A congestion management and transmission price simulator for competitive electricity markets

In a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.

Long-term price range forecast applied to risk management using regression models

Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level α. Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.

Transmission price simulator in a liberalized electricity market

This paper presents a software tool (SIM_CMTP) that solves congestion situations and evaluates the taxes to be paid to the transmission system by market agents. SIM_CMTP provides users with a set of alternative methods for cost allocation and enables the definition of specific rules, according to each market and/or situation needs. With these characteristics, SIM_CMTP can be used as an operation aid for Transmission System Operator (TSO) or Independent System Operator (ISO). Due to its openness, it can also be used as a decision-making support tool for evaluating different options of market rules in competitive market environment, guarantying the economic sustainability of the transmission system.

Desirable role in a price-setting international mixed duopoly

In this paper, we study the order of moves in a mixed international duopoly for differentiated goods, where firms choose whether to set prices sequentially or simultaneously. We discuss the desirable role of the public firm by comparing welfare among three games. We find that, in the three possible roles, the domestic public firm put a lower price, and then produces more than the foreign private firm.

Efeito país de origem e etnocentrismo: caso dos vinhos espumantes italianos

Dissertação de Mestrado Mestrado em Empreendedorismo e Internacionalização Orientada por Mestre Anabela Ribeiro

Demand Response Programs Definition Using Demand Price Elasticity to Define Consumers Aggregation for an Improved Remuneration Structure

The positioning of the consumers in the power systems operation has been changed in the recent years, namely due to the implementation of competitive electricity markets. Demand response is an opportunity for the consumers’ participation in electricity markets. Smart grids can give an important support for the integration of demand response. The methodology proposed in the present paper aims to create an improved demand response program definition and remuneration scheme for aggregated resources. The consumers are aggregated in a certain number of clusters, each one corresponding to a distinct demand response program, according to the economic impact of the resulting remuneration tariff. The knowledge about the consumers is obtained from its demand price elasticity values. The illustrative case study included in the paper is based on a 218 consumers’ scenario.

European Union emissions trading scheme impact on the Spanish electricity price during phase II and phase III implementation

The European Union Emissions Trading Scheme (EU ETS) is a cornerstone of the European Union's policy to combat climate change and its key tool for reducing industrial greenhouse gas emissions cost-effectively. The purpose of the present work is to evaluate the influence of CO2 opportunity cost on the Spanish wholesale electricity price. Our sample includes all Phase II of the EU ETS and the first year of Phase III implementation, from January 2008 to December 2013. A vector error correction model (VECM) is applied to estimate not only long-run equilibrium relations, but also short-run interactions between the electricity price and the fuel (natural gas and coal) and carbon prices. The four commodities prices are modeled as joint endogenous variables with air temperature and renewable energy as exogenous variables. We found a long-run relationship (cointegration) between electricity price, carbon price, and fuel prices. By estimating the dynamic pass-through of carbon price into electricity price for different periods of our sample, it is possible to observe the weakening of the link between carbon and electricity prices as a result from the collapse on CO2 prices, therefore compromising the efficacy of the system to reach proposed environmental goals. This conclusion is in line with the need to shape new policies within the framework of the EU ETS that prevent excessive low prices for carbon over extended periods of time.

Scalable and Efficient Configuration of TimeDivision Multiplexed Resources

Consumer-electronics systems are becoming increasingly complex as the number of integrated applications is growing. Some of these applications have real-time requirements, while other non-real-time applications only require good average performance. For cost-efficient design, contemporary platforms feature an increasing number of cores that share resources, such as memories and interconnects. However, resource sharing causes contention that must be resolved by a resource arbiter, such as Time-Division Multiplexing. A key challenge is to configure this arbiter to satisfy the bandwidth and latency requirements of the real-time applications, while maximizing the slack capacity to improve performance of their non-real-time counterparts. As this configuration problem is NP-hard, a sophisticated automated configuration method is required to avoid negatively impacting design time. The main contributions of this article are: 1) An optimal approach that takes an existing integer linear programming (ILP) model addressing the problem and wraps it in a branch-and-price framework to improve scalability. 2) A faster heuristic algorithm that typically provides near-optimal solutions. 3) An experimental evaluation that quantitatively compares the branch-and-price approach to the previously formulated ILP model and the proposed heuristic. 4) A case study of an HD video and graphics processing system that demonstrates the practical applicability of the approach.

Asymmetric dynamic price competition with uncertainty

We consider a dynamic setting-price duopoly model in which a dominant (leader) firm moves first and a subordinate (follower) firm moves second. We suppose that each firm has two different technologies, and uses one of them according to a certain probability distribution. The use of either one or the other technology affects the unitary production cost. We analyse the effect of the production costs uncertainty on the profits of the firms, for different values of the intercept demand parameters.

Estratégias defensivas em contexto nacional e comportamentos acionistas das empresas em situação de OPA

A compreensão do conceito de OPA é essencial de forma a entender o funcionamento das combinações empresariais. Esta dissertação tem dois objetivos. O primeiro objetivo tem a finalidade de perceber quais as estratégias defensivas mais eficazes em contexto de OPA. Foi através de um inquérito realizado a 192 empresas envolvidas em situação de OPA entre os anos 1991 e 2014. Através dos resultados das 14 respostas destaca-se que a Recompra de Ações é a estratégia defensiva mais utilizada, tanto em situações de defesas pré-proposta e pós-proposta. A defesa consegue evitar o sucesso, da proposta efetuada pela empresa adquirente, em mais de metade das situações em que é utilizada, tendo sido classificada como muito eficaz. 5 das operações foram de cariz hostil e 7 delas eram expectáveis pela Gestão. Em nenhuma das operações se verificou contraoperação e as áreas mais prejudicadas, pela iniciativa de OPA, foram as respeitantes ao tempo, Time-consuming, e estratégicas. O segundo objetivo tenta perceber o comportamento dos retornos médios anormais das empresas envolvidas numa OPA em face do respetivo anúncio preliminar. Seguiram-se as metodologias de Ball & Brown (1968) e Beaver (1968). Identificaram-se 100 operações compreendidas entre os anos 2000 e 2014. Através do resultado das 12 operações analisadas confirma-se que as empresas-alvo apresentam um retorno médio anormal superior ao das empresas adquirentes e que têm a tendência de acumular retornos médios anormais positivos, pelo contrário as empresas adquirentes têm a tendência de acumular retornos médios anormais negativos. Globalmente, as empresas reagem fortemente ao anúncio preliminar e apresentam uma tendência de ganho nos períodos circundantes e não-circundantes.