Systolic random number generation for genetic algorithms

A parallel hardware random number generator for use with a VLSI genetic algorithm processing device is proposed. The design uses an systolic array of mixed congruential random number generators. The generators are constantly reseeded with the outputs of the proceeding generators to avoid significant biasing of the randomness of the array which would result in longer times for the algorithm to converge to a solution. 1 Introduction In recent years there has been a growing interest in developing hardware genetic algorithm devices [1, 2, 3]. A genetic algorithm (GA) is a stochastic search and optimization technique which attempts to capture the power of natural selection by evolving a population of candidate solutions by a process of selection and reproduction [4]. In keeping with the evolutionary analogy, the solutions are called chromosomes with each chromosome containing a number of genes. Chromosomes are commonly simple binary strings, the bits being the genes.

Wind generation's contribution to supporting peak electricity demand: meteorological insights

Wind generation’s contribution to meeting extreme peaks in electricity demand is a key concern for the integration of wind power. In Great Britain (GB), robustly assessing this contribution directly from power system data (i.e. metered wind-supply and electricity demand) is difficult as extreme peaks occur infrequently (by definition) and measurement records are both short and inhomogeneous. Atmospheric circulation-typing combined with meteorological reanalysis data is proposed as a means to address some of these difficulties, motivated by a case study of the extreme peak demand events in January 2010. A preliminary investigation of the physical and statistical properties of these circulation types suggests that they can be used to identify the conditions that are most likely to be associated with extreme peak demand events. Three broad cases are highlighted as requiring further investigation. The high-over-Britain anticyclone is found to be generally associated with very low winds but relatively moderate temperatures (and therefore moderate peak demands, somewhat in contrast to the classic low-wind cold snap that is sometimes apparent in the literature). In contrast, both longitudinally extended blocking over Scotland/Scandinavia and latitudinally extended troughs over western Europe appear to be more closely linked to the very cold GB temperatures (usually associated with extreme peak demands). In both of these latter situations, wind resource averaged across GB appears to be more moderate.

Using meteorological wind data to estimate turbine generation output: a sensitivity analysis

Various studies investigating the future impacts of integrating high levels of renewable energy make use of historical meteorological (met) station data to produce estimates of future generation. Hourly means of 10m horizontal wind are extrapolated to a standard turbine hub height using the wind profile power or log law and used to simulate the hypothetical power output of a turbine at that location; repeating this procedure using many viable locations can produce a picture of future electricity generation. However, the estimate of hub height wind speed is dependent on the choice of the wind shear exponent a or the roughness length z0, and requires a number of simplifying assumptions. This paper investigates the sensitivity of this estimation on generation output using a case study of a met station in West Freugh, Scotland. The results show that the choice of wind shear exponent is a particularly sensitive parameter which can lead to significant variation of estimated hub height wind speed and hence estimated future generation potential of a region.

Toward a new generation of world climate research and computing facilities

The impending threat of global climate change and its regional manifestations is among the most important and urgent problems facing humanity. Society needs accurate and reliable estimates of changes in the probability of regional weather variations to develop science-based adaptation and mitigation strategies. Recent advances in weather prediction and in our understanding and ability to model the climate system suggest that it is both necessary and possible to revolutionize climate prediction to meet these societal needs. However, the scientific workforce and the computational capability required to bring about such a revolution is not available in any single nation. Motivated by the success of internationally funded infrastructure in other areas of science, this paper argues that, because of the complexity of the climate system, and because the regional manifestations of climate change are mainly through changes in the statistics of regional weather variations, the scientific and computational requirements to predict its behavior reliably are so enormous that the nations of the world should create a small number of multinational high-performance computing facilities dedicated to the grand challenges of developing the capabilities to predict climate variability and change on both global and regional scales over the coming decades. Such facilities will play a key role in the development of next-generation climate models, build global capacity in climate research, nurture a highly trained workforce, and engage the global user community, policy-makers, and stakeholders. We recommend the creation of a small number of multinational facilities with computer capability at each facility of about 20 peta-flops in the near term, about 200 petaflops within five years, and 1 exaflop by the end of the next decade. Each facility should have sufficient scientific workforce to develop and maintain the software and data analysis infrastructure. Such facilities will enable questions of what resolution, both horizontal and vertical, in atmospheric and ocean models, is necessary for more confident predictions at the regional and local level. Current limitations in computing power have placed severe limitations on such an investigation, which is now badly needed. These facilities will also provide the world's scientists with the computational laboratories for fundamental research on weather–climate interactions using 1-km resolution models and on atmospheric, terrestrial, cryospheric, and oceanic processes at even finer scales. Each facility should have enabling infrastructure including hardware, software, and data analysis support, and scientific capacity to interact with the national centers and other visitors. This will accelerate our understanding of how the climate system works and how to model it. It will ultimately enable the climate community to provide society with climate predictions, which are based on our best knowledge of science and the most advanced technology.

The role of conventional generation in managing variability

As electricity systems incorporate increasing levels of variable renewable generation, conventional plant will be required to operate more flexibly, with potential impacts for economic viability and reliability. Northern Ireland is pursuing an ambitious target of 40% of electricity to be supplied from renewable sources by 2020. The dominant source of this energy is anticipated to come from inherently variable wind power, one of the most mature renewable technologies. Conventional thermal generators will have a significant role to play in maintaining security of supply. However, running conventional generation more flexibly in order to cater for a wind led regime can reduce its efficiency, as well as shortening its lifespan and increasing O&M costs. This paper examines the impacts of variable operation on existing fossil fuel based generators, with a particular focus on Northern Ireland. Access to plant operators and industry experts has provided insight not currently evident in the energy literature. Characteristics of plant operation and the market framework are identified that present significant challenges in moving to the proposed levels of wind penetration. Opportunities for increasing flexible operation are proposed and future research needs identified.

The kinetics of thermal generation of flavour

Control and optimization of flavor is the ultimate challenge for the food and flavor industry. The major route to flavor formation during thermal processing is the Maillard reaction, which is a complex cascade of interdependent reactions initiated by the reaction between a reducing sugar and an amino compd. The complexity of the reaction means that researchers turn to kinetic modeling in order to understand the control points of the reaction and to manipulate the flavor profile. Studies of the kinetics of flavor formation have developed over the past 30 years from single- response empirical models of binary aq. systems to sophisticated multi-response models in food matrixes, based on the underlying chem., with the power to predict the formation of some key aroma compds. This paper discusses in detail the development of kinetic models of thermal generation of flavor and looks at the challenges involved in predicting flavor.

Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

Challenges in quantifying wind generation's contribution to securing peak demand

Wind generation's contribution to supporting peak electricity demand is one of the key questions in wind integration studies. Differently from conventional units, the available outputs of different wind farms cannot be approximated as being statistically independent, and hence near-zero wind output is possible across an entire power system. This paper will review the risk model structures currently used to assess wind's capacity value, along with discussion of the resulting data requirements. A central theme is the benefits from performing statistical estimation of the joint distribution for demand and available wind capacity, focusing attention on uncertainties due to limited histories of wind and demand data; examination of Great Britain data from the last 25 years shows that the data requirements are greater than generally thought. A discussion is therefore presented into how analysis of the types of weather system which have historically driven extreme electricity demands can help to deliver robust insights into wind's contribution to supporting demand, even in the face of such data limitations. The role of the form of the probability distribution for available conventional capacity in driving wind capacity credit results is also discussed.

Increasing thermal plant flexibility in a high renewables power system

Thermal generation is a vital component of mature and reliable electricity markets. As the share of renewable electricity in such markets grows, so too do the challenges associated with its variability. Proposed solutions to these challenges typically focus on alternatives to primary generation, such as energy storage, demand side management, or increased interconnection. Less attention is given to the demands placed on conventional thermal generation or its potential for increased flexibility. However, for the foreseeable future, conventional plants will have to operate alongside new renewables and have an essential role in accommodating increasing supply-side variability. This paper explores the role that conventional generation has to play in managing variability through the sub-system case study of Northern Ireland, identifying the significance of specific plant characteristics for reliable system operation. Particular attention is given to the challenges of wind ramping and the need to avoid excessive wind curtailment. Potential for conflict is identified with the role for conventional plant in addressing these two challenges. Market specific strategies for using the existing fleet of generation to reduce the impact of renewable resource variability are proposed, and wider lessons from the approach taken are identified.

Effect of power densities and irradiation times on the degree of conversion and temperature increase of a microhybrid dental composite resin

The different parameters used for the photoactivation process provide changes in the degree of conversion (DC%) and temperature rise (TR) of the composite resins. Thus, the purpose of this study was to evaluate the DC (%) and TR of the microhybrid composite resin photoactivated by a new generation LED. For the KBr pellet technique, the composite resin was placed into a metallic mould (1-mm thickness and 4-mm diameter) and photoactivated as follows: continuous LED LCU with different power density values (50-1000 mW/cm(2)). The measurements for the DC (%) were made in a FTIR Spectrometer Bomen (model MB-102, Quebec-Canada). The spectroscopy (FTIR) spectra for both uncured and cured samples were analyzed using an accessory for the diffuse reflectance. The measurements were recorded in the absorbance operating under the following conditions: 32 scans, 4-cm(-1) resolution, and a 300 to 4000-cm(-1) wavelength. The percentage of unreacted carbon-carbon double bonds (% C=C) was determined from the ratio of the absorbance intensities of aliphatic C=C (peak at 1638 cm(-1)) against an internal standard before and after the curing of the specimen: aromatic C-C (peak at 1608 cm-1). For the TR, the samples were made in a metallic mould (2-mm thickness and 4-mm diameter) and photoactivated during 5, 10, and 20 s. The thermocouple was attached to the multimeter to allow the temperature readings. The DC (%) and TR were calculated by the standard technique and submitted to ANOVA and Tukey`s test (p < 0.05). The degree of conversion values varied from 35.0 (+/- 1.3) to 45.0 (+/- 2.4) for 5 s, 45.0 (+/- 1.3) to 55.0 (+/- 2.4) for 10 s, and 47.0 (+/- 1.3) to 52.0 (+/- 2.4) for 20 s. For the TR, the values ranged from 0.3 (+/- 0.01) to 5.4 (+/- 0.11)degrees C for 5 s, from 0.5 (+/- 0.02) to 9.3 (+/- 0.28)degrees C for 10 s, and from 1.0 (+/- 0.06) to 15.0 (+/- 0.95)degrees C for 20 s. The power densities and irradiation times showed a significant effect on the degree of conversion and temperature rise.

EDF and the Brazilian Power Sector

Electricité de France (EDF) is a leading player in the European energy market by being both the first electricity producer in Europe and the world’s leading nuclear plant operator. EDF is also the first electricity producer and supplier in France. However, Europe, EDF’s core market, is currently underperforming: the European sovereign debt crisis is lowering significantly the growth perspective of an energy market that has already reached its maturity. As a consequence, European energy companies are now looking at international markets and especially BRIC economies where economic growth potential remains high. Among them, Brazil is expected to keep its strong economic and electricity demand growth perspectives for the coming decades. Though Brazil has not been considered as a strategic priority for EDF after the Light reversal in 2006, the current economic situation has led the Group to reconsider its position toward the country. EDF’s current presence in Brazil is limited to its stake in UTE Norte Fluminense, a thermal plant, located in the state of Rio de Janeiro. This report investigates the possibility and the feasibility of EDF’s activities expansion in Brazil and what added value it could bring for the Brazilian power market. Considering that the status quo would not allow EDF to take full advantage of Brazil’s future growth, this work is identifying the various options that are currently opened to EDF: market exit, status quo, EDF alone, local partner. For that purpose, this study collects and analyses the latest energy market data as well as generation companies’ information which are necessary to give a relevant overview of the current brazilian power sector and to present EDF strategic options for the country.

Optimal reactive power flow via the modified barrier Lagrangian function approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Combined cycle versus one thousand diesel power plants: pollutant emissions, ecological efficiency and economic analysis

The increase in the use of natural gas in Brazil has stimulated public and private sectors to analyse the possibility of using combined cycle systems for generation of electrical energy. Gas turbine combined cycle power plants are becoming increasingly common due to their high efficiency, short lead times, and ability to meet environmental standards. Power is produced in a generator linked directly to the gas turbine. The gas turbine exhaust gases are sent to a heat recovery steam generator to produce superheated steam that can be used in a steam turbine to produce additional power. In this paper a comparative study between a 1000 MW combined cycle power plant and 1000 kW diesel power plant is presented. In first step, the energetic situation in Brazil, the needs of the electric sector modification and the needs of demand management and integrated means planning are clarified. In another step the characteristics of large and small thermoelectric power plants that use natural gas and diesel fuel, respectively, are presented. The ecological efficiency levels of each type of power plant is considered in the discussion, presenting the emissions of particulate material, sulphur dioxide (SO2), carbon dioxide (CO2) and nitrogen oxides (NOx). (c) 2006 Elsevier Ltd. All rights reserved.

Line-pack management for producing electric power on peak periods

The distribution of natural gas is carried out by means of long ducts and intermediate compression stations to compensate the pressure drops due to friction. The natural gas compressors are usually driven by an electric motor or a gas turbine system, offering possibilities for energy management, one of these consisting in generating energy for use in-plant or to commercialize as independent power producer. It can be done by matching the natural gas demand, at the minimum pressure allowed in the reception point, and the storage capacity of the feed duct with the maximum compressor capacity, for storing the natural gas at the maximum permitted pressure. This allows the gas turbine to drive an electric generator during the time in which the decreasing pressure in duct is above the minimum acceptable by the sink unit. In this paper, a line-pack management analysis is done for an existing compression station considering its actual demand curve for determining the economic feasibility of maintaining the gas turbine system driver generating electricity in a peak and off-peak tariff structure. The potential of cost reduction from the point of view of energy resources (natural gas and electric costs) is also analyzed. (C) 2010 Elsevier Ltd. All rights reserved.

A new method for real time computation of power quality indices based on instantaneous space phasors

One of the important issues about using renewable energy is the integration of dispersed generation in the distribution networks. Previous experience has shown that the integration of dispersed generation can improve voltage profile in the network, decrease loss, etc. but can create safety and technical problems as well. This work report the application of the instantaneous space phasors and the instantaneous complex power in observing performances of the distribution networks with dispersed generators in steady state. New IEEE apparent power definition, the so-called Buchholz-Goodhue effective apparent power, as well as new proposed power quality (oscillation) index in the three-phase distribution systems with unbalanced loads and dispersed generators, are applied. Results obtained from several case studies using IEEE 34 nodes test network are presented and discussed. (C) 2006 Elsevier B.V. All rights reserved.