组合白腐真菌预处理木质纤维素原料的研究

木质纤维素原料种类多、分布广、数量巨大，通过燃料乙醇生产技术、厌氧沼气发酵技术将其转化成乙醇、沼气等二次能源，一定程度上可以缓解化石能源的不断消耗所带来的能源危机，也解决了农林废弃物引起的环境污染问题。其中以木质纤维素原料生产燃料乙醇，还可以避免以淀粉类和糖类原料生产燃料乙醇时带来的“与人争粮”等一系列问题。因此具有重要的经济效益、环境效益和社会效益。 然而，木质纤维素原料结构致密，木质素包裹在纤维素、半纤维素外围，导致其很难被降解利用，必须进行适当的预处理，去除木质素，打破原有的致密结构，利于原料的后续利用。因此，预处理成为木质纤维素原料能源化利用的关键。而目前预处理环节的费用过于昂贵，于是寻找一种高效、低成本的预处理方法是当今研究的热点。 本论文采用组合白腐真菌对木质纤维素原料进行生物预处理研究，与其他物理化学法相比，该法有着专一性较强、反应温和、不造成环境污染、成本低等优势。白腐真菌主要通过分泌木质素降解酶对木质素进行降解，从而破坏原料的致密结构，提高后续利用效率。所以木质素降解酶酶活的高低是影响原料预处理效果的一个关键因素。于是本论文首先通过将白腐真菌进行组合的方式提高木质素降解酶（漆酶，Lac）酶活；接着对组合菌的菌株相互作用机理进行研究，阐明组合菌Lac 酶活提高的原因，为菌株组合提高Lac 酶活这种方法的应用提供理论依据，同时也为后续组合白腐真菌预处理木质纤维素原料提供指导；进一步采用固态发酵和木质素降解酶两种方式对木质纤维素原料进行预处理研究，最大化去除木质素成分，破坏原料的致密结构；最终对预处理后原料的酶解糖化进行初步研究，为原料后续的能源化应用奠定基础。具体研究结果如下： （1） 以实验室保存的三株主要分泌Lac 的白腐真菌为出发菌株，筛选得到一组Lac 酶活明显提高的组合菌55+m-6，其中菌株55 为Trametes trogii sp.，m-6 为Trametes versicolor sp.，组合后Lac 酶活较单菌株分别提高24.13倍和4.07 倍。组合菌的最适产酶条件为pH 6.5、C/N 16:1、Tween 80 添加量为0.01%，在该条件下组合菌的Lac 酶活峰值比未优化时提高4.11倍。 （2） 对组合菌55+m-6 菌株间相互作用机理进行研究，发现菌株之间不存在抑制作用；平板培养时，菌丝交界处Lac 酶活最高并分泌棕色色素；液体培养时，菌株m-6 对组合后Lac 酶活的提高起着更为重要的作用：菌株m-6的菌块、过滤灭菌胞外物以及高温灭菌胞外物均能明显刺激菌株55 的Lac产生；菌株55、m-6 进行组合后，同工酶种类未发生增减，但有三种Lac同工酶浓度有所提高；对菌株胞外物进行薄层层析和质谱分析，结果表明组合前后菌株胞外物中各物质在浓度上存在较大的变化。推测组合菌Lac酶活的明显提高，主要是由于菌株m-6 胞外物中的一些物质能刺激菌株55 分泌大量Lac 进行代谢，且这些刺激物质并非菌株m-6 特有，菌株55自身也可以代谢生成，但是适当的浓度才能刺激Lac 的大量分泌。 （3） 将组合菌55+m-6 用于固态发酵预处理木质纤维素原料，发现其对玉米秆的降解程度最大，在粉碎度40 目、含水率65%的最优处理条件下，处理至第15d，秸秆失重率为41.24%，其中木质素、纤维素、半纤维素均有降解，且Lac 和纤维素酶（CMC）酶活以及还原糖量均达到峰值。 （4） 对玉米秆进行木质素降解酶预处理，发现Lac/1-羟基苯并三唑（HBT）系统对玉米秆木质素的降解效果最好，在最优处理条件时，即HBT 用量0.2%、处理时间1d、Lac 用量50U/g，木质素降解率可达12.60%。预处理后玉米秆的致密结构被破坏，比表面积增大，利于后续酶与纤维素、半纤维素成分的结合。 （5） 对预处理后的玉米秆进行酶解糖化，其中组合菌固态发酵预处理后玉米秆的糖化率比对照高4.33 倍；Lac/HBT 系统预处理后玉米秆的糖化率比对照高2.99％，糖化液中主要含有木糖、葡萄糖两种单糖。 There are many kinds and large quantities of lignocellulosic biomass widely distributed on the earth. They can be converted into secondary energy such as fuel ethanol, biogas, et al., which can relieve the energy crisis caused by consumption of fossil energy resources and solve the problem of environmental pollution caused by agriculture and forestry waste. Meanwhile, the production of fuel ethanol from lignocellulosic biomass can ensure food supply to human kind instead of starch- and sugar-containing raw materials. So the energy conversion of lignocellulosic biomass contributes considerable economic, environment and social benefits. However, lignocellulosic biomass has the compact structure, in which lignin surrounds cellulose and hemicellulose, so it must be pretreated before energy usage and pretreatment is one of the most critical steps in the energy conversion of lignocellulosic biomass. At present, the cost of pretreatment is too expensive, so looking for an efficient and low-cost pre-treatment method is one of recent research hot spots. In this research, combined white rot fungi pretreatment method was used, which had some advantages in low cost, high specificity, mild reacting conditions and friendly environmental effects compared with the other physical and chemical methods. White rot fungi secrete lignin degrading enzymes to degrade the content of lignin and damage the contact structure of lignocellulosic biomass, so the activity of the lignin degrading enzymes is the key factor to the degradation effect of raw materials. Firstly, the combined fungi with high laccase activity were screened; secondly, the interaction mechanism between strains was studied, and the cause of higher laccase activity after strains combination was also preliminary clarified; under the guidance of the mechanism, lignocellulosic biomass was pretreated by the combined fungi; lastly, the enzymatic hydrolysis of pretreated lignocellulosic biomass was also preliminary studied; all of the researches could lay the foundation for the energy application of lignocellulosic biomass. The specific research results were as follows: (1) The combined fungi 55+m-6 with significant higher laccase activity were screened from the three white rot fungi stored in our lab which mainly secreted laccase. Strain 55 and strain m-6 were Trametes trogii sp. and Trametes versicolor sp., respectively. The laccase activity of combined fungi was 24.13 and 4.07-fold than strain 55 and strain m-6, respectively. The optimized condition for laccase production of the combined fungi in liquid medium was pH 6.5, C/N 16:1 and Tween 80 0.01%. In this optimized condition, the laccase activity of combined fungi was 4.11-fold higher comparing with which in non-optimized medium. (2) The interaction mechanism between strain 55 and strain m-6 was further studied, and no inhibition effect was observed. Brown pigment was secreted on the junction of the two strains on the plate, where the highest laccase activity was detected. Strain m-6 was much important to boost laccase activity of combined fungi in liquid medium, and strain 55 was stimulated by fungal plug, filter sterilized extracellular substances and high temperature sterilized extracellular substances of strain m-6 to produce laccase. The types of laccase isozymes did not change after combining strain 55 and strain m-6, but the concentrations of three types increased. Mass Spectrometry and TLC analysis of extracellular substances of each strain showed that concentration of some substances considerably changed after strains were combined. It was supposed that the cause of higher laccase activity of combined fungi was mainly due to some extracellular substances of strain m-6 with the appropriate concentration which stimulated laccase secretion of strain 55 and generated not only by strain m-6 but also by strain 55. (3) Combined fungi 55+m-6 were used to lignocellulosic biomass pretreatment with the type of solid-state fermentation. The highest degree of degradation of corn straw was obtained, including the rate of weight loss was 41.24% and the lignin, cellulose and hemicellulose were degraded partially under the optimized condition of 40 mesh, 65% water content on 15th day. Laccase, CMCase activities and content of reducing sugar reached the maximum value on that day. (4) Lignin degrading enzymes from combined fungi 55+m-6 were used for corn straw pretreatment. The most remarkable degradation of lignin in corn straw with Lac/1-hydroxybenzotriazole (HBT) system was observed, and the 12.60% lignin degradation was obtained under the optimized condition of 0.2% HBT, 50 U/g laccase for 1 d. After pretreated by Lac/HBT, the tight structure of corn straw was demolished and specific surface area increased, which had advantages for accessible of enzyme to cellulose and hemicellulose. (5) The corn straws pretreated by combined fungi 55+m-6 with the type of solid-state fermentation and Lac/HBT were used for enzymatic hydrolysis, and the saccharification rates of each pretreatment type were 4.33 times and 2.99% higher than CK, respectively. The enzymatic hydrolysis liquid of corn straw pretreated by Lac/HBT mainly contained xylose and glucose.

SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor networks

We study the impact of heterogeneity of nodes, in terms of their energy, in wireless sensor networks that are hierarchically clustered. In these networks some of the nodes become cluster heads, aggregate the data of their cluster members and transmit it to the sink. We assume that a percentage of the population of sensor nodes is equipped with additional energy resources-this is a source of heterogeneity which may result from the initial setting or as the operation of the network evolves. We also assume that the sensors are randomly (uniformly) distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. We show that the behavior of such sensor networks becomes very unstable once the first node dies, especially in the presence of node heterogeneity. Classical clustering protocols assume that all the nodes are equipped with the same amount of energy and as a result, they can not take full advantage of the presence of node heterogeneity. We propose SEP, a heterogeneous-aware protocol to prolong the time interval before the death of the first node (we refer to as stability period), which is crucial for many applications where the feedback from the sensor network must be reliable. SEP is based on weighted election probabilities of each node to become cluster head according to the remaining energy in each node. We show by simulation that SEP always prolongs the stability period compared to (and that the average throughput is greater than) the one obtained using current clustering protocols. We conclude by studying the sensitivity of our SEP protocol to heterogeneity parameters capturing energy imbalance in the network. We found that SEP yields longer stability region for higher values of extra energy brought by more powerful nodes.

Engineering of metal oxide interfaces for renewable energy applications

Diminishing non-renewable energy resources and planet-wide de-pollution on our planet are among the major problems which mankind faces into the future. To solve these problems, renewable energy sources such as readily available and inexhaustible sunlight will have to be used. There are however no readily available photocatalysts that are photocatalytically active under visible light; it is well established that the band gap of the prototypical photocatalyst, titanium dioxide, is the UV region with the consequence that only 4% of sun light is utilized. For this reason, this PhD project focused on developing new materials, based on titanium dioxide, which can be used in visible light activated photocatalytic hydrogen production and destruction of pollutant molecules. The main goal of this project is to use simulations based on first principles to engineer and understand rationally, materials based on modifying TiO2 that will have the following properties: (1) a suitable band gap in order to increase the efficiency of visible light absorption, with a gap around 2 – 2.5 eV considered optimum. (2). The second key aspect in the photocatalytic process is electron and hole separation after photoexcitation, which enable oxidation/reduction reactions necessary to i.e. decompose pollutants. (3) Enhanced activity over unmodified TiO2. In this thesis I present results on new materials based on modifying TiO2 with supported metal oxide nanoclusters, from two classes, namely: transition metal oxides (Ti, Ni, Cu) and p-block metal oxides (Sn, Pb, Bi). We find that the deposited metal oxide nanoclusters are stable at rutile and anatase TiO2 surfaces and present an analysis of changes to the band gap of TiO2, identifying those modifiers that can change the band gap to the desirable range and the origin of this. A successful collaboration with experimental researchers in Japan confirms many of the simulation results where the origin of improved visible light photocatalytic activity of oxide nanocluster-modified TiO2 is now well understood. The work presented in this thesis, creates a road map for the design of materials with desired photocatalytic properties and contributes to better understanding these properties which are of great application in renewable energy utilization.

Wind-Induced Vibration Energy Harvesting Using Piezoelectric Transducers Coupled with Dynamic Magnification

Flexible cylindrical structures subjected to wind loading experience vibrations from periodic shedding of vortices in their wake. Vibrations become excessive when the natural frequencies of the cylinder coincide with the vortex shedding frequency. In this study, cylinder vibrations are transmitted to a beam inside the structure via dynamic magnifier system. This system amplifies the strain experienced by piezoelectric patches bonded to the beam to maximize the conversion from vibrational energy into electrical energy. Realworld applicability is tested using a wind tunnel to create vortex shedding and comparing the results to finite element modeling that shows the structural vibrational modes. A crucial part of this study is conditioning and storing the harvested energy, focusing on theoretical modeling, design parameter optimization, and experimental validation. The developed system is helpful in designing wind-induced energy harvesters to meet the necessity for novel energy resources.

Different energy sources for three symbiont-dependent bivalve molluscs at the Lagatchve hydrothermal site (Mid Atlantic Ridge)

The vent mussel Bathymodiolus puteoserpentis, a large vesicomyid clam and a smaller thyasirid were collected from an area of sediment subject to diffuse hydrothermal flow. The mussels live on the surface, the vesicomyids are partly buried and the thyasirids burrow in the sediment. The fine structure of the gills differs in the three bivalves. Bathymodiolus puteoserpentis hosts two types of bacterial symbiont, one methanotrophic, and another probably thiotrophic. The other two bivalves have single types of symbiont of different shapes. Stable isotope ratios of carbon and nitrogen indicate thiotrophy in the vesicomyid and thyasirid, but a predominance of methanotrophy in the mussel. This is the first time that such an assemblage has been found at a hydrothermal site on the Mid-Atlantic Ridge (MAR), with the different faunistic elements exploiting different energy resources

Foraging success of biological Levy flights recorded in situ

It is an open question how animals find food in dynamic natural environments where they possess little or no knowledge of where resources are located. Foraging theory predicts that in environments with sparsely distributed target resources, where forager knowledge about resources’ locations is incomplete, Lévy flight movements optimize the success of random searches. However, the putative success of Lévy foraging has been demonstrated only in model simulations. Here, we use high-temporal-resolution Global Positioning System (GPS) tracking of wandering (Diomedea exulans) and black-browed albatrosses (Thalassarche melanophrys) with simultaneous recording of prey captures, to show that both species exhibit Lévy and Brownian movement patterns. We find that total prey masses captured by wandering albatrosses during Lévy movements exceed daily energy requirements by nearly fourfold, and approached yields by Brownian movements in other habitats. These results, together with our reanalysis of previously published albatross data, overturn the notion that albatrosses do not exhibit Lévy patterns during foraging, and demonstrate that Lévy flights of predators in dynamic natural environments present a beneficial alternative strategy to simple, spatially intensive behaviors. Our findings add support to the possibility that biological Lévy flight may have naturally evolved as a search strategy in response to sparse resources and scant information.

Levels of glucose and triglycerides in seminal plasma and spermatic motility in guinea pig fed with 10% more in digestible energy

The objective the study was to determine the levels of glucose and triglycerides in seminal plasma of 10 guinea pigs, which were fed for a period of 2 months with a diet containing 10% more ED. The level of glucose found in seminal plasma was 11.59 ± 0.5 mg/dL and triglyceride value was 55.95 ± 3.2 mg/dL, while the motility was 97% on average. We conclude that in guinea pigs the levels both glucose and triglycerides were increased by major level of ED in feed, but the spermatic motility was not.

Virtual power players demand response programs management based on locational marginal prices

Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

Energy efficiency analysis considering the use of an intelligent systems management in a smart home

In this abstract is presented an energy management system included in a SCADA system existent in a intelligent home. The system control the home energy resources according to the players definitions (electricity consumption and comfort levels), the electricity prices variation in real time mode and the DR events proposed by the aggregators.

Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

An optimal scheduling problem in distribution networks considering V2G

This paper addresses the problem of energy resource scheduling. An aggregator will manage all distributed resources connected to its distribution network, including distributed generation based on renewable energy resources, demand response, storage systems, and electrical gridable vehicles. The use of gridable vehicles will have a significant impact on power systems management, especially in distribution networks. Therefore, the inclusion of vehicles in the optimal scheduling problem will be very important in future network management. The proposed particle swarm optimization approach is compared with a reference methodology based on mixed integer non-linear programming, implemented in GAMS, to evaluate the effectiveness of the proposed methodology. The paper includes a case study that consider a 32 bus distribution network with 66 distributed generators, 32 loads and 50 electric vehicles.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

LMP triggered real time demand response events

Recent changes in power systems mainly due to the substantial increase of distributed generation and to the operation in competitive environments has created new challenges to operation and planning. In this context, Virtual Power Players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Demand response market implementation has been done in recent years. Several implementation models have been considered. An important characteristic of a demand response program is the trigger criterion. A program for which the event trigger depends on the Locational Marginal Price (LMP) used by the New England Independent System operator (ISO-NE) inspired the present paper. This paper proposes a methodology to support VPP demand response programs management. The proposed method has been computationally implemented and its application is illustrated using a 32 bus network with intensive use of distributed generation. Results concerning the evaluation of the impact of using demand response events are also presented.

Distribution network short term scheduling in Smart Grid context

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.