Dispatch of distributed Energy Resources to Provide Energy and Reserve in Smart Grids using a Particle Swarm Optimization Approach

The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. 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 optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.

Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

This paper presents a decision support tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy resource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.

Application-Specific Modified Particle Swarm Optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Electricity Markets Portfolio Optimization using a Particle Swarm Approach

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.

GB virus C/Hepatitis G virus and other putative hepatitis non A-E viruses

The identification of the major agents causing human hepatitis (Hepatitis A, B, C, D and E Viruses) was achieved during the last 30 years. These viruses are responsible for the vast majority of human viral hepatitis cases, but there are still some cases epidemiologically related to infectious agents without any evidence of infection with known virus, designated as hepatitis non A - E. Those cases are considered to be associated with at least three different viruses: 1 - Hepatitis B Virus mutants expressing its surface antigen (HBsAg) with altered epitopes or in low quantities; 2 - Another virus probably associated with enteral transmitted non A-E hepatitis, called Hepatitis F Virus. Still more studies are necessary to better characterize this agent; 3 - Hepatitis G Virus or GB virus C, recently identified throughout the world (including Brazil) as a Flavivirus responsible for about 10% of parenteral transmitted hepatitis non A-E. Probably still other unknown viruses are responsible for human hepatitis cases without evidence of infection by any of these viruses, that could be called as non A-G hepatitis.

Detection and identification of dengue virus isolates from Brazil by a simplified reverse transcription - polymerase chain reaction (RT-PCR) method

We show here a simplified RT-PCR for identification of dengue virus types 1 and 2. Five dengue virus strains, isolated from Brazilian patients, and yellow fever vaccine 17DD as a negative control, were used in this study. C6/36 cells were infected and supernatants were collected after 7 days. The RT-PCR, done in a single reaction vessel, was carried out following a 1/10 dilution of virus in distilled water or in a detergent mixture containing Nonidet P40. The 50 µl assay reaction mixture included 50 pmol of specific primers amplifying a 482 base pair sequence for dengue type 1 and 210 base pair sequence for dengue type 2. In other assays, we used dengue virus consensus primers having maximum sequence similarity to the four serotypes, amplifying a 511 base pair sequence. The reaction mixture also contained 0.1 mM of the four deoxynucleoside triphosphates, 7.5 U of reverse transcriptase, 1U of thermostable Taq DNA polymerase. The mixture was incubated for 5 minutes at 37ºC for reverse transcription followed by 30 cycles of two-step PCR amplification (92ºC for 60 seconds, 53ºC for 60 seconds) with slow temperature increment. The PCR products were subjected to 1.7% agarose gel electrophoresis and visualized by UV light after staining with ethidium bromide solution. Low virus titer around 10 3, 6 TCID50/ml was detected by RT-PCR for dengue type 1. Specific DNA amplification was observed with all the Brazilian dengue strains by using dengue virus consensus primers. As compared to other RT-PCRs, this assay is less laborious, done in a shorter time, and has reduced risk of contamination

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

Neutralizing antibodies in Brazilian sera against three strains of human immunodeficiency virus type 1 (HIV-1)

The MN strain of HIV-1 is known to be more prevalent in Brazil, the BRU strain is more prevalent in Europe, and the NDK strain in Africa. It has been suggested in the literature to include different strains in the same vaccine against HIV-1. To contribute to the studies for the development of a universal vaccine, the occurrence of antibodies (Ab) against three HIV-1 strains (MN, BRU and NDK) was determined in serum samples from 85 HIV-1-positive patients, adult volunteers seen at the University Hospital of the Faculty of Medicine of Ribeirão Preto-USP. One-hundred tissue culture infective unit (TCIU) of the viruses reacted with serial dilutions of the sera (2x) and with MT4 cells added at a final concentration of 0.3 × 106 cells/ml, and a cytopathic effect was observed on the 7th and 11th days of incubation. Titres of less than 1/50 were considered to be negative. In 129 tests, the sera were negative for one of the three strains: 40 for MN, 29 for BRU and 60 for NDK. There was a predominance of strains MN and BRU, most of them presenting titres from 1/50 to 1/200. Titres for NDK were detected in 25 sera. We conclude that there seems to be a predominance of strains MN and BRU among the individuals from the region tested; however, the detection of sera with positive NKD titres indicates the need for further studies of this strain in other populations and regions of Brazil

Cytotoxicity in L929 fibroblasts and inhibition of herpes simplex virus type 1 Kupka by estuarine cyanobacteria extracts

The cyanobacteria are known to be a rich source of metabolites with a variety of biological activities in different biological systems. In the present work, the bioactivity of aqueous and organic (methanolic and hexane) crude extracts of cyanobacteria isolated from estuarine ecosystems was studied using different bioassays. The assessment of DNA damage on the SOS gene repair region of mutant PQ37 strain of Escherichia coli was performed. Antiviral activity was evaluated against influenza virus, HRV-2, CVB3 and HSV-1 viruses using crystal violet dye uptake on HeLa, MDCK and GMK cell lines. Cytotoxicity evaluation was performed with L929 fibroblasts by MTT assay. Of a total of 18 cyanobacterial isolates studied, only the crude methanolic extract of LEGE 06078 proved to be genotoxic (IF > 1.5) in a dose-dependent manner and other four were putative candidates to induce DNA damage. Furthermore, the crude aqueous extract of LEGE 07085 showed anti- herpes type 1 activity (IC50 = 174.10 μg dry extract mL−1) while not presenting any cytotoxic activity against GMK cell lines. Of the 54 cyanobacterial extracts tested, only the crude methanolic and hexane ones showed impair on metabolic activity of L929 fibroblasts after long exposure (48–72 h). The inhibition of HSV-1 and the strong cytotoxicity against L929 cells observed emphasizes the importance of evaluating the impact of those estuarine cyanobacteria on aquatic ecosystem and on human health. The data also point out their potential application in HSV-1 treatment and pharmacological interest.

HEPATITIS B VIRUS INFECTION PROFILE IN CENTRAL BRAZILIAN HEMODIALYSIS POPULATION

Hepatitis B has proved to be a major health hazard in hemodialysis patients. In order to investigate the hepatitis B virus (HBV) infection profile in the hemodialysis population of Goiânia city - Central Brazil, all dialysis patients (N=282) were studied. The prevalence of any HBV marker (HBsAg, anti-HBs, and anti-HBc) was 56.7% (95% CI: 51.1-62.7), ranging from 33.3% to 77.7% depending on dialysis unit. HBV-DNA was detected in 67.6% and 88.2% of the HBsAg-positive serum samples, in 91.3% and 100% of the HBsAg/HBeAg-positive samples, and in 18.2% and 63.6% of the HBsAg/anti-HBe-reactive sera by hybridization and PCR, respectively. The length of time on hemodialysis was significantly associated with HBV seropositivity. Only 10% of the patients reported received hepatitis B vaccination. The findings of a high HBV infection prevalence in this population and the increased risk for HBV infection on long-term hemodialysis suggest the environmental transmission, emphasizing the urgent need to evaluate strategies of control and prevention followed in these units.

TRANFUSION-TRANSMITED VIRUS (TTV) IN BRAZIL. PRELIMINARY REPORT

TTV is a recently discovered DNA virus, isolated from a patient with post-transfusion hepatitis of unknown etiology by Japanese researchers. In the present study, we evaluated the presence of TTV among chronic liver diseases patients in São Paulo and Pará states, representing two geographically distinct Brazilian regions. TTV DNA was found in 21/105 (20%) and 9/20 (45%) cases from São Paulo and Pará States, respectively. DNA sequence data confirmed the presence of TTV genotypes 1a and 2a, as well as other genotypes not yet described. In conclusion, TTV is present in chronic liver diseases cases from Southeast and North Brazil. However, further studies involving healthy populations are necessary before establishing any causal relationship among TTV and human hepatitis.

AN ELISA SUITABLE FOR THE DETECTION OF RABIES VIRUS ANTIBODIES IN SERUM SAMPLES FROM HUMAN VACCINATED WITH EITHER CELL-CULTURE VACCINE OR SUCKLING-MOUSE-BRAIN VACCINE

An indirect ELISA for determination of post-vaccination rabies antibody was applied. Purified rabies virus was used as antigen to coat plates, and staphylococcal protein A linked with horseradish peroxidase was used for detecting IgG antibody in human sera. Sera from humans, vaccinated with cell-culture vaccine or suckling-mouse-brain vaccine, were examined. ELISA results were compared to those obtained from the virus neutralization test. The mean and standard deviation of OD were determined for 126 negative sera (pre-vaccination) and for 73 sera from vaccinated persons showing antibody titers lower than 0.5 IU/ml. Results were defined as ELISA -positive, -negative or -doubtful. Establishment of a doubtful region reduced the number of sera otherwise classified as positive (false-positive sera). In this way, the sensitivity, specificity and agreement values were respectively 87.5%, 92.4% and 88.5%. No significant differences were observed in these values when the group vaccinated with cell-culture vaccine and the group vaccinated with suckling-mouse-brain vaccine were compared. It was shown that much of the disagreement between the values obtained by neutralization test and ELISA occurred in sera obtained at the beginning of the immunization process, and was probably due to the presence of IgM in the serum samples, detected only by the former test. This ELISA method can be used as a screening test in rabies laboratories regardless of the kind of vaccine used for immunization.

Chronic hepatitis C virus infections in Brazilian patients: association with genotypes, clinical parameters and response to long term alpha interferon therapy

The present study assessed the clinical significance of hepatitis C virus (HCV) genotypes and their influence on response to long term recombinant-interferon-alpha (r-IFN-a) therapy in Brazilian patients. One hundred and thirty samples from patients previously genotyped for the HCV and with histologically confirmed chronic hepatitis C (CH-C) were evaluated for clinical and epidemiological parameters (sex, age, time of HCV infection and transmission routes). No difference in disease activity, sex, age or mode and time of transmission were seen among patients infected with HCV types 1, 2 or 3. One hundred and thirteen of them were treated with 3 million units of r-IFN-a, 3 times a week for 12 months. Initial response (IR) was significantly better in patients with genotype 2 (100%) and 3 (46%) infections than in patients with genotype 1 (29%) (p < 0.005). Among subtypes, difference in IR was observed between 1b and 2 (p < 0.005), and between 1b and 3a (p < 0.05). Sustained response (SR) was observed in 12% for (sub)type 1a, 13% for 1b, 19% for 3a, and 40% for type 2; significant differences were found between 1b and 2 (p < 0.001), and between 1b and 3a (p < 0.05). Moreover, presence of cirrhosis was significantly associated with non response and response with relapse (p < 0.05). In conclusion, non-1 HCV genotype and lack of histological diagnosis of cirrhosis were the only baseline features associated with sustained response to treatment. These data indicate that HCV genotyping may have prognostic relevance in the responsiveness to r-IFN-a therapy in Brazilian patients with chronic HCV infection, as seen in other reports worldwide.