Abstract
Solar photovoltaic (PV) systems under partial shading conditions (PSCs) have a nonmonotonic P -V characteristic with multiple local maximum power points, which makes the existing maximum power point tracking (MPPT) algorithms unsatisfactory performance for global MPPT, if not invalid. This paper proposes a novel overall distribution (OD) MPPT algorithm to rapidly search the area near the global maximum power points, which is further integrated with the particle swarm optimization (PSO) MPPT algorithm to improve the accuracy of MPPT. Through simulations and experimentations, the higher effectiveness and accuracy of the proposed OD-PSO MPPT algorithm in solar PV systems is demonstrated in comparison to two existing artificial intelligence MPPT algorithms.
| Original language | English |
|---|---|
| Article number | 8345715 |
| Pages (from-to) | 265-275 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Industrial Electronics |
| Volume | 66 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Maximum power point tracking (MPPT)
- partial shading conditions (PSCs)
- particle swarm optimization (PSO)
- solar photovoltaic (PV) systems
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