Sensor psychrometric approaches to mitigating aflatoxins in maize dried on farms in Kenya

Kenia liegt in den Äquatorialtropen von Ostafrika und ist als ein weltweiter Hot-Spot für Aflatoxinbelastung insbesondere bei Mais bekannt. Diese toxischen und karzinogenen Verbindungen sind Stoffwechselprodukte von Pilzen und so insbesondere von der Wasseraktivität abhängig. Diese beeinflusst sowohl die Trocknung als auch die Lagerfähigkeit von Nahrungsmitteln und ist somit ein wichtiger Faktor bei der Entwicklung von energieeffizienten und qualitätsorientierten Verarbeitungsprozessen. Die vorliegende Arbeit hat sich zum Ziel gesetzt, die Veränderung der Wasseraktivität während der konvektiven Trocknung von Mais zu untersuchen. Mittels einer Optimierungssoftware (MS Excel Solver) wurde basierend auf sensorerfassten thermo-hygrometrischen Daten der gravimetrische Feuchteverlust von Maiskolben bei 37°C, 43°C und 53°C vorausberechnet. Dieser Bereich stellt den Übergang zwischen Niedrig- und Hochtemperaturtrocknung dar. Die Ergebnisse zeigen deutliche Unterschiede im Verhalten der Körner und der Spindel. Die Trocknung im Bereich von 35°C bis 45°C kombiniert mit hohen Strömungsgeschwindigkeiten (> 1,5 m / s) begünstigte die Trocknung der Körner gegenüber der Spindel und kann daher für eine energieeffiziente Trocknung von Kolben mit hohem Anfangsfeuchtegehalt empfohlen werden. Weitere Untersuchungen wurden zum Verhalten unterschiedlicher Schüttungen bei der bei Mais üblichen Satztrocknung durchgeführt. Entlieschter und gedroschener Mais führte zu einem vergrößerten Luftwiderstand in der Schüttung und sowohl zu einem höheren Energiebedarf als auch zu ungleichmäßigerer Trocknung, was nur durch einen erhöhten technischen Aufwand etwa durch Mischeinrichtungen oder Luftumkehr behoben werden könnte. Aufgrund des geringeren Aufwandes für die Belüftung und die Kontrolle kann für kleine landwirtschaftliche Praxisbetriebe in Kenia daher insbesondere die Trocknung ganzer Kolben in ungestörten Schüttungen empfohlen werden. Weiterhin wurde in der Arbeit die Entfeuchtung mittels eines Trockenmittels (Silikagel) kombiniert mit einer Heizquelle und abgegrenztem Luftvolumen untersucht und der konventionellen Trocknung gegenüber gestellt. Die Ergebnisse zeigten vergleichbare Entfeuchtungsraten während der ersten 5 Stunden der Trocknung. Der jeweilige Luftzustand bei Verwendung von Silikagel wurde insbesondere durch das eingeschlossene Luftvolumen und die Temperatur beeinflusst. Granulierte Trockenmittel sind bei der Maistrocknung unter hygienischen Gesichtspunkten vorteilhaft und können beispielsweise mit einfachen Öfen regeneriert werden, so dass Qualitätsbeeinträchtigungen wie bei Hochtemperatur- oder auch Freilufttrocknung vermieden werden können. Eine hochwertige Maistrocknungstechnik ist sehr kapitalintensiv. Aus der vorliegenden Arbeit kann aber abgeleitet werden, dass einfache Verbesserungen wie eine sensorgestützte Belüftung von Satztrocknern, der Einsatz von Trockenmitteln und eine angepasste Schüttungshöhe praktikable Lösungen für Kleinbauern in Kenia sein können. Hierzu besteht, ggf. auch zum Aspekt der Verwendung regenerativer Energien, weiterer Forschungsbedarf.

Investigation of methods for increasing the energy efficiency on unmanned aerial vehicles (UAVS)

In recent years, development of Unmanned Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This thesis presents an investigation of methods for increasing the energy efficiency on UAVs. One method is via the development of a Mission Waypoint Optimisation (MWO) procedure for a small fixed-wing UAV, focusing on improving the onboard fuel economy. MWO deals with a pre-specified set of waypoints by modifying the given waypoints within certain limits to achieve its optimisation objectives of minimising/maximising specific parameters. A simulation model of a UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. This simulation model was separately integrated with a multi-objective Evolutionary Algorithm (MOEA) optimiser and a Sequential Quadratic Programming (SQP) solver to perform single-objective and multi-objective optimisation procedures of a set of real-world waypoints in order to minimise the onboard fuel consumption. The results of both procedures show potential in reducing fuel consumption on a UAV in a ight mission. Additionally, a parallel Hybrid-Electric Propulsion System (HEPS) on a small fixedwing UAV incorporating an Ideal Operating Line (IOL) control strategy was developed. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine was determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

Energy- and environmentally efficient road management: The case of the Spanish motorway network

Transport is responsible for 41% of CO2 emissions in Spain, and around 65% of that figure is due to road traffic. Tolled motorways are currently managed according to economic criteria: minimizing operational costs and maximizing revenues from tolls. Within this framework, this paper develops a new methodology for managing motorways based on a target of maximum energy efficiency. It includes technological and demand-driven policies, which are applied to two case studies. Various conclusions emerge from this study. One is, that the use of intelligent payment systems is recommended; and another, is that the most sustainable policy would involve defining the most efficient strategy for each motorway section, including the maximum use of its capacity, the toll level which attracts the most vehicles, and the optimum speed limit for each type of vehicle.

Optimum demand side response of smart grid with renewable energy source and electrical vehicles

The paper presents a demand side response scheme,which assists electricity consumers to proactively control own demands in such a way to deliberately avert congestion periods on the electrical network. The scheme allows shifting loads from peak to low demand periods in an attempt to flattening the national electricity requirement. The scheme can be concurrently used to accommodate the utilization of renewable energy sources,that might be available at user’s premises. In addition the scheme allows a full-capacity utilization of the available electrical infrastructure by organizing a wide-use of electric vehicles. The scheme is applicable in the Eastern and Southern States of Australia managed by the Australian Energy Market Operator. The results indicate the potential of the scheme to achieve energy savings and release capacity to accommodate renewable energy and electrical vehicle technologies.

Analysis and correction of voltage profile in low voltage distribution networks containing photovoltaic cells and electric vehicles

Voltage drop and rise at network peak and off–peak periods along with voltage unbalance are the major power quality problems in low voltage distribution networks. Usually, the utilities try to use adjusting the transformer tap changers as a solution for the voltage drop. They also try to distribute the loads equally as a solution for network voltage unbalance problem. On the other hand, the ever increasing energy demand, along with the necessity of cost reduction and higher reliability requirements, are driving the modern power systems towards Distributed Generation (DG) units. This can be in the form of small rooftop photovoltaic cells (PV), Plug–in Electric Vehicles (PEVs) or Micro Grids (MGs). Rooftop PVs, typically with power levels ranging from 1–5 kW installed by the householders are gaining popularity due to their financial benefits for the householders. Also PEVs will be soon emerged in residential distribution networks which behave as a huge residential load when they are being charged while in their later generation, they are also expected to support the network as small DG units which transfer the energy stored in their battery into grid. Furthermore, the MG which is a cluster of loads and several DG units such as diesel generators, PVs, fuel cells and batteries are recently introduced to distribution networks. The voltage unbalance in the network can be increased due to the uncertainties in the random connection point of the PVs and PEVs to the network, their nominal capacity and time of operation. Therefore, it is of high interest to investigate the voltage unbalance in these networks as the result of MGs, PVs and PEVs integration to low voltage networks. In addition, the network might experience non–standard voltage drop due to high penetration of PEVs, being charged at night periods, or non–standard voltage rise due to high penetration of PVs and PEVs generating electricity back into the grid in the network off–peak periods. In this thesis, a voltage unbalance sensitivity analysis and stochastic evaluation is carried out for PVs installed by the householders versus their installation point, their nominal capacity and penetration level as different uncertainties. A similar analysis is carried out for PEVs penetration in the network working in two different modes: Grid to vehicle and Vehicle to grid. Furthermore, the conventional methods are discussed for improving the voltage unbalance within these networks. This is later continued by proposing new and efficient improvement methods for voltage profile improvement at network peak and off–peak periods and voltage unbalance reduction. In addition, voltage unbalance reduction is investigated for MGs and new improvement methods are proposed and applied for the MG test bed, planned to be established at Queensland University of Technology (QUT). MATLAB and PSCAD/EMTDC simulation softwares are used for verification of the analyses and the proposals.

Unit commitment in power systems with plug-in hybrid electric vehicles

With the continued development of renewable energy generation technologies and increasing pressure to combat the global effects of greenhouse warming, plug-in hybrid electric vehicles (PHEVs) have received worldwide attention, finding applications in North America and Europe. When a large number of PHEVs are introduced into a power system, there will be extensive impacts on power system planning and operation, as well as on electricity market development. It is therefore necessary to properly control PHEV charging and discharging behaviors. Given this background, a new unit commitment model and its solution method that takes into account the optimal PHEV charging and discharging controls is presented in this paper. A 10-unit and 24-hour unit commitment (UC) problem is employed to demonstrate the feasibility and efficiency of the developed method, and the impacts of the wide applications of PHEVs on the operating costs and the emission of the power system are studied. Case studies are also carried out to investigate the impacts of different PHEV penetration levels and different PHEV charging modes on the results of the UC problem. A 100-unit system is employed for further analysis on the impacts of PHEVs on the UC problem in a larger system application. Simulation results demonstrate that the employment of optimized PHEV charging and discharging modes is very helpful for smoothing the load curve profile and enhancing the ability of the power system to accommodate more PHEVs. Furthermore, an optimal Vehicle to Grid (V2G) discharging control provides economic and efficient backups and spinning reserves for the secure and economic operation of the power system

Wind-energy based path planning for unmanned aerial vehicles using Markov decision processes

Exploiting wind-energy is one possible way to extend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

Design, simulation and analysis of a parallel hybrid electric propulsion system for unmanned aerial vehicles

Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This paper presents the development of a parallel Hybrid Electric Propulsion System (HEPS) on a small fixed-wing UAV incorporating an Ideal Operating Line (IOL) control strategy. A simulation model of an UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine were determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

A hierarchical decomposition approach for coordinated dispatch of plug-in electric vehicles

Plug-in electric vehicles (PEVs) are increasingly popular in the global trend of energy saving and environmental protection. However, the uncoordinated charging of numerous PEVs can produce significant negative impacts on the secure and economic operation of the power system concerned. In this context, a hierarchical decomposition approach is presented to coordinate the charging/discharging behaviors of PEVs. The major objective of the upper-level model is to minimize the total cost of system operation by jointly dispatching generators and electric vehicle aggregators (EVAs). On the other hand, the lower-level model aims at strictly following the dispatching instructions from the upper-level decision-maker by designing appropriate charging/discharging strategies for each individual PEV in a specified dispatching period. Two highly efficient commercial solvers, namely AMPL/IPOPT and AMPL/CPLEX, respectively, are used to solve the developed hierarchical decomposition model. Finally, a modified IEEE 118-bus testing system including 6 EVAs is employed to demonstrate the performance of the developed model and method.

On parallel hybrid-electric propulsion system for unmanned aerial vehicles

This paper presents a review of existing and current developments and the analysis of Hybrid-Electric Propulsion Systems (HEPS) for small fixed-wing Unmanned Aerial Vehicles (UAVs). Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. One technology with potential in this area is with the use of HEPS. In this paper, information on the state-of-art technology in this field of research is provided. A description and simulation of a parallel HEPS for a small fixed-wing UAV by incorporating an Ideal Operating Line (IOL) control strategy is described. Simulation models of the components in a HEPS were designed in the MATLAB Simulink environment. An IOL analysis of an UAV piston engine was used to determine the most efficient points of operation for this engine. The results show that an UAV equipped with this HEPS configuration is capable of achieving a fuel saving of 6.5%, compared to the engine-only configuration.

Energy-based motion control of marine vehicles using interconnection and damping assignment passivity-based control : a survey

This paper reviews some recent results in motion control of marine vehicles using a technique called Interconnection and Damping Assignment Passivity-based Control (IDA-PBC). This approach to motion control exploits the fact that vehicle dynamics can be described in terms of energy storage, distribution, and dissipation, and that the stable equilibrium points of mechanical systems are those at which the potential energy attains a minima. The control forces are used to transform the closed-loop dynamics into a port-controlled Hamiltonian system with dissipation. This is achieved by shaping the energy-storing characteristics of the system, modifying its interconnection structure (how the energy is distributed), and injecting damping. The end result is that the closed-loop system presents a stable equilibrium (hopefully global) at the desired operating point. By forcing the closed-loop dynamics into a Hamiltonian form, the resulting total energy function of the system serves as a Lyapunov function that can be used to demonstrate stability. We consider the tracking and regulation of fully actuated unmanned underwater vehicles, its extension to under-actuated slender vehicles, and also manifold regulation of under-actuated surface vessels. The paper is concluded with an outlook on future research.

Energy-based positioning control of underactuated vehicles using manifold regulation

In this paper, we consider the problem of position regulation of a class of underactuated rigid-body vehicles that operate within a gravitational field and have fully-actuated attitude. The control objective is to regulate the vehicle position to a manifold of dimension equal to the underactuation degree. We address the problem using Port-Hamiltonian theory, and reduce the associated matching PDEs to a set of algebraic equations using a kinematic identity. The resulting method for control design is constructive. The point within the manifold to which the position is regulated is determined by the action of the potential field and the geometry of the manifold. We illustrate the performance of the controller for an unmanned aerial vehicle with underactuation degree two-a quadrotor helicopter.

Energy and matter-efficient size-selective growth of thin quantum wires in a plasma

It is shown that plasmas can minimize the adverse Gibbs-Thompson effect in thin quantum wire growth. The model of Si nanowirenucleation includes the unprecedented combination of the plasma sheath, ion- and radical-induced species creation and heating effects on the surface and within an Au catalyst nanoparticle. Compared to neutral gas thermal processes, much thinner, size-selective wires can nucleate at the same temperature and pressure while much lower energy and matter budget is needed to grow same-size wires. This explains the experimental observations and may lead to energy- and matter-efficient synthesis of a broader range of one-dimensional quantum structures.

Contactless and replaceable modularized battery energy storage system for electric vehicles

A novel replaceable, modularized energy storage system with wireless interface is proposed for a battery operated electric vehicle (EV). The operation of the proposed system is explained and analyzed with an equivalent circuit and an averaged state-space model. A non-linear feedback linearization based controller is developed and implemented to regulate the DC link voltage by modulating the phase shift ratio. The working and control of the proposed system is verified through simulation and some preliminary results are presented.

Efficient Energy Management Policies for Networks with Energy Harvesting Sensor Nodes

We study sensor networks with energy harvesting nodes. The generated energy at a node can be stored in a buffer. A sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time at the node. For such networks we develop efficient energy management policies. First, for a single node, we obtain policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable suboptimal policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay. Next using the results for a single node, we develop efficient MAC policies.