An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Modeling and Control of Power Electronics Interfaced Load for Transmission Power Network Analysis

The penetration level of power electronics (PE) interfaced loads has been gradually increasing in recent years. It is beneficial to equip the electric load with a PE interface since it allows for more advanced control of the load performance. Furthermore, the increasing penetration of PE interfaced loads will bring both challenges and opportunities to power network resilience and reliability. However, the lack of modeling and control design for PE interfaced load units in the transmission-level power network analysis, especially for these high-penetrated high-power-rating load applications, limits the accuracy of evaluating the dynamic performance and stability status of the power network. Additionally, the complex configuration and high bandwidth dynamic performance of the PE interfaced load computationally prohibit the model development in transient stability (TS) simulation programs. Therefore, the dynamic PE interfaced load model can be characterized considering the following aspects: 1) Utilize the real-time experimental platform to represent the PE load dynamic performance since the power testbed can reflect the power grid operation with more robustness. 2) Adapt the simplified PE-based model to TS simulation tools, which focus on grid electromechanical transients and oscillations between 0.1 and 3 Hz. Research of the PE interfaced load towards its modeling and control design in different simulation environments and the flexible contribution to the grid operation has been conducted. First, the variable speed drive (VSD) based motor load is studied as a typical PE interfaced load, which can actively interact with power grid operation. The model of VSD load is introduced and applied to the power emulator for the multi-converter-based hardware testbed (HTB) in the Center of Ultra-wide-area Resilient Electric Energy Transmission Network (CURENT). Second, the aggregated performance of multiple VSD load units with grid frequency support function is characterized. Third, the fast electric vehicle (EV) charging unit is studied as a typical PE interfaced load with high power consumption. The generic model of EV charger load is developed based on the detailed switching model. The accuracy of the proposed EV charger load TS model has been verified by comparing it to simulation results of the equivalent electromagnetic (EMT) model

Modelling and Co-simulation of Multi-Energy Systems: Distributed Software Methods and Platforms

L'abstract è presente nell'allegato / the abstract is in the attachmen

Ontologies for the Interoperability of Heterogeneous Multi-Agent Systems in the scope of Energy and Power Systems

Tesis por compendio de publicaciones[ES]El sector eléctrico, tradicionalmente dirigido por monopolios y poderosas empresas de servicios públicos, ha experimentado cambios significativos en las últimas décadas. Los avances más notables son una mayor penetración de las fuentes de energía renovable (RES por sus siglas en inglés) y la generación distribuida, que han llevado a la adopción del paradigma de las redes inteligentes (SG por sus siglas en inglés) y a la introducción de enfoques competitivos en los mercados de electricidad (EMs por sus siglas en inglés) mayoristas y algunos minoristas. Las SG emergieron rápidamente de un concepto ampliamente aceptado en la realidad. La intermitencia de las fuentes de energía renovable y su integración a gran escala plantea nuevas limitaciones y desafíos que afectan en gran medida las operaciones de los EMs. El desafiante entorno de los sistemas de potencia y energía (PES por sus siglas en inglés) refuerza la necesidad de estudiar, experimentar y validar operaciones e interacciones competitivas, dinámicas y complejas. En este contexto, la simulación, el apoyo a la toma de decisiones, y las herramientas de gestión inteligente, se vuelven imprescindibles para estudiar los diferentes mecanismos del mercado y las relaciones entre los actores involucrados. Para ello, la nueva generación de herramientas debe ser capaz de hacer frente a la rápida evolución de los PES, proporcionando a los participantes los medios adecuados para adaptarse, abordando nuevos modelos y limitaciones, y su compleja relación con los desarrollos tecnológicos y de negocios. Las plataformas basadas en múltiples agentes son particularmente adecuadas para analizar interacciones complejas en sistemas dinámicos, como PES, debido a su naturaleza distribuida e independiente. La descomposición de tareas complejas en asignaciones simples y la fácil inclusión de nuevos datos y modelos de negocio, restricciones, tipos de actores y operadores, y sus interacciones, son algunas de las principales ventajas de los enfoques basados en agentes. En este dominio, han surgido varias herramientas de modelado para simular, estudiar y resolver problemas de subdominios específicos de PES. Sin embargo, existe una limitación generalizada referida a la importante falta de interoperabilidad entre sistemas heterogéneos, que impide abordar el problema de manera global, considerando todas las interrelaciones relevantes existentes. Esto es esencial para que los jugadores puedan aprovechar al máximo las oportunidades en evolución. Por lo tanto, para lograr un marco tan completo aprovechando las herramientas existentes que permiten el estudio de partes específicas del problema global, se requiere la interoperabilidad entre estos sistemas. Las ontologías facilitan la interoperabilidad entre sistemas heterogéneos al dar un significado semántico a la información intercambiada entre las distintas partes. La ventaja radica en el hecho de que todos los involucrados en un dominio particular los conocen, comprenden y están de acuerdo con la conceptualización allí definida. Existen, en la literatura, varias propuestas para el uso de ontologías dentro de PES, fomentando su reutilización y extensión. Sin embargo, la mayoría de las ontologías se centran en un escenario de aplicación específico o en una abstracción de alto nivel de un subdominio de los PES. Además, existe una considerable heterogeneidad entre estos modelos, lo que complica su integración y adopción. Es fundamental desarrollar ontologías que representen distintas fuentes de conocimiento para facilitar las interacciones entre entidades de diferente naturaleza, promoviendo la interoperabilidad entre sistemas heterogéneos basados en agentes que permitan resolver problemas específicos de PES. Estas brechas motivan el desarrollo del trabajo de investigación de este doctorado, que surge para brindar una solución a la interoperabilidad de sistemas heterogéneos dentro de los PES. Las diversas aportaciones de este trabajo dan como resultado una sociedad de sistemas multi-agente (MAS por sus siglas en inglés) para la simulación, estudio, soporte de decisiones, operación y gestión inteligente de PES. Esta sociedad de MAS aborda los PES desde el EM mayorista hasta el SG y la eficiencia energética del consumidor, aprovechando las herramientas de simulación y apoyo a la toma de decisiones existentes, complementadas con las desarrolladas recientemente, asegurando la interoperabilidad entre ellas. Utiliza ontologías para la representación del conocimiento en un vocabulario común, lo que facilita la interoperabilidad entre los distintos sistemas. Además, el uso de ontologías y tecnologías de web semántica permite el desarrollo de herramientas agnósticas de modelos para una adaptación flexible a nuevas reglas y restricciones, promoviendo el razonamiento semántico para sistemas sensibles al contexto

Secure Control and Operation of Energy Cyber-Physical Systems Through Intelligent Agents

The operation of the smart grid is expected to be heavily reliant on microprocessor-based control. Thus, there is a strong need for interoperability standards to address the heterogeneous nature of the data in the smart grid. In this research, we analyzed in detail the security threats of the Generic Object Oriented Substation Events (GOOSE) and Sampled Measured Values (SMV) protocol mappings of the IEC 61850 data modeling standard, which is the most widely industry-accepted standard for power system automation and control. We found that there is a strong need for security solutions that are capable of defending the grid against cyber-attacks, minimizing the damage in case a cyber-incident occurs, and restoring services within minimal time. To address these risks, we focused on correlating cyber security algorithms with physical characteristics of the power system by developing intelligent agents that use this knowledge as an important second line of defense in detecting malicious activity. This will complement the cyber security methods, including encryption and authentication. Firstly, we developed a physical-model-checking algorithm, which uses artificial neural networks to identify switching-related attacks on power systems based on load flow characteristics. Secondly, the feasibility of using neural network forecasters to detect spoofed sampled values was investigated. We showed that although such forecasters have high spoofed-data-detection accuracy, they are prone to the accumulation of forecasting error. In this research, we proposed an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed algorithms was experimentally verified on the Smart Grid testbed at FIU. The test results showed that the proposed techniques have a minimal detection latency, in the range of microseconds. Also, in this research we developed a network-in-the-loop co-simulation platform that seamlessly integrates the components of the smart grid together, especially since they are governed by different regulations and owned by different entities. Power system simulation software, microcontrollers, and a real communication infrastructure were combined together to provide a cohesive smart grid platform. A data-centric communication scheme was selected to provide an interoperability layer between multi-vendor devices, software packages, and to bridge different protocols together

Smart Grid Technologies and Implementations

Smart grid has been advocated in both developing and developed countries in many years to deal with large amount of energy deficit and air pollutions. However, many literatures talked about some specific technologies and implementations, few of them could give a clear picture on the smart grid implementations in a macro scale like what is the main consideration for the smart grid implementations, how to examine the power system operation with communication network deployment, how to determine the optimal technology scheme with consideration of economic and political constraints, and so on. Governments and related institutions are keen to evaluate the cost and benefit of new technologies or mechanisms in a scientific way rather than making decision blindly. Decision Support System, which is an information system based on interactive computers to support decision making in planning, management, operations for evaluating technologies, is an essential tool to provide decision makers with powerful scientific evidence. The objective of the thesis is to identify the data and information processing technologies and mechanisms which will enable the further development of decision support systems that can be used to evaluate the indices for smart grid technology investment in the future. First of all, the thesis introduces the smart grid and its features and technologies in order to clarify the benefits can be obtained from smart grid deployment in many aspects such as economics, environment, reliability, efficiency, security and safety. Besides, it is necessary to understand power system business and operation scenarios which may affect the communication network model. This thesis, for the first time, will give detailed requirements for smart grid simulation according to the power system business and operation. In addition, state of art monitoring system and communication system involved in smart grid for better demand side management will be reviewed in order to find out their impacts reflecting to the power systems. The methods and algorithms applied to the smart grid monitoring, communication technologies for smart grid are summarized and the monitoring systems are compared with each other to see the merits and drawbacks in each type of the monitoring system. In smart grid environment, large number of data are need to be processed and useful information are required to be abstracted for further operation in power systems. Machine learning is a useful tool for data mining and prediction. One of the typical machine learning artificial algorithms, artificial neural network (ANN) for load forecasting in large power system is proposed in this thesis and different learning methods of back-propagation, Quasi-Newton and Levenberg-Marquardt, are compared with each other to seek the best result in load forecasting. Bad load forecasting may leads to demand and generation mismatch, which could cause blackout in power systems. Load shedding schemes are powerful defender for power system from collapsing and keep the grid in integral to a maximum extent. A lesson learned from India blackout in July 2012 is analyzed and recommendations on preventing grid from blackout are given in this work. Also, a new load shedding schemes for an isolated system is proposed in this thesis to take full advantage from information sharing and communication network deployment in smart grid. Lastly, the new trend of decision support system (DSS) for smart grid implementation is summarized and reliability index and stability scenarios for cost benefit analysis are under DSS consideration. Many countries and organizations are setting renewable penetration goals when planning the contribution to reduce the greenhouse gas emission in the future 10 or 20 years. For instance, UK government is expecting to produce 27% of renewable energies EU-wide before 2030. Some simulations have been carried out to demonstrate the physical insight of a power system operation with renewable energy integration and to study the non-dispatchable energy source penetration level. Meanwhile, issues from power system reliability which may affect consumers are required to take into account. Reliability index of Centralized wind generations and that of distributed wind generations are compared with each other under an investment perspective