Well-designed demand response is expected to play a vital role in operatingpower systems by reducing economic and environmental costs. However,the current system is operated without much information on the benefits ofend-users, especially the small ones, who use electricity. This thesis proposes aframework of operating power systems with demand models including the diversityof end-users’ benefits, namely adaptive load management (ALM). Sincethere are a large number of end-users having different preferences and conditionsin energy consumption, the information on the end-users’ benefits needsto be aggregated at the system level. This leads us to model the system ina multi-layered way, including end-users, load serving entities, and a systemoperator. On the other hand, the information of the end-users’ benefits can beuncertain even to the end-users themselves ahead of time. This information isdiscovered incrementally as the actual consumption approaches and occurs. Forthis reason ALM requires a multi-temporal model of a system operation andend-users’ benefits within. Due to the different levels of uncertainty along thedecision-making time horizons, the risks from the uncertainty of informationon both the system and the end-users need to be managed. The methodologyof ALM is based on Lagrange dual decomposition that utilizes interactive communicationbetween the system, load serving entities, and end-users. We showthat under certain conditions, a power system with a large number of end-userscan balance at its optimum efficiently over the horizon of a day ahead of operationto near real time. Numerical examples include designing ALM for theright types of loads over different time horizons, and balancing a system with a large number of different loads on a congested network. We conclude thatwith the right information exchange by each entity in the system over differenttime horizons, a power system can reach its optimum including a variety ofend-users’ preferences and their values of consuming electricity.

In recent years, the share of renewable energy sources (RESs) has been increasing in the electricity generation mix with a mandate to reduce greenhouse gas emissions that are released from burning fossil fuels. Indeed, a large share of electricity from renewable resources is required to de-carbonize the electricity sector. With the evolution of smart grids and microgrids, effective and efficient penetration of renewable generation such as wind and solar can possibly be attained. However, the intermittent nature of wind and solar generation makes microgrid operation and planning a complex problem and there is a need for a flexible grid to cope with the variability and uncertainty in their generation profiles. This research focuses on the coordination of distributed energy resources, such as energy storage systems (ESSs) and demand response (DR) to present an efficient solution towards improving the flexibility of microgrids, and supporting high levels of renewables generation. The overall goal of this research is to examine the influence of coordinated operation of ESS and DR on microgrid operations in the presence of high penetration levels of renewable generation. Deterministic and stochastic short-term operational planning models are developed to analyze the effects of coordinating ESS and DR, vis-à-vis their independent operation, on microgrids with high renewable generation. Special focus is on operation costs, scheduling and dispatching of controllable distributed generators, and levels of renewable generation. A set of valid probabilistic scenarios is considered for the uncertainties of load, and intermittency in wind and solar generation sources. The numerical results considering a benchmark microgrid indicate that coordinated operation of ESS and DR is beneficial in terms of operation costs, vis-à-vis their independent presence in the microgrid, when there is sufficient renewable generation. The coordinated operation reduces the risk in scheduling and increases the flexibility of the microgrid in supporting high levels of renewable generation.

As the introduction of renewable energy sources increase in the power market, the need for effective use of electricity by consumers gains importance. The Swedishpower market is characterized by demand inelasticity. Thus, resulting in a system where supply follows demand. Increased demand response in electricity markets is essential in order to cope with future challenges. Electricity retailers can encourage an increased demand response by offering contracts to their customers such as “Realtime pricing” and “Fixed price with the right to return”. Under these contracts consumers are exposed to the hourly prices of electricity, thus benefitting by shifting the load to hours when the price is low. Electricity retailers benefits theoretically by risk eliminations. The aim of this paper is to quantify the economic consequences of increased demand response, for electricity retailers by offering the two contracts.This is done in two parts; firstly a simulation model of demand response is developed based on spot prices and different levels of price elasticity, secondly the results from the simulations are used in a model for calculations regarding an electricity retailers’ economy. The results show that an electricity retailers’ profit increases with increased demand response, greater response results in greater profits. Using low,medium and high demand response results in a profit increase of 34 %, 38 % and 55 % respectively. / Marknadsbaserade styrmedel i bostadssektorn

Electric hot water tanks play a pivotal role as demand response assets within the UK's energy system by storing heat when energy is inexpensive and delivering domestic hot water when it is required. This role will become increasingly important if non-dispatchable renewable energy sources are to play a bigger part in the energy mix. Historically, the design standards relating to hot water tanks have focused primarily on minimising heat losses. However, in addition to preserving energy, a hot water tank should preserve the availability of heat above a useful temperature for as long as possible to avoid energy usage during peak times when it is costly or carbon intensive. To do this, thermal stratification within hot water tanks must be promoted. Unfortunately, thermal stratification leads to conditions that are conducive to bacterial growth due to the hospitable temperatures that arise during operation. For this reason, question marks have arisen over the extent to which more flexible control strategies, designed to allow for increasing penetrations of intermittent renewable energy sources, might lead to the growth of pathogenic bacteria within hot water tanks. The objective of the work discussed in this thesis was to understand the extent to which there is a conflict between thermal stratification and bacterial growth in practice, whether this conflict can be resolved and the potential implications for electric hot water tanks operating on a time of use tariff. A small field study demonstrated that there is prolific bacterial growth within conventional electric cylinders and that this can be attributed to thermal stratification with a confidence of (P<0.01). Fitting a de-stratification pump, to enhance sanitary performance, resulted in a 19% decrease in the recovery of useable hot water above 43°C. Given that the tanks tested during the field study were made of copper, the consequences of alternative material choices on thermal performance were explored. It was found that the rate of useable hot water loss, due to de-stratification associated with thermal diffusion across the thermocline, could be reduced by a factor of 2.7 by making the tank liner wall from stainless steel instead of copper. Further numerical work indicated that this improvement in stratifying performance was most significant for small tanks with high aspect ratios. In addition to de-stratification that arises due to vertical conduction, de-stratification due to inlet mixing was reduced by up to 30% by installing a spiral diffuser into the base of a test cylinder. In addition, by lowering the immersion heating element to ensure there is sufficient heat transfer to the base of the cylinder, sterilising temperatures could be attained throughout the stored volume of water in the tank during heating. This showed that the conflict between thermal and sanitary performance within electric tanks could potentially be resolved. A bespoke tank, made from stainless steel and fitted with a diffuser, was built and subjected to typical draw cycles that reflect real world operation. These tests showed that more useable hot water could be delivered in comparison to a commercial off the shelf copper tank and consequently the utilisation of the Economy 7 time of use tariff would be enhanced.

There are presently worldwide targets for decreasing anthropogenic greenhouse gases (GHGs) emissions owing to global climate change concerns. Here in the United Kingdom, the government has committed to reduce its GHGs emissions by at least 80% by 2050 relative to 1990 levels. In order to achieve the ambitious 2050 targets and minimise cumulative emissions along the way, modern power systems are facing a series of great challenges. These challenges include extensive utilisation of renewable generation, diverse demand--side participation in power system operation and planning, as well as considerable application of emerging smart devices and appliances. All of these challenges will significantly increase the complexity of future power systems in terms of both operation and design. Regardless, the primary objective of power systems remains the same. That is the system must supply all the customers (responsive ones and non-responsive ones) with electricity as economically as possible and with an adequate level of continuity and quality. With the widespread utilisation of smart meters and appliances as well as the large-scale installation of different storage technologies, the services that demand response (DR) and electrical energy storage (EES) resources can provide will cover a wide range of ancillary services. More importantly, the grid-scale penetration of DR and EES resources is able to provide energy management and capacity support services, which can be considered as the alternative to generation resources. In this light, considerable amount of research has been done focusing on engaging particular types of electricity users with different kinds of incentives and/or tariff schemes, so that the economic benefits to both utilities and customers are optimised. However, no general framework for systematic assessment of the contribution to power system adequacy of supply from potential grid-scale penetration of DR and EES resources is available up till now, particularly taking specific consideration of DR's flexibility and payback characteristics as well as EES's operational parameters. The research work in this thesis therefore emphasises exclusively on the potential of grid-scale DR and EES resources to serve as alternative resources to electricity generation within the context of power system adequacy of supply. More specifically, based on literature survey of existing studies in similar topics, this thesis has made some substantial contributions and innovations, such as developing novel models of these emerging demand-side resources, implementing a systematic adequacy of supply assessment with new aspect to measure the level of adequacy of supply (new indices), proposing a novel and comprehensive framework for evaluation of the capacity credit of DR and EES, and analysing the economic value based on power system fundamental long--term costs of interruption and supply. Ultimately, this thesis has established a comprehensive framework for assessment of the contribution of DR and EES to power system adequacy of supply. Additionally, the numerical studies carried out in this thesis have enabled the inference of general adequacy of supply implications in terms of deploying DR and EES resources to provide capacity support to power systems.

La problématique de cette thèse porte sur les impacts du marché de capacité français sur le déploiement des énergies renouvelables en présence d'incertitude. Ce marché est mis en place en France dans le but de couvrir les fortes pointes de consommation électrique. Il demande aux fournisseurs d’assurer la consommation de leurs clients lors de ces pointes en achetant des garanties auprès des producteurs d’électricité. Ce mécanisme rémunère la capacité disponible durant les périodes de tension entre offre et demande, et sa valorisation dépend de sa contribution à la sécurité d’approvisionnement. Du fait de leur nature intermittente, la rémunération des énergies renouvelables est plus incertaine que pour les autres moyens de production électrique. Cette thèse étudie l'adéquation entre un objectif de sécurité d'approvisionnement et un objectif de déploiement des énergies renouvelables, deux visées du gouvernement français. / The problematic of this thesis focuses on the impacts of the French capacity marketon the deployment of renewable energies in the presence of uncertainty. This marketis set up in France in order to cover high peaks in electricity consumption. It asks suppliers to ensure the consumption of their customers at these peaks by buying guarantees from electricity producers. This mechanism compensates for theavailable capacity during periods of tension between supply and demand, and itsvaluation depends on its contribution to security of supply. Due to their intermittent nature, the remuneration of renewable energies is more uncertain than for other means of electricity production. This thesis studies the adequacy between a goal of security of supply and a goal of deployment of renewable energies, two aims of the French government.

abstract: A major problem faced by electric utilities is the need to meet electric loads during certain times of peak demand. One of the widely adopted and promising programs is demand response (DR) where building owners are encouraged, by way of financial incentives, to reduce their electric loads during a few hours of the day when the electric utility is likely to encounter peak loads. In this thesis, we investigate the effect of various DR measures and their resulting indoor occupant comfort implications, on two prototype commercial buildings in the hot and dry climate of Phoenix, AZ. The focus of this study is commercial buildings during peak hours and peak days. Two types of office buildings are modeled using a detailed building energy simulation program (EnergyPlus V6.0.0): medium size office building (53,600 sq. ft.) and large size office building (498,600 sq. ft.). The two prototype buildings selected are those advocated by the Department of Energy and adopted by ASHRAE in the framework of ongoing work on ASHRAE standard 90.1 which reflect 80% of the commercial buildings in the US. After due diligence, the peak time window is selected to be 12:00-18:00 PM (6 hour window). The days when utility companies require demand reduction mostly fall during hot summer days. Therefore, two days, the summer high-peak (15th July) and the mid-peak (29th June) days are selected to perform our investigations. The impact of building thermal mass as well as several other measures such as reducing lighting levels, increasing thermostat set points, adjusting supply air temperature, resetting chilled water temperature are studied using the EnergyPlus building energy simulation program. Subsequently the simulation results are summarized in tabular form so as to provide practical guidance and recommendations of which DR measures are appropriate for different levels of DR reductions and the associated percentage values of people dissatisfied (PPD). This type of tabular recommendations is of direct usefulness to the building owners and operators contemplating DR response. The methodology can be extended to other building types and climates as needed. / Dissertation/Thesis / M.S. Architecture 2012

Recent technological developments are bringing about substantial changes that are converting traditional distribution networks into "smart" distribution networks. In particular, it is possible to observe seamless integration of Information and Communication Technologies (ICTs), including the widespread installation of automatic equipment, smart meters, etc. The increased automation facilitates active network management, interaction between market actors and demand side participation. If we also consider the increasing penetration of distributed generation, renewables and various emerging technologies such as storage and dynamic rating, it can be argued that the capacity of distribution networks should not only depend on conventional asset. In this context, taking into account uncertain load growth and ageing infrastructure, which trigger network investments, the above-mentioned advancements could alter and be used to improve the network design philosophy adopted so far. Hitherto, in fact, networks have been planned according to deterministic and conservative standards, being typically underutilised, in order for capacity to be available during emergencies. This practice could be replaced by a corrective philosophy, where existing infrastructure could be fully unlocked for normal conditions and distributed energy resources could be used for post fault capacity services. Nonetheless, to thoroughly evaluate the contribution of the resources and also to properly model emergency conditions, a probabilistic analysis should be carried out, which captures the stochasticity of some technologies, the randomness of faults and, thus, the risk profile of smart distribution networks. The research work in this thesis proposes a variety of post fault capacity services to increase distribution network utilisation but also to provide reliability support during emergency conditions. In particular, a demand response (DR) scheme is proposed where DR customers are optimally disconnected during contingencies from the operator depending on their cost of interruption. Additionally, time-limited thermal ratings have been used to increase network utilisation and support higher loading levels. Besides that, a collaborative operation of wind farms and electrical energy storage is proposed and evaluated, and their capacity contribution is calculated through the effective load carrying capability. Furthermore, the microgrid concept is examined, where multi-generation technologies collaborate to provide capacity services to internal customers but also to the remaining network. Finally, a distributed software infrastructure is examined which could be effectively used to support services in smart grids. The underlying framework for the reliability analysis is based on Sequential Monte Carlo Simulations, capturing inter-temporal constraints of the resources (payback effects, dynamic rating, DR profile, storage remaining available capacity) and the stochasticity of electrical and ICT equipment. The comprehensive distribution network reliability analysis includes network reconfiguration, restoration process, and ac power flow calculations, supporting a full risk analysis and building the risk profile for the arising smart distribution networks. Real case studies from ongoing project in England North West demonstrate the concepts and tools developed and provide noteworthy conclusions to network planners, including to inform design of DR contracts.

Submitted by Thays Aparecida de Abreu Silva null (thays7abreu@gmail.com) on 2016-08-24T12:25:29Z No. of bitstreams: 1 Thays - Final03-08-16.pdf: 1979884 bytes, checksum: 531230641c5b2eb640f10441ac13f396 (MD5) / Approved for entry into archive by Ana Paula Grisoto (grisotoana@reitoria.unesp.br) on 2016-08-25T13:57:50Z (GMT) No. of bitstreams: 1 santos_taa_dr_ilha.pdf: 1979884 bytes, checksum: 531230641c5b2eb640f10441ac13f396 (MD5) / Made available in DSpace on 2016-08-25T13:57:50Z (GMT). No. of bitstreams: 1 santos_taa_dr_ilha.pdf: 1979884 bytes, checksum: 531230641c5b2eb640f10441ac13f396 (MD5) Previous issue date: 2016-06-09 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Considerando a crescente demanda de energia elétrica no setor residencial, faz-se necessário conhecer o padrão de consumo de eletricidade de forma detalhada, impulsionando a mudança do comportamento dos consumidores finais, com o objetivo de reduzir o consumo global e a racionalização do uso da energia elétrica. Portanto, conhecer o perfil da curva de carga, com antecedência, é importante para detectar os picos e os vales, e incentivar os consumidores a mudar seus hábitos de consumo de energia, principalmente durante os períodos em que as tarifas são mais caras. Assim, nesta pesquisa propõe-se a utilização de um sistema fuzzy para obter o perfil de carga elétrica residencial. Como o consumo de energia elétrica, em residências, está altamente correlacionado com a ocupação ativa, foram levados em consideração o número de ocupantes na residência e os diferentes períodos do dia ao longo de 24 horas. Com base neste modelo foi possível simular o perfil de carga elétrica, a detecção dos picos que podem comprometer a eficiência do sistema e, consequentemente, oferecer mecanismos para melhorar o gerenciamento de demanda e incentivar a utilização racional de energia elétrica. Com objetivo de verificar a eficiência do sistema fuzzy, comparou-se as curvas de carga obtidas pelo sistema proposto com as curvas de carga reais e por meio desta comparação foi possível observar que os resultados são promissores. / The electrical energy demand is increasing mainly in residences. Therefore, it is necessary to know in advance the electricity pattern consumption. This knowledge is important to change behavior and reduce the global consumption. Furthermore, the load curve profile known in advance can detect the highest points and valleys and force the consumers to change their behavior principally during the high tariffs. Thus, this work proposes a fuzzy system to obtain the electrical load profile in residences. The electrical energy consumption is correlated with the active occupation of the residences, therefore the system considers the quantity of inhabitants and the different periods of the day during 24 hours. Based on this parameters it is possible to obtain the electrical load profile detecting the highest points that can compromise the efficiency of the system, and provide mechanisms to improve the demand managing besides forcing the rational use of electrical energy. To verify the efficiency of the proposed system, the results obtained are compared with real load curves measured in loco concluding that these results are promising.

Orientador: Anna Diva Plasencia Lotufo / Resumo: Considerando a crescente demanda de energia elétrica no setor residencial, faz-se necessário conhecer o padrão de consumo de eletricidade de forma detalhada, impulsionando a mudança do comportamento dos consumidores finais, com o objetivo de reduzir o consumo global e a racionalização do uso da energia elétrica. Portanto, conhecer o perfil da curva de carga, com antecedência, é importante para detectar os picos e os vales, e incentivar os consumidores a mudar seus hábitos de consumo de energia, principalmente durante os períodos em que as tarifas são mais caras. Assim, nesta pesquisa propõe-se a utilização de um sistema fuzzy para obter o perfil de carga elétrica residencial. Como o consumo de energia elétrica, em residências, está altamente correlacionado com a ocupação ativa, foram levados em consideração o número de ocupantes na residência e os diferentes períodos do dia ao longo de 24 horas. Com base neste modelo foi possível simular o perfil de carga elétrica, a detecção dos picos que podem comprometer a eficiência do sistema e, consequentemente, oferecer mecanismos para melhorar o gerenciamento de demanda e incentivar a utilização racional de energia elétrica. Com objetivo de verificar a eficiência do sistema fuzzy, comparou-se as curvas de carga obtidas pelo sistema proposto com as curvas de carga reais e por meio desta comparação foi possível observar que os resultados são promissores. / Abstract: The electrical energy demand is increasing mainly in residences. Therefore, it is necessary to know in advance the electricity pattern consumption. This knowledge is important to change behavior and reduce the global consumption. Furthermore, the load curve profile known in advance can detect the highest points and valleys and force the consumers to change their behavior principally during the high tariffs. Thus, this work proposes a fuzzy system to obtain the electrical load profile in residences. The electrical energy consumption is correlated with the active occupation of the residences, therefore the system considers the quantity of inhabitants and the different periods of the day during 24 hours. Based on this parameters it is possible to obtain the electrical load profile detecting the highest points that can compromise the efficiency of the system, and provide mechanisms to improve the demand managing besides forcing the rational use of electrical energy. To verify the efficiency of the proposed system, the results obtained are compared with real load curves measured in loco concluding that these results are promising. / Doutor