Model Predictive Control Based Energy Management of a Household Microgrid

Yan, Hui; Zhuo, Fang; Lv, Nian; Hao, Yi; Wang, Zhenxiong; Liu, Cuicui

doi:10.1109/pedg.2019.8807657

Cited by 6 publications

(1 citation statement)

References 10 publications

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“…A microgrid platform was deployed that included an Open Platform Communication technology-based communication system to ensure the realtime operation of advanced energy management strategies. The experimental outcome confirmed the validation and possibility of the proposed MPC-based energy management strategy [37].…”

Section: Microgrid Ems-mpcsupporting

confidence: 67%

Analysis of Model Predictive Control-Based Energy Management System Performance to Enhance Energy Transmission

Chowdhury,

Yusoff,

Gunawan

et al. 2024

Energies

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A supervisory control system using Model Predictive Control (MPC) has been designed to evaluate the efficiency of wind and solar power and is consistent with the cost function in the supervisory MPC optimization problem. A two-layer Economic Model Predictive Control (EMPC) framework has been developed and has improved results such as cost reductions compared to recent advanced methods. A speed Generalized Predictive Control (GPC) scheme intended for wind energy conversion systems was developed last year, with simulation results indicating superior performance over previous models. A Hierarchical Distributed Model Predictive Control (HDMPC) can work under different weather conditions with improved economic performance and keep a good balance between power delivery and load demand. An energy management system (EMS), built on the basis of MPC, can be quite lucrative for the sphere in the present climate scenario, with the selection and testing of suitable algorithms, controlled processes, cost functions, and a set of constraints as well as with proper optimizations carried out. Previous research indicates that an MPC-based EMS has the potential to be a good solution to manage energy well and also introduced it to the world experimentally. The key intention of this research study is to explore the existing advances that have been introduced and to analyze their performance in terms of cost function, different sets of constraints, variant conversion processes, and scalability to achieve more optimized operation of MPC-based EMS.

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Section: Microgrid Ems-mpcsupporting

confidence: 67%

Analysis of Model Predictive Control-Based Energy Management System Performance to Enhance Energy Transmission

Chowdhury,

Yusoff,

Gunawan

et al. 2024

Energies

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Optimal sizing of hybrid renewable energy systems for reliability enhancement and cost minimization using multiobjective technique in microgrids

Vaka

Kumari

2022

Energy Storage

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Microgrids can meet their electrical energy needs through the use of renewable energy systems and energy storage. Combining hybrid renewable energy system (HRES) with a battery energy storage system (BESS) is the best way to increase the systems reliability while still satisfying load demand. Suitable sizing of microgrid with optimal power allocations of HRES and BESS in terms of capacity and discharge leads to improved reliability. Cost and reliability are two important aspects of microgrid system functioning. While designing the system with HRES and BESS, there must be an appropriate balance between cost and reliability. This paper presents an algorithm for optimal design of HRES with BESS for optimizing levelized cost of electricity (LCOE) and power supply reliability factor (PSRF) Particle swarm optimization and epsilon constraint based multi‐objective PSO algorithms are used to solve the objectives considering 24 hours time horizon. A hybrid Wind‐PV system with Diesel Generator and BESS is considered for the study. In this work, 12 trails of simulation runs are made to obtain accurate values of average levelized cost of electricity and power supply reliability factor along with the optimal power allocations of DGs and BESS. According to the findings, sizing of HRES with BESS optimally lowers the LCOE by reducing the quantity of power drawn from the grid and improves PSRF. ε‐MPSO provides the optimal results in minimizing the LCOE by obtaining proper energy management between HRES and BESS with improved reliability.

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Model predictive control-based energy management strategy for grid-connected residential photovoltaic–wind–battery system

Azaroual¹,

Ouassaid²,

Maâroufi³

2021

Renewable Energy Systems

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Model Predictive Control Based Energy Management of a Household Microgrid

Cited by 6 publications

References 10 publications

Analysis of Model Predictive Control-Based Energy Management System Performance to Enhance Energy Transmission

Analysis of Model Predictive Control-Based Energy Management System Performance to Enhance Energy Transmission

Optimal sizing of hybrid renewable energy systems for reliability enhancement and cost minimization using multiobjective technique in microgrids

Model predictive control-based energy management strategy for grid-connected residential photovoltaic–wind–battery system

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