Hierarchical and Distributed Architecture for Large-Scale Residential Demand Response Management

The implementation of smart grid brings several challenges to the power system. The ‘prosumer’ concept, proposed by the smart grid, allows small-scale ‘nano-grids’ to buy or sell electric power at their own discretion. One major problem in integrating prosumers is that they tend to follow the same pattern of generation and consumption, which is un-optimal for grid operations. One tool to optimize grid operations is demand response (DR). DR attempts to optimize by altering the power consumption patterns. DR is an integrated tool of the smart grid. FERC Order No. 2222 caters for distributed energy resources, including demand response resources, in participating in energy markets. However, DR contribution of an average residential energy consumer is insignificant. Most residential energy consumers pay a flat price for their energy usage and the established market for residential DR is quite small. In this dissertation, a survey is carried out on the current state-of-the-art in DR research and generalizations of the mathematical models are made. Additionally, a service provider model is developed along with an incentive program and user interfaces (UI). These UIs and incentive program are designed to be attractive and easily comprehended by a large customer base. Furthermore, customer behavior models are developed that characterize the potential customer base, allowing a demand response aggregator to understand and quantify the quality of the customer. Optimization methods for DR management with various characteristics are also explored in this dissertation. Moreover, A scalable demand response management framework that can incorporate millions of participants in the program is introduced. The framework is based on a hierarchical architecture. To improve DR management, hierarchical load forecasting method is studied. Specifically, optimal combination method for hierarchical forecast reconciliation is applied to the DR program. It is shown that the optimal combination for reconciliation of hierarchical predictions could reduce the stress levels of the consumer close to the ideal values for all scenarios

An Evaluation of a Metaheuristic Artificial Immune System for Household Energy Optimization

[EN] Devices in a smart home should be connected in an optimal way; this helps save energy and money. Among numerous optimization models that can be found in the literature, we would like to highlight artificial immune systems, which use special bioinspired algorithms to solve optimization problems effectively. The aim of this work is to present the application of an artificial immune system in the context of different energy optimization problems. Likewise, a case study is performed in which an artificial immune system is incorporated in order to solve an energy management problem in a domestic environment. A thorough analysis of the different strategies is carried out to demonstrate the ability of an artificial immune system to find a successful optima which satisfies the problem constraints

Computational Intelligence Based Demand Response Management in a Microgrid

A demand response management (DRM) system is proposed here, in which a service provider determines a mutual optimal solution for the utility and the customers in a microgrid setting. Such a system may find use with a service provider interacting with the respective customers and utilities under the existence of some DRM agreements. The service provider is an entity which acts at different levels of the electrical grid and carry out the optimization. The lowest level controls one ‘neighborhood’ while higher levels of service providers control other lower level service providers. A microgrid consisting of a smart neighborhood of twelve customers was used as experimental case study and an advanced metering infrastructure (AMI) was implemented. Based on the formulation of an optimization problem which exploits price-responsive demand flexibility and the AMI infrastructure, a win-win-win strategy is presented. The interior point method was used to solve the objective function and the application of particle swarm optimization and artificial immune systems for demand response was explored. Results for a range of typical scenarios were presented to demonstrate the effectiveness of the proposed demand-response management framework

Human Milk Composition and Dietary Intakes of Breastfeeding Women of Different Ethnicity from the Manawatu-Wanganui Region of New Zealand

Human milk is nutrient rich, complex in its composition, and is key to a baby’s health through its role in nutrition, gastrointestinal tract and immune development. Seventy-eight mothers (19–42 years of age) of Asian, Māori, Pacific Island, or of European ethnicity living in Manawatu-Wanganui, New Zealand (NZ) completed the study. The women provided three breast milk samples over a one-week period (6–8 weeks postpartum), completed a three-day food diary and provided information regarding their pregnancy and lactation experiences. The breast milk samples were analyzed for protein, fat, fatty acid profile, ash, selected minerals (calcium, magnesium, selenium, zinc), and carbohydrates. Breast milk nutrient profiles showed no significant differences between the mothers of different ethnicities in their macronutrient (protein, fat, carbohydrate, and moisture) content. The breast milk of Asian mothers contained significantly higher levels of polyunsaturated fatty acids (PUFAs), omega-3 (n-3) and omega-6 (n-6) fatty acids, docosahexaenoic acid (DHA), and linoleic acids. Arachidonic acid was significantly lower in the breast milk of Māori and Pacific Island women. Dietary intakes of protein, total energy, saturated and polyunsaturated fat, calcium, phosphorus, zinc, iodine, vitamin A equivalents, and folate differed between the ethnic groups, as well as the number of serves of dairy foods, chicken, and legumes. No strong correlations between dietary nutrients and breast milk components were found

Veraenderlich elastisches und plastisches Verhalten nichtbindiger Boeden und Schotter unter zyklisch-dynamischer Beanspruchung

SIGLEAvailable from TIB Hannover: RR 2797(12) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman