Contingency Management in Power Systems and Demand Response Market for Ancillary Services in Smart Grids with High Renewable Energy Penetration.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Is Energy Storage an Economic Opportunity for the Eco-Neighborhood?

International audienceIn this article, we consider houses belonging to an eco-neighborhood in which inhabitants have the capacity to optimize dynamically the energy demand and the energy storage level so as to maximize their utility. The inhabitants' preferences are characterized by their sensitivity toward comfort versus price, the optimal expected temperature in the house, thermal loss and heating efficiency of their house. At his level, the eco-neighborhood manager shares the resource produced by the eco-neighborhood according to two schemes: an equal allocation between the houses and a priority based one. The problem is modeled as a stochastic game and solved using stochastic dynamic programming. We simulate the energy consumption of the eco-neighborhood under various pricing mechanisms: flat rate, peak and off-peak hour, blue/white/red day, peak day clearing and a dynamic update of the price based on the consumption of the eco-neighborhood. We observe that economic incentives for houses to store energy depend deeply on the implemented pricing mechanism and on the homogeneity in the houses' characteristics. Furthermore, when prices are based on the consumption of the eco-neighborhood, storage appears as a compensation for the errors made by the service provider in the prediction of the consumption of the eco-neighborhood

Decision support for participation in electricity markets considering the transaction of services and electricity at the local level

[EN] The growing concerns regarding the lack of fossil fuels, their costs, and their impact on the environment have led governmental institutions to launch energy policies that promote the increasing installation of technologies that use renewable energy sources to generate energy. The increasing penetration of renewable energy sources brings a great fluctuation on the generation side, which strongly affects the power and energy system management. The control of this system is moving from hierarchical and central to a smart and distributed approach. The system operators are nowadays starting to consider the final end users (consumers and prosumers) as a part of the solution in power system operation activities. In this sense, the end-users are changing their behavior from passive to active players. The role of aggregators is essential in order to empower the end-users, also contributing to those behavior changes. Although in several countries aggregators are legally recognized as an entity of the power and energy system, its role being mainly centered on representing end-users in wholesale market participation. This work contributes to the advancement of the state-of-the-art with models that enable the active involvement of the end-users in electricity markets in order to become key participants in the management of power and energy systems. Aggregators are expected to play an essential role in these models, making the connection between the residential end-users, electricity markets, and network operators. Thus, this work focuses on providing solutions to a wide variety of challenges faced by aggregators. The main results of this work include the developed models to enable consumers and prosumers participation in electricity markets and power and energy systems management. The proposed decision support models consider demand-side management applications, local electricity market models, electricity portfolio management, and local ancillary services. The proposed models are validated through case studies based on real data. The used scenarios allow a comprehensive validation of the models from different perspectives, namely end-users, aggregators, and network operators. The considered case studies were carefully selected to demonstrate the characteristics of each model, and to demonstrate how each of them contributes to answering the research questions defined to this work.[ES] La creciente preocupación por la escasez de combustibles fósiles, sus costos y su impacto en el medio ambiente ha llevado a las instituciones gubernamentales a lanzar políticas energéticas que promuevan la creciente instalación de tecnologías que utilizan fuentes de energía renovables para generar energía. La creciente penetración de las fuentes de energía renovable trae consigo una gran fluctuación en el lado de la generación, lo que afecta fuertemente la gestión del sistema de potencia y energía. El control de este sistema está pasando de un enfoque jerárquico y central a un enfoque inteligente y distribuido. Actualmente, los operadores del sistema están comenzando a considerar a los usuarios finales (consumidores y prosumidores) como parte de la solución en las actividades de operación del sistema eléctrico. En este sentido, los usuarios finales están cambiando su comportamiento de jugadores pasivos a jugadores activos. El papel de los agregadores es esencial para empoderar a los usuarios finales, contribuyendo también a esos cambios de comportamiento. Aunque en varios países los agregadores están legalmente reconocidos como una entidad del sistema eléctrico y energético, su papel se centra principalmente en representar a los usuarios finales en la participación del mercado mayorista. Este trabajo contribuye al avance del estado del arte con modelos que permiten la participación activa de los usuarios finales en los mercados eléctricos para convertirse en participantes clave en la gestión de los sistemas de potencia y energía. Se espera que los agregadores desempeñen un papel esencial en estos modelos, haciendo la conexión entre los usuarios finales residenciales, los mercados de electricidad y los operadores de red. Por lo tanto, este trabajo se enfoca en brindar soluciones a una amplia variedad de desafíos que enfrentan los agregadores. Los principales resultados de este trabajo incluyen los modelos desarrollados para permitir la participación de los consumidores y prosumidores en los mercados eléctricos y la gestión de los sistemas de potencia y energía. Los modelos de soporte de decisiones propuestos consideran aplicaciones de gestión del lado de la demanda, modelos de mercado eléctrico local, gestión de cartera de electricidad y servicios auxiliares locales. Los modelos propuestos son validan mediante estudios de casos basados en datos reales. Los escenarios utilizados permiten una validación integral de los modelos desde diferentes perspectivas, a saber, usuarios finales, agregadores y operadores de red. Los casos de estudio considerados fueron cuidadosamente seleccionados para demostrar las características de cada modelo y demostrar cómo cada uno de ellos contribuye a responder las preguntas de investigación definidas para este trabajo

Energy patterns for business model innovation

Several transformations are occurring in the energy sector, from new emerging technologies, governmental pressure for decarbonisation and clean energy targets, to new market regulations. This changes impact on how the energy is produced and distributed to consumers, increasing the urge for energy utilities to innovate their traditional established business models, to remain competitive in the energy landscape. Business model innovation is essential to organizational performance, and it has the power to change the logic of entire industries. Business model patterns are a promising tool to support business model innovation, which can be described as solutions to recurrent problems in a business model context. Although there are several published collections of business model patterns, a structured overview on energy patterns in order to support business model innovation in the energy field is missing. In the interest of filling the gap between business models and the energy sector, an energy pattern taxonomy for business model innovation was created. Applying the modified-Delphi card sorting methodology by Paul (2008), in an iterative way, 1 expert in business models and in the energy field was asked to perform a card sorting activity in a model revised and validated by 2 other experts in a previous phase, resulting in a taxonomy with 51 energy patterns organized in 10 meaningful groups. This pattern taxonomy is useful to help energy utilities to innovate and reform their business models, and it can be used from academics and scholars to managers to innovate the business models of their firms.O sector da energia está a sofrer diversas transformações, desde novas tecnologias emergentes, pressões governamentais face a metas de descarbonização e energia limpa, a novas regulações do mercado. Estas mudanças impactam na forma como a energia é produzida e distribuída aos consumidores, aumentado a urgência de inovação das modelos de negócio estabelecidos das utilities energéticas, de forma a manter a sua competitividade no sector. A inovação de modelos de negócio é essencial ao desempenho das organizações, tendo o poder de afectar a lógica de negócio de todo o sector. Padrões de modelos de negócio são uma ferramenta promissora para apoiar a inovação, sendo descritos como soluções já comprovadas para problemas recorrentes. Apesar de existiram diversas colecções de padrões de modelos de negócio na literatura, está em falta uma visão global e estruturada sobre padrões de energia. No interesse de preencher a lacuna entre modelos de negócio e o sector energético, foi criada uma taxonomia de padrões de energia para apoiar inovação no sector. Aplicando a metodologia Delphi modificada (Paul, 2008), de uma forma iterativa, 1 especialista em modelos de negócio e em energia realizou uma actividade de card sortig num modelo revisto e validado por 2 outros especialistas, numa fase anterior, resultando numa taxonomia com 51 padrões organizados em 10 grupos significativos. A taxonomia final resultante será útil para apoiar as utilities energéticas a inovar e reformar os seus modelos de negócio, podendo ser usada desde académicos a gestores com o objectivo de inovar os seus modelos de negócio

Energy Management of Prosumer Communities

The penetration of distributed generation, energy storages and smart loads has resulted in the emergence of prosumers: entities capable of adjusting their electricity production and consumption in order to meet environmental goals and to participate profitably in the available electricity markets. Significant untapped potential remains in the exploitation and coordination of small and medium-sized distributed energy resources. However, such resources usually have a primary purpose, which imposes constraints on the exploitation of the resource; for example, the primary purpose of an electric vehicle battery is for driving, so the battery could be used as temporary storage for excess photovoltaic energy only if the vehicle is available for driving when the owner expects it to be. The aggregation of several distributed energy resources is a solution for coping with the unavailability of one resource. Solutions are needed for managing the electricity production and consumption characteristics of diverse distributed energy resources in order to obtain prosumers with more generic capabilities and services for electricity production, storage, and consumption. This collection of articles studies such prosumers and the emergence of prosumer communities. Demand response-capable smart loads, battery storages and photovoltaic generation resources are forecasted and optimized to ensure energy-efficient and, in some cases, profitable operation of the resources

Control Strategies for Multi-Controller Multi-Objective Systems

This dissertation\u27s focus is control systems controlled by multiple controllers, each having its own objective function. The control of such systems is important in many practical applications such as economic systems, the smart grid, military systems, robotic systems, and others. To reap the benefits of feedback, we consider and discuss the advantages of implementing both the Nash and the Leader-Follower Stackelberg controls in a closed-loop form. However, closed-loop controls require continuous measurements of the system\u27s state vector, which may be expensive or even impossible in many cases. As an alternative, we consider a sampled closed-loop implementation. Such an implementation requires only the state vector measurements at pre-specified instants of time and hence is much more practical and cost-effective compared to the continuous closed-loop implementation. The necessary conditions for existence of such controls are derived for the general linear-quadratic system, and the solutions developed for the Nash and Stackelberg controls in detail for the scalar case. To illustrate the results, an example of a control system with two controllers and state measurements available at integer multiples of 10% of the total control interval is presented. While both Nash and Stackelberg are important approaches to develop the controls, we then considered the advantages of the Leader-Follower Stackelberg strategy. This strategy is appropriate for control systems controlled by two independent controllers whose roles and objectives in terms of the system\u27s performance and implementation of the controls are generally different. In such systems, one controller has an advantage over the other in that it has the capability of designing and implementing its control first, before the other controller. With such a control hierarchy, this controller is designated as the leader while the other is the follower. To take advantage of its primary role, the leader\u27s control is designed by anticipating and considering the follower\u27s control. The follower becomes the sole controller in the system after the leader\u27s control has been implemented. In this study, we describe such systems and derive in detail the controls of both the leader and follower. In systems where the roles of leader and follower are negotiated, it is important to consider each controller\u27s leadership property. This property considers the question for each controller as to whether it is preferable to be a leader and let the other controller be a follower or be a follower and let the other controller be the leader. In this dissertation, we try to answer this question by considering two models, one static and the other dynamic, and illustrating the results with an example in each case. The final chapter of the dissertation considers an application in microeconomics. We consider a dynamic duopoly problem, and we derive the necessary conditions for the Stackelberg solution with one firm as a leader controlling the price in the marke

Mathematical framework for designing energy matching and trading within green building neighbourhood system

Nowadays, energy efficiency, energy matching and trading, power production based on renewable energyresources, improving reliability, increasing power quality and other concepts are providing the most important topics in the power systems analysis especially in green building in the neighbourhood systems (GBNS). To do so, the need to obtain the optimal and economical dispatch of energy matching and trading should be expressed at the same time. Although, there are some solutions in literature but there is still a lack of mathematical framework for energy matching and trading in GBNS. In this dissertation, a mathematical framework is developed with the aim of supporting an optimal energy matching and trading within a GBNS.This aim will be achieved through several optimization algorithms based on heuristic and realistic optimization techniques. The appearance of new methods based on optimization algorithms and the challenges of managing a system contain different type of energy resources was also replicating the challenges encountered in this thesis. As a result, these methods are needed to be applied in such a way to achieve maximum efficiency,enhance the economic dispatch as well as to provide the best performance in GBNS. In order to validate theproposed framework, several case studies are simulated in this thesis and optimized based on various optimization algorithms. The better performances of the proposed algorithms are shown in comparison with the realistic optimization algorithms, and its effectiveness is validated over several GBs. The obtained results show convergence speed increase and the remarkable improvement of efficiency and accuracy under different condition. The obtained results clearly show that the proposed framework is effective in achieving optimal dispatch of generation resources in systems with multiple GBs and minimizing the market clearing price for the consumers and providing the better utilization of renewable energy sources