The use of Model Predictive Control (MPC) in the optimal distribution of electrical  energy in a microgrid located in southeastern of Spain: A case study simulation

Hernández-Hernández, César; Rodríguez, Francisco; Moreno, José Carlos; Mendes, Paulo Renato da Costa; Normey‐Rico, Julio E.

doi:10.24084/repqj15.278

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…The following results comprise the constrained regulation of the outlet temperature x 2 , despite variations upon the solar radiance and outside temperature disturbances w. Real meterological data from the region of the CIESOL testebed is used for the solar radiance and temperature disturbances, considering a full hour of simulation Hernández-Hernández et al (2017). These disturbances are known form a control viewpoint; they are given in Figure 3.…”

Section: Simulation Resultsmentioning

confidence: 99%

Nonlinear Temperature Regulation of Solar Collectors with a Fast Adaptive Polytopic LPV MPC Formulation

Pipino¹,

Morato²,

Bernardi³

et al. 2020

Preprint

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Temperature control in solar collectors is a nonlinear problem: the dynamics of temperature rise vary according to the oil flowing through the collector and to the temperature gradient along the collector area. In this way, this work investigates the formulation of a Model Predictive Control (MPC) application developed within a Linear Parameter Varying (LPV) formalism, which serves as a model of the solar collector process. The proposed system is an adaptive MPC, developed with terminal set constraints and considering the scheduling polytope of the model. At each instant, two Quadratic Programming (QPs) programs are solved: the first considers a backward horizon of N steps to find a virtual modelprocess tuning variable that defines the best LTI prediction model, considering the vertices of the polytopic system; then, the second QP uses this LTI model to optimize performances along a forward horizon of N steps. The paper ends with a realistic solar collector simulation results, comparing the proposed MPC to other techniques from the literature (linear MPC and robust tube-MPC). Discussions regarding the results, the design procedure and the computational effort for the three methods are presented. It is shown how the proposed MPC design is able to outrank these other standard methods in terms of reference tracking and disturbance rejection.

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Section: Simulation Resultsmentioning

confidence: 99%

Nonlinear Temperature Regulation of Solar Collectors with a Fast Adaptive Polytopic LPV MPC Formulation

Pipino¹,

Morato²,

Bernardi³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

Nonlinear temperature regulation of solar collectors with a fast adaptive polytopic LPV MPC formulation

et al. 2020

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Optimum Allocation of Microgrid and D‐STATCOM in Radial Distribution System for Voltage Profile Enhancement Using Particle Swarm Optimization

Yenealem

2024

International Journal of Photoenergy

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The integration of microgrid (MG) and distribution static synchronous compensator (D‐STATCOM) controller in power system has become crucial for enhancing voltage profiles, improving system reliability, and minimizing power losses in radial distribution networks. This study presents an innovative approach for the optimal allocation of MG and D‐STATCOM within a radial distribution system (RDS), aimed at significantly improving voltage profiles. Particle swarm optimization (PSO), a powerful and efficient metaheuristic algorithm, is utilized to determine the optimal sizing of MG and D‐STATCOM controllers. The loss sensitivity factor (LSF) technique is employed to find the optimal position for D‐STATCOM, and the voltage stability index (VSI) is used to determine the optimal location for MG. To validate the effectiveness of the PSO‐based approach, simulations are conducted on a standard IEEE 30 bus RDS. The results indicate that the strategic placement of MGs and D‐STATCOMs markedly enhances the voltage profile across the distribution network, leading to improved power quality and reduced technical losses.

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The use of Model Predictive Control (MPC) in the optimal distribution of electrical energy in a microgrid located in southeastern of Spain: A case study simulation

Cited by 4 publications

References 19 publications

Nonlinear Temperature Regulation of Solar Collectors with a Fast Adaptive Polytopic LPV MPC Formulation

Nonlinear Temperature Regulation of Solar Collectors with a Fast Adaptive Polytopic LPV MPC Formulation

Nonlinear temperature regulation of solar collectors with a fast adaptive polytopic LPV MPC formulation

Optimum Allocation of Microgrid and D‐STATCOM in Radial Distribution System for Voltage Profile Enhancement Using Particle Swarm Optimization

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