Credit risk measures: a case of renewable energy companies

The Basel III will have a significant impact on the European banking sector. In September 2010, supervisors of various countries adopted the new rules proposed by the prudential Committee on Banking Supervision to be applied to the business of credit institutions (hereinafter called ICs) in a phased manner from 2013, assuming to its full implementation by 2019. The purpose of this new regulation is to limit the excessive risk that these institutions took on the period preceding the global financial crisis of 2008. This new regulation is known in slang by Basel III. Depending on the requirement of Basel II for banks and their supervisors to assess the soundness and adequacy of internal risk measurement and credit management systems, the development of methodologies for the validation of internal and external evaluation systems is clearly an important issue . More specifically, there is a need to develop tools to validate the systems used to generate the parameters (such as PD, LGD, EAD and ratings of perceived risk) that serve as starting points for the IRB approach for credit risk. In this context, the work is composed of a number of approaches and tools used to evaluate the robustness of these elements IRB systems.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Industry energy optimization: A case study in a biodiesel production site

This paper presents a case study of heat exchanger network (HEN) retrofit with the objective to reduce the utilities consumption in a biodiesel production process. Pinch analysis studies allow determining the minimum duty utilities as well the maximum of heat recovery. The existence of heat exchangers for heat recovery already running in the process causes a serious restriction for the implementation of grassroot HEN design based on pinch studies. Maintaining the existing HEN, a set of alternatives with additional heat exchangers was created and analysed using some industrial advice and selection criteria. The final proposed solution allows to increase the actual 18 % of recovery heat of the all heating needs of the process to 23 %, with an estimated annual saving in hot utility of 35 k(sic)/y.

WeSenseNET - Plataforma de Visualização, Gestão Remota e Agregação Múltipla de Dados

Nos últimos anos, o avanço da tecnologia e a miniaturização de diversos componentes de electrónica associados a novos conceitos têm permitido nascer novas ideias e projectos, que até há alguns anos não passariam de ficção científica. Talvez o exemplo mais acabado seja actualmente o smartphone, um pequeno bloco de hardware e software, com capacidade de processamento que ultrapassa várias vezes o dos computadores com uma dúzia de anos. Estas capacidades têm sido utilizadas em comunicações, blocos de notas, agendas e até entretenimento. No entanto, podem ser reutilizadas para ajudar a resolver algumas limitações/constrangimentos da actualidade. Dentro destes destacam-se a gestão de recursos escassos. Com efeito, o consumo de energia eléctrica tem aumentado como consequência directa do desenvolvimento global e aumento do número de aparelhos eléctricos. Uma percentagem significativa de energia eléctrica tem sido produzida através de recursos não-renováveis de energia. No entanto, a dependência energética, associada à subida de preços e a redução das emissões de gases do efeito estufa, estimula o desenvolvimento de novas soluções que permitam lidar com esta situação. O desempenho energético por sua vez depende não só das características da estrutura, mas também do comportamento do utilizador. O desempenho energético dos edifícios é muito importante, uma vez que os respectivos consumos são responsáveis por mais de metade do total da energia produzida. Desta forma, a fim de alcançar um melhor desempenho é importante não só considerar o desempenho de estrutura, mas também monitorizar o comportamento do utilizador. Esta última questão coloca várias limitações, uma vez que depende muito do tipo de utilizador. Um dos conceitos actuais emergentes são as chamadas redes de sensores sem fio. Com esta tecnologia, pequenos módulos podem ser desenvolvidos com muitas possibilidades de conectividade, com elevado poder de processamento e com grande autonomia, sem serem excessivamente caros. Isto proporciona os meios para implementar vários dispositivos em toda a instalação, para recolher uma variedade de dados, sendo posteriormente armazenados num servidor. Os blocos fundamentais da infra-estrutura de sensores do projecto foram concebidos na Evoleo Technologies em simultâneo com o decorrer do estágio. Estes blocos recolhem dados específicos na instalação, e periodicamente enviam para o servidor central os valores recolhidos, onde são armazenados e colocados à disposição do utilizador. Os dados recolhidos podem então ser apresentados ao utilizador, proporcionando um registo de consumo de energia associado a um dado período de tempo. Uma vez que todos os dados são armazenados no servidor, podem ser efectuados estudos para determinar o uso típico, possíveis problemas em aparelhos, a qualidade da energia eléctrica, etc., permitindo determinar onde a energia está a ser eventualmente desperdiçada e fornecendo dados ao utilizador para que este possa proceder a alterações, tendo por base dados recolhidos num dado período. O objectivo principal deste trabalho passa por estabelecer a ligação entre o nível máquina e o nível de utilizador, isto é, uma plataforma de interacção entre dispositivos e administrador da instalação. Fornecer os dados de uma forma fácil e sem necessidade de instalação de software específico em cada dispositivo que se pretenda utilizar para monitorizar foi uma das principais preocupações das fases de concepção do projecto.

A stochastic programming approach for the development of offering strategies for a wind power producer

A stochastic programming approach is proposed in this paper for the development of offering strategies for a wind power producer. The optimization model is characterized by making the analysis of several scenarios and treating simultaneously two kinds of uncertainty: wind power and electricity market prices. The approach developed allows evaluating alternative production and offers strategies to submit to the electricity market with the ultimate goal of maximizing profits. An innovative comparative study is provided, where the imbalances are treated differently. Also, an application to two new realistic case studies is presented. Finally, conclusions are duly drawn.

Assessment and optimization of wind energy integration into the power systems: application to the portuguese system

The increasing integration of wind energy in power systems can be responsible for the occurrence of over-generation, especially during the off-peak periods. This paper presents a dedicated methodology to identify and quantify the occurrence of this over-generation and to evaluate some of the solutions that can be adopted to mitigate this problem. The methodology is applied to the Portuguese power system, in which the wind energy is expected to represent more than 25% of the installed capacity in a near future. The results show that the pumped-hydro units will not provide enough energy storage capacity and, therefore, wind curtailments are expected to occur in the Portuguese system. Additional energy storage devices can be implemented to offset the wind energy curtailments. However, the investment analysis performed show that they are not economically viable, due to the present high capital costs involved.

Commercial agentes portfolio optimization in electricity markets

As it is well known, competitive electricity markets require new computing tools for power companies that operate in retail markets in order to enhance the management of its energy resources. During the last years there has been an increase of the renewable penetration into the micro-generation which begins to co-exist with the other existing power generation, giving rise to a new type of consumers. This paper develops a methodology to be applied to the management of the all the aggregators. The aggregator establishes bilateral contracts with its clients where the energy purchased and selling conditions are negotiated not only in terms of prices but also for other conditions that allow more flexibility in the way generation and consumption is addressed. The aggregator agent needs a tool to support the decision making in order to compose and select its customers' portfolio in an optimal way, for a given level of profitability and risk.

Electric vehicles as a mean to reduce, energy, emissions and electricity costs

Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs), which obtain their fuel from the grid by charging a battery, are set to be introduced into the mass market and expected to contribute to oil consumption reduction. This research is concerned with studying the potential impacts on the electric utilities of large-scale adoption of plug-in electric vehicles from the perspective of electricity demand, fossil fuels use, CO2 emissions and energy costs. Simulations were applied to the Portuguese case study in order to analyze what would be the optimal recharge profile and EV penetration in an energy-oriented, an emissions-oriented and a cost-oriented objective. The objectives considered were: The leveling of load profiles, minimization of daily emissions and minimization of daily wholesale costs. Almost all solutions point to an off-peak recharge and a 50% reduction in daily wholesale costs can be verified from a peak recharge scenario to an off-peak recharge for a 2 million EVs in 2020. A 15% improvement in the daily total wholesale costs can be verified in the costs minimization objective when compared with the off-peak scenario result.

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.

The electric vehicles as a mean to reduce Co2 emissions and energy costs in isolated regions: the São Miguel (Azores) case study

Most of small islands around the world today, are dependent on imported fossil fuels for the majority of their energy needs especially for transport activities and electricity production. The use of locally renewable energy resources and the implementation of energy efficiency measures could make a significant contribution to their economic development by reducing fossil fuel imports. An electrification of vehicles has been suggested as a way to both reduce pollutant emissions and increase security of supply of the transportation sector by reducing the dependence on oil products imports and facilitate the accommodation of renewable electricity generation, such as wind and, in the case of volcanic islands like Sao Miguel (Azores) of the geothermal energy whose penetration has been limited by the valley electricity consumption level. In this research, three scenarios of EV penetration were studied and it was verified that, for a 15% LD fleet replacement by EVs with 90% of all energy needs occurring during the night, the accommodation of 10 MW of new geothermal capacity becomes viable. Under this scenario, reductions of 8% in electricity costs, 14% in energy, 23% in fossil fuels use and CO2 emissions for the transportation and electricity production sectors could be expected.

Long-term dependence in financial prices: evidence from the Belgian stock market returns

This article aims to contribute to the discussion of long-term dependence, focusing on the behavior of the main Belgian stock index. Non-parametric analyzes of the general characteristics of temporal frequency show that daily returns are non-ergodic and non-stationary. Therefore, we use the rescaled-range analysis (R/S) and the detrended fluctuation analysis (DFA), under the fractional Brownian motion approach, and we found slight evidence of long-term dependence. These results refute the random walk hypothesis with i.i.d. increments, which is the basis of the EMH in its weak form, and call into question some theoretical modeling of asset pricing. Other more localized complementary study, to identify the evolution of the degree of dependence over time windows, showed that the index has become less persistent from 2010. This may mean a maturing market by the extension of the effects of current financial crisis.

Energy efficiency of quadruped gaits

This paper studies periodic gaits of quadruped locomotion systems. The purpose is to determine the best set of gait and locomotion variables during walking, for different robot velocities, based on two formulated performance measures. A set of experiments reveals the influence of the gait and locomotion variables upon the proposed indices, namely that the gait and the locomotion parameters should be adapted to the robot forward velocity.

Optimising the energy consumption on pultrusion process

This study is based on a previous experimental work in which embedded cylindrical heaters were applied to a pultrusion machine die, and resultant energetic performance compared with that achieved with the former heating system based on planar resistances. The previous work allowed to conclude that the use of embedded resistances enhances significantly the energetic performance of pultrusion process, leading to 57% decrease of energy consumption. However, the aforementioned study was developed with basis on an existing pultrusion die, which only allowed a single relative position for the heaters. In the present work, new relative positions for the heaters were investigated in order to optimise heat distribution process and energy consumption. Finite Elements Analysis was applied as an efficient tool to identify the best relative position of the heaters into the die, taking into account the usual parameters involved in the process and the control system already tested in the previous study. The analysis was firstly developed based on eight cylindrical heaters located in four different location plans. In a second phase, in order to refine the results, a new approach was adopted using sixteen heaters with the same total power. Final results allow to conclude that the correct positioning of the heaters can contribute to about 10% of energy consumption reduction, decreasing the production costs and leading to a better eco-efficiency of pultrusion process.

Estimating Effective Slowdown of Tasks in Energy-Aware Clouds

Consolidation consists in scheduling multiple virtual machines onto fewer servers in order to improve resource utilization and to reduce operational costs due to power consumption. However, virtualization technologies do not offer performance isolation, causing applications’ slowdown. In this work, we propose a performance enforcing mechanism, composed of a slowdown estimator, and a interference- and power-aware scheduling algorithm. The slowdown estimator determines, based on noisy slowdown data samples obtained from state-of-the-art slowdown meters, if tasks will complete within their deadlines, invoking the scheduling algorithm if needed. When invoked, the scheduling algorithm builds performance and power aware virtual clusters to successfully execute the tasks. We conduct simulations injecting synthetic jobs which characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our strategy can be efficiently integrated with state-of-the-art slowdown meters to fulfil contracted SLAs in real-world environments, while reducing operational costs in about 12%.

Towards high-available and energy-efficient virtual computing environments in the cloud

Empowered by virtualisation technology, cloud infrastructures enable the construction of flexi- ble and elastic computing environments, providing an opportunity for energy and resource cost optimisation while enhancing system availability and achieving high performance. A crucial re- quirement for effective consolidation is the ability to efficiently utilise system resources for high- availability computing and energy-efficiency optimisation to reduce operational costs and carbon footprints in the environment. Additionally, failures in highly networked computing systems can negatively impact system performance substantially, prohibiting the system from achieving its initial objectives. In this paper, we propose algorithms to dynamically construct and readjust vir- tual clusters to enable the execution of users’ jobs. Allied with an energy optimising mechanism to detect and mitigate energy inefficiencies, our decision-making algorithms leverage virtuali- sation tools to provide proactive fault-tolerance and energy-efficiency to virtual clusters. We conducted simulations by injecting random synthetic jobs and jobs using the latest version of the Google cloud tracelogs. The results indicate that our strategy improves the work per Joule ratio by approximately 12.9% and the working efficiency by almost 15.9% compared with other state-of-the-art algorithms.