Stochastic Framework for Strategic Decision-making of Load-serving Entities for Day-ahead Market

The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

Short-term Load Forecasting Based on Load Profiling

Load forecasting has gradually becoming a major field of research in electricity industry. Therefore, Load forecasting is extremely important for the electric sector under deregulated environment as it provides a useful support to the power system management. Accurate power load forecasting models are required to the operation and planning of a utility company, and they have received increasing attention from researches of this field study. Many mathematical methods have been developed for load forecasting. This work aims to develop and implement a load forecasting method for short-term load forecasting (STLF), based on Holt-Winters exponential smoothing and an artificial neural network (ANN). One of the main contributions of this paper is the application of Holt-Winters exponential smoothing approach to the forecasting problem and, as an evaluation of the past forecasting work, data mining techniques are also applied to short-term Load forecasting. Both ANN and Holt-Winters exponential smoothing approaches are compared and evaluated.

Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players

The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.

Determining the Adjustment Baseline Parameters to Define an Accurate Customer Baseline Load

Demand response is an energy resource that has gained increasing importance in the context of competitive electricity markets and of smart grids. New business models and methods designed to integrate demand response in electricity markets and of smart grids have been published, reporting the need of additional work in this field. In order to adequately remunerate the participation of the consumers in demand response programs, improved consumers’ performance evaluation methods are needed. The methodology proposed in the present paper determines the characterization of the baseline approach that better fits the consumer historic consumption, in order to determine the expected consumption in absent of participation in a demand response event and then determine the actual consumption reduction. The defined baseline can then be used to better determine the remuneration of the consumer. The paper includes a case study with real data to illustrate the application of the proposed methodology.

An automatic tool to Extract, Transform and Load data from real electricity markets

The study of Electricity Markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring produced. Currently, lots of information concerning Electricity Markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge, to define realistic scenarios, essential for understanding and forecast Electricity Markets behaviour. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of Electricity Markets and the behaviour of the involved entities. In this paper we present an adaptable tool capable of downloading, parsing and storing data from market operators’ websites, assuring actualization and reliability of stored data.

Load Control Timescales Simulation in a Multi-Agent Smart Grid Platform

Environmental concerns and the shortage in the fossil fuel reserves have been potentiating the growth and globalization of distributed generation. Another resource that has been increasing its importance is the demand response, which is used to change consumers’ consumption profile, helping to reduce peak demand. Aiming to support small players’ participation in demand response events, the Curtailment Service Provider emerged. This player works as an aggregator for demand response events. The control of small and medium players which act in smart grid and micro grid environments is enhanced with a multi-agent system with artificial intelligence techniques – the MASGriP (Multi-Agent Smart Grid Platform). Using strategic behaviours in each player, this system simulates the profile of real players by using software agents. This paper shows the importance of modeling these behaviours for studying this type of scenarios. A case study with three examples shows the differences between each player and the best behaviour in order to achieve the higher profit in each situation.

Load Profiling Tool to Support Smart Grid Operation Scenarios

This paper presents the characterization of high voltage (HV) electric power consumers based on a data clustering approach. The typical load profiles (TLP) are obtained selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The choice of the best partition is supported using several cluster validity indices. The proposed data-mining (DM) based methodology, that includes all steps presented in the process of knowledge discovery in databases (KDD), presents an automatic data treatment application in order to preprocess the initial database in an automatic way, allowing time saving and better accuracy during this phase. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ consumption behavior. To validate our approach, a case study with a real database of 185 HV consumers was used.

HEMAGGLUTINATION TEST FOR THE DIAGNOSIS OF HUMAN NEUROCYSTICERCOSIS: DEVELOPMENT OF A STABLE REAGENT USING HOMOLOGOUS AND HETEROLOGOUS ANTIGENS

A hemagglutination (HA) test was standardized using formalin- and tannin-treated gander red blood cells sensitized with a total salt extract of C. cellulosae (HA-Cc) and an antigenic extract of Cysticercus longicollis (HA-Cl) vesicular fluid. A total of 61 cerebrospinal fluid (CSF) samples were assayed, 41 from patients with neurocysticercosis and 20 from a control group, which were, respectively, reactive and non-reactive to ELISA using C. cellulosae. The CSF samples from the control group did not react and 35 (85.4%) and 34 (82.9%) CSF samples from patients were reactive to the HA-Cc and HA-Cl tests, respectively. The reagents ready for use were stable up to 6 months when stored at 4°C in 50% glycerol. The present results confirm that the reagent using Cysticercus longicollis stabilized with glycerol can be used as an alternative in the immunological diagnosis of neurocysticercosis

Study of Load Curves Concerning the Influence of Socioeconomic and Cultural Issues

The increase of electricity demand in Brazil, the lack of the next major hydroelectric reservoirs implementation, and the growth of environmental concerns lead utilities to seek an improved system planning to meet these energy needs. The great diversity of economic, social, climatic, and cultural conditions in the country have been causing a more difficult planning of the power system. The work presented in this paper concerns the development of an algorithm that aims studying the influence of the issues mentioned in load curves. Focus is given to residential consumers. The consumption device with highest influence in the load curve is also identified. The methodology developed gains increasing importance in the system planning and operation, namely in the smart grids context.

Impact of Distributed Generation in the Transmission System Expansion Planning

In this work, the impact of distributed generation in the transmission expansion planning will be simulated through the performance of an optimization process for three different scenarios: the first without distributed generation, the second with distributed generation equivalent to 1% of the load, and the third with 5% of distributed generation. For modeling the expanding problem the load flow linearized method using genetic algorithms for optimization has been chosen. The test circuit used is a simplification of the south eastern Brazilian electricity system with 46 buses.

EPIDEMIOLOGICAL SURVEY ON CANINE POPULATION WITH THE USE OF IMMUNOLEISH SKIN TEST IN ENDEMIC AREAS OF HUMAN AMERICAN CUTANEOUS LEISHMANIASIS IN THE STATE OF RIO DE JANEIRO, BRAZIL

A survey for canine tegumentary leishmaniasis (CTL) has been carried out between 1986 and 1993 in seven endemic localities for American cutaneous leishmaniasis in the State of Rio de Janeiro. 270 dogs have been examined for their clinical aspects, the development of delayed hypersensitivity (DHS) with Immunoleish antigen and with immunofluorescent antibody research of IgG (IF). 28.2% of them had ulcer lesions and 3.3% had scars. The lesions consisted of single (39.5%) and mucocutaneous lesions (31.6%), multiple cutaneous (25.0%) and mucocutaneous lesions associated with cutaneous ulcers (4.0%). Twelve (15.8%) isolates from biopsies were analyzed by zimodeme and schizodeme and identified as L. (V.) braziliensis. The overall prevalence of canine infection that was evaluated with the skin test was of 40.5% and with IF it was of 25.5%. Both tests showed a high positive rate with relation to the animals with mucosal lesions, as in the case of human mucocutaneous leishmaniasis. The comparison of the two tests showed the skin test to have a better performance although there was no statistical difference (p>0.05) between them. The proportional sensitivity and specificity was of 84.0% and 74.0%, respectively. The Immunoleish skin test and IF are useful tools to be employed in CTL field epidemiological surveys.

THE PERSISTENCE OF LEPTOSPIRAL AGGLUTININS TITERS IN HUMAN SERA DIAGNOSED BY THE MICROSCOPIC AGGLUTINATION TEST

The persistence of agglutinins detected by MAT has created some problems to the interpretation of the results. The aim of this study was to examine the data of serology from 70 patients with serologically confirmed diagnosis of leptospirosis by during 3-13 months after being affected with leptospires in order to elucidate the interpretation of the persistence of agglutinins detected by MAT. Sixty-one patients sera (87.14%) had titers equal or greater than 800. Of these, two individuals maintained titers of 800 thirteen months after the onset. This study showed that only one sample of sera with high titers is not reliable to determine the time at which infection occurred.

VISCERAL LARVA MIGRANS AND TROPICAL PYOMYOSITIS: A CASE REPORT

We report a case of tropical pyomyositis in a boy who presented with a severe febrile illness associated with diffuse erythema, and swelling in many areas of the body which revealed on operation extensive necrotic areas of various muscles that required repeated débridement. The patient gave a history of contact with dogs, and an ELISA test for Toxocara canis was positive. He also presented eosinophilia and high serum IgE levels. Staphylococcus aureus was the sole bacteria isolated from the muscles affected. We suggest that tropical pyomyositis may be caused by the presence of migrating larvae of this or other parasites in the muscles. The immunologic and structural alterations caused by the larvae, in the presence of concomitant bacteremia, would favour seeding of the bacteria and the development of pyomyositis.

VALIDATION OF 14C-UREA BREATH TEST FOR DIAGNOSIS OF Helicobacter pylori

The aim of this study was to validate the 14C-urea breath test for use in diagnosis of Helicobacter pylori infection. Thirty H. pylori positive patients, based on histologic test and thirty H. pylori negative patients by histology and anti-H. pylori IgG entered the study. Fasting patients drank 5 uCi of 14C-urea in 20 ml of water. Breath samples were collected at 0, 5, 10, 15, 20 and 30 min. The difference of cpm values between the two groups was significant at all the time intervals, besides time 0 (p<0.0001). At 20 min, the test gave 100% sensitivity and specificity with a cut-off value of 562 cpm. Females were higher expirers than males (p=0.005). 14C-urea breath test is highly accurate for Helicobacter pylori diagnosis. It is fast, simple and should be the non-invasive test used after treating Helicobacter pylori infection.