Testing the weak-form market efficiency and the day of the week effects of some African countries

The aims of this work are twofold. On the one hand, it aims to find evidence supporting the presence of the weak form efficiency of several emerging African stock markets by using both parametric as well as non parametric tests. The results indicate that none of the markets are characterised by random walks with the exception of the South African stock market. On the other hand, this study aims to detect the presence of the day of the week effects of these African stock markets. Results show the existence of day of the week effects, that is the typical negative Monday and Friday positive effects in several stock markets.

A beautiful day/Um dia lindo

Tradução da peça.

Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

ANN based day-ahead spinning reserve forecast for electricity market simulation

Electricity market players operating in a liberalized environment require adequate decision support tools, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. This paper deals with short-term predication of day-ahead spinning reserve (SR) requirement that helps the ISO to make effective and timely decisions. Based on these forecasted information, market participants can use strategic bidding for day-ahead SR market. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

ANN based day-ahead ancillary services forecast for electricity market simulation

Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Levantamento ambiental de uma indústria conserveira nos Açores

Dissertação de Mestrado em Ambiente, Saúde e Segurança.

Cão de Fila de S. Miguel : património cultural imaterial

Dissertação de Mestrado, Património, Museologia e Desenvolvimento, 2 de Outubro de 2015, Universidade dos Açores.

Alright: a distinctive pathway of change from the 18th century to the present day

The origins of the vast majority of the words we use in contemporary English go back as far as Old or Middle English. In contrast, alright and all right in their present-day application appear to be the result of a more recent evolution, as there is no evidence of their use, not even in the two-word form, in the published fiction before the 18th century. Furthermore, there are not in the research literature, at least to my knowledge, any previous linguistic studies on this specific subject matter. The present article is simply an attempt to describe the various processes of diachronic change that brought about the emergence of alright.

Price forecasting in the day-ahead Iberian electricity market using a conjectural variations Arima model

Price forecast is a matter of concern for all participants in electricity markets, from suppliers to consumers through policy makers, which are interested in the accurate forecast of day-ahead electricity prices either for better decisions making or for an improved evaluation of the effectiveness of market rules and structure. This paper describes a methodology to forecast market prices in an electricity market using an ARIMA model applied to the conjectural variations of the firms acting in an electricity market. This methodology is applied to the Iberian electricity market to forecast market prices in the 24 hours of a working day. The methodology was then compared with two other methodologies, one called naive and the other a direct forecast of market prices using also an ARIMA model. Results show that the conjectural variations price forecast performs better than the naive and that it performs slightly better than the direct price forecast.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

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.

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.

The Intensive Care Global Study on Severe Acute Respiratory Infection (IC-GLOSSARI): a Multicenter, Multinational, 14-Day Inception Cohort Study

PURPOSE: In this prospective, multicenter, 14-day inception cohort study, we investigated the epidemiology, patterns of infections, and outcome in patients admitted to the intensive care unit (ICU) as a result of severe acute respiratory infections (SARIs). METHODS: All patients admitted to one of 206 participating ICUs during two study weeks, one in November 2013 and the other in January 2014, were screened. SARI was defined as possible, probable, or microbiologically confirmed respiratory tract infection with recent onset dyspnea and/or fever. The primary outcome parameter was in-hospital mortality within 60 days of admission to the ICU. RESULTS: Among the 5550 patients admitted during the study periods, 663 (11.9 %) had SARI. On admission to the ICU, Gram-positive and Gram-negative bacteria were found in 29.6 and 26.2 % of SARI patients but rarely atypical bacteria (1.0 %); viruses were present in 7.7 % of patients. Organ failure occurred in 74.7 % of patients in the ICU, mostly respiratory (53.8 %), cardiovascular (44.5 %), and renal (44.6 %). ICU and in-hospital mortality rates in patients with SARI were 20.2 and 27.2 %, respectively. In multivariable analysis, older age, greater severity scores at ICU admission, and hematologic malignancy or liver disease were independently associated with an increased risk of in-hospital death, whereas influenza vaccination prior to ICU admission and adequate antibiotic administration on ICU admission were associated with a lower risk. CONCLUSIONS: Admission to the ICU for SARI is common and associated with high morbidity and mortality rates. We identified several risk factors for in-hospital death that may be useful for risk stratification in these patients.

Smart machines in day-to-day financial management:

Starting from Novabase’s challenge to launch in the UK Millennials a personal financial advisor mobile application, this work project aims to build a planning model to frame a business side of a launch strategy for mobile application in similar market and category. This study culminates on the design of SPOSTAC planning model. The created framework is intended to effectively and efficiently plan a launch strategy, being structured based on seven sequential elements: Situation, Product, Objectives, Strategy, Tactics, Action, and Control.

Has the time for renewables finally arrived? – An event study on EPA’s Clean Power Plan

The recent proposals presented by EPA aimed to reduce the dependency of fossil fuels and to lower current emissions levels, hoping to gradually shift electric generation units to renewable energy sources. Actually, the Final Rule Proposal announcement day exhibited a negative Abnormal Return on Fossil Fuels but the following days had positive Abnormal Returns, mostly due to legislative change perceived by financial markets which eased up implementation periods of the proposed measures in the Final Rule when compared to the Draft Rule. Oppositely, Renewables and Solar Portfolios exhibited negative Cumulative Abnormal Returns over the period surrounding the Final Rule.