Uma condição fundamental para que um mercado seja competitivo é que existam muitos compradores e, em especial, compradores que possam responder aos preços. Os consumidores reagem para se ajustarem aos preços de acordo com sua disposição em consumir um determinado bem. À medida que o preço se eleva, os consumidores tendem a reduzir a quantidade demandada e, quando o preço cai, os consumidores tendem a aumentar o volume demandado. A sensibilidade dos consumidores às mudanças de preços é caracterizada pela elasticidade-preço da demanda. Contudo, nos desenhos de mercados de energia elétrica, é comum a concentração de atenção no lado do suprimento, assumindo-se, implicitamente, que toda a demanda é inelástica. O presente trabalho contempla uma análise dos mecanismos de formação de preços de curto prazo adotados em mercados de energia elétrica (i.e. formação baseada em custos e formação baseada em ofertas) e, a partir desse contexto, avalia os benefícios da introdução de mecanismos de incentivo à participação da demanda na determinação dos preços do mercado de curto prazo como forma de elevar sua eficiência econômica. / Given an economic environmental, a fundamental condition for a market be suitable to competition is that must has a plenty of buyers and, in special, those who can react to price signals. The consumers reaction aims at to adjust their energy requirements to the prices according to their disposal to access a certain product or service. As the price increases, the consumers tend to reduce the demanded volume and, on the other hand, when the prices decreases, the consumers increase the demanded volume. The consumers´ reaction to the price changes is characterized by the price elasticity of demand. However, in the electric energy market design, it is common to pay attention to the supply side, taking into account, implicitly, that all demand is inelastic. This work performs an analysis of mechanisms of spot price formation adopted by electric energy markets (i.e. cost based and bid based prices) and, from this context, evaluates the benefits of incentive mechanisms to the demand participation in determining short-term market price as an option to improve the economic efficiency.

O incremento nos padrões de consumo de energia elétrica e o fácil acesso a diversas tecnologias eletroeletrônicas têm contribuído para a superação anual dos índices de consumo de eletricidade. Tendo em vista que esse insumo ainda não é economicamente armazenável em larga escala, se faz necessário manter o equilíbrio em tempo real entre a oferta/demanda mais perdas. Entretanto, a maioria dos consumidores brasileiros atendidos em baixa tensão paga tarifas baseadas nos custos médios, os quais ocultam os efeitos da alta concentração de consumo de eletricidade em determinados horários do dia. Nesse contexto, o presente estudo analisa o impacto que Programas de Resposta à Demanda (PRD), baseado em tarifas com diferenciação horária, exercem sobre o desempenho dos sistemas de distribuição. A metodologia proposta utiliza o conceito de elasticidade-preço da demanda de energia elétrica, por meio de uma abordagem matricial e permite representar diferentes tipos de consumidores. A partir de uma análise de sensibilidade dos estudos de casos, verificou-se a influência dos parâmetros que compõem as equações do PRD proposto. Para avaliar o desempenho do modelo, foram feitos estudos numéricos usando uma versão modificada do sistema teste IEEE de 34 nós. A análise de sensibilidade entre os estudos de caso apresentou uma avaliação do percentual de adesão dos consumidores, bem como o comportamento das perdas ativas mensais e do perfil de tensão. Os resultados obtidos no presente estudo evidenciam a validade da abordagem proposta, a partir de uma formulação simplificada, além de demonstrar a potencial aplicabilidade a casos reais. / Power consumption behavior increase and easy access to electroelectronics technologies had contributed to annual power consumption rates surpass. As there is not yet an economically sustainable way to store electric power it is necessary to maintain the balance between offer and power demand (considering losses). Brazilian customers majority supplied in low voltage are charged by its mean power consumption masking peak consumption in certain periods of the day. Within this reality the present work analysis the impact of Demand Response Programs (DRP) using Time-Of-Use tariff (TOU) over the power distribution system’s performance. The proposed methodology applies the concept of Price Elasticity demand and uses the representation of different consumers’ types in a matrix approach. The DRP parameters’ variation impact was checked using a sensitivity analysis. In order to evaluate the performance of the proposed model numerical studies were done using the IEEE 34 modified node test feeder. A sensitivity analysis among the case studies presents the customers adherence percentage and the monthly active power losses and voltage profile. The methodology's results besides supporting the proposal approach from a simplified formulation show the potential use on real cases.

Orientador: Prof. Dr. Thales Sousa / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, 2014. / No Brasil a taxa de crescimento de demanda é elevada por se tratar de um país em desenvolvimento. No entanto, em alguns períodos, a capacidade elétrica instalada não acompanha esse ritmo de crescimento. Tal fato resulta em problemas como redução da segurança do sistema e dificuldades em manter a energia a preços baixos nos períodos de maior consumo. A resposta da demanda é um conceito que pode ser aplicado a fim de minimizar esses impactos. Nesse sentido, foi proposto um estudo de como a resposta da demanda pode ser aplicada em mercados de energia elétrica e quais são os impactos no preço de curto prazo nesse tipo de mercado. Além disso, foi discutida a importância do preço de curto prazo na tomada de decisões de diferentes classes de agentes do setor elétrico brasileiro. Os modelos DECOMP e NEWAVE foram apresentados e analisados de forma abrangente. Foram analisados os impactos da implantação da modalidade tarifária branca no preço de curto prazo. Por fim, foi proposta uma política de resposta da demanda de maneira que os impactos na formação do preço de curto prazo fossem avaliados. / In this study, it has been a presented detailing of the electric energy demand and the expectations of the demand evolution in the Brazilian electric system as it is predicted by the system planner. The rate of growth of demand in Brazil is high, since it is a developing country, nevertheless, the installed electrical capacity do not follow this rate of growth. This fact results in problems such as the reducing of the security of the system and difficulties in keeping the low prices of energy in peak period. The demand response is a concept that can be applied in order to minimize these impacts. It has been studied how the demand response can be applied in electric market and what are the impacts in the short term price in this type of market. Besides, it has been discussed the importance of the short term price in decision-making of different classes of electric sector agents. The models to be used in DECOMP and NEWAVE were presented and analysed in a comprehensive manner. It has been analysed the impacts of the implementing of the Brazilian white tariff in the short term pricing. Finally, it has been proposed a demand response policy in a manner that the impacts in the short term pricing were analysed.

Uma condição fundamental para que um mercado seja competitivo é que existam muitos compradores e, em especial, compradores que possam responder aos preços. Os consumidores reagem para se ajustarem aos preços de acordo com sua disposição em consumir um determinado bem. À medida que o preço se eleva, os consumidores tendem a reduzir a quantidade demandada e, quando o preço cai, os consumidores tendem a aumentar o volume demandado. A sensibilidade dos consumidores às mudanças de preços é caracterizada pela elasticidade-preço da demanda. Contudo, nos desenhos de mercados de energia elétrica, é comum a concentração de atenção no lado do suprimento, assumindo-se, implicitamente, que toda a demanda é inelástica. O presente trabalho contempla uma análise dos mecanismos de formação de preços de curto prazo adotados em mercados de energia elétrica (i.e. formação baseada em custos e formação baseada em ofertas) e, a partir desse contexto, avalia os benefícios da introdução de mecanismos de incentivo à participação da demanda na determinação dos preços do mercado de curto prazo como forma de elevar sua eficiência econômica. / Given an economic environmental, a fundamental condition for a market be suitable to competition is that must has a plenty of buyers and, in special, those who can react to price signals. The consumers reaction aims at to adjust their energy requirements to the prices according to their disposal to access a certain product or service. As the price increases, the consumers tend to reduce the demanded volume and, on the other hand, when the prices decreases, the consumers increase the demanded volume. The consumers´ reaction to the price changes is characterized by the price elasticity of demand. However, in the electric energy market design, it is common to pay attention to the supply side, taking into account, implicitly, that all demand is inelastic. This work performs an analysis of mechanisms of spot price formation adopted by electric energy markets (i.e. cost based and bid based prices) and, from this context, evaluates the benefits of incentive mechanisms to the demand participation in determining short-term market price as an option to improve the economic efficiency.

The global energy demand in residential sector is increasing steadily every year due to advancement in technologies. The present electricity grid is designed to support peak demand rather than Peak to Average (PAR) demand. Utilities are investigating the residential Demand Response (DR) to lower the (PAR) ratio and eliminate the need of building new power infrastructure. This requires Home Energy Management System (HEMS) at grid edge to manage and control the energy demand. In this thesis, we presented an MDPSO based DR enabled HEMS model for optimal allocation of energy resources in a smart dwelling. The algorithm is designed to lower peak energy demand as well as encourage the active participation of customers by offering a reward to comply with DR request. We categorized appliances as elastic non-deferrable loads and inelastic deferrable loads based on their DR potential and operating characteristics. The scheduling of elastic and inelastic class of appliances is performed separately using canonical and binary version of PSO given how we expressed out load categories. We performed use case simulation to validate the performance of MDPSO for combination of different tariffs: Time of Use (TOU), TOU and Critical peak rebate signal (CPR), TOU and upper demand limit. Simulation results show that algorithm can reduce the electricity cost in range of 28% to 7% under increasing comfort conditions in response to TOU prices and Peak demand reduction of about 24% under TOU pricing and medium comfort conditions for single household. Under CPR DR requests, with respect to TOU pricing, there is effectively no change in the peak under the minimum comfort scenario. Furthermore, algorithm is able to suppress the peak upto 25% under combination of TOU and hard constraint on maximum power withdrawn from grid with no change in the electricity cost. Scheduling of multiple houses under TOU pricing results in peak reduction of 7 % as compared to baseline state. Under combination of TOU and CPR the aggregate peak energy demand of multiple households during DR activation time intervals is reduced by 32 %. The algorithm can suppress the peak demand by 27% under TOU and hard constraint on maximum power withdrawn from grid by multiple houses.

Within the broad topical designation of “smart grid,” research in demand response, or demand-side management, focuses on investigating possibilities for electrically powered devices to adapt their power consumption patterns to better match the availability of intermittent renewable energy sources, especially wind. Devices such as battery chargers, heating and cooling systems, and computers can be controlled to change the time, duration, and magnitude of their power consumption while still meeting workload constraints such as deadlines and rate of throughput. This thesis presents a system by which a computer server, or multiple servers in a data center, can estimate the power imbalance on the electrical grid and use that information to dynamically change the power consumption as a service to the grid. Implementation on a testbed demonstrates the system with a hypothetical but realistic usage case scenario of an online video streaming service in which there are workloads with deadlines (high-priority) and workloads without deadlines (low-priority). The testbed is implemented with real servers, estimates the power imbalance from the grid frequency with real-time measurements of the live outlet, and uses a distributed, real-time algorithm to dynamically adjust the power consumption of the servers based on the frequency estimate and the throughput of video transcoder workloads. Analysis of the system explains and justifies multiple design choices, compares the significance of the system in relation to similar publications in the literature, and explores the potential impact of the system.

The future of the electric grid requires advanced control technologies to reliably integrate high level of renewable generation and residential and small commercial distributed energy resources (DERs). Flexible loads are known as a vital component of future power systems with the potential to boost the overall system efficiency. Recent work has expanded the role of flexible and controllable energy resources, such as energy storage and dispatchable demand, to regulate power imbalances and stabilize grid frequency. This leads to the DER aggregators to develop concepts such as the virtual energy storage system (VESS). VESSs aggregate the flexible loads and energy resources and dispatch them akin to a grid-scale battery to provide flexibility to the system operator. Since the level of flexibility from aggregated DERs is uncertain and time varying, the VESSs’ dispatch can be challenging. To optimally dispatch uncertain, energy-constrained reserves, model predictive control offers a viable tool to develop an appropriate trade-off between closed-loop performance and robustness of the dispatch. To improve the system operation, flexible VESSs can be formulated probabilistically and can be realized with chance-constrained model predictive control. The large-scale deployment of flexible loads needs to carefully consider the existing regulation schemes in power systems, i.e., generator droop control. In this work first, we investigate the complex nature of system-wide frequency stability from time-delays in actuation of dispatchable loads. Then, we studied the robustness and performance trade-offs in receding horizon control with uncertain energy resources. The uncertainty studied herein is associated with estimating the capacity of and the estimated state of charge from an aggregation of DERs. The concept of uncertain flexible resources in markets leads to maximizing capacity bids or control authority which leads to dynamic capacity saturation (DCS) of flexible resources. We show there exists a sensitive trade-off between robustness of the optimized dispatch and closed-loop system performance and sacrificing some robustness in the dispatch of the uncertain energy capacity can significantly improve system performance. We proposed and formulated a risk-based chance constrained MPC (RB-CC-MPC) to co-optimize the operational risk of prematurely saturating the virtual energy storage system against deviating generators from their scheduled set-point. On a fast minutely timescale, the RB-CC-MPC coordinates energy-constrained virtual resources to minimize unscheduled participation of ramp-rate limited generators for balancing variability from renewable generation, while taking into account grid conditions. We show under the proposed method it is possible to improve the performance of the controller over conventional distributionally robust methods by more than 20%. Moreover, a hardware-in-the-loop (HIL) simulation of a cyber-physical system consisting of packetized energy management (PEM) enabled DERs, flexible VESSs and transmission grid is developed in this work. A predictive, energy-constrained dispatch of aggregated PEM-enabled DERs is formulated, implemented, and validated on the HIL cyber-physical platform. The experimental results demonstrate that the existing control schemes, such as AGC, dispatch VESSs without regard to their energy state, which leads to unexpected capacity saturation. By accounting for the energy states of VESSs, model-predictive control (MPC) can optimally dispatch conventional generators and VESSs to overcome disturbances while avoiding undesired capacity saturation. The results show the improvement in dynamics by using MPC over conventional AGC and droop for a system with energy-constrained resources.

The growing computational demand of scientific applications has greatly motivated the development of large-scale high-performance computing (HPC) systems in the past decade. To accommodate the increasing demand of applications, HPC systems have been going through dramatic architectural changes (e.g., introduction of many-core and multi-core systems, rapid growth of complex interconnection network for efficient communication between thousands of nodes), as well as significant increase in size (e.g., modern supercomputers consist of hundreds of thousands of nodes). With such changes in architecture and size, the energy consumption by these systems has increased significantly. With the advent of exascale supercomputers in the next few years, power consumption of the HPC systems will surely increase; some systems may even consume hundreds of megawatts of electricity. Demand response programs are designed to help the energy service providers to stabilize the power system by reducing the energy consumption of participating systems during the time periods of high demand power usage or temporary shortage in power supply. This dissertation focuses on developing energy-efficient demand-response models and algorithms to enable HPC system's demand response participation. In the first part, we present interconnection network models for performance prediction of large-scale HPC applications. They are based on interconnected topologies widely used in HPC systems: dragonfly, torus, and fat-tree. Our interconnect models are fully integrated with an implementation of message-passing interface (MPI) that can mimic most of its functions with packet-level accuracy. Extensive experiments show that our integrated models provide good accuracy for predicting the network behavior, while at the same time allowing for good parallel scaling performance. In the second part, we present an energy-efficient demand-response model to reduce HPC systems' energy consumption during demand response periods. We propose HPC job scheduling and resource provisioning schemes to enable HPC system's emergency demand response participation. In the final part, we propose an economic demand-response model to allow both HPC operator and HPC users to jointly reduce HPC system's energy cost. Our proposed model allows the participation of HPC systems in economic demand-response programs through a contract-based rewarding scheme that can incentivize HPC users to participate in demand response.

Access to reliable electric power is considered by the developed world to be a minimum requirement for a reasonable standard of living. In addition to meeting a fluctuating demand, the modern electricity industry must now integrate intermittent generation sources like wind into the grid. Reserve margin allocation (RMA) for an acceptable loss of load expectation (LOLE) allows traditional generators to maintain grid reliability in the presence of small penetrations of wind energy. However, traditional RMA over-allocates the reserve capacity in the presence of short-term intermittency mitigation techniques like energy storage and demand response. For economic operation of the modern, grid better characterization techniques are needed for reserve margin reduction behavior in the presence of wind energy. This thesis addresses this challenge with a quantitative RMA analysis using real-world and simulated wind data for three different grid scenarios, with and without intermittency mitigation. The research is novel in its first-principles approach and its investigation into the practical validity of the analogy between demand response and energy response.

Les défis environnementaux et l'augmentation de la population viennent en preuve de l'importance de réfléchir à d'autres moyens de production tout en maintenant la sécurité et la fiabilité du système électrique. La sûreté du système électrique exige à tout moment que la production soit égale à la demande des consommateurs, pour ça, différentes solutions sont déjà mises en place, ces solutions consistent à mettre en marche des moyens de pointes couteux et polluants pendant les périodes de pointes, mais comme les moyens de production son insuffisants et vue la difficulté d'exploitation de nouveaux moyens de production, une nouvelle réflexion sur la gestion de la demande est apparue; celle-ci se base sur la possibilité à gérer la demande du consommateur final au lieu de la satisfaire.L'objectif de la thèse est d'étudier la possibilité à rendre des services au système électrique en appliquant des actions de contrôle dites de DR (Demand Response), sur différents types de charges électriques. Ces actions de DR représentent des interruptions partielles appliquées sur les charges électriques de type thermique. Notre choix s'est basé sur ces types de charges parce que celles-ci emmagasinent de la chaleur respectivement dans l'air et dans l'eau; qui peut être restituée pendant la période de contrôle ou d'interruption. Néanmoins, il existe un effet négatif qui suit le contrôle de ces charges car l'énergie effacée de ces charges est reportée à l'instant de reconnexion de celles-ci; ce report prend la forme d'un pic de consommation nommé CLPU (Cold Load Pick-Up) et qui apparait au moment de la reconnexion. Le CLPU représente un problème qui doit être géré, et sa magnitude dépend des types d'actions de contrôle qu'on veut implanter et aussi des conditions du système électrique (contingence, défaillance d'une unité de production ou besoin de réserve de puissance). Pendant la thèse, le CLPU est contrôlé et optimisé ainsi que la puissance effacée. Un cas d'étude est présenté sur la contribution des actions de gestion de la demande à l'ajustement entre la demande et la production et l'effet généré sur le réglage secondaire de fréquence.