Moisès Graells

Characterization of the degradation performance of the sulfamethazine antibiotic by photo-Fenton process.

The present study provides results describing the degradation performance of the Sulfamethazine (SMT) antibiotic via photo-Fenton treatment. Experiments were carried out using 1 L solution samples of SMT (50 mg L(-1)) under different conditions. HPLC results reveal that both Fenton and photo-Fenton reactions were able to completely remove SMT antibiotic from the studied samples in less than 2 min treatment. Half-life times and kinetic parameters (assuming a pseudo-first-order kinetics at reaction initial stage, far from the equilibrium) for SMT degradation were determined and discussed. Hence, appropriate Fenton reagent loads are given to attain different targets proposed. TOC and HPLC data also revealed the presence of reaction intermediates; thus toxicity assays were performed regarding bacterial growth rate. The toxicity of an SMT solution was shown to increase during its degradation by means of photo-Fenton reactions.

Global strategy for energy and waste analysis in scheduling and planning of multiproduct batch chemical processes

Abstract Energy integration and waste minimization have received increasing attention in the chemical industry. Recent studies have addressed the specific problems that arise in batch chemical processes. However, a production plan built up using schedules developed beforehand may become inefficient or even fail to attain its production targets. Furthermore, production plans satisfying demand objectives may reduce or even eliminate energy integration or waste minimization opportunities. In this work, waste and energy minimization are treated as an integral part of the constrained production scheduling problem with limited resources. The methodology developed is based on a comprehensive and rigorous modelling framework used to describe the detailed batch process operations as a preliminary step towards their optimization. The methodology will be presented and results from case studies will be provided to illustrate the complex interaction between energy integration, waste minimization and production planning in multiproduct batch processes.

Flexible System Integration and Advanced Hierarchical Control Architectures in the Microgrid Research Laboratory of Aalborg University

This paper presents the system integration and hierarchical control implementation in an inverter-based Microgrid Research Laboratory (MGRL) at Aalborg University, Denmark. MGRL aims to provide a flexible experimental platform for comprehensive studies of microgrids. The structure of the laboratory, including the facilities, configurations, and communication network, is first introduced. The complete control system is based on a generic hierarchical control scheme including primary, secondary, and tertiary control. Primary control loops are developed and implemented in digital control platform, while system supervision, advanced secondary, and tertiary management are realized in a microgrid central controller. The software and hardware schemes are described. Several example case studies are introduced and performed to achieve power quality regulation, energy management, and flywheel energy storage system control. Experimental results are presented to show the performance of the whole system.

General approach and tool for the scheduling of complex production systems

Abstract The aim of this paper is to present a flexible modelling framework implemented into a basic general scheduling tool for both, the study of scheduling problems (for application developers and analysts) and as an efficient way to find practical solutions in complex industrial applications (for users). Thus, the basis to assist process modelling (simulation and simple optimisation procedures) is provided as well as an open framework capable to be easily customised (implementation of particular constraints, rules, exceptions, etc.). This approach and tool have been especially addressed to complex manufacturing systems (batch chemical processes, pharmaceutical, fine chemicals, etc.). Thus, the kind of recipes considered require a detailed description of tasks and subtasks and of the hard time and storage constraints implicated (simultaneous activities, unstable intermediates, product synthesis and other concurrent processes…). Towards this end, this work presents a general and practical description of production processes and recipes, as well as the mathematical model for the timing of the activities involved. Yet, the compact description attained does not introduce extra complexity to simpler cases. The approach introduced is based in a hierarchical description of the production processes and activities in which schedules are described by means of sequences of production runs associated to structured sets of assigned activities. This work shows how this sequences may be rearranged using general techniques as simulated annealing (SA), proving that this can be successful when specific rules are not available. Finally, different case studies are analysed to show the potential and flexibility of the approach presented.

Mixed-Integer-Linear-Programming-Based Energy Management System for Hybrid PV-Wind-Battery Microgrids: Modeling, Design, and Experimental Verification

Microgrids are energy systems that aggregate distributed energy resources, loads, and power electronics devices in a stable and balanced way. They rely on energy management systems to schedule optimally the distributed energy resources. Conventionally, many scheduling problems have been solved by using complex algorithms that, even so, do not consider the operation of the distributed energy resources. This paper presents the modeling and design of a modular energy management system and its integration to a grid-connected battery-based microgrid. The scheduling model is a power generation-side strategy, defined as a general mixed-integer linear programming by taking into account two stages for proper charging of the storage units. This model is considered as a deterministic problem that aims to minimize operating costs and promote self-consumption based on 24-hour ahead forecast data. The operation of the microgrid is complemented with a supervisory control stage that compensates any mismatch between the offline scheduling process and the real time microgrid operation. The proposal has been tested experimentally in a hybrid microgrid at the Microgrid Research Laboratory, Aalborg University.

Fault diagnosis of a benchmark fermentation process: a comparative study of feature extraction and classification techniques

This paper investigates fault diagnosis in batch processes and presents a comparative study of feature extraction and classification techniques applied to a specific biotechnological case study: the fermentation process model by Birol et al. (Comput Chem Eng 26:1553–1565, 2002), which is a benchmark for advanced batch processes monitoring, diagnosis and control. Fault diagnosis is achieved using four approaches on four different process scenarios based on the different levels of noise so as to evaluate their effects on the performance. Each approach combines a feature extraction method, either multi-way principal component analysis (MPCA) or multi-way independent component analysis (MICA), with a classification method, either artificial neural network (ANN) or support vector machines (SVM). The performance obtained by the different approaches is assessed and discussed for a set of simulated faults under different scenarios. One of the faults (a loss in mixing power) could not be detected due to the minimal effect of mixing on the simulated data. The remaining faults could be easily diagnosed and the subsequent discussion provides practical insight into the selection and use of the available techniques to specific applications. Irrespective of the classification algorithm, MPCA renders better results than MICA, hence the diagnosis performance proves to be more sensitive to the selection of the feature extraction technique.

Sequencing intermediate products: A practical solution for multipurpose production scheduling

Abstract In the present work, the production scheduling problem in multipurpose batch chemical plants operating under mixed intermediate storage policies is submitted to a new practical review leading to simplified and realistic solutions. Customer satisfaction is set as the main problem objective instead of minimization of well-known performance criteria such as makespan or flowtime and deviation of resulting production profile from desired deliveries is minimised using penalty functions including costs for stock and delay. The need to synchronise requirements and availability of the precise amounts of intermediates and products to a timetable is achieved by identifying multipurpose schedules as sequences of integers related to production runs of stable intermediates. Such a dramatic simplification of the problem allows the satisfactory use of stochastic optimization techniques (SA) for the matching of deliveries and due dates.

Microgrid central controller development and hierarchical control implementation in the intelligent microgrid lab of Aalborg University

This paper presents the development of a microgrid central controller in an inverter-based intelligent microgrid (iMG) lab in Aalborg University, Denmark. The iMG lab aims to provide a flexible experimental platform for comprehensive studies of microgrids. The complete control system applied in this lab is based on the hierarchical control scheme for microgrids and includes primary, secondary and tertiary control. The structure of the lab, including the lab facilities, configurations and communication network, is first introduced. Primary control loops are developed in MATLAB/Simulink and compiled to dSPACEs for local control purposes. In order to realize system supervision and proper secondary and tertiary management, a LabVIEW-based microgrid central controller is also developed. The software and hardware schemes are described. An example case is introduced and tested in the iMG lab for voltage/frequency restoration and voltage unbalance compensation. Experimental results are presented to show the performance of the whole system.

A rolling horizon rescheduling strategy for flexible energy in a microgrid

In this work an Energy Management System (EMS) prototype for an isolated renewable-based microgrid is presented. The proposed management model not only considers the management of energy sources (generation) but also includes the possibility of flexible timing of energy consumptions (demand management) by modelling controllable and uncontrollable loads. The EMS consists of two stages: first a deterministic management model is formulated and subsequently is integrated into a rolling horizon control strategy, in which the actions on microgrid devices respond to an optimization criterion related to the estimation of the future system behaviour that is continually predicted by updatable forecasts in order to reduce uncertainty in both, production capacity and energy demand. Finally, this contribution presents and discusses a case study where the results of the operation with and without optimal demand management for the same group of loads are evaluated.

Detailed Operation Scheduling and Control for Renewable Energy Powered Microgrids

Abstract The distributed paradigm is gaining popularity at the expense of the centralized production models inspired by the economy of scale. This includes energy transformation, storage and use, for which microgrids emerge as the most practical solution to interconnect and interoperate a network of energy dealers (typically known as producers and consumers, despite the conservation principle). Accordingly, the need for efficient management arises as a key issue not only in a specific planning or control level, but for all the hierarchy of decision levels. This work investigates the elements of a coordinated planning and control system for energy management in a microgrid.