The perturb and observe (P&O) maximum power point tracking (MPPT) algorithm is a simple and efficient tracking technique. However, the P&O tracking method suffers from drift in case of an increase in insolation $(G) $ , and this drift effect is severe in case of a rapid increase in insolation. Drift occurs due to the incorrect decision taken by the conventional P&O algorithm at the first step change in duty cycle during increase in insolation. A modified P&O technique is proposed to avoid the drift problem by incorporating the information of change in current $(\Delta I) $ in the decision process in addition to change in power $(\Delta P)$ and change in voltage $(\Delta V) $ . The drift phenomena and its effects are clearly demonstrated in this paper for conventional P&O algorithm with both fixed and adaptive step size technique. A single-ended primary inductance converter is considered to validate the proposed drift-free P&O MPPT using direct duty ratio control technique. MATLAB/Simulink is used for simulation studies, and for experimental validation, a microcontroller is used as a digital platform to implement the proposed algorithm. The simulation and experimental results showed that the proposed algorithm accurately tracks the maximum power and avoids the drift in fast changing weather conditions.

Modified Perturb and Observe MPPT Algorithm for Drift Avoidance in Photovoltaic Systems

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.

An Overall Distribution Particle Swarm Optimization MPPT Algorithm for Photovoltaic System Under Partial Shading

This paper proposes a method to reduce the steady-state oscillation and to mitigate the probability of losing the tracking direction of the perturb and observed (P&O)-based maximum power point tracking (MPPT) for PV system. The modified scheme retains the conventional P&O structure, but with a unique technique to dynamically alter the perturbation size. At the same time, a dynamic boundary condition is introduced to ensure that the algorithm will not diverge from its tracking locus. The modified P&O is simulated in MATLAB Simulink and its performance is benchmarked using the standard MPPT efficiency ${{\boldsymbol{\eta }}_{MPPT}}$ calculation. Furthermore, the proposed concept is validated experimentally using a buck-boost converter, fed by a solar PV array simulator (PVAS). Based on the EN 50530 dynamic irradiance tests, the proposed method achieved an average ${{\boldsymbol{\eta }}_{MPPT}}$ almost 1.1% higher than the conventional P&O when irradiance changes slowly and about 12% higher under fast change of irradiance.

A Modified P&O Maximum Power Point Tracking Method With Reduced Steady-State Oscillation and Improved Tracking Efficiency

This paper proposes an enhanced adaptive perturb and observe (EA-PO second, modified incremental conduction; third, cuckoo search; and fourth, the hybrid ant colony optimization-P&O. The results show that the proposed method tracks the global peak successfully under distinctive patterns of partial shading, when other algorithms fail occasionally. On top of that, it improves the tracking speed by two to three times, while efficiency is maintained over 99%.

An Enhanced Adaptive P&O MPPT for Fast and Efficient Tracking Under Varying Environmental Conditions

This paper describes a new maximum-power-point-tracking method for a photovoltaic system based on the Lagrange Interpolation Formula and proposes the particle swarm optimization method. The proposed control scheme eliminates the problems of conventional methods by using only a simple numerical calculation to initialize the particles around the global maximum power point. Hence, the suggested control scheme will utilize less iterations to reach the maximum power point. Simulation study is carried out using MATLAB/SIMULINK and compared with the Perturb and Observe method, the Incremental Conductance method, and the conventional Particle Swarm Optimization algorithm. The proposed algorithm is verified with the OPAL-RT real-time simulator. The simulation results confirm that the proposed algorithm can effectively enhance the stability and the fast tracking capability under abnormal insolation conditions.

/pdf/a-novel-mppt-algorithm-based-on-particle-swarm-optimization-148e09ucc3.pdf

A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems

Photovoltaic (PV) systems are one of the main actors in distributed power generation. In particular, in urban contexts, the PV generators can be subjected to mismatching phenomena due to the different orientation of the modules with respect to the sun rays or due to shadowing. In these cases, the maximum power point tracking (MPPT) function must be designed carefully. In this paper, architecture, including one dc/dc converter for each PV generator, is considered. The converters' output terminals are series connected to a high-voltage dc bus, where also a bidirectional dc/dc converter managing the power from/to a storage device is plugged. The functional constraints deriving from the dc/dc converters' connection, the mismatching phenomena, the MPPT capabilities of the inverter, connected with its input terminals at the dc bus, are taken into account in order to determine the best operating point of the system as a whole. The real-time constrained optimization problem is solved by using the particle swarm optimization method, which needs the knowledge of the actual current versus voltage curve of each PV generator. The practical impact of this need is also discussed in the paper. The feasibility and the performances of the proposed approach are experimentally validated by using a laboratory prototype.

A PSO-Based Global MPPT Technique for Distributed PV Power Generation

The purpose of this paper is to use a new rational approach for the design of some magnetic couplings. Our method is based on the association of analytical models and an exact global optimization algorithm named IBBA and developed by the third author. The analytical model presented in this paper is more sophisticated than those previously dealt using IBBA. Therefore, some under and over estimating functions have been constructed for those particular problems of design in order to improve the convergence of IBBA. Some optimal results highlight the efficiency of this approach.

/pdf/some-co-axial-magnetic-couplings-designed-using-an-3ynz7ln8gn.pdf

Some Co-Axial Magnetic Couplings Designed Using an Analytical Model and an Exact Global Optimization Code

This paper presents a new methodology of design of electrical rotating machines. The methodology is an extension of previous works of the second author. Indeed, associating combinatorial analytical models with exact global optimization algorithms leads to rational solutions of predesign. These solutions need to be validated by a numerical tool (using a finite-element method) before the expansive phase of hand-making a prototype. Such an automatic numerical tool for computing some characteristic values, such as the torque, was previously developed. The idea of this paper is to extend the exact global optimization algorithm by inserting the direct use of this automatic numerical tool. This new methodology makes it possible to solve design problems more rationally. Some numerical examples validate the usefulness of this new approach.

/pdf/design-of-electrical-rotating-machines-by-associating-zrai0lm3qf.pdf

Design of Electrical Rotating Machines by Associating Deterministic Global Optimization Algorithm With Combinatorial Analytical and Numerical Models

Designing a claw-pole synchronous machine implies solving many 3D nonlinear magnetostatic problems which makes the computation (CPU) time very long. In our model, the mesh is refined to reach the desired level of precision on global quantities such as torque. Since the airgap is very thin (around 0.3 mm for a 100 mm diameter) and a Newton Raphson algorithm requires several iterations to converge, CPU time may be too high. Nowadays, many researches are ongoing to reduce the CPU time, while preserving an acceptable accuracy. One of the most efficient methods is permeance networks but this method is not suitable for complex geometries. Our main contribution is to use a permeance network in the areas where flux lines are easy to guess and to solve a 3D FEM problem in complex geometry areas of the magnetic device: the claw poles and the air gap for example. Moreover, current sources belong to the permeance network model, so that there are no current sources in the 3D FEM problem. Then, a 3D scalar magnetic potential formulation can be used easily. The two classical magnetostatic formulations (magnetic scalar potential formulation (Um – hs) and vector potential formulation (a – j)) are presented in this paper. Then, the hybridization of 3D FEM formulation and the permeance network, is presented. Numerical results are compared with experimental measurements and a good agreement is obtained while reducing the CPU time. Index Terms—Claw-pole synchronous machine, 3D FEM, permeance networks, hybrid models.

/pdf/hybrid-model-permeance-network-and-3-d-finite-element-for-41mp9o7mnz.pdf

Hybrid Model: Permeance Network and 3-D Finite Element for Modeling Claw-Pole Synchronous Machines

This paper proposes to determine the radial forces in bearingless permanent magnet motor topology. We consider normal and tangential components of the magnetic field in the air gap. Their harmonic components and their evolution versus current and rotor position are considered. This allows establishing the semianalytical expressions of the radial forces considering different field sources. Their precision has been verified using a full finite element model and statistic analysis. The advantage of this semianalytical model lies in the swiftness of the different force components evaluation and consequently the reduction of CPU time.

Julien Fontchastagner

Papers

A PSO-Based Global MPPT Technique for Distributed PV Power Generation

Some Co-Axial Magnetic Couplings Designed Using an Analytical Model and an Exact Global Optimization Code

Design of Electrical Rotating Machines by Associating Deterministic Global Optimization Algorithm With Combinatorial Analytical and Numerical Models

Hybrid Model: Permeance Network and 3-D Finite Element for Modeling Claw-Pole Synchronous Machines

New Model of Radial Force Determination in Bearingless Motor