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Vegetable oil and animal fat derived fatty acid methyl esters are commonly known as biodiesel and provide an environment friendly and renewable substitute for the conventional diesel fuel. The present work demonstrates an easy preparation of potassium ion impregnated calcium oxide in nano crystalline form (supported by powder X-ray diffraction and transmission electron microscopic studies) and its application as a solid catalyst for the transesterification of waste cottonseed oil with methanol. The catalyst prepared by impregnating 3.5 wt% of potassium in CaO support was found to show the best catalytic activity among the prepared catalysts. The same catalyst was found to be effective for the complete transesterification of less expensive feedstock, waste cotton seed oil, even in the presence of 10.26 wt% moisture and 4.35 wt% free fatty acid contents. The selected catalyst has also been reused successfully for three catalytic cycles. Few physicochemical properties of the prepared biodiesel sample have been studied and found to be within the acceptable limits of EN 14214 standards.

Sustainability of agro-food supply chains has recently become the subject of greater interest from consumers, firms, governmental organizations and academia as the environment continues to deteriorate. One of the most critical factors influencing the sustainability of an agro-food supply chain is its network design. A particularly challenging aspect in this context is the broad range of influencing indicators associated with the Triple Bottom Line (TBL) of sustainability that need to be considered. However, many of these indicators could not be fully integrated or measured by single-step optimization problems. This paper presents a critical literature review of operational research methods for the design of sustainable supply chains. A novel two-stage hybrid solution methodology is proposed. In the first stage, a partner selection is performed using a hybrid multi criteria decision making based on Analytic Hierarchy Process (AHP) method and the Ordered Weighted Averaging (OWA) aggregation method. The result obtained in the first stage is used in the second stage to develop a multi-objective mathematical model to optimize the design of the supply chain network. This approach allows the simultaneous consideration of all three dimensions of sustainability including carbon footprint, water footprint, number of jobs created and the total cost of the supply chain design. The proposed approach generates a Pareto frontier to aid users in making decisions. Numerical experiments are completed utilizing data from an agro-food company to demonstrate the efficiency and effectiveness of the proposed solution methodology. The analyzes of the numerical results provide important organizational, practical and policy insights on (1) the impact of financial and environmental sustainability on supply chain network design (2) the tradeoff analysis between environmental emission, water footprint, societal implications and associated cost for making informed decision on supply chain investment.

Abstract The rapid increase in energy demand and the limited resources of fossil fuel as well as the environmentally damaging effects, drive the world to find new options for sustainable electricity generation, which is represented by renewable energies. Concentrating solar power (CSP) is one of the most promising technologies in the field of electricity generation to tackle this issue with a competitive cost in the future. This paper presents an investigation of the potential of implementation of CSP plants in Libya. The socio-economic context, current energy situation of the country and different types of CSP plants are discussed. Moreover, an assessment of site parameters required for CSP plants including solar resources, land use and topography, water resources and grid connections are investigated in detail. In addition, thermo-economic simulation of a 50 MW parabolic trough power plant is performed. The simulation is conducted based on meteorological data measured by the weather station installed at the Centre for Solar Energy Research and Studies (CSERS) in Tajoura city. The performance results are compared with the reference plant Andasol-1 in Spain. Even though the proposed plant is located on the North coast where solar resources are at their minimum compared with other regions of the country, the outcome of the study proves that Libya is not only suitable but it can be economically competitive in the implementation of CSP technology.

ABSTRACTThe California generation fleet manages the existing variability and uncertainty in the demand for electric power (load). When wind power is added, the dispatchable generators manage the variability and uncertainty of the net load (load minus wind power). The variability and uncertainty of the load and the net load are compared when 8790 MW of wind power are added to the California power system, a level expected when California achieves its 33% renewable portfolio standard, using a data set of 26,296 h of synchronous historic load and modeled historic wind power output. Variability was calculated as the rate of change in power generated by wind farms or consumed by the load from 1 h to the next (MW/h). Uncertainty was calculated as the 1 h ahead forecast error [MW] of the wind power or of the load. The data show that wind power adds no additional variability than is already present in the load variability. However, wind power adds additional uncertainty through increased forecast errors in the net load compared with the load. Forecast errors in the net load increase 18.7% for negative forecast errors (actual less than forecast) and 5.4% for positive forecast errors (actual greater than forecast). The increase in negative forecast errors occurs only during the afternoon hours when negative load forecasts and positive wind forecasts are strongly correlated. Managing the integration of wind power in the California power system should focus on reducing wind power forecast uncertainty for wind ramp ups during the afternoon hours. Copyright © 2013 John Wiley & Sons, Ltd.

Abstract Gold nanoparticles (Au-NPs) seeded plasmonic nanofluids (PNFs) have shown promising results in overall performance enhancement of direct absorption solar collector (DASC) due to localized surface plasmon resonance (LSPR) effect. For the work presented here, Au-NPs were synthesized by the wet chemical method and were utilized to prepare plasmonic nanofluid. The surface plasmon resonance peak of Au-NPs was observed at 531 nm using UV–Visible spectrophotometer study. The testing for performance enhancement of gold plasmonic nanofluid (GPNF) laden DASC so far is limited to laboratory scale setups or simulation studies. Considering the dearth of outdoor experimental studies, an attempt has been made in the present study to evaluate the thermal performance of Au-NPs (∼40 nm) based nanofluid (∼0.0002 wt%) in full scale DASC. The experiments have been performed at different flow rates under clear sky outdoor conditions in winter season at Jalandhar, India. The maximum collector outlet temperature was measured to be 55 °C with GPNF which is about 7 °C higher than the maximum outlet temperature obtained with de-ionized water as working fluid. Thermal efficiency with GPNF is about 33% higher than de-ionized water at the optimal flow rate of 0.030 kg/s.

LoRA stands for Long Range communication. Lo-RAwan is the specification used for the battery operated and wireless systems. The main aim of the LoRA is to target the Internet Of Things requirement and also Bidirectional communication. In order to prove the proof of concept, here we are creating a smart prepaid electric meter which will consist of lora module along with it. All the data related to the meters i.e voltage, energy power etc will be send to a gateway. Gateway is the central unit or router which collects all the data from all the meters and it is connected with the local storage device or PC which will create the database for all the data, Now this data is again uploaded to the cloud by this pc to the public network, which can be accessed from any of the place. The most important part of this is that this concept of communication can be extended to other application in which the data transmitted bits is less. As a result of this we can overcome the disadvantage of the 3G/4G GSM modules and low power WAN i.e. LORA can be used for communication.

In this paper, we investigate the energy harvesting (EH) technique and accordingly design transceivers for a $K$ link multiple-input multiple-output interference channel. Each link consists of two full-duplex (FD) Internet of Things (IoT) nodes exchanging information simultaneously in a bi-directional communication channel. All the nodes suffer from interference, in particular strong self-interference and inter-node interference, due to operating in FD mode and simultaneous transmission at each link, respectively. Further, we divide the received signal at each node into two parts. While one part of the signal is used for information decoding, the other part is used for EH. We jointly design the transmit and receive beamforming vectors and receiver power splitting ratios by minimizing the total transmission power of the system, subject to both signal-to-interference-plus-noise ratio and EH threshold constraints. Furthermore, the case of multiple-input single-output interference channel is also included for the sake of comparison. We also revisit the above problems for the case when the available channel state information (CSI) at the transmitters is imperfect, where the errors of the CSI are assumed to be norm bounded. Simulation results show that the EH technique can harvest enough energy to support power consumption limited IoT devices by aiding in recharging their respective batteries.