Multi‐Objective Real‐Time Dispatching Problem in Electric Utilities: An Application to Emergency Service Routing

This chapter presents a novel application of real‐time dispatching problem to electric utilities when multi‐objective is involved. It is described how the problem related to emergency services in electric utilities is considered, with an aggregated objective function developed to handle the minimization of the waiting time, the total distance traveled, the sum of all delays related to already assigned orders, and the cost of non‐assigned emergency orders. After that, actual cases have shown the effectiveness of the proposed model to be adopted in real‐world applications either as a search for optimal solution or by applying a heuristic‐based algorithm developed

A Decision Support System for Planning and Operation of Maintenance and Customer Services in Electric Power Distribution Systems

This chapter aims to present the design and development of a decision support system (DSS) for the analysis, simulation, planning, and operation of maintenance and customer services in electric power distribution system (EPDS). The main objective of the DSS is to improve the decision‐making processes through visualization tools and simulation of real cases in the EPDS, in order to allow better planning in the short, medium, and long term. Therefore, the DSS helps managers and decision‐makers to reduce maintenance and operational costs, to improve system reliability, and to analyze new scenarios and conditions for system expansion planning. First, we introduce the key challenges faced by the decision‐makers in the planning and operation of maintenance and customer services in EPDS. Next, we discuss the benefits and the requirements for the DSS design and development, including use cases modeling and the software architecture. Afterwards, we present the capabilities of the DSS and discuss important decisions made during the implementation phases. We conclude the chapter with a discussion about the obtained results, pointing out the possible enhancements of the DSS, future extensions, and new use cases that may be addressed

Resource Planning to Service Restoration in Power Distribution Systems

Whenever there are extreme weather events, electric power distribution systems are generally affected largely because they are highly subject by their constructive nature: overhead networks. In this context, the management of maintenance actions is generally referred to as emergency service order, usually associated with a lack of supply and requiring human intervention. The key issue for the resource planning refers to an estimation of service time that allows for more assertive planning possible. This chapter proposes a predictive modelling of emergency services for resource planning when considering the geographic dispersion of such services and also the time windows that comprise the amount of service time demanded. After presenting the methodological procedures, a case study depicts the application of the proposed method in order to support proactive service routing

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

A parallel memetic algorithm applied to the total tardiness machine scheduling problem

This work proposes a parallel memetic algorithm applied to the total tardiness single machine scheduling problem. Classical models of parallel evolutionary algorithms and the general structure of memetic algorithms are discussed. The classical model of global parallel genetic algorithm was used to model the global parallel memetic analogue where the parallelization is only applied to the individual optimization phase of the algorithm. Computational tests show the efficiency of the parallel approach when compared to the sequential version. A set of eight instances, with sizes ranging from 56 up to 323 jobs and with known optimal solutions, is used for the comparisons

A Flexible-Reliable Operation Model of Storage and Distributed Generation in a Biogas Power Plant

This paper presents a novel methodology for planning and operating biogas energy systems based on the transactive energy concept to determine multilevel operating regimes for distributed generation. The developed model is used to manage the production, storage, and dispatch of biogas energy systems to meet the load demands of the biogas producer and support the operation of the distribution network operator. An Integer Linear Programming (ILP) is fitted to optimize the biogas production of the biogas producer, including the operation of the biogas storage systems and their interaction with the network operator. The model’s objective is to maximize benefits for the participating agents in a transactive energy context. The model’s effectiveness is validated using seven case studies involving biogas systems having different operating ranges and modes to achieve enhanced flexibility and reliability for the system operation with a large proportion of intermittent energy resources. The simulation results showed that the approach could effectively manage the operation of biogas systems and their interaction with the network operator. The developed model is suitable for systems fostering net metering charging and real-time pricing

A Flexible-Reliable Operation Model of Storage and Distributed Generation in a Biogas Power Plant

This paper presents a novel methodology for planning and operating biogas energy systems based on the transactive energy concept to determine multilevel operating regimes for distributed generation. The developed model is used to manage the production, storage, and dispatch of biogas energy systems to meet the load demands of the biogas producer and support the operation of the distribution network operator. An Integer Linear Programming (ILP) is fitted to optimize the biogas production of the biogas producer, including the operation of the biogas storage systems and their interaction with the network operator. The model’s objective is to maximize benefits for the participating agents in a transactive energy context. The model’s effectiveness is validated using seven case studies involving biogas systems having different operating ranges and modes to achieve enhanced flexibility and reliability for the system operation with a large proportion of intermittent energy resources. The simulation results showed that the approach could effectively manage the operation of biogas systems and their interaction with the network operator. The developed model is suitable for systems fostering net metering charging and real-time pricing

A Parallel Memetic Algorithm Applied to the Total Tardiness Machine Scheduling Problem

This work proposes a parallel memetic algorithm applied to the total tardiness single machine scheduling problem. Classical models of parallel evolutionary algorithms and the general structure of memetic algorithms are discussed. The classical model of global parallel genetic algorithm was used to model the global parallel memetic analogue where the parallelization is only applied to the individual optimization phase of the algorithm. Computational tests show the efficiency of the parallel approach when compared to the sequential version. A set of eight instances, with sizes ranging from 56 up to 323 jobs and with known optimal solutions, is used for the comparisons. 1