Bid definition method for electricity markets based on an adaptive multiagent system

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. Each agent has the knowledge about a different method for defining a strategy for playing in the market, the main agent chooses the best among all those, and provides it to the market player that requests, to be used in the market. This paper also presents a methodology to manage the efficiency/effectiveness balance of this method, to guarantee that the degradation of the simulator processing times takes the correct measure.

Strategic bidding methodology for electricity markets using adaptive learning

The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players’ models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition.

Multi-agent negotiation for coalition formation and management in electricity markets

Negotiation is a fundamental tool for reaching understandings that allow each involved party to gain an advantage for themselves by the end of the process. In recent years, with the increasing of compe-titiveness in most sectors, negotiation procedures become present in practically all of them. One particular environment in which the competitiveness has been increasing exponentially is the electricity markets sector. This work is directed to the study of electricity markets’ partici-pating entities interaction, namely in what concerns the formation, management and operation of aggregating entities – Virtual Power Players (VPPs). VPPs are responsible for managing coalitions of market players with small market negotiating influence, which take strategic advantage in entering such aggregations, to increase their negotiating power. This chapter presents a negotiation methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using MASCEM, taking advantage of its ability to provide the means to model and simulate VPPs. VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself.

Virtual power producers simulation - negotiating renewable distributed generation in competitive electricity markets

Sustainable development concerns made renewable energy sources to be increasingly used for electricity distributed generation. However, this is mainly due to incentives or mandatory targets determined by energy policies as in European Union. Assuring a sustainable future requires distributed generation to be able to participate in competitive electricity markets. To get more negotiation power in the market and to get advantages of scale economy, distributed generators can be aggregated giving place to a new concept: the Virtual Power Producer (VPP). VPPs are multi-technology and multisite heterogeneous entities that should adopt organization and management methodologies so that they can make distributed generation a really profitable activity, able to participate in the market. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, in the context of MASCEM, a multi-agent based eletricity market simulator.

Transmission tariffs in competitive electricity markets

In context of electricity market, the transmission price is an important tool to an efficient development of the electricity system. The electricity market is influenced by several factors; however the transmission network management is one of the most important aspects, because the network is a natural monopoly. The transmission tariffs can help to regulate the market, for that reason evaluate tariff must have strict criterions. This paper explains several methodologies to tariff the use of transmission network by transmission network users. The methods presented are: Post-Stamp Method; MW-Mile Method; Distribution Factors Methods; Tracing Methodology; Bialek’s Tracing Method and Locational Marginal Price.

Nodal price simulation in competitive electricity markets

Locational Marginal Prices (LMP) are important pricing signals for the participants of competitive electricity markets, as the effects of transmission losses and binding constraints are embedded in LMPs [1],[2]. This paper presents a software tool that evaluates the nodal marginal prices considering losses and congestion. The initial dispatch is based on all the electricity transactions negotiated in the pool and in bilateral contracts. It must be checked if the proposed initial dispatch leads to congestion problems; if a congestion situation is detected, it must be solved. An AC power flow is used to verify if there are congestion situations in the initial dispatch. Whenever congestion situations are detected, they are solved and a feasible dispatch (re-dispatch) is obtained. After solving the congestion problems, the simulator evaluates LMP. The paper presents a case study based on the the 118 IEEE bus test network.

Dgenco market balancing - cost repartition under light regulation markets

In this paper we present a new methodology, based in game theory, to obtain the market balancing between Distribution Generation Companies (DGENCO), in liberalized electricity markets. The new contribution of this methodology is the verification of the participation rate of each agent based in Nucléolo Balancing and in Shapley Value. To validate the results we use the Zaragoza Distribution Network with 42 Bus and 5 DGENCO.

A long-term swarm intelligence hedging tool applied to electricity markets

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

Electricity markets: transmission prices methods

In the context of electricity markets, transmission pricing is an important tool to achieve an efficient operation of the electricity system. The electricity market is influenced by several factors; however the transmission network management is one of the most important aspects, because the network is a natural monopoly. The transmission tariffs can help to regulate the market, for this reason transmission tariffs must follow strict criteria. This paper presents the following methods to tariff the use of transmission networks by electricity market players: Post-Stamp Method; MW-Mile Method Distribution Factors Methods; Tracing Methodology; Bialek’s Tracing Method and Locational Marginal Price. A nine bus transmission network is used to illustrate the application of the tariff methods.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

AI in power systems and energy markets

In a world increasingly conscientious about environmental effects, power and energy systems are undergoing huge transformations. Electric energy produced from power plants is transmitted and distributed to end users through a power grid. The power industry performs the engineering design, installation, operation, and maintenance tasks to provide a high-quality, secure energy supply while accounting for its systems’ abilities to withstand uncertain events, such as weather-related outages. Competitive, deregulated electricity markets and new renewable energy sources, however, have further complicated this already complex infrastructure.Sustainable development has also been a challenge for power systems. Recently, there has been a signifi cant increase in the installation of distributed generations, mainly based on renewable resources such as wind and solar. Integrating these new generation systems leads to more complexity. Indeed, the number of generation sources greatly increases as the grid embraces numerous smaller and distributed resources. In addition, the inherent uncertainties of wind and solar energy lead to technical challenges such as forecasting, scheduling, operation, control, and risk management. In this special issue introductory article, we analyze the key areas in this field that can benefi t most from AI and intelligent systems now and in the future.We also identify new opportunities for cross-fertilization between power systems and energy markets and intelligent systems researchers.

Commercial agents 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.

Adaptive learning in agents behaviour: a framework for electricity markets simulation

Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

Optimização do tratamento por lamas activadas do efluente líquido da Mundotêxtil

A Mundotêxtil foi fundada em 1975 tendo iniciado a sua actividade na área comercial de produtos têxteis. Actualmente é o maior produtor nacional de atoalhados de felpo e emprega 575 colaboradores. Como resultado do seu crescimento e sobretudo da actividade de tingimento de fio e felpo, as necessidades de água são consideráveis e o volume de efluentes gerados nos processos industriais é cada vez maior a empresa avançou com a construção de uma estação de tratamento por lamas activadas, colocando-a em funcionamento em Setembro de 2004. Inicialmente surgiram dificuldades para a remoção da cor e da concentração da Carência Química de Oxigénio (CQO) de modo a cumprir os limites máximos de emissão permitidos nas normas de descarga no rio Ave e no Decreto-Lei nº 236/98, de 1 de Agosto. Com a descarga de parte dos efluentes no SIDVA e a utilização de um coagulante adicionado ao reactor o tratamento passou a apresentar melhores resultados. O intuito deste trabalho é o de apresentar soluções de modo a optimizar o funcionamento do tratamento biológico da Mundotêxtil. A optimização pode começar na concepção dos produtos, pode incidir no processo de fabrico para além de poder ser efectuada no seio da estação de tratamento biológico. Foi efectuado um estudo do tratamento biológico por lamas activadas no Laboratório de Tecnologia Química Profª Doutora Lída de Vasconcelos, laboratório tecnológico do Instituto Superior de Engenharia do Porto (ISEP) que decorreu nos meses de Maio, Junho e Julho de 2010. O estudo laboratorial foi efectuado para três situações distintas: 1) tratamento do efluente bruto sem qualquer tipo de pré-tratamento (ensaios 1 a 3); 2) tratamento do efluente bruto submetido a pré-tratamento com coagulante Ambifloc BIO MD (ensaios 4 e 5) e 3) tratamento com adição de fungos ao tanque de arejamento (ensaio 6). Foram utilizadas duas instalações de tratamento alimentadas a partir do mesmo tanque de alimentação. Os dois sistemas eram idênticos, diferiram nos caudais de alimentação de efluente que foram alterados ao longo do estudo. O efluente a tratar foi fornecido pela empresa Mundotêxtil, sendo recolhido por diversas vezes ao longo dos ensaios. Este efluente foi retirado após o pré-tratamento da empresa, ou seja este efluente é o mesmo que alimenta o tratamento biológico da Mundotêxtil. Devido a este facto o efluente usado no estudo laboratorial teve uma variabilidade no período em que decorreu o estudo, nomeadamente em termos de concentração de CQO e cor. A relação entre a Carência Bioquímica (CBO5) e a CQO situouse entre 0,47 e 0,63 o que traduz que está dentro dos valores típicos para um efluente têxtil. Os melhores resultados globais de remoção de CQO foram obtidos no ensaio 5 e estiveram compreendidos entre 73,2% e 77,5% para o ensaio 5.1 e entre 62,9 e 73,2% para o ensaio 5.2. Neste ensaio foi utilizado o coagulante. Todos os valores de concentração de CQO obtidos nos efluentes dos decantadores para os ensaios 2, 5 e 6 são inferiores aos valores limite de descarga definidos nas normas de descarga no rio Ave e o Decreto-Lei 236/98. Os valores de concentração de Sólidos Suspensos Totais (SST), pH, fósforo, CBO5 e cor nos decantadores cumpriram os limites de descarga definidos nas normas de descarga no rio Ave e no Decreto-Lei nº 236/98 em todos os ensaios. Os parâmetros cinéticos obtidos para os ensaios com descorante são os que melhor se ajustam ao projecto de uma instalação de tratamento biológico por lamas activadas do efluente da Mundotêxtil. Os valores obtidos, após ajuste, são os seguintes: k=0,015 L/(mgSSV*d); Sn=12 mg/L; a=0,7982 kgO2/kgCBO5; b=0,0233 [kgO2/(kgSSV*d); y=0,2253 kgSSV/kgCBO5; kd=0,0036 kgSSV/(kgSSV*d. Com base nos parâmetros cinéticos obtiveram-se os seguintes resultados para o projecto de uma estação de tratamento biológico por lamas activadas: · Tempo de retenção hidráulica no reactor de 1,79 d, · Volume do reactor igual a 3643 m3 · Consumo de oxigénio no reactor de 604 kg/d · Razão de recirculação igual a 0,8 · Volume total do decantador secundário igual a 540 m3 · Diâmetro do decantador secundário igual a 15 m A quantidade de oxigénio necessário é baixa e o valor mais adequado deverá ser da ordem de 1200 kg/d. Também foi efectuada uma análise aos produtos químicos consumidos pela empresa na área das tinturarias com a finalidade de identificar as substâncias com uma maior influência potencial no funcionamento da Estação de Tratamento Biológico. O encolante CB, Cera Têxtil P Líquida, Perfemina P-12, Meropan DPE-P, Meropan BRE-P, Indimina STS e Benzym TEC são os produtos químicos que têm uma influência potencial mais significativa na qualidade dos efluentes. Devido ao facto das temperaturas do efluente alimentado ao tratamento biológico da Mundotêxtil oscilarem entre 35 ºC e 43ºC efectuou-se um estudo às necessidades de água quente das tinturarias e por outro lado à capacidade de aquecimento dos efluentes disponíveis. Actualmente a racionalização dos consumos de água é cada vez mais premente, por isso também é apresentado neste trabalho um estudo para a substituição das máquinas convencionais das tinturarias com uma relação de banho 1:10 por máquinas de banho curto (1:6,5). Verifica-se a redução de consumos de 40% de água, 52% de energia eléctrica, 35% de produtos químicos, 51% das necessidades de vapor e por consequência um aumento da produtividade. A empresa pode reduzir os consumos de água em cerca de 280.000 m3/ano. A utilização do pré-tratamento com o coagulante permitirá baixar a concentração da CQO e reduzir a cor à entrada do reactor tratamento biológico. Deste modo é possível manter um tratamento eficiente à saída do tratamento biológico nas situações de descarga de cores carregadas e carga orgânica elevada. Com este conjunto de soluções, quer sejam aplicadas na totalidade ou não, a empresa Mundotêxtil pode enfrentar o futuro com mais confiança podendo estar preparada para fazer face à escassez de água e custos cada vez maiores da energia. Por outro lado pode tratar os seus efluentes a custos menores. A substituição das máquinas de tingimento por máquinas com relação de banho mais baixa (banho curto) implica investimentos elevados mas estes investimentos são necessários não só por motivos ambientais mas também devido à grande competitividade dos mercados.