Real-Time Simulation of Real-Time Pricing Demand Response to Meet Wind Variations

Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer’ loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.

Consumption Management of Air Conditioning Devices for the Participation in Demand Response Programs

Demand Response has been taking over the years an extreme importance. There’s a lot of demand response programs, one of them proposed in this paper, using air conditioners that could increase the power quality and decrease the spent money in many ways like: infrastructures and customers energy bill reduction. This paper proposes a method and a study on how air conditioners could integrate demand response programs. The proposed method has been modelled as an energy resources management optimization problem. This paper presents two case studies, the first one with all costumers participating and second one with some of costumers. The results obtained for both case studies have been analyzed.

Influence of Immunopreventable Diseases and AIDS on the Demand of an Infectious Diseases Department in Rio de Janeiro State, Brazil, in the Course of Thirty Years (1965-1994)

Brazil's nosologic profile has been sustaining profound modifications. Some occurred because of massive immunization campaigns and socioeconomic and demographic trends. Some yet were pure nosologic transitions, such as the emergence of AIDS. In this demand study it is described how these changes reflected on the 8,630 admissions of an Infectious Diseases Department in Niterói, along a thirty year period. Brazilian rural endemic diseases were infrequent (3.45%). Men predominated (62%) all the time, in all age strata and in nearly all diseases. Children under fifteen predominated until 1983. There was, in the case of tetanus, a striking rise in age strata. Institutional mortality dropped from 31% in 1965 to 10% in 1984, but rose since then to 15% in 1994. However, if AIDS patients had not been computed, mortality would have kept descending till 8% at the end of the study period. The crescent unimportance of immunopreventable diseases paralleled with the growing prominence of AIDS. In less than a decade, AIDS ranked fifth among the most frequent diseases in the whole period of thirty years. As opposed to the immunopreventable diseases, neither meningitides nor pneumonia appear to be in decline. AIDS, by its exponential incidence, by its chronic character, and by the uncountable opportunistic infections it determines, imposes itself as a challenge for the coming years.

Double coverage and demand for health care: Evidence from quantile regression

An individual experiences double coverage when he bene ts from more than one health insurance plan at the same time. This paper examines the impact of such supplementary insurance on the demand for health care services. Its novelty is that within the context of count data modelling and without imposing restrictive parametric assumptions, the analysis is carried out for di¤erent points of the conditional distribution, not only for its mean location. Results indicate that moral hazard is present across the whole outcome distribution for both public and private second layers of health insurance coverage but with greater magnitude in the latter group. By looking at di¤erent points we unveil that stronger double coverage e¤ects are smaller for high levels of usage. We use data for Portugal, taking advantage of particular features of the public and private protection schemes on top of the statutory National Health Service. By exploring the last Portuguese Health Survey, we were able to evaluate their impacts on the consumption of doctor visi

Modelização do despacho económico de Gás Natural

Com as variações e instabilidade dos preços do petróleo, assim como as políticas europeias para adoção de estratégias para o desenvolvimento sustentável, têm levado à procura de forma crescente de novas tecnologias e fontes de energia alternativas. Neste contexto, tem-se assistido a políticas energéticas que estimulam o aumento da produção e a utilização do gás natural, visto que é considerado uma fonte de energia limpa. O crescimento do mercado do gás natural implica um reforço significativo das redes de transporte deste combustível, quer ao nível do armazenamento e fornecimento, quer ao nível dos gasodutos e da sua gestão. O investimento em gasodutos de transporte implica grandes investimentos, que poderiam não ser remunerados da forma esperada, sendo um dos motivos para que exista em Portugal cinco distritos se veem privados deste tipo de infraestruturas. O transporte de gás natural acarreta custos elevados para os consumidores, tanto maiores quanto maior forem as quantidades de gás transacionadas e quanto maior for o percurso pelo gás natural percorrido. Assim assume especial importância a realização de um despacho de gás natural: quais as cargas que cada unidade de fornecimento de gás irá alimentar, qual a quantidade de gás natural que cada UFGs deve injetar na rede, qual o menor percurso possível para o fazer, o tipo de transporte que será utilizado? Estas questões são abordadas na presente dissertação, por forma a minimizar a função custo de transporte, diminuindo assim as perdas na rede de alta pressão e os custos de transporte que serão suportados pelos consumidores. A rede de testes adotada foi a rede nacional de transporte, constituída por 18 nós de consumos, e os tipos de transporte considerados, foram o transporte por gasoduto físico e o transporte através de gasoduto virtual – rotas de transporte rodoviário de gás natural liquefeito. Foram criados diversos cenários, baseados em períodos de inverno e verão, os diferentes cenários abrangeram de forma distinta as variáveis de forma a analisar os impactos que estas variáveis teriam no custo relativo ao transporte de gás natural. Para dar suporte ao modelo de despacho económico, foi desenvolvida uma aplicação computacional – Despacho_GN com o objetivo de despachar as quantidades de gás natural que cada UFG deveria injetar na rede, assim como apresentar os custos acumulados relativos ao transporte. Com o apoio desta aplicação foram testados diversos cenários, sendo apresentados os respectivos resultados. A metodologia elaborada para a criação de um despacho através da aplicação “Despacho_GN” demonstrou ser eficiente na obtenção das soluções, mostrando ser suficientemente rápida para realizar as simulações em poucos segundos. A dissertação proporciona uma contribuição para a exploração de problemas relacionados com o despacho de gás natural, e sugere perspectivas futuras de investigação e desenvolvimento.

Desenvolvimento de um modelo para a gestão de stocks no grupo Nors

Hoje em dia, um dos grandes objetivos das empresas é conseguirem uma gestão eficiente. Em particular, empresas que lidam com grandes volumes de stocks têm a necessidade de otimizar as quantidades dos seus produtos armazenados, com o objetivo, de entre outros, reduzir os seus custos associados. O trabalho documentado descreve um novo modelo, desenvolvido para a gestão de encomendas de uma empresa líder em soluções de transporte. A eficiência do modelo foi alcançada com a utilização de vários métodos matemáticos de previsão. Salientam-se os métodos de Croston, Teunter e de Syntetos e Boylan adequados para artigos com procuras intermitentes e a utilização de métodos mais tradicionais, tais como médias móveis ou alisamento exponencial. Os conceitos de lead time, stock de segurança, ponto de encomenda e quantidade económica a encomendar foram explorados e serviram de suporte ao modelo desenvolvido. O stock de segurança recebeu especial atenção. Foi estabelecida uma nova fórmula de cálculo em conformidade com as necessidades reais da empresa. A eficiência do modelo foi testada com o acompanhamento da evolução do stock real. Para além de uma redução significativa do valor dos stocks armazenados, a viabilidade do modelo é reflectida pelo nível de serviço alcançado.

Stackelberg leadership with demand uncertainty in a differentiated duopoly

On a symmetric differentiated Stackelberg duopoly model in which there is asymmetric demand information owned by leading and follower firms, we show that the leading firm does not necessarily have advantage over the following one. The reason for this is that the second mover can adjust its output level after observing the realized demand, while the first mover chooses its output level only with the knowledge of demand distribution.

Quantity-setting competition under uncertain demand

We consider a quantity-setting duopoly model, and we study the decision to move first or second, by assuming that. the firms produce homogeneous goods and that. there is some demand uncertainty. The competitive phase consists of two periods, and in either period, the firms can make a production decision that is irreversible. As far as the firms are allowed to choose (non-cooperatively) the period they make the decision, we study the circumstances that favour sequential rather than simultaneous decisions.

Stackelberg duopoly with demand uncertainty

We consider a symmetric Stackelberg model in which there is asymmetric demand information owned by first and second movers. We analyse the advantages of leadership and flexibility, and prove that when the leading firm faces demand uncertainty, but the follower does not, the first mover does not necessarily have advantage over the second mover. Moreover, we show that the advantage of one firm over the other depends upon the demand fluctuation and also upon the degree of substitutability of the products.

Flexibility and leadership advantages in a model with uncertain demand

We consider a differentiated Stackelberg model with demand uncertainty only for the first mover. We study the advantages of flexibility over leadership as the degree of the differentiation of the goods changes.

Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation

Further improvements in demand response programs implementation are needed in order to take full advantage of this resource, namely for the participation in energy and reserve market products, requiring adequate aggregation and remuneration of small size resources. The present paper focuses on SPIDER, a demand response simulation that has been improved in order to simulate demand response, including realistic power system simulation. For illustration of the simulator’s capabilities, the present paper is proposes a methodology focusing on the aggregation of consumers and generators, providing adequate tolls for the demand response program’s adoption by evolved players. The methodology proposed in the present paper focuses on a Virtual Power Player that manages and aggregates the available demand response and distributed generation resources in order to satisfy the required electrical energy demand and reserve. The aggregation of resources is addressed by the use of clustering algorithms, and operation costs for the VPP are minimized. The presented case study is based on a set of 32 consumers and 66 distributed generation units, running on 180 distinct operation scenarios.

A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers

In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

The effect of demand information sharing in a supply chain under demand uncertainty: a simulation study

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Energy efficiency in energy policy: Empirical evidence of direct rebound effect in Portuguese households' demand for electricity

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics