S/MIMO MC-CDMA Heuristic Multiuser Detectors Based on Single-Objective Optimization

This paper analyzes the complexity-performance trade-off of several heuristic near-optimum multiuser detection (MuD) approaches applied to the uplink of synchronous single/multiple-input multiple-output multicarrier code division multiple access (S/MIMO MC-CDMA) systems. Genetic algorithm (GA), short term tabu search (STTS) and reactive tabu search (RTS), simulated annealing (SA), particle swarm optimization (PSO), and 1-opt local search (1-LS) heuristic multiuser detection algorithms (Heur-MuDs) are analyzed in details, using a single-objective antenna-diversity-aided optimization approach. Monte- Carlo simulations show that, after convergence, the performances reached by all near-optimum Heur-MuDs are similar. However, the computational complexities may differ substantially, depending on the system operation conditions. Their complexities are carefully analyzed in order to obtain a general complexity-performance framework comparison and to show that unitary Hamming distance search MuD (uH-ds) approaches (1-LS, SA, RTS and STTS) reach the best convergence rates, and among them, the 1-LS-MuD provides the best trade-off between implementation complexity and bit error rate (BER) performance.

Assessing the competitiveness of loss allocation methods in a deregulated electricity market

This paper critically assesses several loss allocation methods based on the type of competition each method promotes. This understanding assists in determining which method will promote more efficient network operations when implemented in deregulated electricity industries. The methods addressed in this paper include the pro rata [1], proportional sharing [2], loss formula [3], incremental [4], and a new method proposed by the authors of this paper, which is loop-based [5]. These methods are tested on a modified Nordic 32-bus network, where different case studies of different operating points are investigated. The varying results obtained for each allocation method at different operating points make it possible to distinguish methods that promote unhealthy competition from those that encourage better system operation.

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

A hybrid planning method for transmission networks in a deregulated environment

The reconstruction of power industries has brought fundamental changes to both power system operation and planning. This paper presents a new planning method using multi-objective optimization (MOOP) technique, as well as human knowledge, to expand the transmission network in open access schemes. The method starts with a candidate pool of feasible expansion plans. Consequent selection of the best candidates is carried out through a MOOP approach, of which multiple objectives are tackled simultaneously, aiming at integrating the market operation and planning as one unified process in context of deregulated system. Human knowledge has been applied in both stages to ensure the selection with practical engineering and management concerns. The expansion plan from MOOP is assessed by reliability criteria before it is finalized. The proposed method has been tested with the IEEE 14-bus system and relevant analyses and discussions have been presented.

Stability Condition Based Sliding Mode Modulators for Multilevel Power Converters

Sliding mode controllers for power converters usually employ hysteresis comparators to directly generate the power semiconductors switching states. This paper presents a new sliding mode modulator based on the direct implementation of the sliding mode stability condition, which for multilevel power converters shows advantages, as branch equalized switching frequencies and less distortion on the ac currents when operating near the rated converter power. The new sliding mode multilevel modulator is used to control a three-phase multilevel converter, operated as a reactive power compensator (STATCOM), implementing the stability condition in a digital signal processing system. The performance of this new sliding mode modulator is compared with a multilevel modulator based on hysteresis comparators. Simulation and experimental results are presented in order to highlight the system operation and control robustness.

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.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Data mining applications in power systems - case-studies and future trends

Presently power system operation produces huge volumes of data that is still treated in a very limited way. Knowledge discovery and machine learning can make use of these data resulting in relevant knowledge with very positive impact. In the context of competitive electricity markets these data is of even higher value making clear the trend to make data mining techniques application in power systems more relevant. This paper presents two cases based on real data, showing the importance of the use of data mining for supporting demand response and for supporting player strategic behavior.

Estudo da eficiência de sistemas fotovoltaicos

Mestrado em Engenharia Química. Ramo optimização energética na indústria química

Avaliação de qualidade de energia de um sistema fotovoltaico numa rede elétrica

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Energy resource management in smart grids considering an Intensive use of electric vehicles

The introduction of electricity markets and integration of Distributed Generation (DG) have been influencing the power system’s structure change. Recently, the smart grid concept has been introduced, to guarantee a more efficient operation of the power system using the advantages of this new paradigm. Basically, a smart grid is a structure that integrates different players, considering constant communication between them to improve power system operation and management. One of the players revealing a big importance in this context is the Virtual Power Player (VPP). In the transportation sector the Electric Vehicle (EV) is arising as an alternative to conventional vehicles propel by fossil fuels. The power system can benefit from this massive introduction of EVs, taking advantage on EVs’ ability to connect to the electric network to charge, and on the future expectation of EVs ability to discharge to the network using the Vehicle-to-Grid (V2G) capacity. This thesis proposes alternative strategies to control these two EV modes with the objective of enhancing the management of the power system. Moreover, power system must ensure the trips of EVs that will be connected to the electric network. The EV user specifies a certain amount of energy that will be necessary to charge, in order to ensure the distance to travel. The introduction of EVs in the power system turns the Energy Resource Management (ERM) under a smart grid environment, into a complex problem that can take several minutes or hours to reach the optimal solution. Adequate optimization techniques are required to accommodate this kind of complexity while solving the ERM problem in a reasonable execution time. This thesis presents a tool that solves the ERM considering the intensive use of EVs in the smart grid context. The objective is to obtain the minimum cost of ERM considering: the operation cost of DG, the cost of the energy acquired to external suppliers, the EV users payments and remuneration and penalty costs. This tool is directed to VPPs that manage specific network areas, where a high penetration level of EVs is expected to be connected in these areas. The ERM is solved using two methodologies: the adaptation of a deterministic technique proposed in a previous work, and the adaptation of the Simulated Annealing (SA) technique. With the purpose of improving the SA performance for this case, three heuristics are additionally proposed, taking advantage on the particularities and specificities of an ERM with these characteristics. A set of case studies are presented in this thesis, considering a 32 bus distribution network and up to 3000 EVs. The first case study solves the scheduling without considering EVs, to be used as a reference case for comparisons with the proposed approaches. The second case study evaluates the complexity of the ERM with the integration of EVs. The third case study evaluates the performance of scheduling with different control modes for EVs. These control modes, combined with the proposed SA approach and with the developed heuristics, aim at improving the quality of the ERM, while reducing drastically its execution time. The proposed control modes are: uncoordinated charging, smart charging and V2G capability. The fourth and final case study presents the ERM approach applied to consecutive days.

Análise técnica e económico-financeira de um sistema de abastecimento de veículos zero emissões integrando um sistema fotovoltaico

Com o aumento da população mundial registado nos últimos anos surgiu também uma maior procura energética. Esse aumento foi inicialmente colmatado recorrendo essencialmente a fontes de origem fóssil, pelo facto destas serem mais baratas. No entanto, essa tendência de preços baixos sofreu o primeiro abalo nos anos 70 do século passado, altura em que o preço do petróleo disparou, devido a questões políticas. Nessa altura ficou visível para os países ocidentais o quanto estes eram dependentes dos países produtores de petróleo que, em geral, são instáveis politicamente. Começou então a procura de fontes energéticas alternativas. Além da questão económica do aumento do preço dos combustíveis, existe também o problema ambiental. Os maiores responsáveis pela emissão de gases efeito estufa (GEE) são os combustíveis fósseis. Os GEE contribuem para o aquecimento global, o que origina fenómenos ambientais severos que poderão levar a mudanças climáticas significativas. As energias renováveis apresentam-se como a solução mais viável ao problema energético e ambiental que se verifica actualmente, porque permitem colmatar o aumento da procura energética de uma forma limpa e sustentável. Na sequência destes problemas surgiram nos últimos anos veículos que permitem reduzir ou mesmo eliminar o consumo de combustíveis fósseis, como os veículos híbridos eléctricos, eléctricos e a hidrogénio. Nesta dissertação analisa-se um sistema que foi pensado para ser implementado em áreas de serviço, que permite efectuar o carregamento de electric vehicles (EV) utilizando energia eléctrica de origem fotovoltaica e a produção de hidrogénio para os fuels cell electric vehicles (FCEV). É efectuada uma análise económica do sistema, uma análise ambiental e analisou-se também o impacto na redução da dependência do país em relação ao exterior, sendo ainda efectuada uma pequena análise ao sistema MOBIE. No caso dos veículos a hidrogénio, foi determinada qual seria a melhor opção em termos económicos, para a produção de hidrogénio considerando três regimes de produção: recorrendo apenas à energia eléctrica proveniente do sistema fotovoltaico, apenas à energia eléctrica da rede, ou uma combinação dos dois regimes. O sistema estudado nesta dissertação apresenta um enorme potencial a nível energético e ambiental, surgindo como alternativa para abastecer os veículos que irão permitir, no futuro, eliminar a dependência energética em relação às fontes fósseis e ao mesmo tempo diminuir a quantidade de gases efeito estufa emitidos para a atmosfera.

Projeto e implementação de um protótipo para microprodução de energia elétrica destinado a alimentar um sistema de iluminação decorativa exterior

Com o presente trabalho é pretendido demonstrar a possibilidade de alimentação de um sistema de iluminação decorativa com recurso a soluções alternativas renováveis. O estudo é focado essencialmente na produção local de energia solar fotovoltaica e eólica. Inicialmente é efetuado o estudo técnico-económico da implementação de um sistema fotovoltaico. Posteriormente é efetuado o estudo da viabilidade técnico-económica da implementação do sistema hibrido, composto por um sistema fotovoltaico e um sistema eólico, optando pelo que mais se adequa à alimentação do sistema de iluminação decorativa exterior. Esta dissertação descreve a metodologia que procura melhorar a eficiência do sistema de led com o auxílio de ensaios em laboratório e simulação em software, com o objetivo de adaptar os sistemas de led instalados pela empresa ao sistema hibrido dimensionado. Finalmente, é efetuada a análise comparativa entre o atual sistema de iluminação decorativa e o sistema renovável dimensionado mais favorável para alimentar sistemas de iluminação decorativa. Procura-se assim com este projeto para além de apresentar um estudo teórico, proporcionar uma orientação à implementação de sistemas de microprodução destinados a alimentar sistemas de iluminação decorativa exterior.

Implementação do TFM na Sakthi Portugal com recurso à metodologia Kaizen

No âmbito da unidade curricular Dissertação/Projeto/Estágio do 2ºano do Mestrado em Engenharia mecânica – Ramo Gestão Industrial do Instituto Superior de Engenharia do Porto, o presente trabalho de dissertação foi enquadrado num projeto industrial de melhoria com Instituto Kaizen, empresa de consultoria operacional. O projeto foi desenvolvido numa empresa de produção de componentes em ferro nodular destinados à indústria automóvel do mercado europeu, a Sakthi Portugal,SA. A realização deste projeto teve como objetivo a implementação do sistema de planeamento em Pull (produção puxada) na logística interna da Sakthi Portugal,SA recorrendo à metodologia Kaizen. Esta metodologia consiste na aplicação de ferramentas de TFM - Total Flow Management, integradas no Kaizen Management System. Neste projeto recorreu-se especialmente a um dos pilares que o constituem, o pilar do “Fluxo da Logística Interna”. Neste pilar encontram-se as várias metodologias utilizadas na otimização do fluxo de material e informação na logística interna. Estas metodologias foram aplicadas, com o objetivo do sistema produtivo operar de acordo com a necessidade do cliente, obtendo deste modo a minimização dos custo e o aumento da produtividade e qualidade. Em resultado da aplicação da metodologia seguida, foi possível atingir-se os objetivos definidos inicialmente e em alguns casos foi possível superar esses objetivos. Em função da abordagem integrada que foi seguida, conseguiu-se uma diminuição do “lead time” do processo de fabrico, redução dos produtos em curso de fabrico, libertação de espaço e redução de inventários. Estas melhorias resultaram numa movimentação interna na fábrica mais facilitada e num aumento global da produtividade. Como consequência positiva dos efeitos deste trabalho, pode-se apontar o facto de que a Sakthi Portugal SA aumentou a sua competitividade por tornar-se numa empresa mais dinâmica, mais adaptada ao mercado e com níveis de satisfação do cliente muito superiores.