Maintenance Management with Application of Computational Intelligence Generating a Decision Support System for the Load Dispatch in Power Plants

The development of a computational tool to support the decision of load dispatch according to the operational conditions of motors and generators of power plants is proposed, which are classified in relation to the probabilities of faults by a fuzzy system developed in this text, from indicators obtained from the analysis of lubricating oil, vibration analysis, and thermography of power generation equipment. The basis for the study is based on the principle of operation and operational conditions of the equipment to be dispatched for generation in a power plant, in addition to its particularities as specific consumption and the polluting emission for each equipment. In this way, this work aims not only to provide the tools to monitor these equipment but also, based on the management reports of vibration, temperature, and oil analysis, take corrective actions to maintain the necessary reliability and achieve the quality of the service through a preclearance procedure that takes into account the operating conditions of the equipment, obtaining performance indicators of the plan

Multi-Objective Optimization Techniques to Solve the Economic Emission Load Dispatch Problem Using Various Heuristic and Metaheuristic Algorithms

The main objective of thermoelectric power plants is to meet the power demand with the lowest fuel cost and emission levels of pollutant and greenhouse gas emissions, considering the operational restrictions of the power plant. Optimization techniques have been widely used to solve engineering problems as in this case with the objective of minimizing the cost and the pollution damages. Heuristic and metaheuristic algorithms have been extensively studied and used to successfully solve this multi-objective problem. This chapter, several optimization techniques (simulated annealing, ant lion, dragonfly, NSGA II, and differential evolution) are analyzed and their application to economic-emission load dispatch (EELD) is also discussed. In addition, a comparison of all approaches and its results are offered through a case study

Modeling the Socioeconomic Metabolism of End-of-Life Tires Using Structural Equations: A Brazilian Case Study

Socioeconomic metabolism (SEM) is the exchange of materials and energy between society and the environment involving the social, economic and environmental sectors. In this paper, a boundary was defined between the economic (consumption) and environmental (waste recovery) limits in a city of 300,000 inhabitants in relation to the circulation (generation, reuse and disposal) of end-of-life tires (ELTs). The objective was to elaborate a theoretical structural model to evaluate the socioeconomic metabolism of waste (SEMw) by means of technical constructs (direct material flows (DMF), reverse material flows (RMF), socioeconomic environment (SEF) and sociodemographic factors (SDF)). Structural Equation Modeling (SEMm) was performed using Partial Least Squares Structural Equation Modeling (SmartPLS) software. The results obtained from the hypotheses show the causal relationships between the technical and social constructs and suggest guidelines for supporting the planning and management of urban solid waste in the collection and final disposal of ELTs. The processed information also contributes to the analysis of the city’s socioeconomic scenarios in relation to the disposal of ELTs. One of the hypotheses tested (RMF have a direct effect on SEMw) shows the importance of managing ELTs through the correct final disposal of waste and recycling. SEMw was evaluated from the perception of the local society and it is concluded that it is possible to plan public policies to avoid the formation of waste inventory in the city