Management of an island and grid-connected microgrid using hybrid economic model predictive control with weather data

Silva, Danilo P. e; Salles, José Leandro Félix; Fardin, Jussara Farias; Pereira, Maxsuel M. Rocha

doi:10.1016/j.apenergy.2020.115581

Cited by 47 publications

(24 citation statements)

References 42 publications

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“…These models convert the temperature, GHI and wind speed data into photovoltaic and wind powers. The management algorithm presented in [1] use all these data to solve the optimal economic dispatch problem. The data presented in this brief-data article can assist researchers and companies in the energy sector to simulate and compare various energy management and conversion systems that combine heat and power [4] , intelligent buildings [5] , virtual power plants [6] , microgrids [7] , among others.…”

Section: Value Of the Datamentioning

confidence: 99%

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Measured and forecasted weather and power dataset for management of an island and grid-connected microgrid

et al. 2021

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Section: Value Of the Datamentioning

confidence: 99%

Section: Value Of the Datamentioning

confidence: 99%

Measured and forecasted weather and power dataset for management of an island and grid-connected microgrid

et al. 2021

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“…Inequality constraints are also added to handle the transitions between the charge and discharge of the battery or state of charge (SOC). These are observed in Equation ( 13); other restrictions are added to handle the voltage levels and the phase angle values to keep them within acceptable values for the operation, which are expressed in Equation ( 14) [37].…”

Section: Model-based Predictive Control (Mpc)mentioning

confidence: 99%

Optimal Management of a Microgrid with Radiation and Wind-Speed Forecasting: A Case Study Applied to a Bioclimatic Building

et al. 2021

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An Energy Management System (EMS) that uses a Model Predictive Control (MPC) to manage the flow of the microgrids is described in this work. The EMS integrates both wind speed and solar radiation predictors by using a time series to perform the primary grid forecasts. At each sampling data measurement, the power of the photovoltaic system and wind turbine are predicted. Then, the MPC algorithm uses those predictions to obtain the optimal power flows of the microgrid elements and the main network. In this work, three time-series predictors are analyzed. As the results will show, the MPC strategy becomes a powerful energy management tool when it is integrated with the Double Exponential Smoothing (DES) predictor. This new scheme of integrating the DES method with an MPC presents a good management response in real-time and overcomes the results provided by the Optimal Power Flow method, which was previously proposed in the literature. For the case studies, the test microgrid located in the CIESOL bioclimatic building of the University of Almeria (Spain) is used.

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“…In this case, the MPC used three input variables and one output variable, and it was evaluated for a 24 hours-simulation. In [19], an economic MPC-based EMS was implemented to optimize the economic dispatch of a microgrid integrating a wind turbine, a PV system, and a BES. The input variables were the electricity price, weather forecast, and energy demand, and the simulation was conducted over a week.…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Control-Based Optimized Operation of a Hybrid Charging Station for Electric Vehicles

et al. 2021

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This paper presents an energy management system (EMS) based on a novel approach using model predictive control (MPC) for the optimized operation of power sources in a hybrid charging station for electric vehicles (EVs). The hybrid charging station is composed of a photovoltaic (PV) system, a battery, a complete hydrogen system based on a fuel cell (FC), electrolyzer (EZ), and tank as an energy storage system (ESS), grid connection, and six fast charging units, all of which are connected to a common MVDC bus through Z-source converters (ZSC). The MPC-based EMS is designed to control the power flow among the energy sources of the hybrid charging station and reduce the utilization costs of the ESS and the dependency on the grid. The viability of the EMS was proved under a long-term simulation of 25 years in Simulink, using real data for the sun irradiance and a European load profile for EVs. Furthermore, this EMS is compared with a simpler alternative that is used as a benchmark, which pursues the same objectives, although using a states-based strategy. The results prove the suitability of the EMS, achieving a lower utilization cost (-25.3%), a notable reduction in grid use (-60% approximately) and an improvement in efficiency.

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Management of an island and grid-connected microgrid using hybrid economic model predictive control with weather data

Cited by 47 publications

References 42 publications

Measured and forecasted weather and power dataset for management of an island and grid-connected microgrid

Measured and forecasted weather and power dataset for management of an island and grid-connected microgrid

Optimal Management of a Microgrid with Radiation and Wind-Speed Forecasting: A Case Study Applied to a Bioclimatic Building

Model Predictive Control-Based Optimized Operation of a Hybrid Charging Station for Electric Vehicles

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