Integration of numerical models in geographic databases: the case of Sado estuary management

Geographic information systems (GIS) are now widely applied in coastal resource management. Their ability to organise and interface information from a large range of public and private data sources, and their ability to combine this information, using management criteria, to develop a comprehensive picture of the system explains the success of GIS in this area. The use of numerical models as a tool to improve coastal management is also widespread. Less usual is a GIS-based management to ol implementing a comprehensive management model and integrating a numerical modelling system into itself. In this paper such a methodology is proposed. A GIS-based management tool based on the DPSIR model is presented. An overview of the MOHID numerical modelling system is given and the method of integrating this model in the management tool is described. This system is applied to the Sado Estuary (Portugal). Some preliminary results of the integration are presented, demonstrating the capabilities of the management system.

A system approach framework to the management of lake Baringo, Kenya

Dissertação de Mestrado, Gestão da Água e da Costa, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2010

Hydrodynamic and sediment fluxes through the inlets of the Ria Formosa

Tese de dout., Ciências do Mar, da Terra e do Ambiente (Ciências do Mar-Oceanografia Física), Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2011

Beach quality assessment and management in the Sotavento (Eastern) Algarve, Portugal

The purpose of this study on beach quality assessment and management was to evaluate the quality of five beaches in the Algarve Sotavento region of Portugal and to identify beach users’ preferences and priorities regarding their visit to a beach. The Algarve is one of the country’s most internationally known regions and it is generally perceived as a major tourist destination. Because of the increasing level of tourists, there is a specific need to address beach quality, as overcrowding can result in excessive litter, reduce water quality and consequently reduce the socio-economic value of the area. The main methodology for the evaluation of the beach quality in this pilot project was the Bathing Area Registration and Evaluation framework (BARE), which recognizes five beach types (rural, remote, resort, urban and village) through five main priority issues of concern to beach users (water quality, scenery, litter, safety, facilities) and evaluates the beach quality, ranging from one (low) to five (high) stars. After overall bathing area classification, Quarteira-Vilamoura, Ilha do Farol, Ilha Deserta and Ilha da Armona received three-star rating and Quinta do Lago site obtained a one-star rating. The quantitative research data on beach users’ preferences and priorities was obtained through administration of 50 questionnaires per beach and showed that beach users at all sites expressed the need for improved cleanliness, safety and facilities on the beach. The BARE framework, together with the questionnaire surveys, allowed the identification of management priorities required to improve the quality of individual beaches and therefore increase income from tourism.

Introducing Game Development into the Computing Curriculum: a Progressive Methodology

The Computer Game industry is big business, the demand for graduates is high, indeed there is a continuing shortage of skilled employees. As with most professions, the skill set required is both specific and diverse. There are currently over 30 Higher Education Institutions (HEIs) in the UK offering Computer games related courses. We expect that as the demand from the industry is sustained, more HEIs will respond with the introduction of game-related degrees. This is quite a considerable undertaking involving many issues from integration of new modules or complete courses within the existing curriculum, to staff development. In this paper we share our experiences of introducing elements of game development into our curriculum. This has occurred over the past two years, starting with the inclusion of elements of game development into existing programming modules, followed by the validation of complete modules, and culminating in a complete degree course. Our experience is that our adopting a progressive approach to development, spread over a number of years, was crucial in achieving a successful outcome.

The Contribution of Academic Scholarship to Management Development.

Purpose: This paper explores the impact of academic scholarship on the development and practice of experienced managers. Design / Methodology: Semi-structured interviews with experienced managers, modelled on the critical incident technique. ‘Intertextuality’ and framework analysis technique are used to examine whether the use of academic scholarship is a sub-conscious phenomenon. Findings: Experienced managers make little direct use of academic scholarship, using it only occasionally to provide retrospective confirmation of decisions or a technique they can apply. However, academic scholarship informs their practice in an indirect way, their understanding of the ‘gist’ of scholarship comprising one of many sources which they synthesise and evaluate as part of their development process. Practical implications: Managers and management development practitioners should focus upon developing skills of synthesising the ‘gist’ of academic scholarship with other sources of data, rather than upon the detailed remembering, understanding and application of specific scholarship, and upon finding / providing the time and space for that ‘gisting’ and synthesis to take place. Originality / Value: The paper addresses contemporary concerns about the appropriateness of the material delivered on management education programmes for management development. It is original in doing this from the perspective of experienced managers, and in using intertextual analysis to reveal not only the direct but also the indirect uses of they make of such scholarship. The finding of the importance of understanding the ‘gist’ rather than the detail of academic theory represents a key conceptual innovation.

A generic model for integration of Quality, Environment and Safety Management Systems

Purpose – The purpose of this paper is to propose a generic model of Integrated Management System of Quality, Environment and Safety (IMS-QES) that can be adapted and progressively to assimilate various Management Systems, of which highlights: ISO 9001 for Quality; ISO 14001 for Environment; OHSAS 18001 for Occupational Health and Safety. Design/methodology/approach – The model was designed in the real environment of a Portuguese Organization and 160 employees were surveyed. The rate response was equal to 86 percent. The conceived model was implemented in a first phase for the integration of Quality, Environment and Safety Management Systems. Findings – Among the main findings of the survey the paper highlights: the elimination of conflicts between individual systems with resources optimization; creation of added value to the business by eliminating several types of wastes; the integrated management of sustainability components in a global market; the improvement of partnerships with suppliers of goods and services; reducing the number of internal and external audits. Originality/value – This case study is one of the first Portuguese empirical researches about IMS-QES and the paper believes that it can be useful in the creation of a Portuguese guideline for integration, namely the Quality Management Systems; Environmental Management Systems and Occupational Health and Safety Management Systems among others.

Integration of Standardized Management Systems: A Dilemma?

Abstract: The growing proliferation of management systems standards (MSSs), and their individualized implementation, is a real problem faced by organizations. On the other hand, MSSs are aimed at improving efficiency and effectiveness of organizational responses in order to satisfy the requirements, needs and expectations of the stakeholders. Each organization has its own identity and this is an issue that cannot be neglected; hence, two possible approaches can be attended. First, continue with the implementation of individualized management systems (MSs); or, integrate the several MSSs versus related MSs into an integrated management system (IMS). Therefore, in this context, organizations are faced with a dilemma, as a result of the increasing proliferation and diversity of MSSs. This paper takes into account the knowledge gained through a case study conducted in the context of a Portuguese company and unveils some of the advantages and disadvantages of integration. A methodology is also proposed and presented to support organizations in developing and structuring the integration process of their individualized MSs, and consequently minimize problems that are generators of inefficiencies, value destruction and loss of competitiveness. The obtained results provide relevant information that can support Top Management decision in solving that dilemma and consequently promote a successful integration, including a better control of business risks associated to MSSs requirements and enhancing sustainable performance, considering the context in which organizations operate.

A congestion management and transmission price simulator for competitive electricity markets

In a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.

Long-term price range forecast applied to risk management using regression models

Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level α. Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.

Virtual power players demand response programs management based on locational marginal prices

Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Intelligent management of end consumers loads including electric vehicles through a SCADA system

The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

Intelligent energy resource management considering vehicle-to-grid: A simulated annealing approach

This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.