

Exploring the research fronts of low carbon and energy-efficiency in economic environmental development: a scientometric analysis from a multidisciplinary literature

In the increasingly severe global economic environment, low-carbon and energy efficiency have become a hot topic in contemporary times. In order to provide low-carbon and energy efficiency at the forefront of economic and environmental development, this article is based on 192 data retrieved from the Web of Science (WoS) database. This article conducted a comprehensive data and visualization analysis on keywords such as “low-carbon economy” and “low-carbon development”.

Drying kinetics of natural rubber sheets under two solar thermal drying systems

This work describes the thermal behavior and evaluation of kinetics drying of natural rubber sheets using two solar drying technologies: direct and indirect. The solar drying tests were carried out simultaneously in order to compare the behavior under same weather conditions. The moisture content of the rubber sheets was reduced from 45.8 to 0.59% and from 49.7 to 0.33% on a dry basis (d.b.) for direct solar drying and indirect solar drying, respectively. The direct drying mode was carried out for 12 days with average temperature and relative humidity inside the greenhouse, during sunny hours, of 37.04 °C and 14.1%, respectively. Meanwhile, the indirect drying operation was carried out in 9 days (61.62 h intermittently) with 61 °C and 4.77%, respectively. The average global energy efficiency of the field of SAH was 33.77%. Thirteen thin layer models were used to evaluate the drying behavior of which the Modified Henderson and Pabis model was the best to describe the solar drying of rubber sheets for the direct and indirect system. As a conclusion, the direct greenhouse-type solar dryer is recommended for small producers and the indirect tunnel-type solar dryer for companies with high and continuous production.