Data Extraction Tool to Analyse, Transform and Store Real Data from Electricity Markets

The study of electricity markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring process produced. Currently, lots of information concerning electricity markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge to define realistic scenarios, which are essential for understanding and forecast electricity markets behavior. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of electricity markets and of the behaviour of the involved entities. In this paper an adaptable tool capable of downloading, parsing and storing data from market operators’ websites is presented, assuring constant updating and reliability of the stored data.

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.

Metalearner based on Dynamic Neural Network for Strategic Bidding in electricity Markets

The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.

Cost Allocation Model for Distribution Networks Considering High Penetration of Distributed Energy Resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.

An automatic tool to Extract, Transform and Load data from real electricity markets

The study of Electricity Markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring produced. Currently, lots of information concerning Electricity Markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge, to define realistic scenarios, essential for understanding and forecast Electricity Markets behaviour. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of Electricity Markets and the behaviour of the involved entities. In this paper we present an adaptable tool capable of downloading, parsing and storing data from market operators’ websites, assuring actualization and reliability of stored data.

Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

Multiagent System Architecture for Short-term Operation of Integrated Microgrids

The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid’s internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

Study of Load Curves Concerning the Influence of Socioeconomic and Cultural Issues

The increase of electricity demand in Brazil, the lack of the next major hydroelectric reservoirs implementation, and the growth of environmental concerns lead utilities to seek an improved system planning to meet these energy needs. The great diversity of economic, social, climatic, and cultural conditions in the country have been causing a more difficult planning of the power system. The work presented in this paper concerns the development of an algorithm that aims studying the influence of the issues mentioned in load curves. Focus is given to residential consumers. The consumption device with highest influence in the load curve is also identified. The methodology developed gains increasing importance in the system planning and operation, namely in the smart grids context.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

Electricity markets modeling considering complex contracts and aggregators

All over the world, the liberalization of electricity markets, which follows different paradigms, has created new challenges for those involved in this sector. In order to respond to these challenges, electric power systems suffered a significant restructuring in its mode of operation and planning. This restructuring resulted in a considerable increase of the electric sector competitiveness. Particularly, the Ancillary Services (AS) market has been target of constant renovations in its operation mode as it is a targeted market for the trading of services, which have as main objective to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. In this way, with the increasing penetration of distributed energy resources including distributed generation, demand response, storage units and electric vehicles, it is essential to develop new smarter and hierarchical methods of operation of electric power systems. As these resources are mostly connected to the distribution network, it is important to consider the introduction of this kind of resources in AS delivery in order to achieve greater reliability and cost efficiency of electrical power systems operation. The main contribution of this work is the design and development of mechanisms and methodologies of AS market and for energy and AS joint market, considering different management entities of transmission and distribution networks. Several models developed in this work consider the most common AS in the liberalized market environment: Regulation Down; Regulation Up; Spinning Reserve and Non-Spinning Reserve. The presented models consider different rules and ways of operation, such as the division of market by network areas, which allows the congestion management of interconnections between areas; or the ancillary service cascading process, which allows the replacement of AS of superior quality by lower quality of AS, ensuring a better economic performance of the market. A major contribution of this work is the development an innovative methodology of market clearing process to be used in the energy and AS joint market, able to ensure viable and feasible solutions in markets, where there are technical constraints in the transmission network involving its division into areas or regions. The proposed method is based on the determination of Bialek topological factors and considers the contribution of the dispatch for all services of increase of generation (energy, Regulation Up, Spinning and Non-Spinning reserves) in network congestion. The use of Bialek factors in each iteration of the proposed methodology allows limiting the bids in the market while ensuring that the solution is feasible in any context of system operation. Another important contribution of this work is the model of the contribution of distributed energy resources in the ancillary services. In this way, a Virtual Power Player (VPP) is considered in order to aggregate, manage and interact with distributed energy resources. The VPP manages all the agents aggregated, being able to supply AS to the system operator, with the main purpose of participation in electricity market. In order to ensure their participation in the AS, the VPP should have a set of contracts with the agents that include a set of diversified and adapted rules to each kind of distributed resource. All methodologies developed and implemented in this work have been integrated into the MASCEM simulator, which is a simulator based on a multi-agent system that allows to study complex operation of electricity markets. In this way, the developed methodologies allow the simulator to cover more operation contexts of the present and future of the electricity market. In this way, this dissertation offers a huge contribution to the AS market simulation, based on models and mechanisms currently used in several real markets, as well as the introduction of innovative methodologies of market clearing process on the energy and AS joint market. This dissertation presents five case studies; each one consists of multiple scenarios. The first case study illustrates the application of AS market simulation considering several bids of market players. The energy and ancillary services joint market simulation is exposed in the second case study. In the third case study it is developed a comparison between the simulation of the joint market methodology, in which the player bids to the ancillary services is considered by network areas and a reference methodology. The fourth case study presents the simulation of joint market methodology based on Bialek topological distribution factors applied to transmission network with 7 buses managed by a TSO. The last case study presents a joint market model simulation which considers the aggregation of small players to a VPP, as well as complex contracts related to these entities. The case study comprises a distribution network with 33 buses managed by VPP, which comprises several kinds of distributed resources, such as photovoltaic, CHP, fuel cells, wind turbines, biomass, small hydro, municipal solid waste, demand response, and storage units.

Cost allocation model for distribution networks considering high penetration of distributed energy resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

Estratégias de Comercialização de Potência como Medida de Eficiência Energética

A presente dissertação insere-se no âmbito da unidade curricular “ Dissertação” do 2º ano do mestrado em Engenharia Eletrotécnica – Sistemas Elétricos de Energia. Com o aumento crescente do número de consumidores de energia, é cada vez mais imperioso a adoção de medidas de racionalização e gestão dos consumos da energia elétrica. Existem diferentes tipos de dificuldades no planeamento e implementação de novas centrais produtoras de energia renovável, pelo que também por este motivo é cada vez mais importante adoção de medidas de gestão de consumos, quer ao nível dos clientes alimentados em média tensão como de baixa tensão. Desta forma será mais acessível a criação de padrões de eficiência energética elevados em toda a rede de distribuição de energia elétrica. Também a economia é afetada por uma fraca gestão dos consumos por parte dos clientes. Elevados desperdícios energéticos levam a que mais energia tenha que ser produzida, energia essa que contribui ainda mais para a elevada taxa de dependência energética em Portugal, e para o degradar da economia nacional. Coloca-se assim a necessidade de implementar planos e métodos que promovam a eficiência energética e a gestão racional de consumos de energia elétrica. Apresenta-se nesta dissertação várias propostas, algumas na forma de projetos já em execução, que visam sensibilizar o consumidor para a importância da utilização eficiente de energia e, ao mesmo tempo, disponibilizam as ferramentas tecnológicas adequadas para auxiliar a implementação dos métodos propostos. Embora os planos apresentados, sobejamente conhecidos, tenham imensa importância, a implementação nos vários consumidores de sistemas capazes de efetivamente reduzir consumos tem um papel fundamental. Equipamentos de gestão de consumos, que são apresentados nesta dissertação, permitem ao consumidor aceder diretamente ao seu consumo. Podem aceder não apenas ao consumo global da instalação mas também ao consumo específico por equipamento, permitindo perceber onde se verifica a situação mais desfavorável. Funcionalidades de programação de perfis tipo, com limitações de potência em vários períodos horários, bem como possibilidades de controlo remoto com recurso a aplicações para Smartphones permitem a redução de consumos ao nível da rede de distribuição e, desta forma, contribuir para a redução dos desperdícios e da dependência energética em Portugal. No âmbito do trabalho de dissertação é desenvolvida uma metodologia de comercialização de potência, que é apresentada nesta tese. Esta metodologia propõem que o consumidor, em função dos seus consumos, pague apenas a quantidade de potência que efetivamente necessita num certo período de tempo. Assim, o consumidor deixa de pagar uma tarifa mensal fixa associada á sua potência contratada, e passará a pagar um valor correspondente apenas à potência que efetivamente solicitou em todas as horas durante o mês. Nesta metodologia que é apresentada, o consumidor poderá também fazer uma análise do seu diagrama de cargas e simular uma alteração da sua tarifa, tarifa esta que varia entre tarifa simples, bi-horária semanal, bi-horária diária, tri-horária semanal ou tri-horária diária, de forma a perceber em qual destas pagará um menor valor pela mesma energia. De forma a que o consumidor possa perceber se haverá vantagem de uma alteração para uma potência contratada flexível, ou para uma outra tarifa associada á energia, tem ao seu dispor uma ferramenta, que em função dos seus consumos, permite retirar conclusões sobre o preço final a pagar na fatura, após cada tipo de alteração. Esta ferramenta foi validada com recurso a várias simulações, para diferentes perfis de consumidores. Desta forma, o utilizador fica a perceber que realmente pode poupar com uma potência contratada flexível, ao mesmo tempo que pode identificar-se com um perfil de simulação e, mais facilmente, perceber para que alteração tarifária pode usufruir de uma maior poupança.

Production of ellagitannins concentrate by UF-NF from tropical highland blackberries

Dissertation presented to Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa for obtaining the master degree in Membrane Engineering

The ambivalence of two-part tariffs for bottleneck access

Two-part tariffs, when used at the retail level, increase efficiency by lowering the price of marginal units. The same potential for higher efficiency exists for two-part tariffs at wholesale level for a given market structure, but the fixed part of the wholesale tariff can negatively affect the latter. In a simulated competition model of next-generation telecommunications access networks that has been calibrated with engineering cost data, we show that the latter effects strongly outweigh the former. That is, substituting a cost-based linear wholesale access tariff with revenue-equivalent two-part tariffs reduces the number of access seekers and therefore leads to higher prices and lower welfare and consumer surplus.

Portuguese average cost of capital

The oldest Portuguese share index still being calculated is the BVL/PSI-General, one which started the daily series on 5/Jan/1988 with a base value of 1000 points. Everyday a single value is computed based on the closing prices of all the shares included in the sample. Also, all corporate events affecting the price of any share beyond market sentiment are taken into account through proper adjustments, either in the numerator or the denominator of the formula. However, for dates before January 1988, there is nothing comparable to this index since the two different series known either never disclosed the methodology adopted to calculate the index or followed solutions not compatible with the above index. The present paper explains the solutions adopted to replicate as closely as possible the methodology of the BVL-General index to the main market of the Lisbon Exchange for the period 1978 – 1987. This is the first estimate of the historical Equity Risk Premium in Portugal above short-term risk-free rate from the re-opening of the market following the Carnation Revolution (and the accompanying nationalizations), to the present. In showing a value of the same order of magnitude found in other countries, the paper invites further studies on the effects of political decisions such as privatizations and joining the European Union.