Tastes and odours in potable water:perception versus reality

Tastes and odours are amongst the few water quality standards immediately apparent to a consumer and, as a result, account for most consumer complaints about water quality. Although taste and odour problems can arise from a great many sources, from an operational point of view they are either ”predictable” or ”unpredictable”. The former - which include problems related to actinomycete and algal growth - have a tendency to occur in certain types of water under certain combinations of conditions, whereas the latter - typically chemical spills - can occur anywhere. Long-term control is one option for predictable problems, although biomanipulation on a large scale has had utile success. Detection and avoidance is a more practicable option for both predictable and unpredictable problems, particularly if the distribution network can be serviced from other sources. Where these are not feasible, then water treatment, typically using activated carbon, is possible. In general there is a reasonable understanding of what compounds cause taste and odour problems, and how to treat these. An efficient taste and odour control programme therefore relies ultimately on good management of existing resources. However, a number of problems lie outside the remit of water supply companies and will require more fundamental regulation of activities in the catchment.

Modelagem Fuzzy para previsão de uma série temporal de energia elétrica.

Esta dissertação testa e compara dois tipos de modelagem para previsão de uma mesma série temporal. Foi observada uma série temporal de distribuição de energia elétrica e, como estudo de caso, optou-se pela região metropolitana do Estado da Bahia. Foram testadas as combinações de três variáveis exógenas em cada modelo: a quantidade de clientes ligados na rede de distribuição de energia elétrica, a temperatura ambiente e a precipitação de chuvas. O modelo linear de previsão de séries temporais utilizado foi um SARIMAX. A modelagem de inteligência computacional utilizada para a previsão da série temporal foi um sistema de Inferência Fuzzy. Na busca de um melhor desempenho, foram feitos testes de quais variáveis exógenas melhor influenciam no comportamento da energia distribuída em cada modelo. Segundo a avaliação dos testes, o sistema Fuzzy de previsão foi o que obteve o menor erro. Porém dentre os menores erros, os resultados dos testes também indicaram diferentes variáveis exógenas para cada modelo de previsão.

Tests for conceptual design of 6.6 kV class superconducting fault current limiter with YBCO thin film elements

A superconducting fault current limiter (SFCL) for 6.6 kV and 400 A installed in a cubicle for a distribution network substation was conceptually designed. The SFCL consists of parallel- and series-connected superconducting YBCO elements and a limiting resistor. Before designing the SFCL, some tests were carried out. The width and length of each element used in the tests are 30 mm and 210 mm, respectively. The element consists of YBCO thin film of about 200 nm in thickness on cerium dioxide (CeO2) as a cap-layer on a sapphire substrate by metal-organic deposition with a protective metal coat. In the tests, characteristics of each element, such as over-current, withstand-voltage, and so on, were obtained. From these characteristics, series and parallel connections of the elements, called units, were considered. The characteristics of the units were obtained by tests. From the test results, a single phase prototype SFCL was manufactured and tested. Thus, an SFCL rated at 6.6 kV and 400 A can be designed. © 2009 IEEE.

DNS-based Internet Client Clustering and Characterization

This paper proposes a novel protocol which uses the Internet Domain Name System (DNS) to partition Web clients into disjoint sets, each of which is associated with a single DNS server. We define an L-DNS cluster to be a grouping of Web Clients that use the same Local DNS server to resolve Internet host names. We identify such clusters in real-time using data obtained from a Web Server in conjunction with that server's Authoritative DNS―both instrumented with an implementation of our clustering algorithm. Using these clusters, we perform measurements from four distinct Internet locations. Our results show that L-DNS clustering enables a better estimation of proximity of a Web Client to a Web Server than previously proposed techniques. Thus, in a Content Distribution Network, a DNS-based scheme that redirects a request from a web client to one of many servers based on the client's name server coordinates (e.g., hops/latency/loss-rates between the client and servers) would perform better with our algorithm.

The Irish hospitals sweepstake in the United States of America, 1930-1939

The Irish hospitals sweepstake was established by statute in the Irish Free State in 1930 to fund the state’s hospital service. The vast majority of tickets were sold outside Ireland, particularly in countries where such gambling was illegal at the time. Initially the largest market was in the United Kingdom, but following the introduction of restrictive legislation there in 1934, the promoters of the sweepstake turned their attentions to North America and after 1936 the United States became the largest source of contributions to the Irish sweep. This article examines a number of factors concerning the relationship of the Irish sweep with the USA, including: an effort to estimate the amount of money contributed to the sweep by Americans; the role of the Irish diaspora and of prominent republicans, including Joseph McGarrity and Connie Neenan, in the illegal ticket distribution network; the efforts of American Federal agencies and government departments to disrupt the sweepstake organisation in America; how the sweep was used by those who sought to legalise gambling in the USA; the attitudes of both the Irish and American governments to the sweep’s activities in America; and how the legalisation of gambling in America brought about the demise of the Irish sweep.

Synchronous Islanded Operation of a Diesel Generator

The amount of distributed generation connected to the distribution network is increasing. To use this resource more effectively, splitting of the distribution network, or islanding the system, for prevention of power outages is being considered by some utilities. In this paper an islanding method that avoids out-ofsynchronism re-closure is proposed. The island is kept in synchronism with the rest of the utility while it is not electrically connected. This is referred to as synchronous islanded operation. A phase difference control algorithm, developed by the authors, was tested in a single set scenario on a 50-kVA diesel generator using two different governors. These are the “standard product” variable gain governor of the diesel generator and a governor developed by the authors, which utilizes supplementary inputs in addition to engine speed. The results show that phase difference can be controlled within acceptable limits, both in steady state and after load disturbances are applied. The advantages of employing supplementary governor inputs are fully evaluated.

Loss-of-Mains Protection System by Application of Phasor Measurement Unit Technology with Experimentally Assessed Threshold Settings

Loss-of-mains protection is an important component of the protection systems of embedded generation. The role of loss-of-mains is to disconnect the embedded generator from the utility grid in the event that connection to utility dispatched generation is lost. This is necessary for a number of reasons, including the safety of personnel during fault restoration and the protection of plant against out-of-synchronism reclosure to the mains supply. The incumbent methods of loss-of-mains protection were designed when the installed capacity of embedded generation was low, and known problems with nuisance tripping of the devices were considered acceptable because of the insignificant consequence to system operation. With the dramatic increase in the installed capacity of embedded generation over the last decade, the limitations of current islanding detection methods are no longer acceptable. This study describes a new method of loss-of-mains protection based on phasor measurement unit (PMU) technology, specifically using a low cost PMU device of the authors' design which has been developed for distribution network applications. The proposed method addresses the limitations of the incumbent methods, providing a solution that is free of nuisance tripping and has a zero non-detection zone. This system has been tested experimentally and is shown to be practical, feasible and effective. Threshold settings for the new method are recommended based on data acquired from both the Great Britain and Ireland power systems.

New multi-stage DC-DC converters for grid-connected photovoltaic systems

Renewable energy is high on international and national agendas. Currently, grid-connected photovoltaic (PV) systems are a popular technology to convert solar energy into electricity. Existing PV panels have a relatively low and varying output voltage so that the converter installed between the PVs and the grid should be equipped with high step-up and versatile control capabilities. In addition, the output current of PV systems is rich in harmonics which affect the power quality of the grid. In this paper, a new multi-stage hysteresis control of a step-up DC-DC converter is proposed for integrating PVs into a single-phase power grid. The proposed circuitry and control method is experimentally validated by testing on a 600W prototype converter. The developed technology has significant economic implications and could be applied to many distributed generation (DG) systems, especially for the developing countries which have a large number of small PVs connected to their single-phase distribution network. 

Residential electrical vehicle charging strategies: the good, the bad and the ugly

In recent years, a wide variety of centralised and decentralised algorithms have been proposed for residential charging of electric vehicles (EVs). In this paper, we present a mathematical framework which casts the EV charging scenarios addressed by these algorithms as optimisation problems having either temporal or instantaneous optimisation objectives with respect to the different actors in the power system. Using this framework and a realistic distribution network simulation testbed, we provide a comparative evaluation of a range of different residential EV charging strategies, highlighting in each case positive and negative characteristics.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

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 and reserve provision dispatch considering distributed generation and demand response

In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

Increase of the delivered energy probability in DES using a fuzzy probabilistic modeling

The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.