Optimal operation scheduling for a smart greenhouse integrated microgrid

Ouammi, Ahmed; Achour, Yasmine; Dagdougui, Hanane; Zejli, Driss

doi:10.1016/j.esd.2020.08.001

Cited by 36 publications

(22 citation statements)

References 40 publications

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“…[84] has employed data driven techniques for the modeling of the occupancy estimation. Determined by the nature of the models and constraints, mixed integers linear programming (MILP) [73,85] or nonlinear programming (NLP) [86,87] optimization methods have been exploited in the literature. The HVAC Building system has significant influence on the disturbances on its dynamics.…”

Section: Microgrid Connected Building Comfort Management Systemsmentioning

confidence: 99%

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Model Predictive Control for Microgrid Functionalities: Review and Future Challenges

et al. 2021

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Renewable generation and energy storage systems are technologies which evoke the future energy paradigm. While these technologies have reached their technological maturity, the way they are integrated and operated in the future smart grids still presents several challenges. Microgrids appear as a key technology to pave the path towards the integration and optimized operation in smart grids. However, the optimization of microgrids considered as a set of subsystems introduces a high degree of complexity in the associated control problem. Model Predictive Control (MPC) is a control methodology which has been satisfactorily applied to solve complex control problems in the industry and also currently it is widely researched and adopted in the research community. This paper reviews the application of MPC to microgrids from the point of view of their main functionalities, describing the design methodology and the main current advances. Finally, challenges and future perspectives of MPC and its applications in microgrids are described and summarized.

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Section: Microgrid Connected Building Comfort Management Systemsmentioning

confidence: 99%

“…Ref. [89] demonstrated MPC strategy on its microgrid system coupled with the marina of Ballen similarly [85] for the application of greenhouse and Ref. [90] has explored the possibility of subways integrated with a smart microgrid and its optimal performance.…”

Section: Microgrid Connected Building Comfort Management Systemsmentioning

confidence: 99%

Model Predictive Control for Microgrid Functionalities: Review and Future Challenges

et al. 2021

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“…The essence of using the physical method is to establish a physical model of a greenhouse through mechanism analysis and use a multivariate decoupling method to achieve control [25]. More specifically, control strategies include robust controls proposed by Linker [26] and Bennis [27], nonlinear controls used by Pasgianos [28] and Wu Xiuhua [29], adaptive controls used by Cunha [30], Guzman [31], Ahmed [32], etc., and model prediction control, etc. used by Camacho [33], Ramirez [34], Berenguer [35], etc.…”

Section: Related Workmentioning

confidence: 99%

Complex Event Processing Methods for Greenhouse Control

Jia

2021

Agriculture

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In the greenhouse environment, the application of complex event processing (CEP) technology can effectively tackle the problem of recognition of the complex patterns that appeared in greenhouse conditions. In the existing research, few scholars have proposed a scheme to integrate complicated scenes within the greenhouse environment with high efficiency, convenience, and low coupling. Therefore, in order to solve the problem of hard recognition and fusion of complex patterns in the greenhouse environment, based on the characteristics of the greenhouse, this paper proposes a complex event processing method for greenhouse control. Our method has high applicability and high expansibility, including 13 types of event processing agents and 21 types of typical events involved in greenhouse automatic control. This method has the advantages of low information coupling and multi-domain integration, which can be directly used by agricultural experts and related workers and is of great significance to promote the extensive application of CEP technology in the greenhouse field. Our experiment successfully realized a greenhouse intelligent control system based on CEP technology is successfully realized in our experiment. The experimental statistics shows that the structure of the control system was accessible and effective.

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“…Only the second expression will be used from now on, as it will allow generalizations to the first one. In any case, as both P 1 and δ D,1 are decision variables, their product would turn the optimization problem into a non-linear one when substituting O 2 into Equation (18). To avoid this, δ D,1 can be removed from δ O (making that element equal to one), since P 1 is already constrained by the on/off state of the pump through Equations ( 22) and ( 23), which leads to transformation of Equation ( 18) into Equation ( 24):…”

Section: Device-dependent Fixed and Variable Loadsmentioning

confidence: 99%

“…Another concern, particularly in greenhouses, is that energy consumption seems to have settled down as a significant factor that hinders their development [16], and many proposals have started to tackle dispatch problems from a wider perspective, that is, integrating all the resources required for crop development (water, energy, CO 2 , etc. ); just to cite a few examples: optimally using combined heating and power facilities [17], determining the operation scheduling of a greenhouse with CO 2 enrichment and artificial lighting [18], or managing water production and its use [19,20].…”

Section: Introductionmentioning

confidence: 99%

A Flexible Tool for Modeling and Optimal Dispatch of Resources in Agri-Energy Hubs

et al. 2020

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The dispatch of energy and resources in agricultural systems often involves the definition and resolution of optimization problems. This paper presents a novel tool composed of a set of MATLAB® and Simulink® files that has been developed to ease such tasks. In contrast to other alternatives, it allows the consideration of multiple kinds of resources in the problem and the relationships between the inputs and outputs of the system; its parametrization can be defined graphically in Simulink® without requiring third party software, and the entire package is freely available on Github. The package can generate the constraints in MATLAB® code and can get the optimal dispatch schedule for the deterministic mixed-integer linear problem that represents the defined system. Its main functions and blocks as well as a case study based on a traditional Mediterranean greenhouse and a photovoltaic parking lot located in Almeria (Spain) are included to demonstrate its use and clarify how the problem is formulated. The simulation performed validates the tool as being useful for decision-making (schedule irrigation and CO2 enrichment, as well as managing storage systems) in these and similar environments. Future implementations are intended to incorporate the interconnection of agents with opposed interests and robust optimization strategies for uncertain scenarios.

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Optimal operation scheduling for a smart greenhouse integrated microgrid

Cited by 36 publications

References 40 publications

Model Predictive Control for Microgrid Functionalities: Review and Future Challenges

Model Predictive Control for Microgrid Functionalities: Review and Future Challenges

Complex Event Processing Methods for Greenhouse Control

A Flexible Tool for Modeling and Optimal Dispatch of Resources in Agri-Energy Hubs

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