Optimal configuration of hybrid AC/DC urban distribution networks for high penetration renewable energy

Existing AC medium-voltage distribution networks are facing challenges on handling increasing loads and renewable energy integrations. However, it is very difficult to build new distribution lines in urban areas. This study proposes a configuration method of hybrid AC/DC medium-voltage distribution networks, in which some existing AC lines are converted to DC operation. Existing topologies and dispatching scenarios are considered during configuration because the overall power flow can be rescheduled in the hybrid AC/DC distribution network. Therefore, transfer capacities of the lines are fully utilised, and more renewable energies are accommodated. A bi-level programming model is established embedding chance constraint programming to consider the intermittent output of renewable energy. In the upper level, a multiple objective optimal model is proposed in order to balance investments, power losses, and the maximum load level and renewable energy capacity. In the lower level, daily operations of the newly installed VSCs are optimised by a chance constraint programming. The influences of energy storage systems on the configuration are also analysed. Simulation studies are performed to verify the proposed method

Wind Power Integration Control Technology for Sustainable, Stable and Smart Trend: A Review

The key to achieve sustainable development of wind power is integration absorptive, involving the generation, transmission, distribution, operation, scheduling plurality of electric production processes. The paper based on the analyses of the situation of wind power development and grid integration requirements for wind power, summarized wind power integration technologies' development, characteristics, applicability and trends from five aspects, grid mode, control technology, transmission technology, scheduling, and forecasting techniques. And friendly integration, intelligent control, reliable transmission, and accurate prediction would be the major trends of wind power integration, these five aspects interactive and mutually reinforcing would realize common development both grid and wind power, both economic and ecological

Achieving the Dispatchability of Distribution Feeders through Prosumers Data Driven Forecasting and Model Predictive Control of Electrochemical Storage

We propose and experimentally validate a control strategy to dispatch the operation of a distribution feeder interfacing heterogeneous prosumers by using a grid-connected battery energy storage system (BESS) as a controllable element coupled with a minimally invasive monitoring infrastructure. It consists in a two-stage procedure: day-ahead dispatch planning, where the feeder 5-minute average power consumption trajectory for the next day of operation (called \emph{dispatch plan}) is determined, and intra-day/real-time operation, where the mismatch with respect to the \emph{dispatch plan} is corrected by applying receding horizon model predictive control (MPC) to decide the BESS charging/discharging profile while accounting for operational constraints. The consumption forecast necessary to compute the \emph{dispatch plan} and the battery model for the MPC algorithm are built by applying adaptive data driven methodologies. The discussed control framework currently operates on a daily basis to dispatch the operation of a 20~kV feeder of the EPFL university campus using a 750~kW/500~kWh lithium titanate BESS.Comment: Submitted for publication, 201

Power System Simulation, Control and Optimization

This Special Issue “Power System Simulation, Control and Optimization” offers valuable insights into the most recent research developments in these topics. The analysis, operation, and control of power systems are increasingly complex tasks that require advanced simulation models to analyze and control the effects of transformations concerning electricity grids today: Massive integration of renewable energies, progressive implementation of electric vehicles, development of intelligent networks, and progressive evolution of the applications of artificial intelligence

Optimisation and Integration of Variable Renewable Energy Sources in Electricity Networks

The growing penetration of renewable energy sources (RESs) into the electricity power grid is profitable from a sustainable point of view and provides economic benefit for long-term operation. Nevertheless, balancing production and consumption is and will always be a crucial requirement for power system operation. However, the trend towards increasing RESs penetration has raised concerns about the stability, reliability and security of future electricity grids. The clearest observation in this regard is the intermittent nature of RESs. Moreover, the location of renewable generation tends to be heavily defined by meteorological and geographical conditions, which makes the generation sites distant from load centres. These facts make the analysis of electricity grid operation under both dynamic and the steady state more difficult, posing challenges in effectively integrating variable RESs into electricity networks. The thesis reports on studies that were conducted to design efficient tools and algorithms for system operators, especially transmission system operators for reliable short-term system operation that accounts for intermittency and security requirements. Initially, the impact of renewable generation on the steady state is studied in the operation stage. Then, based on the first study, more sophisticated modeling on the electricity network are investigated in the third and fourth chapters. Extending the previous studies, the fourth chapter explores the potential of using multiple microgrids to support the main grid’s security control. Finally, the questions regarding the computational efficiency and convergence analysis are addressed in chapter 5 and a DSM model in a real-time pricing environment is introduced. This model presents an alternative way of using flexibility on the demand side to compensate for the uncertainties on the generation side

Optimal dispatch of uncertain energy resources

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

Competitive power control of distributed power plants

Nowadays, the electrical energy sector is currently found in a dramatic changing paradigm, which moves towards an increasing trend in generating power at distribution levels, where electricity is typically consumed, by means of non-conventional/renewable based generation units. These new generation technologies, termed as distributed generation, not only offers a non-pollutant, cheap and efficient source of energy to cover increasing demand, but also enhance the reliability of supply to critical loads and reduce the need for additional grid reinforcements. Aside of the technical benefits provided, distributed generation will massively integrate renewable energy resources, with new type of loads and end-user actors, such as prosumers, demand responsive loads, or electric vehicles. Where these actors will actively participate in energy and auxiliary service markets, depending on their available or constrained energy needs. For this reason, the work presented in this Thesis deals with designing and implementing advanced hierarchical control solutions to renewable-based power plants with the purpose of achieving advanced grid conection performance while reaching maximum economic benefits from its optimum real-time operation. Initially, an extensive analysis on the main renewable-based power plant hierarchical control solutions currently on the shelf, is performed. This study not only covered the specific case of renewable-based power plants, but also advanced microgrid and smart grid control solutions. Once the main renewable-based power plant hierarchical solutions were analized, a novel Hierarchical Distributed Control Structure (HDCS) is proposed for increased management of renewable-based active distributed plants. This hierarchical control structure comprises all possible functional levels from the higher long-term economic scheduling layer, to the instantaneous supervisory control of the resource, emphasizing the entire operation and control functionalities needed for increasing the integration of active distributed power plants. In order to achieve real-time control capabilities in active distribution systems, the present thesis introduces a novel power sharing control strategy, based on the competitive operation of multiple active participating agents (distributed generators, demand response and energy storage systems) through the implementation of market rules. Such control capabilities are satisfied by applying a price control signal over the entire grid control architecture, being the final-end participating agent, the responsible entity in charge of deciding its own generation/demand involvement based on its marginal or affordable electricity costs. In addition, it reduces the information volume to be transmitted and processing requirements, as the higher control levels do not need to have knowledge on the detailed distribution system topology and contributing actors. In order to have a meaningful evaluation of the proposed competitive control capabilities, a wave power plant application has been selected, which constitutes a challenging scenario for the controller itself to achieve advanced real-time control capabilities in such an oscillating renewable energy resource. In order to suitably characterize the wave energy resource profile resulting from maximum energy absorption, this Thesis introduce a novel adaptive vector controller, which maximizes the energy extraction from the resource regardless of the dominant irregular wave frequency characteristics. For the specific wave power plant application considered, the competitive control does not only ensures real-time optimum resource allocation for satisfying a given production objective, but also provides optimum long term operation of the system. As a result, overall plant costs reductions can be achieved under the competitive operation, since the plant scheduled energy is satisfied by making use of the generation units with cheaper cumulative operation costsActualmente, el sector eléctrico se encuentra inmerso en un profundo proceso de restructuración, donde de cada vez más se tiende a generar energía a nivel de distribución, mediante el uso de generación no convencional/renovable. Estas nuevas tecnologías de generación, referidas como generación distribuida, no proporcionan unicamente una fuente de energía no-contaminante, barata y eficiente para cubrir el incremento de demanda, sinó que también pueden proporcionar seguridad de suministro a cargas críticas, así como reducir la necesidad de expansiones futuras de red. Además de las capacidades técnicas proporcionadas, la generación distribuida hará posible la integración masiva de sistemas de generación renovable, con nuevos tipos de cargas y usuarios finales, como prosumidores, cargas regulables, o vehiculos eléctricos, donde todos estos usuarios participaran activamente en mercados de energía y servicios auxiliares, dependiendo de sus requisitos de uso de energía. Por lo tanto, el trabajo realizado en esta tesis se centra en el diseño e implementación de soluciones jerárquicas de control avanzado en plantas de generación renovable, con el objetivo de obtener un comportamiento harmonioso de intercacción con la red, mientras la operación de la planta maximiza los beneficios derivados de su operación en tiempo real. Inicialmente, se ha llevado a cabo una revisión extensa sobre los sistemas de control jerárquico comunmente implementados en plantas de generación renovable, en microredes y en redes inteligentes. Una vez revisados los principales sistemas de control jerárquico en este tipo de aplicaciones, se propone un una novedosa estructura de control, que cubre todos los niveles de control posibles, desde el más alto nivel de gestión económica, hasta el control detallado del recurso de generación. Para lograr capacidades de control en tiempo real en sistemas activos de distribución, la presente tesis propone una nueva estrategia de control de reparto de potencia, basada en la operación competitiva de múltiples agentes participantes activos (generadores distribuidos, respuesta de demanda y sistemas de almacenamiento de energía) mediante la implementación de reglas del mercado. Dichas capacidades de control se satisfacen aplicando una señal de precio a lo largo de toda la arquitectura de control, siendo el agente de final, el ente responsable de decidir su propia participación en la generación/demanda en función de sus propios costes de electricidad marginales o asumibles. Además, reduce el volumen de información a transmitir y los requisitos de procesamiento de datos, ya que los niveles de control más altos no necesitan tener conocimiento sobre la topología del sistema de distribución detallado ni de la contribución de los actores adyacentes. Para llevar a cabo una evaluación significativa de las capacidades del controlador competitivo propuesto, se ha seleccionado una planta de generación undimotriz, como escenario más desfavorable, ya que el controlador debe asegurar un control estable de la potencia inyectada en un escenario altamente oscilante. Con el fin de caracterizar adecuadamente el perfil de recursos de energía de las olas resultante de la máxima absorción de energía, esta Tesis introduce un nuevo controlador de vector adaptativo, que maximiza la extracción de energía del recurso independientemente de las características dominantes de frecuencia de onda irregular. Para la aplicación de la planta de energía de onda específica considerada, el control competitivo no solo garantiza la asignación óptima de recursos en tiempo real para satisfacer un objetivo de producción dado, sino que también proporciona una operación óptima del sistema a largo plazo. Como resultado, se pueden lograr reducciones generales de los costos de la planta en el marco de la operación competitiva, ya que la energía programada de la planta se satisface haciendo uso de las unida

A Review of Energy Management of Renewable Multisources in Industrial Microgrids

This review aims to consolidate recent advancements in power control within microgrids and multi-microgrids. It specifically focuses on analyzing the comparative benefits of various architectures concerning energy sharing and demand cost management. The paper provides a comprehensive technical analysis of different architectures found in existing literature, which are designed for energy management and demand cost optimization. In summary, this review paper provides a thorough examination of power control in microgrids and multi-microgrids and compares different architectural approaches for energy management and demand cost optimization