The energy problem is one of the most important and serious problems that humanity is faced with it and this is while the fossil fuels are running out, so finding new sources of energy is one of the challenges of modern man. Solar energy is an available, newable and almost eternal energy which can be converted directly to electrical energy by photovoltaic (PV) cells. Although the use of sunlight costs nothing but PV cells are relatively expensive so it's necessary to extract maximum power from these cells because of economic reasons. To achieve the maximum power point, there are many techniques and also many review papers but just few papers have compared these techniques from economical and technical point of view. This paper presents a review of MPPT techniques using of comprehensive and relatively new classification with emphasizing on comparison of methods.

Comparative and comprehensive review of maximum power point tracking methods for PV cells

Solar energy source can be utilized into electric energy using Photovoltaic (PV) panel. Maximum power in PV can be obtained in sunny weather conditions, optimum temperature, and unshaded surface. When PV is blocked by an object, the resulting power will decrease depending on the size of the barrier. Barriers of the sun intensity are shadows of trees, buildings, peoples, and others. These conditions cause PV can't absorb the maximum intensity of sunlight. Unfortunately, an obstructed PV surface condition may affect the resulting characteristic curves. These conditions can produce different characteristic curves. The difference is the position of the maximum power point that should be only one that is GMPP (Global Maximum Power Point) but this is divided into two there are GMPP and LMPP (Local Maximum Power Point). These conditions make a simple MPPT trapped in LMPP or an unreal maximum power point. To solve this problem, in this paper proposed MPPT Partial Shading using Modified Particle Swarm Optimization (MPSO) method. The MPSO method is chosen to solve partial shading conditions so the MPPT can reach GMPP without being trapped in LMPP. The MPSO method is applied to the Sepic converter to generate maximum power. According to simulation result, the MPSO method has a good accuracy greater than 95% and a fast time convergence is about 0.5 until 1 second to obtain a MPP depend on the shading pattern.

Modeling and simulation of MPPT sepie converter using modified PSO to overcome partial shading impact on DC microgrid system

Solar energy can be utilized through photovoltaic (PV) into electrical energy. The output power of PV can reach maximum point when the irradiation of the sun is exposed to the surface without any object being obstructed. Unfortunately, In the actual implementation of irradiation received by PV it is often blocked by a moving object or a shadow of a non-moving object. This problem resulted in the emergence of more than one maximum power point on the P-V characteristic curve. The condition can't be solved by using the usual MPPT Algorithm so that MPPT Partial shading algorithm is required. Partial shading algorithm has been developed from conventional methods to artificial intelligence methods. Hence, in this paper proposed comparison method of MPSO, FPA, and GWO in MPPT SEPIC converter under dynamic partial shading condition. The level of accuracy of all three methods is validated through simulation. The simulation results show that the three methods are able to overcome the problem of partial shading very well with a high level of accuracy. The simulation results also show that the FPA method has advantages compared to other proposed methods. The simulation results also show that the MPSO method has more advantages compared to other proposed methods in tracking accuracy and the FPA method is faster to reach convergence situation by other proposed method.

Comparison method of MPSO, FPA, and GWO algorithm in MPPT SEPIC converter under dynamic partial shading condition

Renewable energy becomes very important because energy requirement can't always depend on fossil energy. Renewable energy such as solar energy is a great natural energy that can be utilized in the morning until the afternoon. Unfortunately, The problem of the output power in solar energy such as Photovoltaic (PV) is influenced by irradiation and temperature that can change suddenly. The output power released by PV depends on the value of irradiation and the temperature forming P-V and I-V characteristic curves. The maximum power output on the PV characteristic curve can be achieved using the MPPT algorithm. MPPT algorithm widely developed from conventional Algorithm up to AI algorithm. Hence, in this paper discussed the comparison of FPA (Flower Pollination Algorithm), MPSO (Modified Particle Swarm Optimization), and P&O (Perturb and Observe) methods in MPPT coupled inductor SEPIC converter on DC Microgrid Isolated System. Sepic converter used to reduce ripple current in part of input. Furthermore, simulated performance experiments show that all three methods were able to find the maximum power point with an accuracy greater than 95%. The simulation results show that the FPA method is superior compared to the MPSO and P&O methods.

Comparison method of flower pollination algorithm, modified particle swarm optimization and perturb & observe in MPPT coupled inductor sepic converter on DC microgrid isolated system

Renewable energy source is a clean source of energy which will cause no environmental impacts. The major drawback of renewable energy resource is their intermittency, moreover in solar energy shading is also an issue. Electric Vehicles help in reducing emission as it is fed from solar grids. Presently, automotive manufacturers have solar roofed vehicles for charging the vehicle battery while it is running or parked outdoors. As the vehicles are moving there is a possibility of solar panels being under complete shading or partial shading. Thus PV modules are used along with a MPPT to get the maximum power from panels. Shading is one major issue that will lead to the formation of local peak and global peak in the I-V and P-V curve, finally delivering a reduced power output. It causes serious problem for the MPPT algorithm as it will not be able to find the maximum power point. This paper focuses on the effect of partial shading in solar roofed electric vehicle and the variation of output power with different patterns of shading. Four Trina Solar TSM 250PA05.08A solar panels were connected in series along with a boost converter to analyse the shading conditions. MATLAB simulation is presented which shows the output power variation and the formation of multiple peaks due to shading.

Effect of Partial Shading on Vehicle Integrated PV System

This paper presents an improved particle swarm optimization (PSO) based maximum power point tracking (MPPT) strategy. Modeling of the PV cell and effect of the partially shaded condition (PSC) on the P_V characteristics are investigated. Typical PSO algorithm is modified to provide a better convergence and faster performance. A novel strategy is also proposed for reinitialization to reduce tracking time and power fluctuations in case of cloudy sky. The performance of the proposed system under uniform insolation, PSC and rapid fluctuation of the insolation is evaluated by MATLAB 2010B.

An improved PSO based MPPT approach to cope with partially shaded condition

Drum boilers consume is one of the most important equipment of the thermal power plants in many countries and are widely used in industrial process applications. A boiler-turbine unit is a typical multivariable industrial control system in power plant. The boiler is so manufactured that the drum level must be in the specified range. Output constraints are an important challenge in boiler drum systems to have safety and efficient operation. In this paper, the problem of state space model predictive control for a constrained nonlinear boiler drum systems is investigated. Predictive control is a highly efficient and strong method since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. Simulation results demonstrate the satisfactory performance and effectiveness of this method and compatibility with practical implementation in boiler.

Mohsen Razzazan

Papers

An improved PSO based MPPT approach to cope with partially shaded condition

Drum Boiler Control with Output Constraints using Model Predictive Control Method