Abstract

This paper presents two gradient algorithms applied to the economic optimization of reinforced concrete vaults, typically used in the construction of underpasses. The algorithms are gradient multi start neighbourhood exhaustive search procedures. The vault is defined by 45 design variables and the objective function is an economic one. Both methods have been applied to a vault of 12.40 m of diameter and 3.00 m of lateral walls. Design variables have been coded in base 2 for algorithms GB1 and in Gray coding for GB2. The neighbourhood is defined by the set of solutions that differ in one bit. The Gray coding solves the lack of proximity between two solutions typical of the ordinary binary coding. The positive effect of the Gray coding is proven in the present paper, where the average cost of 3, 000 runs of GB2 improves by 3.81% a similar run by algorithm GB1. In addition, GB2 attains the best cost solution. The paper includes a stop criterion for the algorithm based on the stability of the statistics of the multi start results. The algorithms are simple and can be applied to other structural problems. The structure of best cost has a high slenderness and a span to depth ratio of 40. The study reports savings of 6% when compared to a design by an experienced practitioner office.

Abstract

This paper deals with the minimum cost automatic design of precast bridge decks made of U-beams and an upper slab. It uses a hybrid memetic algorithm that combines the population search of solutions by genetic algorithms and a search by variable neighborhood. This algorithm is applied to a bridge made of two isostatic U-beams of 20-40 m of span and a width of 12 m. This example has 40 discrete variables. The evaluation module takes into account the service and ultimate limit states usually considered for these structures, i.e. flexure, shear, torsion, cracking, deflections, etc. The use of the memetic algorithm requires its previous calibration. Each of the heuristics is run 12 times, obtaining information about the minimum and average values, as well as the scatter. The parametric study showed a good correlation for the cost, the number of strands and the steel and concrete quantities with the span length. Savings have been found between 8 and 50% compared to other structures really executed. The presented procedure allows the practical application to the real design and its adaptation to the precast process.

Abstract

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. A introdução dos mercados de electricidade e integração da produção distribuída tem causado alterações na estrutura e no modo de operação dos sistemas eléctricos de energia. Recentemente, o conceito de SmartGrid foi introduzido com o objectivo de garantir uma operação mais eficiente dos sistemas eléctricos de energia. Basicamente, uma SmartGrid é uma estrutura que envolve as diferentes entidades, e considera uma constante interacção e comunicação entre as mesmas, para melhorar a operação do sistema eléctrico de energia. Umas das entidades com grande relevância neste contexto são os Virtual Power Players (VPP). Os Veículos Eléctricos (VE) têm surgido no sector dos transportes como uma alternativa aos veículos convencionais abastecidos por combustíveis fósseis. O sistema eléctrico de energia pode beneficiar dessa introdução massiva de VEs, aproveitando a sua capacidade de ligação à rede eléctrica para a carga dos veículos, e numa perspectiva mais vanguardista para descarga, fornecendo energia à rede. Nesta tese são propostas estratégias de gestão das cargas/descargas do VE com o objectivo de melhorar a operação do sistema eléctrico de energia. No processo de gestão de recursos, o operador da rede ou agregadores deverão considerar as necessidades dos utilizadores dos VEs, nomeadamente garantir a existência de energia suficiente nas baterias para que os utilizadores possam efectuar as viagens que tem programadas. A introdução dos veículos eléctricos nos sistemas eléctricos de energia torna a gestão de recurso energéticos num ambiente de SmartGrid, um problema complexo que pode levar vários minutos ou horas para se obter uma solução. Considerando o período para o qual é necessário efectuar o escalonamento, que normalmente é para o dia seguinte ou para os 15 minutos seguintes no caso de escalonamento em tempo real, é necessário desenvolver algoritmos que permitam a resolução dos problemas em tempos muito razoáveis. Nesta tese é apresentada uma ferramenta que permite a resolução do problema do escalonamento de recursos, considerando o uso intensivo de VEs no contexto das SmartGrid. O objectivo é obter o custo mínimo de operação, considerando: o custo de operação da produção distribuída, o custo da energia adquirida a fornecedores externos, a remuneração do uso de VEs e os custos associados ao incumprimento de condições contratuais. A ferramenta desenvolvida é direccionada para a utilização pelos VPPs que gerem áreas de rede específicas, com um nível de penetração elevado de VEs. O escalonamento de recursos é resolvido usando duas metodologias: a adaptação de uma técnica determinista proposta em trabalhos anteriores, e a adaptação da técnica de Simulated Annealing, sendo propostas três abordagens para melhorar a solução obtida através da técnica de Simulated Annealing. Diversos casos de estudo são apresentados, considerando uma rede de distribuição com 32 barramentos e cenários de evolução da penetração de VE até 3000 veículos. O primeiro caso de estudo, usado como um caso de referência para comparações com as abordagens propostas, resolve o escalonamento de recursos sem considerar VEs. O segundo caso avalia a complexidade do escalonamento de recursos com a integração de VEs, permitindo testar as técnicas propostas. O terceiro caso avalia o desempenho do escalonamento com diferentes modos de controlo de EVs. O quarto caso de estudo apresenta a abordagem aplicada ao escalonamento de recursos em diversos dias consecutivos.