Effective Data Management Enables Intelligent Utility Management

Instrumentation and automation plays a vital role to managing the water industry. These systems generate vast amounts of data that must be effectively managed in order to enable intelligent decision making. Time series data management software, commonly known as data historians are used for collecting and managing real-time (time series) information. More advanced software solutions provide a data infrastructure or utility wide Operations Data Management System (ODMS) that stores, manages, calculates, displays, shares, and integrates data from multiple disparate automation and business systems that are used daily in water utilities. These ODMS solutions are proven and have the ability to manage data from smart water meters to the collaboration of data across third party corporations. This paper focuses on practical, utility successes in the water industry where utility managers are leveraging instantaneous access to data from proven, commercial off-the-shelf ODMS solutions to enable better real-time decision making. Successes include saving $650,000 / year in water loss control, safeguarding water quality, saving millions of dollars in energy management and asset management. Immediate opportunities exist to integrate the research being done in academia with these ODMS solutions in the field and to leverage these successes to utilities around the world.

Reservoir Management For Flood And Drought Protection Using Infinite Horizon Model Predictive Control

Model Predictive Control (MPC) is a control method that solves in real time an optimal control problem over a finite horizon. The finiteness of the horizon is both the reason of MPC's success and its main limitation. In operational water resources management, MPC has been in fact successfully employed for controlling systems with a relatively short memory, such as canals, where the horizon length is not an issue. For reservoirs, which have generally a longer memory, MPC applications are presently limited to short term management only. Short term reservoir management can be effectively used to deal with fast process, such as floods, but it is not capable of looking sufficiently ahead to handle long term issues, such as drought. To overcome this limitation, we propose an Infinite Horizon MPC (IH-MPC) solution that is particularly suitable for reservoir management. We propose to structure the input signal by use of orthogonal basis functions, therefore reducing the optimization argument to a finite number of variables, and making the control problem solvable in a reasonable time. We applied this solution for the management of the Manantali Reservoir. Manantali is a yearly reservoir located in Mali, on the Senegal river, affecting water systems of Mali, Senegal, and Mauritania. The long term horizon offered by IH-MPC is necessary to deal with the strongly seasonal climate of the region.

Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.

Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for large-scale systems. Nonetheless, a critical obstacle, which needs to be overcome in MPC, is the large computational burden when a large-scale system is considered or a long prediction horizon is involved. In order to solve this problem, we use an adaptive prediction accuracy (APA) approach that can reduce the computational burden almost by half. The proposed MPC scheme with this scheme is tested on the northern Dutch water system, which comprises Lake IJssel, Lake Marker, the River IJssel and the North Sea Canal. The simulation results show that by using the MPC-APA scheme, the computational time can be reduced to a large extent and a flood protection problem over longer prediction horizons can be well solved.

Exchange rate management techniques

This briefing note addresses the question: What revisions of financial regulation and financial governance in Brazil are necessary to support Brazilian development? What’s in place and what’s missing? The focus here is a dimension of financial regulation and governance: the regulation of capital flows and of exchange rate operations. The arguments are organized in the following manner. In the next section, we summarize the impacts of th crisis on the emerging-market economies and on the regulation of the international monetary and financial system. The third section discusses the post-crisis dilemmas faced by these economies. Finally, the fourth section presents some policy recommendations for Brazil.

Structuring a startup's operations in an emerging market

The present work analyzes the establishment of a startup’s operations and the structuring all of the processes required to start up the business, launch the platform and keep it working. The thesis’ main focus can therefore be described as designing and structuring a startup’s operations in an emerging market before and during its global launch. Such business project aims to provide a successful case regarding the creation of a business and its launch into an emerging market, by illustrating a practical example on how to structure the business’ operations within a limited time frame. Moreover, this work will also perform a complete economic analysis of Brazil, thorough analyses of the industries the company is related to, as well as a competitive analysis of the market the venture operates in. Furthermore, an assessment of the venture’s business model and of its first six-month performance will also be included. The thesis’ ultimate goal lies in evaluating the company’s potential of success in the next few years, by highlighting its strengths and criticalities. On top of providing the company’s management with brilliant findings and forecasts about its own business, the present work will represent a reference and a practical roadmap for any entrepreneur willing to establish his operations in Brazil.

Applying supply chain management models in the banking industry: a brazilian case analysis

The study presents the results and recommendations deriving from the application of two supply chain management analysis models as proposed by the Supply Chain Council (SCOR, version 10.0) and by Lambert (1997, Framework for Supply Chain Management) on the logistics of cash transfers in Brazil. Cash transfers consist of the transportation of notes to and from each node of the complex network formed by the bank branches, ATMs, armored transportation providers, the government custodian, Brazilian Central Bank and financial institutions. Although the logistic to sustain these operations is so wide-ranged (country-size), complex and subject to a lot of financial regulations and security procedures, it has been detected that it was probably not fully integrated. Through the use of a primary and a secondary data research and analysis, using the above mentioned models, the study ends up with propositions to strongly improve the operations efficiency

Effects of dredging operations on sediment quality: contaminant mobilization in dredged sediments from the Port of Santos, SP, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effects of plant densities and management of purple nutsedge on sugarcane yield and effect of growth stages and main way of herbicides contact and absorption on the control of tubers

Field experiments carried out with Cyperus rotundus L. at low (58-246), medium (318773), and high (675-1198 shoots/m(2)) densities showed sugarcane yield reductions of 13.5, 29.3, and 45.2%, respectively in relation to the control. In the second field experiment, the integration of a mechanic method with two sequences of plowing and disking operations in the dry season, and complementary applications of trifloxysulfuron-sodium + ametrine and sulfentrazone (rainy season) was studied. Average of the chain connected to original shoot showed 92, 95, and 65% of reduction with trifloxysulfuron-sodium + ametrine and surfactant, at the application stages early, preflowering, and full flowering, respectively.

Environmental management system and human resource practices: is there a link between them in four Brazilian companies?

The aim of this article is to analyze the theoretical model proposed by [Jabbour CJC, Santos FCA. Relationships between human resource dimensions and environmental management in companies: proposal of a model. Journal of Cleaner Production 2008;16(1):5 1-8.] based on the data collected in four Brazilian companies. This model investigates how the phases of the environmental management system can be linked to human resource practices in order to attain continuous improvement of a company's environmental performance. Our aim is to contribute to a field, which has little empirical evidence. Although the interaction between the phases of the environmental management system and human resource practices is recommended by the specialized literature [Daily BE Huang S. Achieving sustainability through attention to human resource factors in environmental management. International Journal of Operations and Production Management 2001:21(12):1539-52.], the results indicate that most of the theoretical assumptions could not be confirmed in these Brazilian companies. (C) 2008 Elsevier Ltd. All rights reserved.

Modeling and analysis of artificial neural networks applied in operations research

Artificial neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements. Systems based on artificial neural networks have high computational rates due to the use of a massive number of these computational elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving problems related to operations research. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

Knowledge-based integrated production management model

Purpose - This paper aims to propose a model of production management that integrates knowledge management, as a third dimension, to the production and work dimensions and to identify factors that promote a favorable context for knowledge sharing and results achievement in the production operations shop floor environment.Design/methodology/approach - The model proposed is built from opportunities identified in the literature review.Findings - The factors in the model integrate its three main components: knowledge management, production organization and work organization, providing a representation of the dynamics of the workplace and shop floor environment.Practical implications - The proposed model and its factors allow managers to better understand and to improve the organization activities, because it integrates knowledge management with the production organization and work organization components of traditional models.Originality/value - Literature acknowledges the role of knowledge as competitive advantage, but it is still dealt in an implicit way within the traditional models of production management. This paper proposes a model and factors that provide a favorable context for tacit knowledge sharing and results achievement in the production operations shop floor environment. The model explicitly integrates knowledge management with traditional models' components.

Interspecific fish hybrids in Brazil: management of genetic resources for sustainable use

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Stock assessment and fishery management of the pink shrimp Farfantepenaeus brasiliensis Latreille, 1970 and F. paulensis Pérez-Farfante, 1967 in Southeastern Brazil (23° to 28° S)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)