Regulation service for the short-term management of renewable energy microgrids with hybrid storage using Model Predictive Control

García, Francisco Ramón Fernández; Bordons, Carlos

doi:10.1109/iecon.2013.6700463

Cited by 10 publications

(6 citation statements)

References 11 publications

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“…In [52] a mixed integer nonlinear optimization to solve the technical challenges is presented. A non linear model is presented in [53] and [54] the MPC problem is solved as Mixed Integer Quadratic Programming (MIQP). • Dynamic programming: The authors proposed in [55] a dynamic programming algorithm for a energy optimization analysis and power management in Microgrids with renewable energy resources and diesel generators.…”

Section: Optimization and Control Of Microgridsmentioning

confidence: 99%

Understanding Microgrids and Their Future Trends

Shrivastwa

Hably

Melizi

et al. 2019

2019 IEEE International Conference on Industrial Technology (ICIT)

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Depletion of natural resources to meet power demands has revolutionized the use of Renewable Energy Sources (RESs).The paradigm shift from the centralized to distributed control is witnessed due to the Microgrids. Different configurations using smart grids and Microgrids are expected to ensure grid stability and security.Eventually, electricity market is subjected to change due to the projected changes in the grid architecture. This paper is a review on the Microgrids, its elements and the controllability. This paper discusses the major issues in the Microgrids, the factors affecting the choice of the Microgrid type and also various generation sources and their combination for reliable power quality and control. Recent developments with future trends are also addressed in this paper.

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Section: Optimization and Control Of Microgridsmentioning

confidence: 99%

Understanding Microgrids and Their Future Trends

Shrivastwa

Hably

Melizi

et al. 2019

2019 IEEE International Conference on Industrial Technology (ICIT)

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“…De esta forma, una planta de generación renovable se puede convertir en una planta despachable. Estas plantas pueden por tanto participar en el mercado en distintas escalas de tiempo, incluido el corto plazo y por tanto colaborar en el servicio de regulación (Garcia and Bordons, 2013b), vendiendo energía a un precio muy alto para el mantenimiento de la frecuencia y de la estabilidad de la red. Esto las hace muy atractivas, por lo que el desarrollo de algoritmos de operaciónóptima de las VPPs es un tema con gran proyección de futuro.…”

Section: Líneas Abiertasunclassified

Gestión Óptima de la Energía en Microrredes con Generación Renovable

Bordons

García-Torres²,

Valverde

2015

Revista Iberoamericana de Automática e Informática Industrial R

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ResumenEste artículo se centra en los temas relacionados con la operaciónóptima de las microrredes, que son conjuntos de cargas, generadores y sistemas de almacenamiento de energía, aislados o conectados al resto de la red eléctrica, que pueden ser gestionados de manera coordinada para suministrar electricidad de forma fiable. Se aborda la problemática y las soluciones de control tanto para la gestión del reparto de la carga entre los distintos generadores y almacenamiento como para la integración de la microrred en el mercado eléctrico. Se presentan diseños de controladores en el marco del Control Predictivo Basado en Modelo (Model Predictive Control, MPC) para casos que incluyen diversas fuentes renovables, como energía solar y eólica, y almacenamiento híbrido con hidrógeno, lo que permite gestionar el balance de energía en distintas escalas de tiempo. Se muestran algunos resultados experimentales en una microrred de laboratorio así como estudios de planificación para el mercado eléctrico. Los resultados obtenidos indican que el desarrollo de controladores adecuados facilitará una participación competitiva de las energías renovables y la integración de las microrredes en el nuevo modelo de sistema eléctrico. Copyright c 2015 CEA. Publicado por Elsevier España, S.L. Todos los derechos reservados.

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“…In the papers presented in References [12,[33][34][35][36][37], the optimization problem is based on complex particular cost functions for all systems, defining an objective function that integrates the economic costs associated with the use of the electrical grid, as well as the equipment's amortization costs. The proposed energy management problem is based on cost minimization, as well as the maintenance of certain levels of energy in the energy storage systems, posing a tracking problem.…”

Section: Introductionmentioning

confidence: 99%

Extended Model Predictive Controller to Develop Energy Management Systems in Renewable Source-Based Smart Microgrids with Hydrogen as Backup. Theoretical Foundation and Case Study

et al. 2020

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This article presents a methodological foundation to design and experimentally test a Model Predictive Controller (MPC) to be applied in renewable source-based microgrids with hydrogen as backup. The Model Predictive Controller has been developed with the aim to guarantee the best energy distribution while the microgrid operation is optimized considering both technical and economic parameters. As a differentiating element, this proposal provides a solution to the problem of energy management in real systems, addressing technological challenges such as charge management in topologies with direct battery connection, or loss of performance associated with equipment degradation or the required dynamics in the operation of hydrogen systems. That is, the proposed Model Predictive Controller achieves the optimization of microgrid operation both in the short and in the long-term basis. For this purpose, a generalized multi-objective function has been defined that considers the energy demand, operating costs, system performance as well as the suffered and accumulated degradation by microgrid elements throughout their lifespan. The generality in the definition of the model and cost function, allows multi-objective optimization problems to be raised depending on the application, topology or design criteria to be considered. For this purpose, a heuristic methodology based on artificial intelligence techniques is presented for the tuning of the controller parameters. The Model Predictive Controller has been validated by simulation and experimental tests in a case study, where the performance of the microgrid under energy excess and deficit situations has been tested, considering the constrains defined by the degradation of the systems that make up the microgrid. The designed controller always made it possible to guarantee both the power balance and the optimal energy distribution between systems according to the predefined priority and accumulated degradation, while guaranteeing the maximum operating voltage of the system with a margin of error less than 1%. The simulation and experimental results for the case study showed the validity of the controller and the design methodology used.

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Regulation service for the short-term management of renewable energy microgrids with hybrid storage using Model Predictive Control

Cited by 10 publications

References 11 publications

Understanding Microgrids and Their Future Trends

Understanding Microgrids and Their Future Trends

Gestión Óptima de la Energía en Microrredes con Generación Renovable

Extended Model Predictive Controller to Develop Energy Management Systems in Renewable Source-Based Smart Microgrids with Hydrogen as Backup. Theoretical Foundation and Case Study

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