Aplicación de tres métodos de solución al problema de dimensionamiento de lotes y MRP.

El contenido del presente documento muestra la aplicación de tres métodos de solución a partir del planteamiento de un problema de dimensionamiento de lotes: Solución mediante la Heurística de Silver – Meal, la Heurística de Balanceo de Período y Parte y la Heurística de Costo Mínimo Unitario. La evaluación de los métodos anteriormente mencionados se realizó de forma manual, a través de recursos bibliográficos proporcionados por el orientador de la asignatura: Control de Producción e Inventarios. Teniendo en cuenta los resultados obtenidos se realizó una comparación entre los mismos y se procedió a elegir la mejor solución la cual se ve justificada mediante una política de costo mínimo

Estudio del problema de corte y empaquetamiento aplicado en una empresa de distribución

En este trabajo se realiza una revisión del Problema de Corte y Empaquetamiento en tres dimensiones, a su vez se describe la heurística aplicada en una empresa de distribución y se realiza una propuesta de mejora para la resolución del problema que allí se presenta. Se realiza una revisión de las principales restricciones del problema de corte y empaquetamiento en tres dimensiones y las heurísticas más usadas. Luego se documentan los modelos utilizados por la empresa de distribución a partir de trabajo de campo, entrevistas e información recolectada del personal directamente relacionado con el proceso. Con base en el análisis de ambas fuentes de información se propone una herramienta de mejora. Se realiza un análisis comparativo en un mismo trimestre de años diferentes y se evalúa el rendimiento de la misma obteniendo buenos resultados para el caso del problema de la mochila

Estudio del problema de corte y empaquetamiento aplicado en una empresa de distribución

En este trabajo se realiza una revisión del Problema de Corte y Empaquetamiento en tres dimensiones, a su vez se describe la heurística aplicada en una empresa de distribución y se realiza una propuesta de mejora para la resolución del problema que allí se presenta. Se realiza una revisión de las principales restricciones del problema de corte y empaquetamiento en tres dimensiones y las heurísticas más usadas. Luego se documentan los modelos utilizados por la empresa de distribución a partir de trabajo de campo, entrevistas e información recolectada del personal directamente relacionado con el proceso. Con base en el análisis de ambas fuentes de información se propone una herramienta de mejora. Se realiza un análisis comparativo en un mismo trimestre de años diferentes y se evalúa el rendimiento de la misma obteniendo buenos resultados para el caso del problema de la mochila

Boosting the Usage of Green Energy for EV Charging in Smart Buildings Managed by an Aggregator Through a Novel Renewable Usage Index

The growing trend of electric vehicles (EVs) and building integrated photovoltaics (BIPVs) is a promising means to reduce related climate change issues. EV loads can be managed via an aggregator to maximize the usage of green energy produced by photovoltaic units (PV) through smart charging strategies that exploit controllable EV demand connected to BIPV. Previous works have focused on the EV charging coordination in a smart BIPV, although without an optimization that encourages EV charging with the energy produced by the PV units. This paper proposes an aggregation strategy that maximizes a green energy index (GEI) for the smart charging coordination of EVs, which takes advantage of periods with high PV availability to charge the EV batteries; moreover, a post-processing stage for the GEI provides EV owners with information about the percentage of charged energy, period by period, that comes from PV generation. The results for a case study with 510 EVs integrated with 17 smart BIPVs show that the strategy effectively optimizes the usage of the energy produced by the PV units to charge the EVs, contributes to reduce non-renewable energy consumption of the building sector, and satisfies the EV owners’ energy requirements for transportation.This work was supported in part by the Coordination for the Improvement of Higher Education Personnel (CAPES); in part by the Brazilian National Council for Scientific and Technological Development (CNPq) under Grant 305318/2016-0; in part by the Sao Paulo Research Foundation (FAPESP) under Grant 2018/08008-4, Grant 2017/02831-8, and Grant 2018/23617-7; and in part by the Portuguese Foundation for Science and Technology (FCT), under Project PTDC/EEI-EEE/28983/2017 [Coordinated ENErgy Resource manaGEment under uncerTainty considering electrIc vehiCles and demand flexibility in distribution networks (CENERGETIC)], Project CEECIND/02814/2017, and Project UIDB/000760/2020.info:eu-repo/semantics/publishedVersio

An IoT-based energy management system for AC microgrids with grid and security constraints

This paper proposes an Internet-of-Things (IoT) based energy management system (EMS) for the optimal operation of unbalanced three-phase AC microgrids. The system utilizes a software architecture based on microservices, which includes a stochastic economic dispatch optimizer (EDO), a database, a web-based graphical user interface (GUI), and an application programming interface (API). The EDO uses a mixed-integer linear programming (MILP) model to ensure the day-ahead dispatch of the distributed energy resources (DERs) in the microgrid while adhering to grid constraints such as voltage, current, and power limits. Additionally, the optimization module takes into account security constraints for unplanned islanded operation, as well as stochastic scenarios of local demand and renewable generation. To assess the performance of the proposed IoT-based EMS, tests are conducted using a real-time simulator in a software-in-the-loop (SIL) experimental setup. Actual data from a microgrid located at the State University of Campinas (UNICAMP) in Brazil is utilized for the tests. The microgrid consisted of a photovoltaic (PV) system, a battery energy storage system (BESS), a thermal generation unit, and variable demands. Results indicated the effectiveness of the proposed IoT-based EMS in monitoring the operation of the microgrid and defining the optimal day-ahead dispatch of local DERs.</p

Aplicação de técnicas metaheurísticas para resolver o problema de coordenação de carregamento de veículos elétricos em sistemas de distribuição

The main objective of the plug-in electric vehicles (PEV) charging problem is to determine the optimal schedule for charging the PEV batteries with the aim of minimizing the total operational cost of the electrical distribution system in order to obtain an efficient and secure system operation. The optimization techniques used to resolve the plug-in electric vehicles charging problem on electrical distribution systems are two metaheuristic: Tabu Search and GRASP. The mathematical model used to represent the PEV charging problem is a mixed-integer nonlinear programing problem. On the other hand, a hybrid algorithm named GRASP-BT is also proposed in order to improve the solutions obtained by the Tabu Search and GRASP methodologies. The solutions found by the proposed methodologies designate the time periods where each PEV battery connected to the electrical distribution system need to be charged, minimizing the total operational costs, satisfying the operational constraints, considering PEV charging priority and providing quality solution on real time. In order to show the efficiency of the proposed methodologies, a 449 nodes test system with HV and LV network and two sources of distributed generation are used. Test cases consider a 47% and a 63% of PEV penetrationO problema do carregamento de veículos elétricos consiste em determinar a programação ótima da recarga dos PEVs (do inglês Plug-in Electric Vehicles) de forma que o custo de operação seja minimizado e as condições de operação do sistema de distribuição de energia elétrica (SDEE) sejam satisfeitas. Neste trabalho são propostas as técnicas de otimização metaheurística: Busca Tabu e GRASP para resolver o problema da coordenação do carregamento de veículos elétricos em sistemas de distribuição, modelado como um problema de programação não linear inteira mista. Posteriormente, é proposto um algoritmo híbrido chamado GRASP-BT com o objetivo principal de melhorar as soluções obtidas com as metodologias Busca Tabu e GRASP. As soluções propostas pelas metaheurísticas desenvolvidas neste trabalho indicam os períodos de tempo em que deve ser carregado cada veículo ligado no SDEE, minimizando os custos totais de operação, satisfazendo as restrições operacionais do SDEE, considerando prioridade de carregamento dos PEVs e permitindo a entrega de soluções de qualidade em tempo real. Para demonstrar a eficiência da metodologia proposta e a adaptação de cada metaheurística na resolução do problema, foi usado um sistema teste de 449 nós que considera os sistemas primário e secundário do SDEE e duas fontes de geração distribuída. Os testes são feitos com níveis de 47% e 63% de penetração de PEVs dentro do sistem