Maximum Power Point Tracking Techniques in Photovoltaic Systems
Summary
Maximum Power Point Tracking (MPPT) techniques are essential for maximising the electrical output of photovoltaic (PV) arrays under variable environmental and loading conditions. PV modules exhibit a non-linear power–voltage characteristic that shifts with irradiance, temperature and partial shading. Classical hill-climbing methods such as Perturb and Observe and Incremental Conductance offer simplicity and low cost, but can suffer from steady-state oscillations and local-peak locking under complex conditions. To address these limitations, intelligent and optimisation-based strategies incorporating fuzzy logic, neural networks, particle swarm optimisation or gravitational search have been developed to improve convergence speed and tracking accuracy. Robust control schemes, including Model Reference Adaptive Controllers and Lyapunov-based designs, further enhance resilience to rapid perturbations and minimise ripple. The integration of advanced algorithms with DC–DC conversion topologies, power-electronics interfaces and microcontroller or DSP implementations has enabled widespread adoption in grid-connected, off-grid and hybrid renewable systems. Such developments balance algorithmic complexity with practical considerations of cost, computational load and reliability, thereby supporting the global transition to cleaner, more efficient solar energy generation.
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Maximum Power Point Tracking Techniques in Photovoltaic Systems publication trend
The graph below shows the total number of articles in maximum power point tracking techniques in photovoltaic systems across all publications each year (not limited to Nature Index journals).
Technical terms
Maximum Power Point Tracking (MPPT): Control strategy to ensure PV arrays operate at the voltage/current combination delivering maximum power.
Global Maximum Power Point Tracking (GMPPT): Advanced MPPT technique addressing multiple local peaks under partial shading to locate the true global peak.
Perturb and Observe (P&O) algorithm: Iterative hill-climbing method that perturbs operating voltage and observes power change to converge on MPP.
Incremental Conductance (INC) algorithm: MPPT method comparing incremental change in current to that in voltage for more precise convergence to MPP.
Model Reference Adaptive Controller (MRAC): Control scheme adjusting system parameters in real time to follow a reference model, ensuring robust MPPT performance.
Fuzzy Logic Control: Rule-based approach allowing uncertain or imprecise input data to guide the adaptation of MPPT algorithms.
References
- Hybrid gravitational search particle swarm optimization algorithm for GMPPT under partial shading conditions. Green Technologies and Sustainability (2023).
- Novel Lyapunov-based rapid and ripple-free MPPT using a robust model reference adaptive controller for solar PV system. Protection and Control of Modern Power Systems (2023).
- An Efficient Fuzzy-Logic Based Variable-Step Incremental Conductance MPPT Method for Grid-Connected PV Systems. IEEE Access (2021).
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