Generation of electric energy through wind turbines is one of the practically inexhaustible alternatives of generation. It is considered a source of clean energy, but still needs a lot of research ...for the development of science and technologies that ensures uniformity in generation, providing a greater participation of this source in the energy matrix, since the wind presents abrupt variations in speed, density and other important variables. In wind-based electrical systems, it is essential to predict at least one day in advance the future values of wind behavior, in order to evaluate the availability of energy for the next period, which is relevant information in the dispatch of the generating units and in the control of the electrical system. This paper develops ultra-short, short, medium and long-term prediction models of wind speed, based on computational intelligence techniques, using artificial neural network models, Autoregressive Integrated Moving Average (ARIMA) and hybrid models including forecasting using wavelets. For the application of the methodology, the meteorological variables of the database of the national organization system of environmental data (SONDA), Petrolina station, from 1 January 2004 to 31 March 2017, were used. A comparison among results by different used approaches is also done and it is also predicted the possibility of power and energy generation using a certain kind of wind generator.
The Extractive Reserve (RESEX) was designed to protect rubber tapping communities and their livelihoods, thus guaranteeing environmental health. This study was carried out between 2021 and 2023 and ...aimed to propose a methodology based on the fuzzy logic method to assess the degree of sustainability in RESEXs in the state of Amazonas, Brazil. For this assessment, 10 indicators were used, represented through input variables in the fuzzy inference systems represented by the Environmental Subsystem (ES), Economic Subsystem (ECS), Social Subsystem (SS), and Institutional Subsystem (IS), with performances that converged so that the Sustainability System in the RESEX (SRE) system reached a performance value of 30.0, on a scale of 0 to 100, which translates into low sustainability in these spaces in the state of Amazonas. The methodology’s ability to represent the main phenomena that impact sustainability in the RESEX studied through linguistic variables and weight them in their complexities, as well as inferring a set of decision rules that reflect the knowledge of experts and which aim to quantitatively contextualise sustainability under uncertainty and imprecision in these areas, makes it a viable instrument to be applied and used by managers and decision-makers in the management of these spaces.
•Our study determines the number, placement, control, and parameters of the compensators.•We unified the compensation of reactive power and harmonics under a single problem.•We also consider the ...constraints of power quality and overstress of the capacitors.•We employed the NSGA-II multi-objective optimization algorithm to solve this problem.
The optimization of passive filters in distribution systems has been addressed through different approaches. In general, these approaches can be classified as single-objective and multi-objective formulations. The single-objective formulations normally try to determine the least costly filters that ensure compliance with the relevant power quality standards. In multi-objective approaches, other goals are added. In general, most studies consider the reactive power of filters at a fundamental frequency to be equal to a previously determined magnitude, and the optimization is devoted to calculate the other parameters of the filters that are required to minimize the distortion indices of the network. In the present approach, the capacitor placement and passive filter placement problems are considered as a unified problem in which a set of passive compensators (capacitors and/or tuned filters) that allow to obtain the maximum annual saving in cost and maximum improvement of the power quality of the circuit are determined. In this study, the annual saving is calculated as the equivalent present value of the compensation project to simultaneously account for the benefits of the reactive power compensation and the cost of investment in the compensators. Although many studies have solved the multi-objective problem by minimizing a single function comprising several subobjectives, this study employs the nondominated sorting genetic algorithm for the optimization of several objective functions. The present approach is tested with two example circuits from literature.
The aim of this manuscript is to introduce solutions to optimize economic dispatch of loads and combined emissions (CEED) in thermal generators. We use metaheuristics, such as particle swarm ...optimization (PSO), ant lion optimization (ALO), dragonfly algorithm (DA), and differential evolution (DE), which are normally used for comparative simulations, and evaluation of CEED optimization, generated in MATLAB. For this study, we used a hybrid model composed of six (06) thermal units and thirteen (13) photovoltaic solar plants (PSP), considering emissions of contaminants into the air and the reduction in the total cost of combustibles. The implementation of a new method that identifies and turns off the least efficient thermal generators allows metaheuristic techniques to determine the value of the optimal power of the other generators, thereby reducing the level of pollutants in the atmosphere. The results are presented in comparative charts of the methods, where the power, emissions, and costs of the thermal plants are analyzed. Finally, the comparative results of the methods were analyzed to characterize the efficiency of the proposed algorithm.
This paper presents a specific method to improve the reliability of the equipment and the quality of power supplied to the electrical systems with the frequency and voltage control of a ...thermoelectric plant, to guarantee a more stable system. The method has the novelty of combining Total Productive Maintenance (TPM) using only four pillars, with Electrical Predictive Maintenance based in failure analysis and diagnostic. It prevents voltage drops caused by excessive reactive consumption, thus guaranteeing the company a perfect functioning of its equipment and providing a longer life of them. The Maintenance Management Program (MMP) seeks to prevent failures from causing the equipment to be shut down from the electrical system, which means large financial losses, either by reducing billing or by paying fines to the regulatory agency, in addition to prejudice the reliability of the system. Using management tools, but applying only four TPM pillars, it was possible to achieve innovation in power plants with internal combustion engines. This study aims to provide maintenance with a more reliable process, through the implantation of measurement, control and diagnostic devices, thus allowing the management to reduce breakdown of plant equipment. Some results have been achieved after the implementation, such as reduction of annual maintenance cost, reduction of corrective maintenance, increase of MTBF (Mean Time between Failures) and reduction of MTTR (Mean Time to Repair) in all areas. Probabilistic models able to describe real processes in a more realistic way, and facilitate the optimization at maximum reliability or minimum costs are presented. Such results are reflected in more reliable and continual power generation.
Summary
Economic‐emission load dispatch optimization problem is an essential task in power plants with internal combustion engines. In power plants, in addition to electricity, a lot of air pollution ...by exhaust gases is generated. There are many international standards that establish the permissible limits of different substances but still have not developed an expression to evaluate the environmental impact caused by all components of the exhaust gases as a whole. A new method to evaluate this impact is developed in this paper. The developed mathematical expression was called “emission index.” To get a better idea of the environmental impact of each type of engine, the “specific emission index”, which is the emission index divided by the power delivered by the engine. This paper also presents a mathematical model for a multiobjective optimization of economic‐emission load dispatch using nondominated sorting genetic algorithm II.
The optimization of economic emission load dispatch is one of the most significant tasks in power plants. This article aims to analyze a new application of the computational optimization by simulated ...annealing technique including turning off the motors with greatest losses. The incremental cost of fuel consumption and the lambda iteration methods are combined to determine the best parameters of active power of each
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generator unit, ensuring that the total losses and demand are equal to the total generated power but minimizing the total cost of fuel consumption and carbon emission. Many materials and methods have been elaborated to fix the economic emission load dispatch, among them are as follows: differential evolution method, gradient method and Newton’s method. The results found for this case study, with the new application of simulated annealing, were outstanding having a reduction of 20.14% in the total fuel cost, comparing to classical methods that distribute the generation of power among all motors, including the least efficient ones. This method helps the expert in the decision making of preventive maintenance of machines that are not working in the moment of multi-objective optimization, improving not only the yield of generation and carbon emission reduction but also of the power plant generation planning.
Industrial production has evolved significantly over the last decade. For this reason, it is necessary to obtain mathematical and computational tools that enable power systems engineers to make ...decisions that reduce harmonic distortions in accordance with international standards. This paper presents a total harmonic distortion (THD) assessment based on full knowledge discovery in databases (KDD) using power quality (PQ) standards and computational intelligence tools. The materials and methods of THD assessment consist of load and layout analysis; choice and installation of PQ analyzers; and the application of the full KDD process, including collection, selection, cleaning, integration, transformation and reduction, mining, interpretation, and evaluation of the data. This research methodology was used in an electrical and electronic industry; the results obtained have characteristics that can be used as a reference for other types of analyses. The results indicate that these methods can be applied to several industrial applications such as: 1) the description of the complete KDD process for THD assessment of the point of common coupling; 2) simultaneous collection using five PQ analyzers at several points in the electrical network; and (3) the use of a decision tree classifier.
Economic-emission load dispatch uses the fuel cost variables and gas emission in a minimized way to obtain an optimal operation in generation units in a power plant, guaranteeing the supply of ...demand. The first variable is definitive to ensure business continuity and the second to comply with environmental legislation and no degradation of the environment. This paper analyzes the use of a new computational optimization algorithm based on the cultural algorithm (CA), improved with local search techniques simulated annealing and Tabu search, using data from a real power plant with 10 generators and the system of the IEEE with 13 generating units. The application has two options of operation: the classic one, which operates with all generators seeking to minimize the cost and emission meeting the specified demand; and the controlled one, which turns off the generators that have the highest incremental fuel cost but guaranteeing the demand and reducing the emission of gases. Simulations were performed on the six possible options in this application. The results obtained were compared with each other and with the results of other techniques reported in the literature. The local search that improved the CA and the new way of updating topographic knowledge allowed the results to be better than those found by other metaheuristics that solved the same problem of the real plant and the IEEE system.
The formulations employed to the optimization of passive filters can be classified as formulations of a single objective or formulations with multiple objectives. The single-objective formulations ...normally are devoted to determine the filters of lowest cost that assure the compliance with the power quality standards, while in the multi-objective approaches are added other goals that are related with the improvement of the power quality indexes. In the presented approach, the problem of the reactive power compensation and the problem of the harmonic distortion compensation are considered a unified multi-objective problem in which is determined a set of passive filters that allows the obtaining of the maximum economic benefits as well as the maximum improvement of the power quality of the circuit. While several previous contributions solve the multi-objective problem by minimizing a single function composed of several sub-objectives, this work employs the non-dominated sorting genetic algorithm (NSGA-II) for the optimization of three independent objective functions. This algorithm obtains the Pareto front of the problem and allows the selection of the most effective solutions. The optimization method that presented in this work allows the selection by the algorithm of the filter type proper for compensation in a node of the circuit as well as the obtaining of their parameters. The set of possible filter configurations to place in one candidate node is defined by the user before the optimization is done. This is a distinctive characteristic of the presented approach that is tested with a practical example.
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