Abstract This thesis proposes a PC based electric energy management system as well as load control strategies for demand side management in high voltage customer. Besides, this thesis proposes a sequential search method for the decision of optimal demand contract. By the proposed approach, We expect to decrease the basic demand charge and the total electrical cost. The load survey and load characteristics of selected high voltage customers are first fulfilled to derive the load composition and statistic data for large air conditioner. Furthermore,digital power meters are installed at each substation and they are connected in star configuration with telephone network to form automatic meter reading system. Power parameters such as V, I, P, Q, P.F. etc. are periodically collected via telephone network. By inspecting the trend of peak load as well as the load composition, the specification and structure of electric energy management system and their application functions are difined. The proposed PC based electric energy management system is integrated programmable logic controller (PLC) with power meters to form basic Supervisory Control And Data Acquisition ¡]SCADA¡^functions. Besides, advance functions such as demand monitoring/load shedding, periodical load control, clock load control, direct load control, alarm, and real time/historical trending are embedded to enhance the capability of proposed system. By the Visual Function Block in Diamond Control View, automatic meter reading system can be simulated and demonstrated. The academic power system in National Sun Yat-Sen University(NSYSU) are selected for testing to demonstrate the effectiveness of proposed system. Finally,the effect of peak load cutting will not only save energy consumption of the customer but also increase the power capacity of substations for Taiwan power system.

This study analyzes the economic and demographic drivers of household demand for at-home consumption of nonalcoholic beverages in 1999. Drivers of available intake of calories, calcium, vitamin C, and caffeine associated with the purchase of nonalcoholic beverages also are analyzed. The 1999 ACNielsen HomeScan Panel, purchased by the U. S. Department of Agriculture, Economic Research Service, is the source of the data for this project. Many different classifications of beverages were analyzed including milk(whole, reduced fat, flavored, and non-flavored), regular and low-calorie carbonated soft drinks, powdered soft drinks, isotonics(sports drinks), juices(orange, apple, vegetable, and other juices), fruit drinks, bottled water, coffee(regular and decaffeinated), and tea(regular and decaffeinated). Probit models were used to find demographic drivers that affect the choice to purchase a nonalcoholic beverage. Heckman sample selection models and cross tabulations were used to find demographic patterns pertaining to the amount of purchase of the nonalcoholic beverages. The nutrient analysis indicated that individuals receive 211 calories, 217 mg of calcium, 45 mg of vitamin C, and 95 mg of caffeine per day from all nonalcoholic beverages. A critical finding for the nutrient analysis was that persons within households below 130% of poverty were receiving more calories and caffeine from nonalcoholic beverages compared to persons within households above 130% of poverty. Likewise, persons in households below 130% of poverty were receiving less calcium and vitamin C from nonalcoholic beverages compared to persons in households above 130% of poverty. Price and cross-price elasticities were examined using the LA/AIDS model. Methodological concerns of data frequency, beverage aggregations, and censoring techniques were explored and discussed. Own-price and cross-price elasticities for the beverages were uncovered. Price elasticities by selected demographic groups also were investigated. Results indicated that price elasticities varied by demographics, specifically for race, region, and presence of children within the household. The information uncovered in this dissertation helps to update consumer demand knowledge and nutritional intake understanding in relation to nonalcoholic beverages. The information can be used as a guide for marketing strategists for targeting and promotion as well as for policy makers looking to improve nutritional intake received from nonalcoholic beverages.

This dissertation analyzes pricing under uncertainty focusing on the U.S. airline industry. It sets to test theories of price dispersion driven by uncertainty in the demand by taking advantage of very detailed information about the dynamics of airline prices and inventory levels as the flight date approaches. Such detailed information about inventories at a ticket level to analyze airline pricing has been used previously by the author to show the importance of capacity constraints in airline pricing. This dissertation proposes and implements many new ideas to analyze airline pricing. Among the most important are: (1) It uses information about inventories at a ticket level. (2) It is the first to note that fare changes can be explained by adding dummy variables representing ticket characteristics. Therefore, the load factor at a ticket level will lose its explanatory power on fares if all ticket characteristics are included in a pricing equation. (3) It is the first to propose and implement a measure of Expected Load Factor as a tool to identify which flights are peak and which ones are not. (4) It introduces a novel idea of comparing actual sales with average sales at various points prior departure. Using these deviations of actual sales from sales under average conditions, it presents is the first study to show empirical evidence of peak load pricing in airlines. (5) It controls for potential endogeneity of sales using dynamic panels. The first essay tests the empirical importance of theories that explain price dispersion under costly capacity and demand uncertainty. The essay calculates a measure of an Expected Load Factor, that is used to calibrate the distribution of demand uncertainty and to identify which flights are peak and which ones are off-peak. It shows that different prices can be explained by the different selling probabilities. The second essay is the first study to provide formal evidence of stochastic peak-load pricing in airlines. It shows that airlines learn about the demand and respond to early sales setting higher prices when expected demand is high and more likely to exceed capacity.

<p>This study aims to evaluate the use of the method Information Demand Analysis (henceforth IDA) against an analysis tool. To gain empirical understanding of IDA, the method will be applied to a cooperation process between two business organisations. The research questions of the study are to investigate what can be required of a method, to identify the information demand for the above mentioned cooperation process, and to identify the strengths and weaknesses of the use of IDA.</p><p>Based on a literature study an evaluation framework, which describes what can be required of a method, was developed. The evaluation framework resulted in an analysis tool, which consists of the elements: method content, method user, method context, method validation, the method creator’s requirements, and the wishes and expectations of the business organisations. The use of IDA implied scoping to delimit the problem situation and a workshop to identify the information demand. In order to gain an understanding of the use of the method IDA, and to identify the information demand, the method was applied to a cooperation process between Steel AB and Wood AB. The information demand was later represented in Extended Enterprise Modelling Language (henceforth EEML). Finally, we analysed if and how the elements in the analysis tool were reflected in IDA and identified the strengths and weaknesses of the use of the method.</p><p>The strengths of IDA are that it is general and applicable on different types of business organisations. Furthermore, it has well defined concepts and the possibility of selecting appropriate concepts ensures that it is applicable on different problem situations. The business organisations, which participated in the workshop, found that IDA resulted in a holistic view and increased the understanding for each other. The weaknesses of IDA are lack of documentation of explicitly defined steps, the implications for selecting certain concepts, guidance, and explicitly described notations. Concerning the involved roles, in IDA, we request a description of them, their responsibilities, and the needed knowledge sets and skills for using the method. Since IDA still is under development we had difficulties understanding how our outcome of the method should fulfil the purpose of IDA.</p>

This report asks how Austin Energy can optimally operate residential energy efficiency and demand side management programs including demand response measures. Efficient energy use is the act of using less energy to provide the same level of service. Demand side management encompasses utility initiatives that modify the level and pattern of electrical use by customers, without adjusting consumer behavior. Demand side management is required when a utility must respond to increasing energy needs, or demand, by its customers. In order to achieve the 20% carbon emissions and 800 MW peak demand reductions mandate of the Generation, Resource and Climate Plan, AE must aggressively pursue an increase in customer participation by expanding education and technical services, enlist the full functionality of a smart grid and subsequently reduce energy consumption, peak demand, and greenhouse gas emissions. Energy efficiency is in fact the cheapest source of energy that Austin Energy has at its disposal between 2010 and 2020. But this service threatens Austin Energy’s revenues. With the ascent of onsite renewable energy generation and advanced demand side management, utilities must address the ways they generate revenues. As greenhouse gas emissions regulations lurk on the horizon, the century-old business model of “spinning meters” will be fundamentally challenged nationally in the coming years. Austin Energy can develop robust analytical methods to determine its most cost-effective energy efficiency options, while creating a clear policy direction of promoting energy efficiency while addressing the three-fold challenges of peak demand, greenhouse gas emissions and total energy savings. This report concludes by providing market-transforming recommendations for Austin Energy. / text

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Based on a previous empirical study of the effect of a residential demand response program in Sala, Sweden, this project  investigated the economic consequences of consumer behaviour change after a demand-based time of use distribution tariff was employed. The economic consequences of consumers were proven to be disadvantageous in terms of unit electricity price. Consumers could achieve more electricity bill saving through stabilising their electricity consumption during peak hours, and this way bring least compromising of their comfort level. In order to estimate the price elasticity of the studies demand response program, a new method of estimation price elasticity was proposed. With this method, the intensity of demand response of the demand response program was estimated in terms of price elasticity. Regression analysis was also applied to find out the price incentives of consumer behaviour change. And the results indicated that the rise in electricity supply charge hardly contributes to load reduction, while the demand-based tariff constituted an advantageous solution on load demand management. However stronger demand response still requires better communication with customers and more incentives other than the rise in distribution tariff.

Thesis (Ph. D.)--University of Washington, 1997. / Vita. Includes bibliographical references (leaves [82]-87).

Thesis (Ph. D.)--Göteborg University, 2004. / Includes bibliographical references.

Thesis (Ph. D.)--University of Hong Kong, 1995. / Includes bibliographical references (leaf 129-132).