Navegando por Assunto "Power generation"

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Acesso aberto (Open Access)
Modelo de gerenciamento de usos múltiplos da água: um estudo de caso para a bacia hidrográfica do rio Tapajós
(Universidade Federal do Pará, 2016-02) FIGUEIREDO, Nelio Moura de; BLANCO, Claudio José Cavalcante; http://lattes.cnpq.br/8319326553139808
This work deals with a model for management of multiple uses of water, for the mitigation of conflicts of use related to the operation of reservoir systems in hydroelectric power plant of water catchment area. The model SOUMA – "system optimization of multiple uses of water", which consists of a stochastic optimization model based on nonlinear programming, was developed and structured in GAMS (General Algebraic Modeling System) with the use of solver MINOS. The SOUMA is composed of two modules. The first is a module for forecasting of water levels, which consists of a stochastic model of type ARIMA (Auto Regressive Integrated Moving Average). The second is a module for forecasting of streamflow, which is a stochastic model of rainfall-streamflow the RNA type. The ARIMA model calibration and validation presented average R² above 0.93 and RMSE below 0.08, capturing in a satisfactory manner the behavior of water levels. The rain-flow model that was used in the composition of influent flow to the reservoir, with the use of RNA architecture, presented average R² 0.954 and of 0.098 RMSE. The SOUMA model was applied to Tapajós River basin for the future hydroelectric power plant of São Luiz do Tapajós, Itaituba, PA. Six scenarios were created to be used as parameters in optimizing and mitigation of conflicts. The reservoir tributaries streamflow were obtained and simulated for dry, medium and moist hydrological scenarios and for El Niño, La Niña and Neutral climatic scenarios. For the power generation and navigation depth uses, considering the tributaries streamflow of the dry, medium and moist hydrological scenarios, the SOUMA showed, in relation to the reference levels of the low, medium and high navigation scenarios, the occurrence of depths below the minimum, for generations averages below 2,411 MW, 2,939 MW and 3,586 MW, respectively. For power generation and cargo capacity, considering the tributaries streamflow of the dry, medium and moist hydrological scenarios, the SOUMA showed, in relation to the low, medium and high reference levels of the navigation scenarios, that generations averages above 2,869 MW, 3,508 MW and 4,740 MW, respectively, do not generate earnings of cargo capacity and that medium generations below 1,344 MW, 2,056 MW and 1,622 MW, respectively, make the river transport of cargo infeasible. For power generation and flood dimension, considering the tributaries streamflow of the dry, medium and moist hydrological scenarios, the SOUMA showed, in relation the reference levels low, medium and high of the flood control, the occurrence of floods downstream to generations above average 4,978 MW, 6,057 MW and 7,390 MW, respectively. Consumptive withdrawals are meaningful only in the period from June to October. Considering the monthly average consumptive demands (145 m ³/s), to tributaries streamflow of the dry, medium and moist hydrological scenarios, the SOUMA showed a monthly loss in power generation of 50 MW, 47 MW and 44 MW, respectively. The measured results show that the models developed are important tools to operational optimization of reservoir systems with multiple uses, allowing the optimization of generations and defluente flow in the hydroelectric power plant of water catchment area, in periods of flood and drought and large energy demands, with maintenance of navigation conditions downstream from dams, through sustainable operational simulations that minimize usage conflicts.
Acesso aberto (Open Access)
Modelo matemático para otimização multiobjetivo do despacho econômico ambiental de usinas térmicas usando o NSGA-II
(Universidade Federal do Pará, 2017-07-14) MORAES, Nadime Mustafa; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
One of the priority tasks for thermoelectric plants is to supply the requested energy demand, ensuring the lowest possible cost. This task is more important in the Northern Region of Brazil, especially in the Industrial Hub of Manaus (PIM) and in the city itself, where a large part of this energy is supplied by Thermoelectric Power Plants (UTE). The selection of generators and their work regime is known as the Economic Dispatch (DE). The essential objective of ED is to operate UTEs by meeting demand at the lowest possible cost of fuel. However, the worldwide concern about pollution caused by fossil fuels in recent times to minimize fuel costs can not be considered the only objective to be achieved in the UTEs and limiting the emission of pollutants has become another primary objective. Thus, the Environmental Economic Dispatch (DEA) appears, which seeks not to reduce costs, but also emissions. To solve the optimization of this task there are several deterministic as well as heuristic methods. One of the most used methods according to the literature is the Genetic Algorithm of Non-dominated Classification, NSGA-II, considering two objective functions, a function of fuel cost and another quantity function. In this thesis, the proposed solution has the following contributions: it develops a new and unprecedented function to evaluate the environmental contamination produced by the UTEs that, in addition to minimizing the amount of pollutants, takes into account the influence of pollutants more harmful to the environment. This function, called the Emissions Index, is applied to the engines of two UTEs in the city of Manaus with satisfactory results. The Emissions Index and the traditional fuel cost function is optimized using the NSGA-II, determining optimal solutions for output power in several characteristic and non-characteristic scenarios of the plants, and can be applied to any thermoelectric plant. In order to analyze the viability of the solution proposed by this thesis, a set of ten thermal generating units of a UTE of the city of Manaus and the IEEE 118-bar System were used as case studies, demonstrating the robustness of the proposal in what refer to the solution presented. These results were significant considering the Emissions Index and using the optimization procedure of the non-dominated classification algorithm II (NSGA-II). This new DEA methodology enables specialists in the area to reduce costs and generate generation planning.
Acesso aberto (Open Access)
Viabilidade da geração de energia a partir de resíduos sólidos urbanos em pequenos municípios do estado do Pará
(UFPA - Universidade Federal do Pará, 2022-07-01) PADILHA, Jessé Luís; MESQUITA, André Luiz Amarante; http://lattes.cnpq.br/1331279630816662
The most common urban solid waste disposal in Brazil is the landfill. Additionally, there are still inadequate disposal units (dumps), but there are technological alternatives for this disposal and some projects are already installed in Brazil. The economic analysis is therefore fundamental to find the best technological option, transforming an environmental problem into a viable solution. This work aims to analyze the financial viability of the combination of consolidated destinations for the management of Municipal Solid Waste (MSW) (technological routes), that use Waste-to-Energy (WTE), considering small cities with populations from 30,000 to 250,000 residents and later apply this analysis considering the grouping of municipalities in Pará, suitable according to the regional plan for solid waste in the state of Pará. A structured algorithm was used with a focus on estimating revenue from the minimum value of rate payers' contributions (RPC) to make these routes viable for most cities considered in the project. Economic indicators used include: Net Present Value (NPV), Internal Rate of Return (IRR), Discounted Payback Period (DPP), and Leveled Cost of Electricity (LCOE). A sensitivity analysis of the two best routes was performed (depending on lower RPC values) based on NPV. The results tend to confirm solutions that can be approved not only by the government, but also by the business sector. The best outcomes are the routes with landfill and landfill gas, and with recycling and anaerobic digestion, considering the sale of digestate and landfill. These presented the best financial values, with discounted payback periods of 15 and 20 years, maximum RPC of US$0.04 and US$0.33, per inhabitant/month, respectively, with an IRR of 11.61%, for both. The sensitivity analysis indicated a greater influence on the investment costs of landfill gas for the first route and for the second route, the urban collection and cleaning services and the estimated average percentage of the population's half-minimum-wage income expenditure was on average a little above 3%.