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The purpose of thesis is to investigate the transient stability and operation feasibility of power islanding with different type of dispersed generation in distribution system. A substation of Taipower system is selected for case study to simulate the system transient stability. The mathematical models of dispersed generations including exciters, governors of gas turbine and pitch controller of wind-driven induction generator are used in the simulation program. To represent the load behavior more accurately, the load ratio of residence, commercial, industrial customer class and the composition of electric equipments in feeder, such as induction motors, air conditioners etc, have been identified through load survey study. The load models of end users are employed in simulation to solve the power consumption as function of bus voltage and system frequency. Besides, the dynamic model of induction motors is integrated to solve more accurate system power demand under transient condition. The simulation analysis of transient stability is executed for unbalance distribution system with dispersed generations of gas turbines and wind-driven turbines with three operations sceneries after the distribution system has been disconnected from Taipower system. Different load shedding schemes and output power control of dispersed generation are considered to maintain the stable operation of islanding power system. It is suggested that the system reliability of power system can be enhanced by the dispersed power generation with proper design of load shedding in the transient stability analysis.

Although power system load modelling is a mature research area, there is a renewed interest in updating available load models and formulating improved load modelling methodologies. The main drivers of this interest are the introduction of new types of non-conventional (e.g. power electronic interfaced) loads, the requirement to operate power supply systems with increasing levels of renewable distributed generation and the implementation of various load control functionalities (e.g. demand side management). As the majority of existing load models do not allow for a full and precise analysis of these new operating conditions, it is essential to develop new load models and update load modelling techniques. This thesis presents a detailed study of modern loads, focussing on the requirements for their correct representation in power system analysis. The developed models of the individual loads are then combined using a new load aggregation methodology for developing aggregate load models, suitable for the analysis of both existing and future power supply systems (so called ’smart grids’). The methodology uses a circuit-based load modelling approach, as this allows reproduction of the instantaneous current waveforms of the modelled load for any given supply voltage. This approach retains all electrical characteristics of the loads and provides a more realistic representation of some important phenomena (e.g. harmonic cancellation and attenuation due to load and supply system interactions) which are often neglected in traditional load modelling procedures. Case studies of the UK residential and commercial load sectors are presented as illustrations of the load aggregation methodology. The results show significant short-term and long-term temporal variations in the load characteristics, which are not available or reported in the existing literature. This information allows for a more comprehensive assessment of demand-side management functionalities and correlation with locally connected distributed generation. Both of these effects are investigated in the thesis by quantifying the possible extent and range of changes in power system performance for some expected near future changes in load configurations and network operating conditions.

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The aim of this study was to develop a load prognosis model for Uppsala district heating system to be used as a tool for heat production optimization. The methodwas to build three models for the different customer types; housing, industry andoffices and then scale them for the total system using data from Uppsala districtheating system. The heat load consists of two parts, one that is temperaturedependent and one that is dependent of the social behavior of the customers. Thetemperature part was modelled with an ARX model using an outdoor temperatureprognosis as input signal. The social behavior part was modelled using the mean ofthe social behavior from some days before and additionally by distinguishing betweenweekdays and weekends. The outcome was a model that would produce a prognosisfor the heat load for each customer type. The total model for the whole districtheating system was less accurate, but still usable. All models developed are howeverrelying on the quality of the available weather prognosis. The benefit of a precise loadprognosis is to facilitate production planning and optimization. Accurate predictions ofthe heat demand, especially in the case of peak load, will result in better productionplanning and thus cost efficiency.

O aumento nos limites de pesos estabelecidos pela legislação brasileira e o surgimento de novas combinações de veículos de carga nos últimos anos tornam necessária a verificação da segurança estrutural das pontes quando submetidas ao tráfego real. Este trabalho verifica o desempenho das obras de arte sob jurisdição do DER-SP através do índice de confiabilidade 'beta' e obtém limites para o peso de caminhões de modo a não comprometer sua integridade estrutural. São consideradas as superestruturas das pontes em concreto armado ou protendido, classes 36 e 45. Verifica-se o estado limite último nas seções transversais mais solicitadas por momento fletor positivo e negativo. No caso de pontes em concreto protendido, acrescenta-se o estado limite de formação de fissuras. Para a representação do tráfego real, é desenvolvido um modelo de carregamento móvel com base em pesagens de caminhões efetuadas em rodovias do estado de São Paulo. Admite-se a presença simultânea de veículos sobre a ponte e diferentes relações entre seus pesos. Os parâmetros estatísticos da resistência são determinados através da técnica de Monte Carlo. Apresenta-se os limites de peso em forma de equações, denominadas ECPLs (equações comprimento-peso limite), aplicáveis a quaisquer grupo de eixos consecutivos. Os resultados indicam restrições à circulação de algumas composições, especialmente ao rodotrem de 740 kN e 19,80 metros de comprimento. Considerando-se apenas o estado limite de serviço, as obras de arte classe 45 apresentam menores limites de peso devido à ponderação de ações durante o projeto / The increase in gross weight limits allowed by Brazilian legislation and the appearance of new truck configurations in last years require the assessment of bridges structural safety when submitted to real traffic. This thesis verifies the performance of the bridges under DER-SP jurisdiction using the reliability index 'beta' and obtains truck weight limits in order to guarantee its structural integrity. The superstructure of reinforced and prestressed concrete bridges, classes 36 and 45, is considered. The ultimate limit state is verified in cross sections submitted to critical positive and negative bending moments. In case of prestressed bridges, the tension limit state in concrete is added. To represent the real traffic, a live load model is developed based on weighting data collected from stations located at highways of the state of Sao Paulo. Multiple presence of vehicles over the bridge and different relations between weights are admitted. The statistical parameters of resistance are determined using the Monte Carlo technique. The gross weight limits are presented in the form of equations, known as bridge formulas, to be applied on any group of two or more consecutive axles. The results indicate restrictions to the traffic of some vehicles, especially the 740 kN and 19,80 meters length roadtrain. Considering only the serviceability limit state, bridges class 45 exhibit lower weight limits due to the load factors recommended by the code during design

The present doctoral thesis outlines a new model in psychological aesthetics, named the Information-Load Model. This model asserts that aesthetic appreciation is grounded in the relationship between the amount of information of stimuli and people’s capacity to process this information. This relationship results in information load, which in turn creates emotional responses to stimuli. Aesthetic appreciation corresponds to an optimal degree of information load. Initially, the optimal degree is relatively low. As an individual learns to master information in a domain (e.g., photography), the degree of information load, which corresponds to aesthetic appreciation, increases. The present doctoral thesis is based on three empirical papers that explored what factors determine aesthetic appreciation of photographs and soundscapes. Experiment 1 of Paper I involved 34 psychology undergraduates and 564 photographs of various motifs. It resulted in a set of 189 adjectives related to the degree of aesthetic appreciation of photographs. The subsequent experiments employed attribute scales that were derived from this set of adjectives. In Experiment 2 of Paper I, 100 university students scaled 50 photographs on 141 attribute scales. Similarly, in Paper II, 100 university students scaled 50 soundscapes on 116 attribute scales. In Paper III, 10 psychology undergraduates and 5 photo professionals scaled 32 photographs on 27 attribute scales. To explore the underlying structure of the data sets, they were subjected to Multidimensional Scaling and Principal Components Analyses. Four general components, related to aesthetic appreciation, were found: Familiarity, Hedonic Tone, Expressiveness, and Uncertainty. These components result from the higher-order latent factor Information Load that underlies aesthetic appreciation.

A spinning reserve assessment technique for a deregulated system has been developed and presented in this thesis. The technique is based on direct search optimization approach. Computer programs have been developed to implement the optimization processes both for transmission loss and without transmission loss.<p> A system commits adequate generation to satisfy its load and export/import commitment. Additional generation known as spinning reserve is also required to satisfy unforeseen load changes or withstand sudden generation loss. In a vertically integrated system, a single entity generates, transmits and distributes electrical energy. As a part of its operational planning, the single entity decides the level of spinning reserve. The cost associated with generation, transmission, distribution including the spinning reserve is then passed on to the customers.<p> In a deregulated system, generation, transmission and distribution are three businesses. Generators compete with each other to sell their energy to the Independent System Operators (ISO). ISO coordinates the bids from the generation as well as the bids from the bulk customers. In order to ensure a reliable operation, ISO must also ensure that the system has adequate spinning reserve. ISO must buy spinning reserve from the spinning reserve market. A probabilistic method called the load forecast uncertainty (LFU)-based spinning reserve assessment (LSRA) is proposed to assess the spinning reserve requirements in a deregulated power system.<p> The LSRA is an energy cost- based approach that incorporates the load forecast uncertainty of the day-ahead market (DAM) and the energy prices within the system in the assessment process. The LSRA technique analyzes every load step of the 49-step LFU model and the probability that the hourly DAM load will be within that load step on the actual day. Economic and reliability decisions are made based on the analysis to determine and minimize the total energy cost for each hour subject to certain system constraints in order to assess the spinning reserve requirements. The direct search optimization approach is easily implemented in the determination of the optimal SR requirements since the objective function is a combination of linear and non-linear functions. This approach involves varying the amount of SR within the system from zero to the maximum available capacity. By varying the amount of SR within the system, the optimal SR for which the hourly total operating cost is minimum and all operating constraints are satisfied is evaluated.<p> One major advantage of the LSRA technique is the inclusion of all the major system variables like DAM hourly loads and energy prices and the utilization of the stochastic nature of the system components in its computation. The setback in this technique is the need to have access to historical load data and spot market energy prices during all seasons. The availability and reliability of these historical data has a huge effect on the LSRA technique to adequately assess the spinning reserve requirements in a deregulated system.<p> The technique, along with the effects of load forecast uncertainty, energy prices of spinning reserve and spot market and the reloading up and down limits of the generating zones on the spinning reserve requirements are illustrated in detail in this thesis work. The effects of the above stochastic components of the power system on the spinning reserve requirements are illustrated numerically by different graphs using a computer simulation of the technique incorporating test systems with and without transmission loss.

A spinning reserve assessment technique for a deregulated system has been developed and presented in this thesis. The technique is based on direct search optimization approach. Computer programs have been developed to implement the optimization processes both for transmission loss and without transmission loss.<p> A system commits adequate generation to satisfy its load and export/import commitment. Additional generation known as spinning reserve is also required to satisfy unforeseen load changes or withstand sudden generation loss. In a vertically integrated system, a single entity generates, transmits and distributes electrical energy. As a part of its operational planning, the single entity decides the level of spinning reserve. The cost associated with generation, transmission, distribution including the spinning reserve is then passed on to the customers.<p> In a deregulated system, generation, transmission and distribution are three businesses. Generators compete with each other to sell their energy to the Independent System Operators (ISO). ISO coordinates the bids from the generation as well as the bids from the bulk customers. In order to ensure a reliable operation, ISO must also ensure that the system has adequate spinning reserve. ISO must buy spinning reserve from the spinning reserve market. A probabilistic method called the load forecast uncertainty (LFU)-based spinning reserve assessment (LSRA) is proposed to assess the spinning reserve requirements in a deregulated power system.<p> The LSRA is an energy cost- based approach that incorporates the load forecast uncertainty of the day-ahead market (DAM) and the energy prices within the system in the assessment process. The LSRA technique analyzes every load step of the 49-step LFU model and the probability that the hourly DAM load will be within that load step on the actual day. Economic and reliability decisions are made based on the analysis to determine and minimize the total energy cost for each hour subject to certain system constraints in order to assess the spinning reserve requirements. The direct search optimization approach is easily implemented in the determination of the optimal SR requirements since the objective function is a combination of linear and non-linear functions. This approach involves varying the amount of SR within the system from zero to the maximum available capacity. By varying the amount of SR within the system, the optimal SR for which the hourly total operating cost is minimum and all operating constraints are satisfied is evaluated.<p> One major advantage of the LSRA technique is the inclusion of all the major system variables like DAM hourly loads and energy prices and the utilization of the stochastic nature of the system components in its computation. The setback in this technique is the need to have access to historical load data and spot market energy prices during all seasons. The availability and reliability of these historical data has a huge effect on the LSRA technique to adequately assess the spinning reserve requirements in a deregulated system.<p> The technique, along with the effects of load forecast uncertainty, energy prices of spinning reserve and spot market and the reloading up and down limits of the generating zones on the spinning reserve requirements are illustrated in detail in this thesis work. The effects of the above stochastic components of the power system on the spinning reserve requirements are illustrated numerically by different graphs using a computer simulation of the technique incorporating test systems with and without transmission loss.

The growing uptake of wind and photovoltaic technologies requires further sources of system-level flexibility to avoid or defer significant investments. The ability to control, to some extent, customer demand (load management, LM) is one of these sources of flexibility. However, the direct involvement of a large number of customers makes the scalability of such approach a major challenge. A mostly unexplored solution to overcome the challenges of managing thousands or millions of customers is to leverage the positive correlation between voltage and demand. More precisely, Distribution Network Operators (DNOs) can control existing regulation devices to reduce customer voltages and so triggering a reduction in demand. This scheme, hereafter called voltage-led LM, avoids the direct involvement of customers overcoming one of the major barriers of traditional LM solutions. To understand whether this approach can be of any significance, a methodology able to quantify such reduction in demand need to be developed. However, the few methodologies available in the literature neglect the interactions across voltage levels and their influence on the benefits of the scheme. Moreover, time-varying demand profiles and load models are not always considered. Finally, the impact that the widespread adoption of distributed energy resources might have, is also neglected. This thesis addressed these gaps by developing a four-stage approach in which the time-varying volume of demand reduction that the scheme can unlock is quantified considering for the first time the influences among all voltage levels in distribution network. To reduce the complexity each voltage level is analysed separately whilst maintaining the corresponding dependencies. The methodology, also able to extrapolate the results at national scale, can quantify the impact that the uptake of residential scale PV units might have on the scheme. The methodology is demonstrated with a real UK case study where 10-min resolution time-series daily and seasonal analysis are performed. For the first time real network models across the whole distribution network, from 132 kV to 400 V, have been adopted. The interactions across voltage levels, the adoption of realistic load models, the variety of network models and the use of a time-varying approach, all aspects simultaneously considered for the first time in a case study, have shown to play a key role in the quantification. In Great Britain the scheme is expected to provide a significant volume of flexibility of around 1.8GW (60 GW of peak demand). The presence of PV, at least in the short term, has shown to have only a marginally effect on the benefits unlocked by the voltage-led LM scheme, making such scheme promising even in a low carbon future.