Uso Sustentável de Vapor

Em 2006, a IEA (Agência Internacional de Energia), publicou alguns estudos de consumos mundiais de energia. Naquela altura, apontava na fabricação de produtos, um consumo mundial de energia elétrica, de origem fóssil de cerca 86,16 EJ/ano (86,16×018 J) e um consumo de energia nos sistemas de vapor de 32,75 EJ/ano. Evidenciou também nesses estudos que o potencial de poupança de energia nos sistemas de vapor era de 3,27 EJ/ano. Ou seja, quase tanto como a energia consumida nos sistemas de vapor da U.E. Não se encontraram números relativamente a Portugal, mas comparativamente com outros Países publicitados com alguma similaridade, o consumo de energia em vapor rondará 0,2 EJ/ano e por conseguinte um potencial de poupança de cerca 0,02 EJ/ano, ou 5,6 × 106 MWh/ano ou uma potência de 646 MW, mais do que a potência de cinco barragens Crestuma/Lever! Trata-se efetivamente de muita energia; interessa por isso perceber o onde e o porquê deste desperdício. De um modo muito modesto, pretende-se com este trabalho dar algum contributo neste sentido. Procurou-se evidenciar as possibilidades reais de os utilizadores de vapor de água na indústria reduzirem os consumos de energia associados à sua produção. Não estão em causa as diferentes formas de energia para a geração de vapor, sejam de origem fóssil ou renovável; interessou neste trabalho estudar o modo de como é manuseado o vapor na sua função de transporte de energia térmica, e de como este poderá ser melhorado na sua eficiência de cedência de calor, idealmente com menor consumo de energia. Com efeito, de que servirá se se optou por substituir o tipo de queima para uma mais sustentável se a jusante se continuarem a verificarem desperdícios, descarga exagerada nas purgas das caldeiras com perda de calor associada, emissões permanentes de vapor para a atmosfera em tanques de condensado, perdas por válvulas nos vedantes, purgadores avariados abertos, pressão de vapor exageradamente alta atendendo às temperaturas necessárias, “layouts” do sistema de distribuição mal desenhados, inexistência de registos de produção e consumos de vapor, etc. A base de organização deste estudo foi o ciclo de vapor: produção, distribuição, consumo e recuperação de condensado. Pareceu importante incluir também o tratamento de água, atendendo às implicações na transferência de calor das superfícies com incrustações. Na produção de vapor, verifica-se que os maiores problemas de perda de energia têm a ver com a falta de controlo, no excesso de ar e purgas das caldeiras em exagero. Na distribuição de vapor aborda-se o dimensionamento das tubagens, necessidade de purgas a v montante das válvulas de controlo, a redução de pressão com válvulas redutoras tradicionais; será de destacar a experiência americana no uso de micro turbinas para a redução de pressão com produção simultânea de eletricidade. Em Portugal não se conhecem instalações com esta opção. Fabricantes da República Checa e Áustria, têm tido sucesso em algumas dezenas de instalações de redução de pressão em diversos países europeus (UK, Alemanha, R. Checa, França, etc.). Para determinação de consumos de vapor, para projeto ou mesmo para estimativa em máquinas existentes, disponibiliza-se uma série de equações para os casos mais comuns. Dá-se especial relevo ao problema que se verifica numa grande percentagem de permutadores de calor, que é a estagnação de condensado - “stalled conditions”. Tenta-se também evidenciar as vantagens da recuperação de vapor de flash (infelizmente de pouca tradição em Portugal), e a aplicação de termocompressores. Finalmente aborda-se o benchmarking e monitorização, quer dos custos de vapor quer dos consumos específicos dos produtos. Esta abordagem é algo ligeira, por manifesta falta de estudos publicados. Como trabalhos práticos, foram efetuados levantamentos a instalações de vapor em diversos sectores de atividades; 1. ISEP - Laboratório de Química. Porto, 2. Prio Energy - Fábrica de Biocombustíveis. Porto de Aveiro. 3. Inapal Plásticos. Componentes de Automóvel. Leça do Balio, 4. Malhas Sonix. Tinturaria Têxtil. Barcelos, 5. Uma instalação de cartão canelado e uma instalação de alimentos derivados de soja. Também se inclui um estudo comparativo de custos de vapor usado nos hospitais: quando produzido por geradores de vapor com queima de combustível e quando é produzido por pequenos geradores elétricos. Os resultados estão resumidos em tabelas e conclui-se que se o potencial de poupança se aproxima do referido no início deste trabalho.

Gestão de Recursos Energéticos para Apoio à Operação dos Virtual Power Players

A liberalização dos mercados de energia elétrica e a crescente integração dos recursos energéticos distribuídos nas redes de distribuição, nomeadamente as unidades de produção distribuída, os sistemas de controlo de cargas através dos programas de demand response, os sistemas de armazenamento e os veículos elétricos, representaram uma evolução no paradigma de operação e gestão dos sistemas elétricos. Este novo paradigma de operação impõe o desenvolvimento de novas metodologias de gestão e controlo que permitam a integração de todas as novas tecnologias de forma eficiente e sustentável. O principal contributo deste trabalho reside no desenvolvimento de metodologias para a gestão de recursos energéticos no contexto de redes inteligentes, que contemplam três horizontes temporais distintos (24 horas, 1 hora e 5 minutos). As metodologias consideram os escalonamentos anteriores assim como as previsões atualizadas de forma a melhorar o desempenho total do sistema e consequentemente aumentar a rentabilidade dos agentes agregadores. As metodologias propostas foram integradas numa ferramenta de simulação, que servirá de apoio à decisão de uma entidade agregadora designada por virtual power player. Ao nível das metodologias desenvolvidas são propostos três algoritmos de gestão distintos, nomeadamente para a segunda (1 hora) e terceira fase (5 minutos) da ferramenta de gestão, diferenciados pela influência que os períodos antecedentes e seguintes têm no período em escalonamento. Outro aspeto relevante apresentado neste documento é o teste e a validação dos modelos propostos numa plataforma de simulação comercial. Para além das metodologias propostas, a aplicação permitiu validar os modelos dos equipamentos considerados, nomeadamente, ao nível das redes de distribuição e dos recursos energéticos distribuidos. Nesta dissertação são apresentados três casos de estudos, cada um com diferentes cenários referentes a cenários de operação futuros. Estes casos de estudos são importantes para verificar a viabilidade da implementação das metodologias e algoritmos propostos. Adicionalmente são apresentadas comparações das metodologias propostas relativamente aos resultados obtidos, complexidade de gestão em ambiente de simulação para as diferentes fases da ferramenta proposta e os benefícios e inconvenientes no uso da ferramenta proposta.

The use of solar colletor for heating and electricity for a single family house

The presented work is related to the use of solar energy for the needs of heating and electricity for a single house located in Poland. Electricity will provided by energy conversion in the turbine by means of Organic Rankine Cycle (ORC), in which the operating medium (water heated in solar collector) is heating refrigerator in the heating exchanger. The solar installation is integrated with heat accumulator and wood boiler, which is used in the situation that collector is not enough to fill requirements of thermal comfort. There are chosen also all the necessary components of the system. In the work is also performed the economic assessment, by F chart method, to evaluate the profitability of the project, taking into total costs and savings.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

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.

Dynamic artificial neural network for electricity market prices forecast

This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

Energy efficiency analysis considering the use of an intelligent systems management in a smart home

In this abstract is presented an energy management system included in a SCADA system existent in a intelligent home. The system control the home energy resources according to the players definitions (electricity consumption and comfort levels), the electricity prices variation in real time mode and the DR events proposed by the aggregators.

A decision-support system based on particle swarm optimization for multiperiod hedging in electricity markets

This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, 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.

ANN based day-ahead spinning reserve forecast for electricity market simulation

Electricity market players operating in a liberalized environment require adequate decision support tools, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. This paper deals with short-term predication of day-ahead spinning reserve (SR) requirement that helps the ISO to make effective and timely decisions. Based on these forecasted information, market participants can use strategic bidding for day-ahead SR market. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Demsi - a demand response simulator in the context of intensive use of distributed generation

Demand response can play a very relevant role in future power systems in which distributed generation can help to assure service continuity in some fault situations. This paper deals with the demand response concept and discusses its use in the context of competitive electricity markets and intensive use of distributed generation. The paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes using a realistic network simulation based on PSCAD. Demand response opportunities are used in an optimized way considering flexible contracts between consumers and suppliers. A case study evidences the advantages of using flexible contracts and optimizing the available generation when there is a lack of supply.

Auction of financial transmission rights in electricity market environment

An auction model is used to increase the individual profits for market players with products they do not use. A Financial Transmission Rights Auction has the goal of trade transmission rights between Bidders and helps them raise their own profits. The ISO plays a major rule on keep the system in technical limits without interfere on the auctions offers. In some auction models the ISO decide want bids are implemented on the network, always with the objective maximize the individual profits for all bidders in the auction. This paper proposes a methodology for a Financial Transmission Rights Auction and an informatics application. The application receives offers from the purchase and sale side and considers bilateral contracts as Base Case. This goal is maximize the individual profits within the system in their technical limits. The paper includes a case study for the 30 bus IEEE test case.

ANN based day-ahead ancillary services forecast for electricity market simulation

Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

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.