Model Predictive Control of Microgrids

Bordons, Carlos; García-Torres, Félix; Ridao, Miguel A.

doi:10.1007/978-3-030-24570-2

Cited by 115 publications

(142 citation statements)

References 0 publications

Supporting

Mentioning

105

Contrasting

Unclassified

Order By: Relevance

“…A major advantage of MPC is the constraints' consideration, even in complicated or nonlinear form. Constraints are essential for MG, where limits are imposed in every component, from voltages and currents of distributed generators and storage units to power flows in the distribution lines [84].…”

Section: A Model Predictive Controlmentioning

confidence: 99%

“…MPC offers a wide range of model structures, prediction horizons and optimization objectives from long-term scheduling with long prediction horizons to fast computations with short prediction horizons and sampling times [84]. Thus, MPC-based controllers have been proposed for various problems, spanning from cost optimization to disturbances mitigation.…”

Section: A Model Predictive Controlmentioning

confidence: 99%

“…However, in decentralized topologies, where each subsystem is managed by a single agent applying local optimization, the lack of knowledge about the overall system leads to sub-optimal solutions, since the prediction accuracy is decreased [96,97]. Distributed MPC is also based on communication among neighboring agents, which, although limited, can suffer from related failures [84].…”

Section: A Model Predictive Controlmentioning

confidence: 99%

See 2 more Smart Citations

The Evolution of Research in Microgrids Control

Vasilakis

Zafeiratou

Lagos

et al. 2020

IEEE Open J. Power Energy

View full text Add to dashboard Cite

Microgrids (MGs), as novel paradigms of active Distribution Networks, have been gaining increasing interest by the research community in the last 20 years. Currently, they are considered as key components in power system decentralization, providing viable solutions for rural electrification, enhancing resilience and supporting local energy communities. Their main characteristic is the coordinated control of the interconnected distributed energy resources (DER), which can be realized by various methods, ranging from decentralized communicationfree approaches to centralized ones, where decisions are taken at a central point. This paper provides an overview of this development focusing on the technical control solutions proposed by reseachers for the various levels of MG organization hierarchy. A critical assessment of selected, popular technologies is provided and open research questions regarding the trend to more decentralized power systems are discussed.

show abstract

Section: A Model Predictive Controlmentioning

confidence: 99%

Section: A Model Predictive Controlmentioning

confidence: 99%

Section: A Model Predictive Controlmentioning

confidence: 99%

See 1 more Smart Citation

The Evolution of Research in Microgrids Control

Vasilakis

Zafeiratou

Lagos

et al. 2020

IEEE Open J. Power Energy

View full text Add to dashboard Cite

show abstract

“…The following assumptions have been considered in order to calculate the optimal prediction of x (t + j). Firstly, the state-space model given by (6) has been rewritten according to (10) where A and C are identity matrices of an appropriate size.…”

Section: State-space Model Predictive Controlmentioning

confidence: 99%

“…For instance, in [8] optimal controllers for distributed renewable generation networks and batteries storage are presented. Likewise [9,10] illustrates the use of centralized MPC techniques. In [11] a review of different types of control approaches applied to microgrids (such as rule-based, model predictive control and occupancy based model predictive control for buildings) is performed.…”

Section: Introductionmentioning

confidence: 99%

Event-based state-space model predictive control of a renewable hydrogen-based microgrid for office power demand profiles

Castilla

Bordons

Visioli

2020

Journal of Power Sources

View full text Add to dashboard Cite

This paper focuses on the design and implementation of an event-based control architecture to manage a renewable-based microgrid. This microgrid has renewable-energy generation and a hybrid energy storage system that uses electricity and hydrogen. The main load of the microgrid is the energy demand of an office. The primary control objective is to satisfy the load demand using the available renewable generation and stored energy while reducing the amount of energy purchased from the Utility Power Grid (UPG). To do that, the control architecture, which has been defined within an event framework, makes use of a set of state-space model predictive controllers which are selected as a function of a variable sampling period. To evaluate the performance of the proposed control architecture, simulation tests for a typical day of summer as well as an analytical study is performed. Furthermore, a comparison of the obtained results with a classic state-space model predictive control approach is also included. The obtained results show that the use of the event-based control architecture allows a significant reduction of the number of changes in the control action at the expense of an acceptable deterioration of set-point tracking for a microgrid with several types of electrochemical storage.

show abstract

Microgrid Control: Concepts and Fundamentals

2023

Microgrids

View full text Add to dashboard Cite

Model Predictive Control of Microgrids

Cited by 115 publications

References 0 publications

The Evolution of Research in Microgrids Control

The Evolution of Research in Microgrids Control

Event-based state-space model predictive control of a renewable hydrogen-based microgrid for office power demand profiles

Microgrid Control: Concepts and Fundamentals

Contact Info

Product

Resources

About