Customer load characteristics plays the ndamental role for more reliable load forecasting. It can also be used to enhance the system expansion planning and economic dispatch more effectively. Besides, the system capacity shortage due to peak loading can be relieved by the strategy of energy conservation and load management with customer load models. A systematic procedure is proposed in this thesis to study the effect of temperature change to the power system load demand by using the typical load patterns of customer classes. The billing data of all service customers are retrieved to derive the daily load profile of the selected Taipower district. To verify the accuracy of the estimated load composition, the simulation results are compared to the actual load profile collected by the SCADA system. The sensitivity analysis of load demand with respect to the temperature change for each customer class is performed by statistic regression according to the actual customer power consumption and temperature data. With temperature rise, the load contribution by each customer class is updated by the corresponding temperature sensitivity and integrated together to form the new load profile of the service district. In the future, the load research will play more important role for power utility companies. Load data will be utilized to a greater extent by various departments in utility companies. For instance, the proposed load survey system can solve the customer load characteristics more accurately to support various applications. By refer the temperature sensitivity analysis based on the customer load research, can evaluate the potential of air conditioner load management to reduce the system peak loading can be inhibit. With this information, the proper incentive of cycling control of air conditioners can be designed to achieve more effective load management.

The Temperature Sensitivity Analysis of Power System Load Demand with Neural Networks Chih-Hung Chen* Chao-Shun Chen** Institute of Electrical Engineering National Sun Yat-Sen University Kaohsiung, Taiwan, R.O.C. ABSTRACT The analysis of customer load characteristic plays the fundamental role of power system operation. Based on the load survey study, the load pattern of each customer class is derived to achieve more effective load forecast for system planning to reduce the risk of system capacity shortage. For the load survey study, a stratified sampling method has been used to select the proper size of customers for meter installation to collect the customer power consumption. By the way, the customer load patterns derived can represent the load behavior of whole customer population. The standardized daily load pattern of each customer class has been solved with the mean per-unit method of customer load. According to the total power consumption by all customers within the same class and considering the corresponding daily load pattern, the daily load profile of the customer class is then determined. The standard daily load pattern of each customer class and total power consumption within the territory of service districts of Taipower system are integrated to construct Taipower system daily load profile. The temperature sensitivity analysis of customer power consumption is performed for each customer class by applying neural networks. The proposed method has been used to investigate the change of power consumption due to temperature rise for each district and Taipower system. For the districts with high ratio of the air conditioner loading, the increase of power consumption is in proportion to the temperature. It is concluded that the research of temperature sensitivity on power consumption can support power system operation and better capacity planning of power system in the future. *Author **Advisor

Based on the load survey study, a stratified sampling method is proposed to select the proper size of customers so that the load patterns derived can represent the load behavior of whole customer population. In this study there are 1315 customers out of Taipower customers over various service classes are selected for the installation of intelligent meters in the field to measure the power consumption within every 15 minutes. The bad data detection is performed to identify the abnormal power consumption by executing the Chi-square test. The standardized daily load pattern of each customer class has been derived with the mean per-unit method of customer load. The billing data are retrieved from the customer information system and applied to derive the customer daily load pattern by considering the customer load patterns. According to the total power consumption by all customers within the same class and considering the corresponding daily load pattern, the daily load profile of the customer class is then determined. By aggregating the load profiles of all customer classes, the daily load composition and load model of each service district can therefore be solved. By the same manner, the daily load pattern of whole Taipower system can be derived and it can be used to support the proper design of tariff structure according to the respective contribution of system power demand by each customer class. To investigate the overloading of distribution main transformers during the summer season, the correlations analysis of customer power consumption and temperature is performed. The effect of temperature change to the power consumption of each customer class is solved by multiple regression analysis with 95% confidential level. Based on the temperature sensitivity and the corresponding load composition, the load change due to temperature rise for various customer classes can be estimated. To demonstrate the impact of temperature change to distribution system operation, considering the temperature sensitivity of power consumption and load composition solves the power demand at each load bus. By updating the bus load demand due to temperature change, the feeder loading and power loss is therefore derived. To resolve the over loading problem of distribution feeders and main transformers during the summer season, a temperature adaptive switching operation has been proposed to perform the proper load transfer among the feeders/main transformers. In this dissertation, the effect of temperature change to the time varying characteristics of load buses and power transmission in Taipower is investigated. The dc circuit model of Taipower system and the temperature effect of customer power consumption are considered in the stochastic load flow analysis. With the temperature rise, the power demand of northern buses is increased dramatically and more power has to be transmitted from the southern region. The large voltage angle difference is significantly various between system buses during the summer peak period. It is suggested that the safety margin assessment of system operation has to be executed by considering the temperature effect to the bus loading of power systems.

Title: Possibilities of physical and sports activities for patients with asthma and their influence on the medical condition Objectives: The aim of the thesis is to discover the level of active lifestyle of asthmatic patients and their participation on physical activity and sport. Another aim is to find out whether asthmatic patients are limited in physical activity or sport because of the medical condition and how the physically active lifestyle influences the medical condition and whether it takes part on improving quality of life. Methods: A survey was used for data collection. A questionnaire was distributed to people working with asthmatic patients, to sports club and university students. The research group consists of 125 respondents. The obtained data was processed into tables and charts via Microsoft Office Word 2016, Microsoft Office Excel 2016 and SPSS program. A verification of hypotheses was carried out according to the results of the survey and the independence test - chi-squared test. Research results are in the form of tables and graphs summarized at the end of the thesis. The results were compared to the resources dealing with the topic to verify if the hypothesis was true or not. Results: According to the chosen data processing methods, the limitation of asthmatic patients in...