Photovoltaic Electrical Power Generation System (PV-EPGS) is gaining more importance due to its benefits like no fuel cost, eco-friendliness and less maintenance. However, harnessing the maximum power from large PV-EPGS has become difficult due to the occurrence of a number of peaks in P-V characteristics under partial shaded conditions. This paper presents simulation study of MPPT under partially shaded conditions using the modified version of Particle Swarm Optimization method known as Enhanced Leader Particle Swarm Optimization (EL-PSO). Proposed ELPSO method has advantages over PSO like fast convergence, better dynamic performance, easy implementation and high efficiency. To evaluate the proposed method simulation result of PV panel, Siemens S75 is provided for three different shaded conditions. © 2017 The Authors. Published by Elsevier Ltd.

Rajasekar N

Department of Energy and Power Electronics

School of Electrical Engineering

Vellore Campus

Gavhane P.S

Krishnamurthy S

Dixit R

Ram J.P

Fulltext

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Energy Procedia

To maximize solar photovoltaic (PV) output under dynamic weather conditions, maximum power point tracking (MPPT) controllers are incorporated in solar PV systems. However, the occurrence of multiple peaks due to partial shading adds complexity to the tracking process. Even though conventional and soft computing techniques are widely used to solve MPPT problem, conventional methods exhibit limited performance due to fixed step size, whereas soft computing techniques are restricted by insufficient randomness after reaching the vicinity of maximum power. Hence, in this paper, a new flower pollination algorithm (FPA) with the ability to reach global peak is proposed. Optimization process in FPA method performs global and local search in single stage and it is a key tool for its success in MPPT application. The ruggedness of the algorithm is tested with zero, weak, and strong shade pattern. Further, comprehensive performance estimation via simulation and hardware are carried out for FPA method and are quantified with conventional perturb and observe and particle swarm optimization (PSO) methods. Results obtained with FPA method show superiority in energy saving and proved to be economical. © 1986-2012 IEEE.

IEEE Transactions on Power Electronics

A Novel Flower Pollination Based Global Maximum Power Point Method for Solar Maximum Power Point Tracking

Increased penetration of wind and solar PV system in Distributed Generation (DG) and isolated micro grid environment necessitates the use of maximum power point tracking method for wind and solar PV resources. Considering the change in environmental conditions and non-linearity, a variety of publications reporting various MPPT algorithms for solar and wind energy systems are put forward in recent times. But the review reports on common MPPT techniques used for solar and wind applications for hybrid power generation have not yet been reported. Hence, in this paper, conventional techniques and artificial intelligent techniques found extensively used in the power generation platform are peerly reviewed and compared. Historical MPPT methods like Perturb &amp; Observe (P&amp;O) / Hill Climbing, Incremental Conductance (INC), Fuzzy and Neural Network methods benchmarked in MPPT province are comprehensively compared in a common platform. In addition to the common existing techniques, recent swarm intelligence and bio-inspired techniques in solar PV and sensor less adaptive techniques in wind MPPT are also been reviewed provided for quality assessment. Finally an economic analysis is arrived for MPPT methods based on (i) Capacity utilization factor (ii) Cost (iii) Energy Savings (iv) payback period (v) Income generated and (vi) stability. © 2017 Elsevier Ltd

Renewable and Sustainable Energy Reviews

Design and overview of maximum power point tracking techniques in wind and solar photovoltaic systems: A review

The inaccurate I-V curve generation in solar PV modeling introduces less efficiency and on the other hand, accurate simulation of PV characteristics becomes a mandatory obligation before experimental validation. Although many optimization methods in literature have attempted to extract accurate PV parameters, all of these methods do not guarantee their convergence to the global optimum. Hence, the authors of this paper have proposed a new hybrid Bee pollinator Flower Pollination Algorithm (BPFPA) for the PV parameter extraction problem. The PV parameters for both single diode and double diode are extracted and tested under different environmental conditions. For brevity, the I01, I02, Ipvfor double diode and I0,Ipvfor single diode models are calculated analytically where the remaining parameters ‘Rs, Rp, a1, a2’ are optimized using BPFPA method. It is found that, the proposed Bee Pollinator method has all the scope to create exploration and exploitation in the control variable to yield a less RMSE value even under lower irradiated conditions. Further for performance validation, the parameters arrived via BPFPA method is compared with Genetic Algorithm (GA), Pattern Search (PS), Harmony Search (HS), Flower Pollination Algorithm (FPA) and Artificial Bee Swarm Optimization (ABSO). In addition, various outcomes of PV modeling and different parameters influencing the accurate PV modeling are critically analyzed. © 2016 Elsevier Ltd

Energy Conversion and Management

A new hybrid bee pollinator flower pollination algorithm for solar PV parameter estimation

In recent years solar energy has received worldwide attention in the field of renewable energy systems. Among the various research thrusts in solar PV, the most proverbial area is extracting maximum power from solar PV system. Application dof Maximum Power Point Tracking (MPPT) for extracting maximum power is very much appreciated and holds the key in developing efficient solar PV system. In this paper, a state of the art review on various maximum power point techniques for solar PV systems covering timeworn conventional methods and latest soft computing algorithms is presented. To date critical analysis on each of the method in terms of (1) tracking speed, (2) algorithm complexity, (3) Dynamic tracking under partial shading and (4) hardware implementation is not been carried out. In this regard the authors have attempted to compile a comprehensive review on various solar PV MPPT techniques based on the above criteria. Further, it is envisaged that the information presented in this review paper will be a valuable gathering of information for practicing engineers as well as for new researchers. © 2016 Elsevier Ltd

A comprehensive review on solar PV maximum power point tracking techniques

Over a period of years, Maximum Power Point Tracking has become a mandatory requirement for Solar Photo Voltaic (PV) systems. Being dependent to environmental changes, the PV power constantly fluctuates due to change in irradiation. Under such conditions, large PV array connected in interconnection will experience non-uniform irradiation thus results multiple peaks in P-V characteristics. Although many conventional and soft computing techniques have been proposed in literature, the ability to identify global peak under strong shading conditions is not guaranteed. Particularly, local peak in close agreement to global peak makes most of the algorithms to get trapped in local peaks. This condition often occurs due to insufficient randomness in algorithm hence, a new Flower Pollination Algorithm (FPA) is investigated in this research. Proposed method has dual mode search ability which creates required randomness in every iteration is the key reason to suit FPA for MPPT. Simulation and experimental results verified with different patterns portray FPA excellence under all irradiated conditions. Further performance of FPA is verified with Particle swarm Optimization method and conventional P&amp;O method. © 2016 Elsevier Ltd

Journal	Data powered by TypesetEnergy Procedia
Publisher	Data powered by TypesetElsevier BV
ISSN	1876-6102
Open Access	Yes