989 resultados para demand response (DR)


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The electricity distribution sector will face significant changes in the future. Increasing reliability demands will call for major network investments. At the same time, electricity end-use is undergoing profound changes. The changes include future energy technologies and other advances in the field. New technologies such as microgeneration and electric vehicles will have different kinds of impacts on electricity distribution network loads. In addition, smart metering provides more accurate electricity consumption data and opportunities to develop sophisticated load modelling and forecasting approaches. Thus, there are both demands and opportunities to develop a new type of long-term forecasting methodology for electricity distribution. The work concentrates on the technical and economic perspectives of electricity distribution. The doctoral dissertation proposes a methodology to forecast electricity consumption in the distribution networks. The forecasting process consists of a spatial analysis, clustering, end-use modelling, scenarios and simulation methods, and the load forecasts are based on the application of automatic meter reading (AMR) data. The developed long-term forecasting process produces power-based load forecasts. By applying these results, it is possible to forecast the impacts of changes on electrical energy in the network, and further, on the distribution system operator’s revenue. These results are applicable to distribution network and business planning. This doctoral dissertation includes a case study, which tests the forecasting process in practice. For the case study, the most prominent future energy technologies are chosen, and their impacts on the electrical energy and power on the network are analysed. The most relevant topics related to changes in the operating environment, namely energy efficiency, microgeneration, electric vehicles, energy storages and demand response, are discussed in more detail. The study shows that changes in electricity end-use may have radical impacts both on electrical energy and power in the distribution networks and on the distribution revenue. These changes will probably pose challenges for distribution system operators. The study suggests solutions for the distribution system operators on how they can prepare for the changing conditions. It is concluded that a new type of load forecasting methodology is needed, because the previous methods are no longer able to produce adequate forecasts.

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Tässä kandidaatintyössä tutkittiin sähkön kysyntäjouston kannattavuutta teollisuuskiinteis-tössä. Tutkimus suoritettiin tutkimalla vuosien 2014 ja 2015 sähkön käyttöraportteja sekä toteutuneita Elspot hintoja. Lisäksi suoritettiin mittauksia ilmalämpöpumpuista, joiden pe-rusteella selvitettiin ilmalämpöpumppujen soveltuvuutta kysyntäjoustoon. Työssä käydään läpi kysyntäjouston vaikutuksia sekä eri kuormanohjaus mahdollisuuksia asiakkaan näkökulmasta. Lisäksi tuodaan esille Elspot hinnan muodostuminen sekä Elspot hintaan vaikuttavat tekijät. Työssä vertaillaan esimerkkikiinteistön sähkönkulutuksen suh-detta toteutuneisiin Elspot hintoihin. Lisäksi tutkitaan lämmityskuormien ohjauspotentiaalia kysyntäjouston näkökulmasta. Potentiaalin kartoittamiseksi suoritettiin mittauksia sekä teh-tiin esimerkkilaskelmia kysyntäjouston kannattavuudesta. Tutkimusten perusteella voidaan huomata, että vuositasolla saavutetut säästöt jäävät pienik-si. Huomioiden riskit Elspot hinnan vaihteluissa voidaan todetta, ettei siirtyminen tuntihin-noiteltuun sähköenergiaan ole kannattavaa esimerkkikiinteistössä. Lämmityskuormien oh-jauksesta tuntitiedon mukaan saatavien lisäsäästöjen jäädessä vähäisiksi kiinteistöön ei ole järkevää investoida erillisiä järjestelmiä kuormien ohjaukseen.

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Collectively small and medium sized enterprises (SMEs) are significant energy users although many are unregulated by existing policies due to their low carbon emissions. Carbon reduction is often not a priority but smart grids may create a new opportunity. A smart grid will give electricity suppliers a picture of real-time energy flows and the opportunity for consumers to receive financial incentives for engaging in demand side management. As well as creating incentives for local carbon reduction, engaging SMEs with smart grids has potential for contributing to wider grid decarbonisation. Modelling of buildings, business activities and technology solutions is needed to identify opportunities for carbon reduction. The diversity of the SME sector complicates strategy development. SMEs are active in almost every business area and occupy the full range of property types. This paper reviews previous modelling work, exposing valuable data on floor space and energy consumption associated with different business activities. Limitations are seen with the age of this data and an inability to distinguish SME energy use. By modelling SME energy use, electrical loads are identified which could be shifted on demand, in a smart network. Initial analysis of consumption, not constrained by existing policies, identifies heating and cooling in retail and commercial offices as having potential for demand response. Hot water in hotel and catering and retail sectors may also be significant because of the energy storage potential. Areas to consider for energy efficiency schemes are also indicated.

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The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

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A energia elétrica é fundamental para o desenvolvimento de qualquer país e o Brasil atravessa atualmente uma crise energética devido ao baixo nível de seus reservatórios, então diversos temas sobre o sistema elétrico brasileiro vêm à tona a fim de dar mais confiabilidade e evitar futuros racionamentos, permitindo assim que a escassez de energia não seja um impeditivo para o crescimento econômico do país. O presente estudo calcula o potencial de redução de demanda por energia elétrica no estado do Rio de Janeiro através do modelo de preço variável, que consiste em ter tarifas distintas para o horário de ponta e fora de ponta. Este é um entre diversos programas de eficiência energética existentes no mundo atualmente. Para tal cálculo as principais premissas são a projeção de demanda máxima coincidente, o número de consumidores por classe e a elasticidade preço da demanda por energia elétrica. A partir dai são sugeridos três cenários de penetração de AMI (Advanced Metering infrastructure), e três cenários de variação de preço, chegando assim a nove resultados possíveis.

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This Master of Science Thesis deals with a study on applying the BSC Balanced Scorecard to assess the performance of Federal Institution for Technological Education Institution in Brazil, a government organizations non for profit. It s accomplished a literature review in order to understand the BSC and its application to non for profit organizations and as a main result it is proposed a BSC conceptual model with an inversion of the main BSC perspective from financial to customer/society. It is used the annual management report of thirteen Institutions and applied a Pearson correlation analysis in order to verify a cause-effect situation between indicators. The main findings suggest that the model teachers qualification in terms of degree earned, quantity of teachers in full time job, and rate of students by teacher in full time job having good pearson correlation with the results expected of quality, throughput, social and demand response. However, the student unit cost use as the sole financial indicator did not get any reasonable correlation with the results, as so the quality and quantity of books in the libraries. Although it suggests a need for improvement in the model, the general model adopted appears to be satisfactory as a starting point to a BSC-like performance measuring system to this kind of Institutions

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Distributed Generation, microgrid technologies, two-way communication systems, and demand response programs are issues that are being studied in recent years within the concept of smart grids. At some level of enough penetration, the Distributed Generators (DGs) can provide benefits for sub-transmission and transmission systems through the so-called ancillary services. This work is focused on the ancillary service of reactive power support provided by DGs, specifically Wind Turbine Generators (WTGs), with high level of impact on transmission systems. The main objective of this work is to propose an optimization methodology to price this service by determining the costs in which a DG incurs when it loses sales opportunity of active power, i.e, by determining the Loss of Opportunity Costs (LOC). LOC occur when more reactive power is required than available, and the active power generation has to be reduced in order to increase the reactive power capacity. In the optimization process, three objectives are considered: active power generation costs of DGs, voltage stability margin of the system, and losses in the lines of the network. Uncertainties of WTGs are reduced solving multi-objective optimal power flows in multiple probabilistic scenarios constructed by Monte Carlo simulations, and modeling the time series associated with the active power generation of each WTG via Fuzzy Logic and Markov Chains. The proposed methodology was tested using the IEEE 14 bus test system with two WTGs installed. © 2011 IEEE.

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Demand response has gained increasing importance in the context of competitive electricity markets and smart grid environments. In addition to the importance that has been given to the development of business models for integrating demand response, several methods have been developed to evaluate the consumers' performance after the participation in a demand response event. The present paper uses those performance evaluation methods, namely customer baseline load calculation methods, to determine the expected consumption in each period of the consumer historic data. In the cases in which there is a certain difference between the actual consumption and the estimated consumption, the consumer is identified as a potential cause of non-technical losses. A case study demonstrates the application of the proposed method to real consumption data. © 2013 IEEE.

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Pós-graduação em Engenharia Elétrica - FEB

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Electric power grids throughout the world suffer from serious inefficiencies associated with under-utilization due to demand patterns, engineering design and load following approaches in use today. These grids consume much of the world’s energy and represent a large carbon footprint. From material utilization perspectives significant hardware is manufactured and installed for this infrastructure often to be used at less than 20-40% of its operational capacity for most of its lifetime. These inefficiencies lead engineers to require additional grid support and conventional generation capacity additions when renewable technologies (such as solar and wind) and electric vehicles are to be added to the utility demand/supply mix. Using actual data from the PJM [PJM 2009] the work shows that consumer load management, real time price signals, sensors and intelligent demand/supply control offer a compelling path forward to increase the efficient utilization and carbon footprint reduction of the world’s grids. Underutilization factors from many distribution companies indicate that distribution feeders are often operated at only 70-80% of their peak capacity for a few hours per year, and on average are loaded to less than 30-40% of their capability. By creating strong societal connections between consumers and energy providers technology can radically change this situation. Intelligent deployment of smart sensors, smart electric vehicles, consumer-based load management technology very high saturations of intermittent renewable energy supplies can be effectively controlled and dispatched to increase the levels of utilization of existing utility distribution, substation, transmission, and generation equipment. The strengthening of these technology, society and consumer relationships requires rapid dissemination of knowledge (real time prices, costs & benefit sharing, demand response requirements) in order to incentivize behaviors that can increase the effective use of technological equipment that represents one of the largest capital assets modern society has created.

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En los últimos años se ha construido un gran número de pasarelas peatonales como respuesta a la demanda de nuevas vías de paso en las ciudades. Estas estructuras tienen requisitos constructivos menos exigentes en comparación con otros tipos de puentes, lo cual ha facilitado el desarrollo de diseños con nuevos esquemas resistentes, complicadas geometrías y el empleo de nuevos materiales. En general estas estructuras son esbeltas, ligeras y poco amortiguadas, lo que en ocasiones ha generado problemas de vi-braciones al paso de peatones una vez puestas en servicio. Las normativas actuales son cada vez más sensibles a esta problemática, recomendando diseños cuyas frecuencias naturales deben estar alejadas de los rangos de frecuencia de paso típicos de los peatones y fijando límites de confort en forma de valores máximos de aceleración permitidos, asegurándose así un correcto comportamiento de la estructura. En el presente artículo se analiza esta problemática desde un punto de vista práctico. Para ello se muestran los puntos clave de las normativas y guías de diseño de pasarelas que se pueden encontrar actualmente en la bibliografía, se presentan las técnicas que habitualmente se emplean en el análisis dinámico experimental de estas estructuras, y se comentan las soluciones a las que generalmente se recurre para mejorar su comportamiento dinámico. Por último, se muestran los trabajos llevados a cabo por el Centro Tecnológico CARTIF en colaboración con las Universidades de Valladolid y Castilla-La Mancha en la pasarela peatonal del Museo de la Ciencia de Valladolid. Estos trabajos incluyen: (1) el estudio dinámico de los tres vanos metálicos de dicha pasarela, (2) el diseño e implementación de un amortiguador de masa sintonizado en el vano más sensible a las vibraciones, (3) la implementación de un amortiguador de masa activo utilizando un excitador electrodinámico, y (4) el desarrollo de pruebas para la verificación del estado de servicio de la pasarela. In the last years, a wide number of footbridges have been built as demand response of more direct pathways in cities. These structures have lower building requirements as compared with standard bridges. This circumstance has facilitated the development of new structural design with complex geometries and innovative materials. As a result, these structures may be slender, light and low damped, leading to vibration problems once in service. The current codes take into account this problem, and recommend designs with natural frequencies away from the typical pedestrian pacing rates and fix comfort limits to guarantee the serviceability of the structure.This paper studies this problem from a practical point of view. Thus, the key points of codes and footbridges guidelines are showed, the typical experimental dynamic analysis techniques are presented, and the usual solutions adopted to improve the dynamic performance of these structures are discussed. Finally, the works carried out on the Valladolid Science Museum Footbridge by Centro Tecnológico CARTIF in collaboration with the Universities of Valladolid and Castilla-La Mancha are showed. These works include: (1) the dynamic study of the three steel spans of the footbridge, (2) the design and implementation of a tuned mass damper in the liveliest span, (3) the implementation of an active mass damper using an electrodynamic shaker, and (4) the development of field tests to assess the serviceability of such span.

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Microgrids are autonomously operated, geographically clustered electricity generation and distribution systems that supply power in closed system settings; they are highly compatible with renewable energy sources and distributed generation technologies. Mocrogrids are currently a serially underutilized and underappreciated commodity in the energy infrastructure portfolio worldwide. To demonstrate feasibility under poor conditions (little renewable energy potential and high demand) this capstone project develops a theoretical case study in which a renewable microgrid is employed to power rural communities of southern Montgomery County, Arkansas. Utilizing commercially manufactured 1.5-megawatt wind turbines and a 1-megawatt solar panel generation system, 4-megawatts of lithium ion battery storage, and demand response technology, a microgrid is designed that supplies 235 households with reliable electricity supply.

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Utilization of renewable energy sources and energy storage systems is increasing with fostering new policies on energy industries. However, the increase of distributed generation hinders the reliability of power systems. In order to stabilize them, a virtual power plant emerges as a novel power grid management system. The VPP has a role to make a participation of different distributed energy resources and energy storage systems. This paper defines core technology of the VPP which are demand response and ancillary service concerning about Korea, America and Europe cases. It also suggests application solutions of the VPP to V2G market for restructuring national power industries in Korea.

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Thesis (Ph.D.)--University of Washington, 2016-08

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Esta tese incide sobre o desenvolvimento de modelos computacionais e de aplicações para a gestão do lado da procura, no âmbito das redes elétricas inteligentes. É estudado o desempenho dos intervenientes da rede elétrica inteligente, sendo apresentado um modelo do produtor-consumidor doméstico. O problema de despacho económico considerando previsão de produção e consumo de energia obtidos a partir de redes neuronais artificiais é apresentado. São estudados os modelos existentes no âmbito dos programas de resposta à procura e é desenvolvida uma ferramenta computacional baseada no algoritmo de fuzzy-clustering subtrativo. São analisados perfis de consumo e modos de operação, incluindo uma breve análise da introdução do veículo elétrico e de contingências na rede de energia elétrica. São apresentadas aplicações para a gestão de energia dos consumidores no âmbito do projeto piloto InovGrid. São desenvolvidos sistemas de automação para, aquisição monitorização, controlo e supervisão do consumo a partir de dados fornecidos pelos contadores inteligente que permitem a incorporação das ações dos consumidores na gestão do consumo de energia elétrica; SMART GRIDS - COMPUTATIONAL MODELS DEVELOPMENT AND DEMAND SIDE MANAGMENT APPLICATIONS Abstract: This thesis focuses on the development of computational models and its applications on the demand side management within the smart grid scope. The performance of the electrical network players is studied and a domestic prosumer model is presented. The economic dispatch problem considering the production forecast and the energy consumption obtained from artificial neural networks is also presented. The existing demand response models are studied and a computational tool based on the fuzzy subtractive clustering algorithm is developed. Energy consumption profiles and operational modes are analyzed, including a brief analysis of the electrical vehicle and contingencies on the electrical network. Consumer energy management applications within the scope of InovGrid pilot project are presented. Computational systems are developed for the acquisition, monitoring, control and supervision of consumption data provided by smart meters allowing to incorporate consumer actions on their electrical energy management.