MASCEM: electricity markets simulation with strategic agents

Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints.1 The restructuring and consequent deregulation of electricity markets introduced a new economic dimension to the power industry. Some observers have criticized the restructuring process, however, because it has failed to improve market efficiency and has complicated the assurance of reliability and fairness of operations. To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short- and mediumterm simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

FASL polymorphism is associated with response to bacillus Calmette-Guérin immunotherapy in bladder cancer

Objective Deregulation of FAS/FASL system may lead to immune escape and influence bacillus Calmette-Guérin (BCG) immunotherapy outcome, which is currently the gold standard adjuvant treatment for high-risk non–muscle invasive bladder tumors. Among other events, functional promoter polymorphisms of FAS and FASL genes may alter their transcriptional activity. Therefore, we aim to evaluate the role of FAS and FASL polymorphisms in the context of BCG therapy, envisaging the validation of these biomarkers to predict response. Patients and methods DNA extracted from peripheral blood from 125 patients with bladder cancer treated with BCG therapy was analyzed by Polymerase Chain Reaction—Restriction Fragment Length Polymorphism for FAS-670 A/G and FASL-844 T/C polymorphisms. FASL mRNA expression was analyzed by real-time Polymerase Chain Reaction. Results Carriers of FASL-844 CC genotype present a decreased recurrence-free survival after BCG treatment when compared with FASL-844 T allele carriers (mean 71.5 vs. 97.8 months, P = 0.030) and have an increased risk of BCG treatment failure (Hazard Ratio = 1.922; 95% Confidence Interval: [1.064–3.471]; P = 0.030). Multivariate analysis shows that FASL-844 T/C and therapeutics scheme are independent predictive markers of recurrence after treatment. The evaluation of FASL gene mRNA levels demonstrated that patients carrying FASL-844 CC genotype had higher FASL expression in bladder tumors (P = 0.0027). Higher FASL levels were also associated with an increased risk of recurrence after BCG treatment (Hazard Ratio = 2.833; 95% Confidence Interval: [1.012–7.929]; P = 0.047). FAS-670 A/G polymorphism analysis did not reveal any association with BCG therapy outcome. Conclusions Our results suggest that analysis of FASL-844 T/C, but not FAS-670 A/G polymorphisms, may be used as a predictive marker of response to BCG immunotherapy.

Identification of neuronal alterations induced by Shank3 mutations using iPS cells from Phelan-McDermid Patients' Fibroblasts

A família de proteínas Shank é o principal conjunto de proteinas de suporte e está localizada na densidade pós-sináptica das sinapses excitatórias. Existem 3 genes na família Shank, Shank1, Shank2 e Shank3 e são caracterizados por múltiplos domínios repetidos de anquirina próximo ao N-terminal seguido pelos domínios Src homologo 3 e PDZ, uma região longa rica em prolina e um domínio de motivo α estéril próximo ao C-terminal. Shank proteínas conectam duas subunidades de receptors glutamatérgicos, recetores NMDA e recetores metabotrópicos de glutamato do tipo-I (mGluRs). O domínio PDZ da Shank conecta-se ao C-terminal do GKAP e este, liga-se, ao complexo recetor PSD-95-NMDA. Por outro lado, a proteína Homer interage com o domínio rico em prolina para confirmar a associação entre a proteína Shank com o mGluR tipo-I. A proteína específica em estudo, Shank3, é haploinsuficiente em pacientes com sindrome Phelan-McDermid devido à deleções no braço comprido do cromossoma 22 levando à danos intelectuais, ausência ou atraso no discurso, comportamentos semelhantes ao autismo, hipotonia e características dismórficas. Neste trabalho, investigamos o papel da Shank3 na função sináptica para compreender a relação entre alterações nesta proteína e as características neurológicas presente em Pacientes com síndrome Phelan-McDermid. Foram utilizados dois modelos diferentes, ratinhos knockout Shank3 e hiPSC de pacientes com PMS. Ratinhos geneticamente modificados são ferramentas uteis no estudo de genes e na compreensão dos mecanismos que experiências in vitro não são capazes de reproduzir, mas de maneira a compreender melhor as patologias humanas, decidimos trabalhar também com células humanas. Os fibroblastos dos pacientes com síndrome Phelan-McDermid fora reprogramados em hiPS cells, diferenciados em neurónios e comparados com os neurónios obtidos a partir de doadores saudavéis e da mesma idade. A reprogramação em iPSC foi realizada por infecção de lentivirus com quatro genes de reprogramação OCT4, c-MYC, SOX2 e KFL4 para posteriormente serem diferenciados em neurónios, com cada passo sendo positivamente confirmado através de marcadores neuronais. Através dos neurónios diferenciados, analisamos a expressão de proteínas sinápticas. Pacientes com haploinsuficiencia na proteína Shank3 apresentam níveis elevados de proteína mGluR5 e decrescidos de proteína Homer sugerindo que a haploinsuficiencia leva a desregulação do complexo mGluR5-Homer-Shank3 conduzindo também, a defeitos na maturação sináptica. Assim, a expressão da proteína mGluR5 está alterada nos pacientes com PMS podendo estar relacionada com defeitos encontrados na diferenciação neuronal e maturação sináptica observados nos neurónios de pacientes. Conclusivamente, iPS cells representam um modelo fundamental no estudo da proteína Shank3 e a sua influência no sindrome de Phelan-McDermid.

Levantamento, reparação e beneficiação do simulador TERCO PST 2200 do Laboratório de Sistemas de Energia do ISEP

Este trabalho é baseado no simulador de redes PST2200 do Laboratório de Sistemas de Energia (LSE) pois está avariado com vários problemas conhecidos, designadamente: - Defeito de isolamento (disparo de diferencial), - Desregulação da velocidade da máquina primária (motor DC), - Circuito de excitação da máquina síncrona inoperacional, - Inexistência de esquemas elétricos dos circuitos do simulador, - Medidas desreguladas e com canais de medida com circuito impresso queimado. O trabalho executado foi: - O levantamento e desenho de raiz (não existe qualquer manual) dos esquemas dos 10 módulos do simulador, designadamente naqueles com avaria ou com desempenho problemático a fim de que se possa ter uma visão mais pormenorizada dos circuitos e seus problemas, por forma a intervir para os minimizar e resolver, - Foi realizado o diagnóstico de avaria do simulador e foram propostas soluções para os mesmos, - Realizaram-se as intervenções propostas e aprovadas. Nas intervenções realizadas, os princípios orientadores foram: - Aumentar a robustez do equipamento por forma a garantir a sua integridade a utilizações menos apropriados e manobras 'exóticas' próprias de alunos, que pela sua condição, estão em fase de aprendizagem, - Atualizar o equipamento, colocando-o em sintonia com o 'estado da arte', - Como fator de valorização suplementar, foi concebida e aplicada a supervisão remota do funcionamento do simulador através da rede informática. Foram detetados inúmeros erros: - Má ligação do motor de corrente continua ao variador, resultando a falta de controlo da frequência da rede do sistema, - Ligações entre painéis trocadas resultando em avarias diversas das fontes de alimentação, - Cartas eletrónicas de medidas avariadas e que além de se reparar, foram também calibradas. Devido ao mecenato da empresa Schnitt + Sohn participando monetariamente, fez-se o projeto de alteração e respetiva execução de grande parte do simulador aumentando a fiabilidade do mesmo, diminuindo assim a frequência das avarias naturais mais as que acontecem involuntariamente devido a este ser um instrumento didático. Além do trabalho elétrico, foi feito muito trabalho de chaparia para alteração de estrutura e suporte do material com diferenças de posicionamento. Neste trabalho dá-se também alguns exemplos de cálculo e simulação das redes de transporte que se pode efetuar no simulador como estudo e simulação de avarias num sistema produtivo real. Realizou-se a monitorização de dois aparelhos indicadores de parâmetros de energia (Janitza UMG96S) através duma rede com dois protocolos ethernet e profibus utilizando o plc (Omron CJ2M) como valorização do trabalho.

Demand response management in power systems using a particle swarm optimization approach

Competitive electricity markets have arisen as a result of power-sector restructuration and power-system deregulation. The players participating in competitive electricity markets must define strategies and make decisions using all the available information and business opportunities.

Deregulated expression of selected histone methylases and demethylases in prostate carcinoma

Prostate cancer (PCa), a leading cause of cancer-related morbidity and mortality, arises through the acquisition of genetic and epigenetic alterations. Deregulation of histone methyltransferases (HMTs) or demethylases (HDMs) has been associated with PCa development and progression. However, the precise influence of altered HMTs or HDMs expression and respective histone marks in PCa onset and progression remains largely unknown. To clarify the role of HMTs and HDMs in prostate carcinogenesis, expression levels of 37 HMTs and 20 HDMs were assessed in normal prostate and PCa tissue samples by RT-qPCR. SMYD3, SUV39H2, PRMT6, KDM5A, and KDM6A were upregulated, whereas KMT2A-E (MLL1-5) and KDM4B were downregulated in PCa, compared with normal prostate tissues. Remarkably, PRMT6 was the histone modifier that best discriminated normal from tumorous tissue samples. Interestingly, EZH2 and SMYD3 expression levels significantly correlated with less differentiated and more aggressive tumors. Remarkably, SMYD3 expression levels were of independent prognostic value for the prediction of disease-specific survival of PCa patients with clinically localized disease submitted to radical prostatectomy. We concluded that expression profiling of HMTs and HDMs, especially SMYD3, might be of clinical usefulness for the assessment of PCa patients and assist in pre-therapeutic decision-making.

Regulation of histone H2A.Z expression is mediated by sirtuin 1 in prostate cancer

Histone variants seem to play a major role in gene expression regulation. In prostate cancer, H2A.Z and its acetylated form are implicated in oncogenes’ upregulation. SIRT1, which may act either as tumor suppressor or oncogene, reduces H2A.Z levels in cardiomyocytes, via proteasome-mediated degradation, and this mechanism might be impaired in prostate cancer cells due to sirtuin 1 downregulation. Thus, we aimed to characterize the mechanisms underlying H2A.Z and SIRT1 deregulation in prostate carcinogenesis and how they interact. We found that H2AFZ and SIRT1 were up- and downregulated, respectively, at transcript level in primary prostate cancer and high-grade prostatic intraepithelial neoplasia compared to normal prostatic tissues. Induced SIRT1 overexpression in prostate cancer cell lines resulted in almost complete absence of H2A.Z. Inhibition of mTOR had a modest effect on H2A.Z levels, but proteasome inhibition prevented the marked reduction of H2A.Z due to sirtuin 1 overexpression. Prostate cancer cells exposed to epigenetic modifying drugs trichostatin A, alone or combined with 5-aza-2’-deoxycytidine, increased H2AFZ transcript, although with a concomitant decrease in protein levels. Conversely, SIRT1 transcript and protein levels increased after exposure. ChIP revealed an increase of activation marks within the TSS region for both genes. Remarkably, inhibition of sirtuin 1 with nicotinamide, increased H2A.Z levels, whereas activation of sirtuin 1 by resveratrol led to an abrupt decrease in H2A.Z. Finally, protein-ligation assay showed that exposure to epigenetic modifying drugs fostered the interaction between sirtuin 1 and H2A.Z. We concluded that sirtuin 1 and H2A.Z deregulation in prostate cancer are reciprocally related. Epigenetic mechanisms, mostly histone post-translational modifications, are likely involved and impair sirtuin 1-mediated downregulation of H2A.Z via proteasome-mediated degradation. Epigenetic modifying drugs in conjunction with enzymatic modulators are able to restore the normal functions of sirtuin 1 and might constitute relevant tools for targeted therapy of prostate cancer patients

Phenotypic impact of deregulated expression of class I histone deacetylases in urothelial cell carcinoma of the bladder

Deregulated expression of histone deacetylases (HDACs) has been implicated in tumorigenesis. Herein, we investigated class I HDACs expression in bladder urothelial cell carcinoma (BUCC), its prognostic value and biological significance. Significantly increased transcript levels of all HDACs were found in BUCC compared to 20 normal mucosas, and these were higher in lower grade and stage tumors. Increased HDAC3 levels were associated with improved patient survival. SiRNA experiments showed decrease cell viability and motility, and increased apoptosis. We concluded that class I HDACs play an important role in bladder carcinogenesis through deregulation of proliferation, migration and apoptosis, constituting putative therapeutic targets

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.

Automatic Electricity Markets Data Extraction for Realistic Multi-agent Simulations

Electricity markets worldwide suffered profound transformations. The privatization of previously nationally owned systems; the deregulation of privately owned systems that were regulated; and the strong interconnection of national systems, are some examples of such transformations [1, 2]. In general, competitive environments, as is the case of electricity markets, require good decision-support tools to assist players in their decisions. Relevant research is being undertaken in this field, namely concerning player modeling and simulation, strategic bidding and decision-support.

Incentive-based demand response programs designed by asset-light retailers for day-ahead market

Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand.

Gestão de Recursos Energéticos nas SmartGrids

A sustentabilidade do sistema energético é crucial para o desenvolvimento económico e social das sociedades presentes e futuras. Para garantir o bom funcionamento dos sistemas de energia actua-se, tipicamente, sobre a produção e sobre as redes de transporte e de distribuição. No entanto, a integração crescente de produção distribuída, principalmente nas redes de distribuição de média e de baixa tensão, a liberalização dos mercados energéticos, o desenvolvimento de mecanismos de armazenamento de energia, o desenvolvimento de sistemas automatizados de controlo de cargas e os avanços tecnológicos das infra-estruturas de comunicação impõem o desenvolvimento de novos métodos de gestão e controlo dos sistemas de energia. O contributo deste trabalho é o desenvolvimento de uma metodologia de gestão de recursos energéticos num contexto de SmartGrids, considerando uma entidade designada por VPP que gere um conjunto de instalações (unidades produtoras, consumidores e unidades de armazenamento) e, em alguns casos, tem ao seu cuidado a gestão de uma parte da rede eléctrica. Os métodos desenvolvidos contemplam a penetração intensiva de produção distribuída, o aparecimento de programas de Demand Response e o desenvolvimento de novos sistemas de armazenamento. São ainda propostos níveis de controlo e de tomada de decisão hierarquizados e geridos por entidades que actuem num ambiente de cooperação mas também de concorrência entre si. A metodologia proposta foi desenvolvida recorrendo a técnicas determinísticas, nomeadamente, à programação não linear inteira mista, tendo sido consideradas três funções objectivo distintas (custos mínimos, emissões mínimas e cortes de carga mínimos), originando, posteriormente, uma função objectivo global, o que permitiu determinar os óptimos de Pareto. São ainda determinados os valores dos custos marginais locais em cada barramento e consideradas as incertezas dos dados de entrada, nomeadamente, produção e consumo. Assim, o VPP tem ao seu dispor um conjunto de soluções que lhe permitirão tomar decisões mais fundamentadas e de acordo com o seu perfil de actuação. São apresentados dois casos de estudo. O primeiro utiliza uma rede de distribuição de 32 barramentos publicada por Baran & Wu. O segundo caso de estudo utiliza uma rede de distribuição de 114 barramentos adaptada da rede de 123 barramentos do IEEE.

MicroRNA-375 plays a dual role in prostate carcinogenesis

Background: Prostate cancer (PCa), a highly incident and heterogeneous malignancy, mostly affects men from developed countries. Increased knowledge of the biological mechanisms underlying PCa onset and progression are critical for improved clinical management. MicroRNAs (miRNAs) deregulation is common in human cancers, and understanding how it impacts in PCa is of major importance. MiRNAs are mostly downregulated in cancer, although some are overexpressed, playing a critical role in tumor initiation and progression. We aimed to identify miRNAs overexpressed in PCa and subsequently determine its impact in tumorigenesis. Results: MicroRNA expression profiling in primary PCa and morphological normal prostate (MNPT) tissues identified 17 miRNAs significantly overexpressed in PCa. Expression of three miRNAs, not previously associated with PCa, was subsequently assessed in large independent sets of primary tumors, in which miR-182 and miR-375 were validated, but not miR-32. Significantly higher expression levels of miR-375 were depicted in patients with higher Gleason score and more advanced pathological stage, as well as with regional lymph nodes metastases. Forced expression of miR-375 in PC-3 cells, which display the lowest miR-375 levels among PCa cell lines, increased apoptosis and reduced invasion ability and cell viability. Intriguingly, in 22Rv1 cells, which displayed the highest miR-375 expression, knockdown experiments also attenuated the malignant phenotype. Gene ontology analysis implicated miR-375 in several key pathways deregulated in PCa, including cell cycle and cell differentiation. Moreover, CCND2 was identified as putative miR-375 target in PCa, confirmed by luciferase assay. Conclusions: A dual role for miR-375 in prostate cancer progression is suggested, highlighting the importance of cellular context on microRNA targeting.

A influência do modelo pedagógico em variáveis psicológicas de estudantes do 1º ano da ESTSP-IPP

Introdução – A adaptação ao ensino superior reveste-se de experiências académicas que podem constituir fonte de stress para os estudantes. A implementação de novos modelos pedagógicos, no âmbito do processo de Bolonha, introduz novas variáveis cujo impacto, designadamente em termos de saúde, importa conhecer. Este estudo tem como objetivo analisar as associações entre modelo pedagógico (Problem Based Learning – PBL vs. modelos próximos do tradicional) e variáveis psicológicas (coping, desregulação emocional, sintomas psicossomáticos, perceção de stress e afeto). Metodologia – O estudo tem um design transversal. Foram usados os seguintes questionários online: Brief-COPE, Escala de Dificuldades de Regulação Emocional, Questionário de Manifestações Físicas de Mal-Estar, Escala de Stress Percebido e Escala de Afeto Positivo e Negativo. A amostra é constituída por 183 estudantes do primeiro ano (84% do género feminino) de cursos da Escola Superior de Tecnologia da Saúde do Porto – Instituto Politécnico do Porto (ESTSP-IPP). Resultados – Foram encontradas correlações significativas entre as variáveis demográficas e psicológicas. Considerando diferentes modelos pedagógicos, foram encontradas diferenças significativas nas variáveis psicológicas. Os principais preditores de stress na amostra foram: ser mulher, frequentar uma licenciatura no modelo PBL, ter maiores índices de desregulação emocional, apresentar mais sintomas psicossomáticos, menos afeto positivo e mais afeto negativo. Conclusão – As diferenças encontradas entre modelos pedagógicos são discutidas, possibilitando a reflexão sobre as implicações práticas e sugestões para futuras investigações.