A stochastic MPC-based energy management system for integrating solar PV, battery storage, and EV charging in residential complexes

This paper presents a Stochastic Model Predictive Control (SMPC)-based energy management system (EMS) for residential complexes with integrated solar photovoltaics (PV), battery energy storage systems (BESS), and electric vehicle (EV) charging infrastructure. The EMS coordinates BESS operations, integrating solar generation, residential load demand, and EV charging. It optimizes BESS charging/discharging based on solar power, load demands, electricity pricing, and feed-in tariffs over a finite horizon, while considering uncertainties through multiple scenarios of load and EV charging demand, as well as solar generation. By accounting for battery degradation, cost savings, and revenue from energy transactions, the proposed EMS enhances BESS longevity and profitability. The EMS also manages reactive power provision from the BESS inverter, ensuring voltage stability in the presence of uncertainties. Extensive case studies on Matlab Simscape Electrical and real-time validation on the OPAL-RT simulator demonstrate the effectiveness of the proposed SMPC-based EMS in optimizing energy use, operational efficiency, and economic returns, contributing significantly to the sustainable energy management of the residential complex.

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Publication Details

Journal
Energy and Buildings
Published
2024-11-13
DOI
https://doi.org/10.1016/j.enbuild.2024.114993
Citations
18
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
3.66
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article

A stochastic MPC-based energy management system for integrating solar PV, battery storage, and EV charging in residential complexes

Umer Izhar, M.I. Saleem, Li-Minn Ang, Sajeeb Saha
18 citations
Energy and Buildings
Advanced Battery Technologies Research
3.66
article

A stochastic MPC-based energy management system for integrating solar PV, battery storage, and EV charging in residential complexes

Umer Izhar, M.I. Saleem, Li-Minn Ang, Sajeeb Saha
article en
18 citations

Abstract

This paper presents a Stochastic Model Predictive Control (SMPC)-based energy management system (EMS) for residential complexes with integrated solar photovoltaics (PV), battery energy storage systems (BESS), and electric vehicle (EV) charging infrastructure. The EMS coordinates BESS operations, integrating solar generation, residential load demand, and EV charging. It optimizes BESS charging/discharging based on solar power, load demands, electricity pricing, and feed-in tariffs over a finite horizon, while considering uncertainties through multiple scenarios of load and EV charging demand, as well as solar generation. By accounting for battery degradation, cost savings, and revenue from energy transactions, the proposed EMS enhances BESS longevity and profitability. The EMS also manages reactive power provision from the BESS inverter, ensuring voltage stability in the presence of uncertainties. Extensive case studies on Matlab Simscape Electrical and real-time validation on the OPAL-RT simulator demonstrate the effectiveness of the proposed SMPC-based EMS in optimizing energy use, operational efficiency, and economic returns, contributing significantly to the sustainable energy management of the residential complex.

Energy and BuildingsVol. 325
University of the Sunshine Coast (AU)
Affordable and clean energy
Openalex Percentile: Top 6%
Advanced Battery Technologies Research
3.66
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