Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: a comparative study

The uncertainties of renewable energy have brought great challenges to power system commitment, dispatches and reserve requirement. This paper presents a comparative study on integration of renewable generation uncertainties into SCUC (stochastic security-constrained unit commitment) considering reserve and risk. Renewable forecast uncertainties are captured by a list of PIs (prediction intervals). A new scenario generation method is proposed to generate scenarios from these PIs. Different system uncertainties are considered as scenarios in the stochastic SCUC problem formulation. Two comparative simulations with single (E1: wind only) and multiple sources of uncertainty (E2: load, wind, solar and generation outages) are investigated. Five deterministic and four stochastic case studies are performed. Different generation costs, reserve strategies and associated risks are compared under various scenarios. Demonstrated results indicate the overall costs of E2 is lower than E1 due to penetration of solar power and the associated risk in deterministic cases of E2 is higher than E1. It implies the superimposed effect of uncertainties during uncertainty integration. The results also demonstrate that power systems run a higher level of risk during peak load hours, and that stochastic models are more robust than deterministic ones.

Renewable energy integration : challenges and solutions

This book presents different aspects of renewable energy integration, from the latest developments in renewable energy technologies to the currently growing smart grids. The importance of different renewable energy sources is discussed, in order to identify the advantages and challenges for each technology. The rules of connecting the renewable energy sources have also been covered along with practical examples. Since solar and wind energy are the most popular forms of renewable energy sources, this book provides the challenges of integrating these renewable generators along with some innovative solutions. As the complexity of power system operation has been raised due to the renewable energy integration, this book also includes some analysis to investigate the characteristics of power systems in a smarter way. This book is intended for those working in the area of renewable energy integration in distribution networks.

Newly Automated System For Integrated Assessment Of The Conditions Of Underwater Gas Pipelines

An underwater gas pipeline is the portion of the pipeline that crosses a river beneath its bottom. Underwater gas pipelines are subject to increasing dangers as time goes by. An accident at an underwater gas pipeline can lead to technological and environmental disaster on the scale of an entire region. Therefore, timely troubleshooting of all underwater gas pipelines in order to prevent any potential accidents will remain a pressing task for the industry. The most important aspect of resolving this challenge is the quality of the automated system in question. Now the industry doesn't have any automated system that fully meets the needs of the experts working in the field maintaining underwater gas pipelines. Principle Aim of this Research: This work aims to develop a new system of automated monitoring which would simplify the process of evaluating the technical condition and decision making on planning and preventive maintenance and repair work on the underwater gas pipeline. Objectives: Creation a shared model for a new, automated system via IDEF3; Development of a new database system which would store all information about underwater gas pipelines; Development a new application that works with database servers, and provides an explanation of the results obtained from the server; Calculation of the values MTBF for specified pipelines based on quantitative data obtained from tests of this system. Conclusion: The new, automated system PodvodGazExpert has been developed for timely and qualitative determination of the physical conditions of underwater gas pipeline; The basis of the mathematical analysis of this new, automated system uses principal component analysis method; The process of determining the physical condition of an underwater gas pipeline with this new, automated system increases the MTBF by a factor of 8.18 above the existing system used today in the industry.

Evaluation Of Reservoir Model Integration With Deterministic And Probabilistic Streamflow Forecasts

Due to the increase in water demand and hydropower energy, it is getting more important to operate hydraulic structures in an efficient manner while sustaining multiple demands. Especially, companies, governmental agencies, consultant offices require effective, practical integrated tools and decision support frameworks to operate reservoirs, cascades of run-of-river plants and related elements such as canals by merging hydrological and reservoir simulation/optimization models with various numerical weather predictions, radar and satellite data. The model performance is highly related with the streamflow forecast, related uncertainty and its consideration in the decision making. While deterministic weather predictions and its corresponding streamflow forecasts directly restrict the manager to single deterministic trajectories, probabilistic forecasts can be a key solution by including uncertainty in flow forecast scenarios for dam operation. The objective of this study is to compare deterministic and probabilistic streamflow forecasts on an earlier developed basin/reservoir model for short term reservoir management. The study is applied to the Yuvacık Reservoir and its upstream basin which is the main water supply of Kocaeli City located in the northwestern part of Turkey. The reservoir represents a typical example by its limited capacity, downstream channel restrictions and high snowmelt potential. Mesoscale Model 5 and Ensemble Prediction System data are used as a main input and the flow forecasts are done for 2012 year using HEC-HMS. Hydrometeorological rule-based reservoir simulation model is accomplished with HEC-ResSim and integrated with forecasts. Since EPS based hydrological model produce a large number of equal probable scenarios, it will indicate how uncertainty spreads in the future. Thus, it will provide risk ranges in terms of spillway discharges and reservoir level for operator when it is compared with deterministic approach. The framework is fully data driven, applicable, useful to the profession and the knowledge can be transferred to other similar reservoir systems.

Um modelo de EIS - enterprise information system - que identifica características para comportamentos proativos na recuperação de informações

Este documento constitui uma dissertação de mestrado, requisito parcial para a obtenção do grau de Mestre em Administração pela Universidade Federal do Rio Grande do Sul. O tema da pesquisa é o relacionamento existente entre as características técnicas de um projeto de sistema de informação e apoio à decisão e os comportamentos dos usuários no seu uso. O objetivo é desenvolver e apresentar um modelo conceitual de EIS (“Enterprise Information Systems”), a partir da literatura, das tendências tecnológicas e de estudos de caso, que identifique características para comportamentos proativos dos usuários na recuperação de informações. Adotou-se o conceito de comportamento proativo na recuperação de informações como a combinação das categorias exploração de dados e busca focada. Entre os principais resultados, pode-se destacar a definição de categorias relacionadas com as características dos sistemas - flexibilidade, integração e apresentação - e de categorias relacionadas com os comportamentos dos usuários na recuperação de informações - exploração de dados e busca focada, bem como a apresentação de um modelo conceitual para sistemas EIS. Pode-se destacar também a exploração de novas técnicas para análise qualitativa de dados, realizada com o objetivo de buscar uma maior preservação do contexto nos estudos de caso.

Seven stories: location based story-delivery system

Location aware content-based experiences have a substantial tradition in HCI, several projects over the last two decades have explored the association of digital media to specific locations or objects. However, a large portion of the literature has little focus on the creative side of designing of the experience and on the iterative process of user evaluations. In this thesis we present two iterations in the design and evaluation of a location based story delivery system (LBSDS), inspired by local folklore and oral storytelling in Madeira. We started by testing an already existing location based story platform, PlaceWear, with short multimedia clips that recounted local traditions and folktales, to this experience we called iLand. An initial evaluation of iLand, was conducted; we shadowed users during the experience and then they responded to a questionnaire. By analyzing the evaluation results we uncovered several issues that informed the redesign of the system itself as well as part of the story content. The outcome of this re design was the 7Stories experience. In the new experience we performed the integration of visual markers in the interface and the framing of the fragmented story content through the literary technique of the narrator. This was done aiming to improving the connection of the audience to the physical context where the experience is delivered. The 7Stories experience was evaluated following a similar methodology to the iLand evaluation but the user’s experience resulted considerably different; because of the same setting for the experience in both versions and the constancy of the most of the content across the two versions we were able to assess the specific effect of the new design and discuss its strengths and shortcomings. Although we did not run a formal and strict comparative test between the two evaluations, it is evident from the collected data how the specific design changes to our LBSDS influenced the user experience.

Using Neo4J geospatial data storage and integration

Online geographic-databases have been growing increasingly as they have become a crucial source of information for both social networks and safety-critical systems. Since the quality of such applications is largely related to the richness and completeness of their data, it becomes imperative to develop adaptable and persistent storage systems, able to make use of several sources of information as well as enabling the fastest possible response from them. This work will create a shared and extensible geographic model, able to retrieve and store information from the major spatial sources available. A geographic-based system also has very high requirements in terms of scalability, computational power and domain complexity, causing several difficulties for a traditional relational database as the number of results increases. NoSQL systems provide valuable advantages for this scenario, in particular graph databases which are capable of modeling vast amounts of inter-connected data while providing a very substantial increase of performance for several spatial requests, such as finding shortestpath routes and performing relationship lookups with high concurrency. In this work, we will analyze the current state of geographic information systems and develop a unified geographic model, named GeoPlace Explorer (GE). GE is able to import and store spatial data from several online sources at a symbolic level in both a relational and a graph databases, where several stress tests were performed in order to find the advantages and disadvantages of each database paradigm.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

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

Integrated sediment quality assessment in Paranagua Estuarine System, Southern Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Operational parameters of soybean seeding in santa fe system

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

Potassium cycling in a corn-brachiaria cropping system

Growing corn mixed with forage crops can be an alternative for pasture and Mulch production during relatively dry winters in tropical areas, making no-till feasible in some regions. However, little is known about nutrient dynamics in this cropping system. The objective of the present work was to evaluate K dynamics in a production system in which corn was either grown as a sole crop or mixed with Brachiaria brizantha. In the second year of the experiment, nitrogen rates ranging from 0 to 200 kg ha(-1) were applied to the system. Dry matter yields and potassium contents in the soil, as well as residues and plants were determined at corn planting and harvest. Potassium balance in the system was calculated. Corn grain yield in mixed crop responded up to 200 kg ha(-1) N. The introduction of brachiaria in the system resulted in higher amounts of straw on the soil Surface and higher K recycling. Soil exchangeable K balance showed an excess K for both N rates only in the mixed system, however, when non-exchangeable K was also included in calculations, excess K was found in both mixed and sole corn systems. Large amounts of non-exchangeable K were taken up in the system involving brachiaria, which showed a considerable capacity in recycling K, increasing its contents in the surface soil layer. (c) 2008 Elsevier B.V. All rights reserved.

Integration of a regional GPS network within ITRF using precise point positioning

GPS precise point positioning (PPP) can provide high precision 3-D coordinates. Combined pseudorange and carrier phase observables, precise ephemeris and satellite clock corrections, together with data from dual frequency receivers, are the key factors for providing such levels of precision (few centimeters). In general, results obtained from PPP are referenced to an arbitrary reference frame, realized from a previous free network adjustment, in which satellite state vectors, station coordinates and other biases are estimated together. In order to obtain consistent results, the coordinates have to be transformed to the relevant reference frame and the appropriate daily transformation parameters must be available. Furthermore, the coordinates have to be mapped to a chosen reference epoch. If a velocity field is not available, an appropriated model, such as NNR-NUVEL-IA, has to be used. The quality of the results provided by this approach was evaluated using data from the Brazilian Network for Continuous Monitoring of the Global Positioning System (RBMC), which was processed using GIPSY-OASIS 11 software. The results obtained were compared to SIRGAS 1995.4 and ITRF2000, and reached precision better than 2cm. A description of the fundamentals of the PPP approach and its application in the integration of regional GPS networks with ITRF is the main purpose of this paper.

The Impact of Domestic Politics and International Changes on the Brazilian Perception of Regional Integration

This article aims to analyze the impact of domestic politics and international changes that influence Brazilian positions regarding regional integration processes in South America, particularly the Southern Common Market, Mercosur. The dynamics of the international system and their impact on the evolution of the elite's perception of the role the country should play in the world are important variables for understanding these positions. The state's postures in relation to integration were and are based on a real interest, but this interest is also linked with the objective of ensuring better conditions for participation in other international arenas. Starting with the hypothesis that transformations in the international setting have strongly influenced Brazil's positioning, the elements of continuity and change in the country's behavior toward Mercosur are identified, with domestic politics as the main explanation.

An intelligent system to real time rainfall prediction using radar data

This work presents a new approach for rainfall measurements making use of weather radar data for real time application to the radar systems operated by institute of Meteorological Research (IPMET) - UNESP - Bauru - SP-Brazil. Several real time adjustment techniques has been presented being most of them based on surface rain-gauge network. However, some of these methods do not regard the effect of the integration area, time integration and distance rainfall-radar. In this paper, artificial neural networks have been applied for generate a radar reflectivity-rain relationships which regard all effects described above. To evaluate prediction procedure, cross validation was performed using data from IPMET weather Doppler radar and rain-gauge network under the radar umbrella. The preliminary results were acceptable for rainfalls prediction. The small errors observed result from the spatial density and the time resolution of the rain-gauges networks used to calibrate the radar.

An Innovative Crop-Forage Intercrop System: Early Cycle Soybean Cultivars and Palisadegrass

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