Este trabalho trata da avaliação dos impactos que os múltiplos usos da água causam à operação dos reservatórios de uma bacia hidrográfica para a geração de energia elétrica. Apresenta-se o equacionamento do modelo HIDRO, desenvolvido em linguagem GAMS para tratamento de problemas de otimização em Programação Não Linear, cuja função objetivo inclui variáveis relacionadas não somente à geração de energia, como também ao fornecimento de água aos diversos usos do recurso hídrico tratados no problema. A aplicação do modelo é feita para a bacia do rio São Francisco, localizada entre as regiões Sudeste e Nordeste do Brasil, que conta com uma capacidade instalada de 10,7 GW em suas usinas hidrelétricas, as quais também realizam operações de controle de cheia. A região apresenta um expressivo uso consuntivo do recurso hídrico, principalmente voltado à irrigação de culturas, além de abastecimento humano e criação animal. Dentre os usos não consuntivos, têm-se a navegação e a conservação ambiental. Uma vez que grande parte da bacia é marcada por escassez hídrica, a operação de seu sistema de reservatórios vem sendo questionada no que se refere ao gerenciamento dos recursos hídricos. São avaliados os índices de atendimento da demanda de energia e da demanda hídrica para cenários de baixa afluência aos reservatórios. As relações de troca entre energia, uso consuntivo e conservação ambiental são avaliadas, levando-se em conta, também, os efeitos decorrentes da transposição das águas do São Francisco para o Nordeste Setentrional. As perdas na geração de energia decorrentes do aumento da demanda hídrica e do aumento da demanda ambiental são avaliadas. São estimados os custos relacionados às perdas na geração de energia se as demandas consuntivas atingirem o valor outorgado na bacia pelo Poder Público, valor este que não consegue ser plenamente atendido. O modelo proposto pode ser aplicado a quaisquer bacias hidrográficas com múltiplos usos do recurso hídrico. / This research presents a study conducted to evaluate the impacts of the hydroelectric power plants operation caused by the multipurpose uses of water resources. There are many conflicts involved in the operation of a reservoir system mainly due to competitive uses of water. That is the case of São Francisco River, located between the Southeast and Northeast regions of Brazil. The hydro system in this region has an installed capacity of 10.7 GW and supports 13% of the Brazilian hydro electrical power. Due to the scarcity of water in this region, the operation of this system has been questioned in the last few years. The competitive uses of water in this region are water supply, irrigation and animal raising. The non-consumptive uses of water are navigation and environmental protection. The electrical sector is planning to review the reservoir operation rules in order to attend these demands. The study was conducted by applying the HIDRO model, which is an optimization PNL model developed with GAMS software that maximizes hydropower production. A new objective function was added to the HIDRO model in order to consider the treatment of energy and water demands the both. The trade-offs among energy, consumptive uses and environment protection are presented. The lack of energy due the increasing water demand implies costs which are evaluated according to some demand scenarios and different scarcity historical periods. Also the effect due the operation of the water transfer system from São Francisco to the neighboring basins is considered.

Este trabalho trata da avaliação dos impactos que os múltiplos usos da água causam à operação dos reservatórios de uma bacia hidrográfica para a geração de energia elétrica. Apresenta-se o equacionamento do modelo HIDRO, desenvolvido em linguagem GAMS para tratamento de problemas de otimização em Programação Não Linear, cuja função objetivo inclui variáveis relacionadas não somente à geração de energia, como também ao fornecimento de água aos diversos usos do recurso hídrico tratados no problema. A aplicação do modelo é feita para a bacia do rio São Francisco, localizada entre as regiões Sudeste e Nordeste do Brasil, que conta com uma capacidade instalada de 10,7 GW em suas usinas hidrelétricas, as quais também realizam operações de controle de cheia. A região apresenta um expressivo uso consuntivo do recurso hídrico, principalmente voltado à irrigação de culturas, além de abastecimento humano e criação animal. Dentre os usos não consuntivos, têm-se a navegação e a conservação ambiental. Uma vez que grande parte da bacia é marcada por escassez hídrica, a operação de seu sistema de reservatórios vem sendo questionada no que se refere ao gerenciamento dos recursos hídricos. São avaliados os índices de atendimento da demanda de energia e da demanda hídrica para cenários de baixa afluência aos reservatórios. As relações de troca entre energia, uso consuntivo e conservação ambiental são avaliadas, levando-se em conta, também, os efeitos decorrentes da transposição das águas do São Francisco para o Nordeste Setentrional. As perdas na geração de energia decorrentes do aumento da demanda hídrica e do aumento da demanda ambiental são avaliadas. São estimados os custos relacionados às perdas na geração de energia se as demandas consuntivas atingirem o valor outorgado na bacia pelo Poder Público, valor este que não consegue ser plenamente atendido. O modelo proposto pode ser aplicado a quaisquer bacias hidrográficas com múltiplos usos do recurso hídrico. / This research presents a study conducted to evaluate the impacts of the hydroelectric power plants operation caused by the multipurpose uses of water resources. There are many conflicts involved in the operation of a reservoir system mainly due to competitive uses of water. That is the case of São Francisco River, located between the Southeast and Northeast regions of Brazil. The hydro system in this region has an installed capacity of 10.7 GW and supports 13% of the Brazilian hydro electrical power. Due to the scarcity of water in this region, the operation of this system has been questioned in the last few years. The competitive uses of water in this region are water supply, irrigation and animal raising. The non-consumptive uses of water are navigation and environmental protection. The electrical sector is planning to review the reservoir operation rules in order to attend these demands. The study was conducted by applying the HIDRO model, which is an optimization PNL model developed with GAMS software that maximizes hydropower production. A new objective function was added to the HIDRO model in order to consider the treatment of energy and water demands the both. The trade-offs among energy, consumptive uses and environment protection are presented. The lack of energy due the increasing water demand implies costs which are evaluated according to some demand scenarios and different scarcity historical periods. Also the effect due the operation of the water transfer system from São Francisco to the neighboring basins is considered.

Submitted by Lucienne Costa (lucienneferreira@ufcg.edu.br) on 2018-04-16T21:10:17Z No. of bitstreams: 1 DÁTIA PAULA MARQUES MAIA LUCENA – DISSERTAÇÃO (PPGECA) 2018.pdf: 1669662 bytes, checksum: e6aeed62df7d854d9943d6f2cf6efe3e (MD5) / Made available in DSpace on 2018-04-16T21:10:17Z (GMT). No. of bitstreams: 1 DÁTIA PAULA MARQUES MAIA LUCENA – DISSERTAÇÃO (PPGECA) 2018.pdf: 1669662 bytes, checksum: e6aeed62df7d854d9943d6f2cf6efe3e (MD5) Previous issue date: 2018-02-28 / CNPq / Reservatórios localizados em regiões semiáridas apresentam alta variabilidade nas afluências hídricas, baixas vazões de regularização, comparadas a outros em climas mais úmidos, e são sujeitos a grandes perdas por evaporação, principalmente quando cheios, fazendo com que a gestão efetiva dos mesmos seja de extrema importância. Este trabalho mostra como modelos matemáticos podem ser utilizados como ferramenta de apoio a tomada de decisão na operação de reservatórios e como medidas de gestão podem afetar situações de racionamento e crise hídrica. O caso de estudo dessa pesquisa é o reservatório Epitácio Pessoa (Boqueirão), localizado em Campina Grande-PB, semiárido brasileiro. O açude Boqueirão recentemente enfrentou a maior crise hídrica desde sua construção, uma gestão não otimizada pode ser apontada como uma das causas do agravamento dessa crise hídrica. É proposta uma metodologia que consiste na definição de oito cenários, compostos por ações ou conjunto de ações que poderiam ter sido tomadas em relação à gestão hídrica do manancial. Dentre o conjunto de ações propostas, tem-se ações meramente gerenciais e outras que envolvem a utilização de técnicas de redução de perdas por evaporação. Tais cenários foram simulados no modelo matemático AcquaNet, para um período de 63 meses, para analisar qual ação teria sido a mais benéfica para a população, e como cada conjunto de ações poderiam ter impactado, quantitativamente, a questão do racionamento em Campina Grande e região. Para fazer a análise e comparação desses cenários, foram utilizados índices de sustentabilidade (confiabilidade, resiliência e vulnerabilidade), bem como os valores dos volumes finais do reservatório e atendimento médio à demanda em cada cenário. A partir destes, foram feitas as comparações entre os cenários para identificação das medidas que causaram maior impacto no sistema. Os resultados encontrados demonstraram que as medidas que incluíram a adoção de técnicas de redução de evaporação na bacia hidráulica do reservatório poderiam ter evitado completamente a adoção do severo racionamento a que a população foi submetida por um longo período de tempo. Adicionalmente, fica demonstrado que modelos matemáticos de simulação podem ser muito úteis na tomada decisão quanto a gestão de reservatórios em épocas de escassez hídrica, principalmente em regiões de clima árido ou semiárido. / Reservoirs located in semi-arid regions present high hydrological variability, low regularization flows, compared to others in more humid climates, and are subject to large evaporation losses, mainly in their periods of high water levels, making their effective management extremely important. This article aims to show how mathematical models can be used as a tool to support decision-making process in the operation of reservoirs and how management measures can affect rationing and water crises. The case study of this research is the Epitacio Pessoa Reservoir (also called Boqueirão), located in the city of Campina Grande-PB, Brazilian semiarid region. The Boqueirão went through the biggest water crisis since its construction, a non-optimized management of these resources can be pointed as one of the causes of these water crisis aggravation. It is proposed a methodology that consists in the definition of eight scenarios, composed by actions or set of actions that could have been taken regarding to the water management of this reservoir during that period. Among the set of actions proposed, there are managing actions and others involving the use of techniques to reduce evaporation losses. The scenarios were simulated with the mathematical model AcquaNet, for a period of 63 months, in order to analyze which action would have been the most beneficial for the population, and how each set of actions could have, quantitatively, affected the water shortage issue in Campina Grande and region. Sustainability indexes (reliability, resilience and vulnerability), reservoir final volumes and average meeting of the water demand requirements, were used to analyze and compare the scenarios. From these results, comparisons were made among the scenarios to identify the measures that would have caused the greatest impact on the system. The results pointed out that measures which included the use of evaporation rates reduction techniques in the reservoir’s hydraulic basin could have completely avoided the adoption of severe rationing to which the population was submitted for a long time. In addition, it is demonstrated that mathematical simulation models can be useful in decision-making processes regarding the management of reservoirs in a water scarcity situation, especially in arid or semi-arid climate regions.

O presente trabalho apresenta um modelo geral de simulação em tempo real de operação de reservatórios que trabalha como parte de um sistema de suporte à decisão, fornecendo informações sobre as disponibilidades hídricas do sistema de múltiplos reservatórios, em função de restrições vinculadas aos volumes armazenados. Este modelo é composto de duas partes: um software de pré-processamento, escrito em linguagem Python, que constrói os arquivos de entrada do programa principal, e um software responsável pela simulação da operação de um sistema de reservatórios (OperRes), escrito parte em Python e parte em Fortran. O modelo é aplicado à bacia do rio Paraguaçu localizada no estado da Bahia. A bacia apresenta como principal reservatório o açude formado pela barragem de Pedra do Cavalo, que é responsável pela maior parte do abastecimento da cidade de Salvador e região metropolitana. A aplicação do modelo é feita com o objetivo de se verificar a sua adequação à região em estudo, através da comparação dos dados reais com os resultados das simulações. Também é feita a simulação da operação dos treze açudes representados no sistema para se obter o resultado do seu comportamento durante um período de sete meses de estiagem. / This work shows a general simulation model of reservoirs operation to be run in real time working as part of a decision support system, which is supposed to give information about water availability in the reservoir system. This model is built in two parts: a pre-processing software, written in Python language, which builds the data files of the main program, and another software dedicated to the simulation of the reservoir system operation (OperRes) written in Python and Fortran languages. The model is applied to the Paraguaçu river basin, at Bahia State, Brazil. Pedra do Cavalo Dam is the basin main reservoir, which is responsible for most of Salvador city and metropolitan region water supply. The model application is performed to verify its adequacy to the studied region, comparing real date and simulation values. The operation of a system composed of thirteen reservoirs is also simulated, in order to obtain results of their behavior during seven months of drought period.

O presente trabalho apresenta um modelo geral de simulação em tempo real de operação de reservatórios que trabalha como parte de um sistema de suporte à decisão, fornecendo informações sobre as disponibilidades hídricas do sistema de múltiplos reservatórios, em função de restrições vinculadas aos volumes armazenados. Este modelo é composto de duas partes: um software de pré-processamento, escrito em linguagem Python, que constrói os arquivos de entrada do programa principal, e um software responsável pela simulação da operação de um sistema de reservatórios (OperRes), escrito parte em Python e parte em Fortran. O modelo é aplicado à bacia do rio Paraguaçu localizada no estado da Bahia. A bacia apresenta como principal reservatório o açude formado pela barragem de Pedra do Cavalo, que é responsável pela maior parte do abastecimento da cidade de Salvador e região metropolitana. A aplicação do modelo é feita com o objetivo de se verificar a sua adequação à região em estudo, através da comparação dos dados reais com os resultados das simulações. Também é feita a simulação da operação dos treze açudes representados no sistema para se obter o resultado do seu comportamento durante um período de sete meses de estiagem. / This work shows a general simulation model of reservoirs operation to be run in real time working as part of a decision support system, which is supposed to give information about water availability in the reservoir system. This model is built in two parts: a pre-processing software, written in Python language, which builds the data files of the main program, and another software dedicated to the simulation of the reservoir system operation (OperRes) written in Python and Fortran languages. The model is applied to the Paraguaçu river basin, at Bahia State, Brazil. Pedra do Cavalo Dam is the basin main reservoir, which is responsible for most of Salvador city and metropolitan region water supply. The model application is performed to verify its adequacy to the studied region, comparing real date and simulation values. The operation of a system composed of thirteen reservoirs is also simulated, in order to obtain results of their behavior during seven months of drought period.

Optimal operation of reservoir systems is necessary for better utilizing the limited water resources and to justify the high capital investments associated with reservoir projects. However, finding optimal policies for real-life problems of reservoir systems operation (RSO) is a challenging task as the available analytical methods can not handle the arbitrary functions of the problem and almost all methods employed are numerical or iterative type that are computer dependent. Since the computer resources in terms of memory and CPU time are limited, a limit exists for the size of the problem, in terms of arithmetic and memory involved, that can be handled. This limit is approached quickly as the dimension and the nonlinearity of the problem increases. In encountering the complex aspects of the problem all the traditionally employed methods have their own drawbacks. Linear programming (LP), though very efficient in dealing with linear functions, can not handle nonlinear functions which is the case mostly in real-life problems. Attempting to approximate nonlinear functions to linear ones results in the problem size growing enormously. Dynamic programming (DP), though suitable for most of the RSO problems, requires exponentially increasing computer resources as the dimension of the problem increases and at present many high dimensional real-life problems can not be solved using DP. Nonlinear programming (NLP) methods are not known to be efficient in RSO problems due to slow rate of convergence and inability to handle stochastic problems. Simulation methods can, practically, explore only a small portion of the search region. Many simplifications in formulations and adoption of approximate methods in literature still fall short in addressing the most critical aspects, namely multidimensionality, stochasticity, and additional complexity in conjunctive operation, of the problem. As the problem complexity increases and the possibility of arriving at the solution recedes, a near optimal solution with the best use of computational resources can be very valuable. In this context, genetic algorithms (GA) can be a promising technique which is believed to have an advantage in terms of efficient use of computer resources. GA is a random search method which find, in general, near optimal solutions using evolutionary mechanism of natural selection and natural genetics. When a pool of feasible solutions, represented in a coded form, are given fitness according to a objective function and explored by genetic operators for obtaining new pools of solutions, then the ensuing trajectories of solutions come closer and closer to the optimal solution which has the greatest fitness associated with it. GA can be applied to arbitrary functions and is not excessively sensitive to the dimension of the problem. Though in general GA finds only the near optimal solutions trapping in local optima is not a serious problem due to global look and random search. Since GA is not fully explored for RSO problems two such problems are selected here to study the usefulness and efficiency of GA in obtaining near optimal solutions. One problem is conjunctive operation of a system consisting of a surface reservoir and an aquifer, taken from the literature for which deterministic and stochastic models are solved. Another problem is real-time operation of a multipurpose reservoir, operated for irrigation (primary purpose) and hydropower production, which is in the form of a case study. The conjunctive operation problem consists of determining optimal policy for a combined system of a surface reservoir and an aquifer. The surface reservoir releases water to an exclusive area for irrigation and to a recharge facility from which it reaches the aquifer in the following period. Another exclusive area is irrigated by water pumped from the aquifer. The objective is to maximize the total benefit from the two irrigated areas. The inflow to the surface reservoir is treated as constant in deterministic model and taken at 6 different classes in stochastic model. The hydrological interactions between aquifer and reservoir are described using a lumped parameter model in which the average aquifer water table is arrived at based on the quantity of water in the aquifer, and local drawdown in pumping well is neglected. In order to evaluate the GA solution both deterministic and stochastic models are solved using DP and stochastic DP (SDP) techniques respectively. In the deterministic model, steady state (SS) cyclic (repetitive) solution is identified in DP as well as in GA. It is shown that the benefit from GA solution converges to as near as 95% of the benefit from exact DP solution at a highly discounted CPU time. In the stochastic model, the steady state solution obtained with SDP consists of converged first stage decisions, which took a 8-stage horizon, for any combination of components of the system state. The GA solution is obtained after simplifying the model to reduce the number of decision variables. Unlike SDP policy which gives decisions considering the state of the system in terms of storages, at reservoir, aquifer, and recharge facility, and previous inflow at the beginning of that period, GA gives decisions for each period of the horizon considering only the past inflow state of the period. In arriving at these decisions the effect of neglected state information is approximately reflected in the decisions by the process of refinement of the decisions, to conform to feasibility of storages in reservoir and aquifer, carried out in a simplified simulation process. Moreover, the validity of the solution is confirmed by simulating the operation with all possible inflow sequences for which the 8-stages benefit converged up to 90 % of the optimum. However, since 8 stages are required for convergence to SS, a 16-stage process is required for GA method in which the first 8 stages policy is valid. Results show that GA convergence to the optimum is satisfactory, justifying the approximations, with significant savings in CPU time. For real-time operation of a multipurpose reservoir, a rule curve (RC) based monthly operation is formulated and applied on a real-life problem involving releases for irrigation as well as power production. The RC operation is based on the target storages that have to be maintained, at each season of the year, in the reservoir during normal hydrological conditions. Exceptions to target storages are allowed when the demands have to be met or for conserving water during the periods of high inflows. The reservoir in the case study supplies water to irrigation fields through two canals where a set of turbines each at the canal heads generate hydropower. A third set of turbines operate on the river bed with the water let out downstream from the dam. The problem consists of determining the the RC target storages that facilitate maximum power production while meeting the irrigation demands up to a given reliability level. The RC target storages are considered at three different levels, corresponding to dry, normal, and wet conditions, according to the system state in terms of actual (beginning of period) storage of the reservoir. That is, if the actual beginning storage of the reservoir is less than some coefficient, dry-coe, times the normal target storage the target for the end of the period storage is taken at the dry storage target (of the three sets of storages). Similarly the wet level is taken for the end of the period target if the actual beginning storage is greater than some coefficient, wet-coe, times the normal storage. For other conditions the target is the normal storage level. The dry-coe and wet-coe parameters are obtained by trial and error analysis working on a small sequence of inflows. The three sets of targets are obtained from optimization over a 1000 year generated inflow sequence. With deterministic DP solutions, for small sequences of inflows, the optimization capability of GA-RC approach, in terms of objective function convergence, and generalization or robustness capability of GA-RC approach, for which the GA-RC benefit is obtained by simulating the reservoir operation using the previously obtained GA-RC solution, are evaluated. In both the cases GA-RC approach proves to be promising. Finally a 15 year real-time simulation of the reservoir is carried out using historical inflows and demands and the comparison with the historical operation shows significant improvement in benefit, i.e. power produced, without compromising irrigation demands throughout the simulation period.