• Energy Research

Abstract The organizational structure of the companies in the biomass energy sector, regarding the supply chain management services, can be greatly improved through the use of software decision support tools. These tools should be able to provide real-time alternative scenarios when deviations from the initial production plans are observed. To make this possible it is necessary to have representative production chain process models where several scenarios and solutions can be evaluated accurately. Due to its nature, this type of process is more adequately represented by means of event-based models. In particular, this work presents the modelling of a typical biomass production chain using the computing platform SIMEVENTS. Throughout the article details about the conceptual model, as well as simulation results, are provided.

Abstract The organizational structure of the companies in the biomass energy sector, regarding the supply chain management services, can be greatly improved through the use of software decision support tools. These tools should be able to provide real-time alternative scenarios when deviations from the initial production plans are observed. To make this possible it is necessary to have representative production chain process models where several scenarios and solutions can be evaluated accurately. Due to its nature, this type of process is more adequately represented by means of event-based models. In particular, this work presents the modelling of a typical biomass production chain using the computing platform SIMEVENTS. Throughout the article details about the conceptual model, as well as simulation results, are provided.

Distributed power sources will become increasingly ubiquitous in the near future. In this power production paradigm, photovoltaic conversion systems will play a fundamental role due to the growing tendency of energy price, and an opposed trend for the photovoltaic panels. This will lead to increased pressure for the installation of this particular renewable energy source in home buildings. In particular, on-grid photovoltaic systems where the generated power can be injected directly to the main power grid. This strategy requires the use of DC-AC inverters whose output is synchronized, in phase, with the main grid voltage. In order to provide steady output in the presence of load disturbances, the inverter must work in closed-loop. This work presents a new way to design an inverter controller by resorting to the CDM design technique. The obtained results suggest that the controller achieved with this method, although simpler than other methods, leads to an acceptable and robust closed-loop response.

Distributed power sources will become increasingly ubiquitous in the near future. In this power production paradigm, photovoltaic conversion systems will play a fundamental role due to the growing tendency of energy price, and an opposed trend for the photovoltaic panels. This will lead to increased pressure for the installation of this particular renewable energy source in home buildings. In particular, on-grid photovoltaic systems where the generated power can be injected directly to the main power grid. This strategy requires the use of DC-AC inverters whose output is synchronized, in phase, with the main grid voltage. In order to provide steady output in the presence of load disturbances, the inverter must work in closed-loop. This work presents a new way to design an inverter controller by resorting to the CDM design technique. The obtained results suggest that the controller achieved with this method, although simpler than other methods, leads to an acceptable and robust closed-loop response.

Supply chains are complex interdependent structures in which tasks' accomplishment is the result of a compromise between all the entities involved. This complexity is particularly pronounced when dealing with chipping and transportation tasks within a forest-based biomass energy production supply chain. The logistic costs involved are significant and the number of network nodes are usually in a considerable number. For this reason, efficient optimization tools should be used in order to derive cost effective scheduling. In this work, soft computing optimization tools, namely genetic algorithms (GA) and particle swarm optimization (PSO), are integrated within a discrete event simulation model to define the vehicles operational schedule in a typical forest biomass supply chain. The presented simulation results show the proposed methodology effectiveness in dealing with the addressed systems.

Supply chains are complex interdependent structures in which tasks' accomplishment is the result of a compromise between all the entities involved. This complexity is particularly pronounced when dealing with chipping and transportation tasks within a forest-based biomass energy production supply chain. The logistic costs involved are significant and the number of network nodes are usually in a considerable number. For this reason, efficient optimization tools should be used in order to derive cost effective scheduling. In this work, soft computing optimization tools, namely genetic algorithms (GA) and particle swarm optimization (PSO), are integrated within a discrete event simulation model to define the vehicles operational schedule in a typical forest biomass supply chain. The presented simulation results show the proposed methodology effectiveness in dealing with the addressed systems.

Supply chains are ubiquitous in any commercial delivery systems. The exchange of goods and services, from different supply points to distinct destinations scattered along a given geographical area, requires the management of stocks and vehicles fleets in order to minimize costs while maintaining good quality services. Even if the operating conditions remain constant over a given time horizon, managing a supply chain is a very complex task. Its complexity increases exponentially with both the number of network nodes and the dynamical operational changes. Moreover, the management system must be adaptive in order to easily cope with several disturbances such as machinery and vehicles breakdowns or changes in demand. This work proposes the use of a model predictive control paradigm in order to tackle the above referred issues. The obtained simulation results suggest that this strategy promotes an easy tasks rescheduling in case of disturbances or anticipated changes in operating conditions.

Supply chains are ubiquitous in any commercial delivery systems. The exchange of goods and services, from different supply points to distinct destinations scattered along a given geographical area, requires the management of stocks and vehicles fleets in order to minimize costs while maintaining good quality services. Even if the operating conditions remain constant over a given time horizon, managing a supply chain is a very complex task. Its complexity increases exponentially with both the number of network nodes and the dynamical operational changes. Moreover, the management system must be adaptive in order to easily cope with several disturbances such as machinery and vehicles breakdowns or changes in demand. This work proposes the use of a model predictive control paradigm in order to tackle the above referred issues. The obtained simulation results suggest that this strategy promotes an easy tasks rescheduling in case of disturbances or anticipated changes in operating conditions.

Abstract The improvement of energy performance in buildings can be achieved through the integration of a Trombe wall system. The literature review reveals that more research work is still required to evaluate the real impact of this system on the building thermal performance. The study here presented aims to define a calculation methodology of the Trombe wall energy performance, based on ISO 13790:2008(E), adapted to the Portuguese climatic conditions. The massive wall thickness, the ventilation system and the external shutters influence in the system thermal performance is demonstrated. It was concluded that the highest contributions to the global heat gains is given by the heat transfer by conduction, convection and radiation. However, the existence of a ventilation system in the massive wall has a significant role in the thermal performance of the Trombe wall, which contribution increases with the increasing of the massive wall thickness. It was also applied the Portuguese thermal regulation to a residential building with this system. It was concluded that energy heating needs can be reduced in 16.36% if a Trombe wall is added to the building envelope. The results also showed that the proposed methodology provides a valid approach to compute the Trombe wall thermal performance.