BRIEF REVIEW ON SOLAR PHOTOVOLTAIC PARAMETER ESTIMATION OF SINGLE AND DOUBLE DIODE MODEL USING EVOLUTIONARY ALGORITHMS S. Senthilkumar 1, V. Mohan 2, G. Krithiga 3 1 Assistant
Professor, Department of Electronics and Communication Engineering, E.G.S.
Pillay Engineering College, Nagapattinam, Tamilnadu, India 2 Professor,
Department of Electrical and Electronics Engineering, E.G.S. Pillay Engineering
College, Nagapattinam, Tamilnadu, India 3 Assistant
Professor, Department of Electrical and Electronics Engineering, E.G.S. Pillay
Engineering College, Nagapattinam, Tamilnadu, India
1. INTRODUCTION With rapid depletion of fossil fuels (petroleum products, natural gas etc.,) consecutively called as non-renewable sources of energy necessity for renewable sources for tapping energy without touching our atmosphere is in tall claim and has involved extensive research in the previous some eras. Well recognized renewable sources of energy contain wind, solar and tidal energies out of which solar is considerably favoured outstanding to its tall insolation levels and plenty in greatest share of the world power requirement. This is main reason and motivation for solar installations to be more dominant in the world. Among many renewable energy resources solar is an important energy source which directly received from sun for entire centuries. Solar energy is categorized into two type’s namely active and passive solar systems. In active systems consists of water heater and concentrated solar systems. Orientation of buildings towards sun, selection of materials and properties of light dispersion comes in passive systems De Groote & Verboven (2019). In recent years power requirement for practical devices starts to utilize solar energy Mohan & Senthilkumar (2022), Nathangashree et al. (2016), Suganya et al. (2014), Senthilkumar et al. (2022), Senthilkumar et al. (2022). Many countries provide subsidies to encourage the renewable energy usage along with different technologies, like solar and wind energy systems. Building construction cost is reduced by installation of solar systems on top of the buildings in order to remain inexpensive Araújo et al. (2019). Earth temperature is increasing day by day and there is a necessity for endorsements to reduce the CO2 productions with the help of renewable energy. A system with fixed sustainability for classification of parameters in the solar is evidently reviewed Choudhary & Srivastava (2019). Figure 1 shows simple block diagram of PV system. Solar PV cell modelling has grown over several decades, with the attention on an analytical approach based on simply accessible constructer data for the complex element. The substitute attitude of trusting on arena measurement to support the progress of a precise model for a collection of attention has been mainly uncharted. The outcomes of a better-quality yet simple model can accurately simulate and calculate the output power of an installed PV array system in a given area with different environment conditions López-Guede et al. (2013). Lots of research works available in the literature on multi-level inverters to reduce the harmonics during the dc to ac conversion G et al. (2023), Chitrakala et al. (2019), Krithiga & Mohan (2022), Chitrakala et al. (2018), Sivamani & Mohan (2022), Bharatiraja et al. (2016). Diverse tactics are hired for parameter approximations are Analytical techniques Ayodele et al. (2016), Numerical extraction Ibrahim & Anani (2017) and Evolutionary algorithm techniques Chen et al. (2019), Senthilkumar et al. (2022). Among different diode models SDM is the frequently used model for modelling solar cell modules and arrays in many cases. In SDM five parameters have to be extracted when modelling a system. Figure 1
The V-I characteristics of the equivalent circuit model of a single-cell is determined with the aid of its explicit non-linear inspirational equation, which is tough to clear the practice of analytical approaches. Due to this reason, in many situations, this method is not considered a correct one. This trouble brought about the enhancement of numerous algorithms for cracking this equation by numerical techniques. This is a prospective instrument for investigators and designers running exclusively in the area of PV assemblies to make conclusions related to determining on the satisfactory achievable set of rubrics for extracting the eye parameters of 5-parameter PV models with single diode Waly et al. (2019). But numerical techniques have some downsides involving of premature integration, low precision, and uncertainty. The claim of curving to the linear equation of a diode is unconditionally limited. However, the parameter extraction of SDM using 3-point method, the evolution algorithm routines most active the relaxation of the curve for outstanding alteration. As an end result, the complexity of the set of rules is substantially reduced and lots extra correct than other documented strategies Muangkote et al. (2019). The evolutionary algorithm techniques are superior for processing nonlinear equations. To estimate solar cell parameters different types of optimization techniques have been introduced. These study ambitions to decide the optimization of energy generation to raise the complete performance of the PV module Kabeel et al. (2019). A fast-converging modest Maximum Power Point Tracking (MPPT) technique with dissimilarities in radiation of solar and load resistance (RL) with cheap losses in generated strength of solar cell was proposed by Tey & Mekhilef (2014). The algorithm proposed is four times faster while in comparison with traditional (incremental conductance) algorithms with appreciate to dissimilarities in solar irradiation and load. Sahu & Nayak (2017) counselled an estimation technique for MPPT the use of Levenberg-Marquardt scheme below specific situations on atmosphere for a DDM of a machine and compare the obtained end result with experimental facts obtain from MATLAB simulation and found a higher overall show from the projected method. Jadli et al. (2018) have modelled solar cell parameters to analyze the feature performance at specific environmental conditions and found that the traits of proposed model are very correct when comparing with present one. 2. MODELING OF SOLAR SYSTEMS Solar energy plays a significant character in total energy creation within the global and swiftly increasing every day. On the alternative side, cost of solar panels, batteries and inverters are lowering appreciably. Due to those motives, many countries in the global are changing their strength rules toward solar energy. In recent years modelling of solar cells attracts many researchers. In solar cell modelling, different types of equivalent circuits are used based number diodes present in that particular circuit. Some models of solar cell are Senthilkumar et al. (2020), 1) Single-Diode Model (SDM) 2) Double-Diode Model (DDM) 2.1. SINGLE-DIODE MODEL Design and implementation of SDM is very simple. The equivalent circuit of SDM is depicted in Figure 2. In the shown SDM model, five unknown parameters need to be estimated namely light induced current (Iph), diode dark saturation current (Id1), series resistance (Rs), shunt resistance (Rsh) and diode ideality factor (n). Figure 2
In many situations, SDM is used to extract I-V curve of a solar cell. Output current from SDM is written as (1)
Equation for diode current of SDM is written as follows (2) The value of ideality
factor ‘n’ is assumed as a constant in the case of SDM. In reality the surfaces and the bulk regions dominates the ideality factor and its value is closer to one. 2.2. DOUBLE-DIODE MODEL The equivalent circuit of DDM is depicted in Figure 3. Output current from DDM is written as follows (3) Figure 3
Current through diodes in DDM is written as follows (4) (5) Shunt resistance in DDM is calculated by the following equation (6) Losses due to recombination current inside the depletion region are considered in DDM which leads to improvement in accuracy which is not considered in SDM. In DDM seven unknown parameters need to be estimated namely Light induced current (Iph), Diode dark saturation current (I01), Diode dark saturation current (I02), Diode quality factor (a1), Diode quality factor (a2), Series resistance (Rs) and Shunt resistance (Rsh). Table 1 shows the comparison between SDM and DDM. Table 1
This study estimates the
contrast among SDM and DDM to enhance the efficiency of solar PV systems. Among
SDM and DDM, design and implementation of SDM is easy with lower accuracy, but
the DDM has extra accurate, which will improve the overall performance of PV
systems. Different algorithms are available to find the parameters of different
solar PV models such as SDM, DDM and TDM. Such algorithms are clearly
summarized in the following section. 3. EVOLUTIONARY ALGORITHM Figure 4 shows different methods available for parameter estimation of various solar PV models. This section describes detailed literatures in parameter estimations using different evolutionary algorithms. Figure 4
3.1. PARTICLE SWARM OPTIMIZATION Meiying et al. (2009), carried out PSO algorithm for estimation of solar PV cell parameters and compare the obtained results some other algorithms like GA for SDM and DDM and decided that that the PSO algorithm provides good accuracy in the estimated parameters with excellent performance in computational time. Hamid et al. (2013) presented a PSO algorithm to estimates the parameters from SDM with 5 unknown values for a silicon solar cell 57 mm diameter and recognized the reliability of predicted parameters accuracy with other strategies. Khanna et al. (2014) developed PSO algorithm to extract the solar PV parameters from DDM and find the V-I characteristics of solar PV cell. Flow chart for PSO algorithm is depicted in Figure 5. Figure 5
3.2. GENETIC
ALGORITHM Bastidas-Rodriguez et al. (2017) have recognized a SDM with five working factors of creators jogging external situations the practice of GA for distinct eco-friendly situations like solar irradiances and hotness; observed that estimated parameters are very accurate whilst in comparison with other available estimating strategies. Jervase et al. (2001) have proposed GA to enhance the already to be had solar cell parameter abstraction techniques and gain a result with errors at the parameters extracted became ± five% at the module standards. Harrag & Messalti (2015) have cautioned a GA mainly based solar parameter extraction approach for five and seven parameter version to improve the possibility of locating global minimal with super accuracy in brief time. Here there's no limit in solution area all through the procedure Warkad & Asole (2019). 3.3. ARTIFICIAL BEE COLONY ALGORITHM ABC algorithm developed to extract the parameters of solar PV cell by Chen et al. (2018), provides a parameters value with more accuracy; it become discovered that ABC affords well seek potential for multi model objective features and reveals top overall performance on parameter extraction while as compared with other optimization algorithms like BFA, PSO, GA and HS. An effective ABC algorithm to find solar PV cell parameters for SDM and DDM models was proposed by Mohammad Jamadi et al. (2015), discovered a fast and accuracy on parameters estimations in comparison with PS, ABSO, GA and PS algorithms. Chen et al. (2018) developed Hybrid Teaching Learning based totally Artificial Bee Colony (TLABC) to estimate the solar cell PV parameters SDM, DDM and TDM; Obtained outcomes whilst compared with different optimization techniques and located the proposed set of rules provides true accuracy and performance for estimation of various cell parameters. More works in this algorithm available in literatures Salmi et al. (2016), Pilakkat & Kanthalakshmi (2019), Hassan et al. (2017), Oliva et al. (2014). 3.4. SIMULATED
ANNEALING SA algorithm for battery model parameterization proposed by Ben (2020), have a long battery life time and very good efficiency when compared with some other optimization algorithms. The same algorithm with three steps for SDM parameter extraction of SDM suggested by Ramzi Ben Messaoud AlRashidi et al. (2013), in first step parameters are extracted using conventional method, in second step parameters are extracted using uncertainty determination and in final step is instantaneous values of parameters determination, the projected algorithm delivers active performance of the solar panel when compared with already existing algorithms. M.R. AlRashidi et al. (2013), Brondani et al. (2017), suggested SA algorithm for solar parameter estimation and found that the suggested algorithm delivers accurate parameter assessments. 3.5. DIFFERENTIAL EVALUATION Abido & Khalid (2018) estimated seven parameters of DDM six solar panels constructed from mono crystalline silicon, poly crystalline silicon and thin film technologies using DE algorithm. The values of seven parameters extracted from DE algorithm were compared with I-V curves of experimental data and found that projected algorithm offers more accuracy on estimated parameters of panels. 3.6. HARMONY SEARCH BASED ALGORITHM Askarzadeh & Rezazadeh (2012) considered solar cells with 57 mm diameter made up of silicon for parameter estimations of both SDM and DDM and proposed HS algorithm with easy and better performance, simulation was done in MATLAB Simulink, detected a reduced RMSE value when compared with other algorithms like PS and SA and also observed a very narrow difference between simulated values and values extracted experimentally from I-V curves. Satapathy et al. (2017), discussed about HS based hybrid firefly algorithm for micro grid applications with rapid convergence time and compact randomization when compared with FA and observed that stability is considerably improved. 3.7. PATTERN SEARCH OPTIMIZATION PS algorithm is proposed by Derick et al. (2016), to invention solar cell parameter of SDM by simulation as well as experimental method and examine the helpfulness of PS algorithm for parameter approximation in MATLAB / Simulink software with respect to different ecological conditions like different solar irradiance and temperature; results of PS algorithm display a better accuracy with short convergence time. PS algorithm for SDM and DDM presented by AlHajri et al. (2012) precisely abstract the parameter standards of stated models. The parameters of SDM and DDM was estimated by Beigi & Maroosi (2018) using PS algorithm, the estimated values are compared with other optimization algorithms available and concluded that the results obtained from PS algorithm is better one for solar cell modeling. 3.8. ARTIFICIAL
IMMUNE SYSTEM AIS algorithm proposed by Jacob et al. (2015) evaluation of the parameters of solar cell for DDM, compare the performance of AIS algorithm with other algorithms like GA and PSO for different types of two modules and find that performance of AIS especially convergence speed is better than GA and PSO algorithms. 3.9. FIREWORKS
ALGORITHM To estimate the parameters sol solar PV systems, FA faced algorithm developed by Sudhakar Babu et al. (2016), the developed algorithm decreases premature in meeting probability and computational difficulty and obtained from parameters value from developed algorithm are very accurate closer to the data sheet values of the given solar panel. 3.10. BACTERIAL
FORAGING ALGORITHM BFA algorithm proposed by Rajasekar et al. (2013) for three different type’s solar cell models observed better results like good accuracy, high precision, low merging time, good consistency and lower error values when matched with additional optimization algorithm like GA and AIS. 3.11. FLOWER
POLLINATION ALGORITHM Alam et al. (2015), suggested FPA for solar PV parameter estimations in order to attain lesser values on RMSE, fast outcome of optimal solution and reduced convergence time under extensive array of temperature and solar irradiations. Only few control parameters needed in the suggested algorithm. 3.12. HYBRID FLOWER POLLINATION ALGORITHM Ram
et al. (2017) offered HFPA for
extractions of solar parameter for both SDM and DDM under different solar
irradiance and temperature; offered algorithm deliver a good parameter
estimations with low Least Mean Square Error (RMSE) value under very lower
values of solar irradiation. A simple HFPA is built by Xu
& Wang (2017) in order to finding
the solar parameters efficiently and precisely for SDM and DDM and stated that
the suggested algorithm offers superior good results like accuracy, convergence
speed and stability of the model under different temperature and solar
irradiations. Table 2 summarizes different evolutionary algorithms
with respect to merits, demerits, and applications. Table 2
4. OPPORTUNITY FOR RESEARCH IN SOLAR PARAMETER ESTIMATION AND MPPT Conventional electric power systems create huge amount of carbon di oxide, which will increase the earth temperature day by day measured the capacity of the device to offer a giant percentage of a utility, creation of a huge hours of the system associates the amount of electricity to be determined and this is the reserving Indeed, penetration stages and further electricity systems inside the production of the current laws and guidelines of movement. Low precision, excessive RMSE value and lower computation time is vital outcomes of this assessment. On comparing the efficiency of different types of meta-heuristics at the problem of extracting solar PV parameters accuracy, convergence rate and steadiness and decisive the maximum suitable meta-heuristics to remedy this hassle, could be a thrilling and useful studies network inside the destiny. Apart from the problems debated overhead, some of troubles statements that could be derived from examine of literature are summarized under. · Researcher can give additional focus maximum energy production from the available solar irradiations by proper mechanism and try to fully utilize the generated power by proper trapping generated energy. · May develop effective algorithms to estimates the parameters of solar PV cells quick computational time with good accuracy. · An appropriate optimization model has to be evolved with admiration to distinct overall performance parameters on the way to enhance the performance of the model. · A powerful MPPT approach must be developed to track maximum strength beneath distinct situations like versions in temperature and irradiations. 5. CONCLUSION Solar PV cell parameter estimation is the principal problem of nowadays researchers in environment friendly renewable energy. In this review, different evaluation algorithms for solar PV cell parameter estimation for both SDM and DDM performed studied by means of thinking about twelve varieties of algorithms. Also, the overall performance and limitations of a few existing methods are analysed. This review article will honestly be very supportive for new researchers and for the researchers already running in this vicinity to be able to replace their information. As in keeping with our preceding discussion, subsequently we can introduce a singular method to triumph over the previous limitations and develop a more suitable applicable technique.
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