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A model predictive control strategy of PV-Battery microgrid under variable power generations and load conditions

Renewable energy sources have been increasingly deployed as distributed generators in remote areas. Meanwhile, fluctuating power generation from renewable energy sources, together with variable power demand, poses challenges in stable and reliable power supply. In this paper, a microgrid with solar photovoltaic (PV) and battery energy storage (BES) is studied. A state of charge (SOC)-oriented charging scheme is developed to control the BES to smooth the PV output. Most importantly, a sophisticated control algorithm, consisting of a model predictive voltage control (MPVC) and a model predictive power control (MPPC), is proposed for the interlinking converter. It enables stable voltage in islanded mode. Also, in grid-connected mode, flexible reactive power can be injected into the main grid for grid support according to the voltage variation level. Finally, by considering the intermittent nature of the PV and the load profile, an energy management system (EMS) is designed to ensure power balance within the system. Case studies are provided to demonstrate the effectiveness of the proposed control strategy.
- Aalborg University Library (AUB) Denmark
- Aalborg University Library (AUB) Aalborg Universitet Research Portal Denmark
- Tsinghua–Berkeley Shenzhen Institute China (People's Republic of)
- Aalborg University Denmark
- Aalborg University Denmark
Energy storage, Power converters, Model predictive control (MPC), Microgrids, Renewable energy sources
Energy storage, Power converters, Model predictive control (MPC), Microgrids, Renewable energy sources
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).132 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
