Elsevier

Energy

Volume 144, 1 February 2018, Pages 765-775
Energy

Evaluation of cumulative impact of partial shading and aerosols on different PV array topologies through combined Shannon's entropy and DEA

https://doi.org/10.1016/j.energy.2017.12.040Get rights and content

Highlights

  • Experimental study on relative performance of 4 conventional and 3 novel PV arrays.

  • Analysis of cumulative impact of environmental factors-partial shading & aerosols.

  • Evaluation of impact of deposition of aerosols from different geographical locations.

  • Analysis of data using Shannon's entropy and Data Envelopment Analysis.

  • Methodology proposed for increasing performance ratio of PV projects.

Abstract

This paper investigates performance of seven photovoltaic (PV) array topologies experimentally under cumulative impact of partial shading and deposition of aerosols at different irradiance levels and aerosol types at their different concentration levels. Different array topologies respond differently with regard to their mismatch power loss and fill factor under partial shaded condition. However, a comprehensive analysis of their behavior under the influence of other environmental phenomena is neglected so far by the researchers. The topologies studied in the present work, include four conventional topologies viz. series-parallel (SP), honey comb (HC), bridge link (BL) and total cross-tied (TCT) along with three novel hybrid topologies proposed in this paper (CT-SP, CT-BL and CT-HC). The complex and large amount of data generated from the experimental study have been analyzed using combined Shannon's entropy and data envelopment analysis to quantify the relative performances of different PV array topologies under different environmental conditions. The proposed methodology of comprehensive analysis will help the policy makers and researchers to enhance the performance ratio of PV projects by leveraging on the environmental factors and thereby increase techno-commercial viability of the PV projects.

Introduction

Researchers and policy makers around the world today, have embraced renewable energy technologies (RET) to meet the policy objectives of the countries to secure sustainable and affordable energy, safeguard against energy price volatility, ensure accessibility to electricity by larger society and kindle social and economic prosperity of respective nations. The world has witnessed an unprecedented growth in generation capacity addition of 138.5 GW in 2016 (8% higher than previous year) from RETs, amongst which 75 GW was from solar energy technologies alone [1]. Solar energy is the most abundantly available RET on earth, with about 885 million TWh of energy reaching the earth surface every year, which is 6200 times the commercial primary energy, the whole world required in 2008, and 3500 times the energy that the global population would require by 2050 [2]. Presently, rapid deployment of solar energy technologies, especially photovoltaics (PV), is increasing the scale and competitiveness of the markets for renewable technologies. More PV capacity has been added globally since 2010, than in the previous four decades and new PV systems are being installed at an astounding rate of over 100 MW per day since 2013 [2]. Various PV technologies developed so far and their best efficiencies recorded at laboratory scale have been presented in Table 1.

The peak efficiencies of most of the PV technologies listed in Table 1 look quite attractive, however, the efficiency of crystalline silicon technology (inclusive of both single crystalline (s-Si) and multi-crystalline (m-Si)), which dominates the PV market with 90% market share (refer Fig. 1), ranges merely between 15 and 20% [6] at commercial scale. Though thin film technology was believed to have enormous possibilities as a future decentralized PV technology, the market share of thin film has declined from 16% in 2009 to about 10% presently, while others represent only below 1%, in commercial scale [2]. Hence, it is need of the hour to improve the efficiency of crystalline silicon technology and performance ratio of PV projects thereof, to bring immediate change in the lives of world community, with regard to energy accessibility, sustainability and security.

Literature shows that performance ratio of the PV projects can be significantly improved by leveraging on or adapting the PV system design to environmental factors such as dust settlement and partial shading. Partial shading is caused by surrounding buildings, trees, clouds and due to self-shading of PV structures, and this phenomenon reduces the power output of the PV array significantly [6]. The PV cells are interconnected in series and parallel combinations to produce desired voltage and current. All the cells connected in series must carry equal current, even if all of those do not produce photon current same as others in series do, under partially shaded condition. In that case, the shaded cell gets reversed biased and acts like a load, consuming power from the fully illuminated cells. A diode is connected in anti-parallel with the PV cells to avoid irreversible damage due to creation of hot spot in the shaded cell. However, the PV cells are extremely non-linear device and the bypass diode creates multi-peak in the PV characteristics and this makes the maximum power tracking complicated [[7], [8], [9], [10]]. This phenomenon causes mismatch power loss in the PV systems.

One of the solutions to the above problem lies in choice of optimal configuration of PV modules. Innovations with PV array topologies are drawing interest of the researchers around the world as it has potential solution to a real-life problem with the PV projects, i.e. mismatch power loss. Some of the existing array topologies are series parallel (SP), total cross tied (TCT), bridge link (BL) and honey comb (HC) [[11], [12], [13], [14], [15], [16], [17], [18]]. Some new hybrid topologies have been also proposed by Yadav et al. [19] recently, which are SP-TCT, BL-TCT and non-symmetrical puzzle pattern based configurations such as NS-1 (non-symmetrical-1) and NS-2 (non-symmetrical-2). Simulation and experimental results of characteristics of various array topologies mentioned above under partial shaded condition have been reported by number of researchers. In the present work, the conventional topologies, i.e. SP, BL, HC, TCT and three novel hybrid topologies proposed in the present work, which are CT-SP, CT-BL and CT-HC have been studied experimentally for their relative performance under cumulative impact of partial shading and different types of aerosols at different concentration and irradiance levels. The array topologies considered in the present work have been briefly discussed in the following section.

Deposition of aerosols aggravates the modest efficiency figures and performance ratio of PV projects more severely than partial shading does. Mekhilef et al. [20] studied performance of PV panels in Saudi Arabia and reported 32% reduction in efficiency due to settlement of aerosols over a period of 8 months. Adinoyi et al. [21] also carried out similar type of study in eastern province of Saudi Arabia, where as high as 20% reduction in power output after a single dust storm and 50% reduction over six months have been reported. Chill et al. [22] reported 20% reduction in efficiency of PV panels over a period of 8 months in a study carried out at Gran Canary Island in the Atlantic Ocean.

Various studies have been carried out on the effect of different type of aerosols as well on PV performances as the magnitude of impact of aerosols depends highly on their physical properties viz. color, diameter and composition etc. Kaldelliset al. [23] studied red soil, limestone and carbonaceous fly-ash particles under same environmental conditions for their effect on PV performance and it was reported that red soil aggravated the PV performance the most, followed by limestone and carbonaceous ash, in order. Kazem et al. [24] also experimentally studied the effects of red soil, sand and ash for their impact on PV performance and they concluded that the ash impacted the performance most, relative to the other pollutants studied. Ghosh et al. [25] studied PV performance under aerosol from different geographical regions of India at their different concentration levels and different irradiance levels. The authors of [25] used combined data envelopment analysis (DEA) and Shannon's entropy for comprehensive analysis of experimental data and finding out the relative impact of the aerosols on the PV performance considering all the inputs and output variables collectively.

DEA is a non-parametric technique used for evaluation of relative performance of a set of comparable entities, commonly referred as decision making units (DMU). It has numerous advantages over other techniques for relative performance evaluation, e.g. flexibility of generation of weights of input and output parameters, and the functional relation between the input and outputs of the DMUs is not required to be known. Due to the unique advantages of DEA, it has presently evolved as an indispensable tool for benchmarking studies in wide and diverse field of research viz. operational, managerial, economic problems both in private and public domain and energy sector as well [[25], [26], [27], [28]]. However, classical DEA models lack power of discrimination and several DMUs are identified as frontier or relatively efficient ones [29]. To overcome the above shortfall of classical DEA, several theoretical extensions of DEA have been introduced by the researchers for complete ranking of DMUs viz. cross efficiency, super efficiency [31], benchmarking [32], multivariate statistical techniques; such as canonical correlation analysis, discriminant analysis [33] and multi-criteria DEA (MCDEA) [34], which have their own advantages and disadvantages with regard to their applicability to specific area of study. In the present work, in order to generate deeper insights from the large data set obtained from the experimental study, complete ranking is carried out through combined Shannon's entropy and DEA models. The methodology adopted for the present work has been discussed in Section 3, in detail.

After this introductory section, the rest of the paper is organized as follows: The components of experimental setup developed for the present work and the protocol of the experiment is briefly described in Section 2. Section 3 discusses the methodology adopted in the present work for analyzing the complex data generated from the experiment, i.e. combined Shannon's entropy and DEA model. The selection of input and output is very crucial step in any DEA based study, which has been discussed in Section 4. Section 5 presents the results and discussions while the concluding remarks have been summarized in Section 6.

Section snippets

Experimental setup and data acquisition

The objective of the experimental study carried out in the present work is to evaluate the performance of different PV array configurations under cumulative impact of partial shading and deposition of aerosols at their different concentration and different irradiance levels. Seven PV array configurations were developed using 16 single crystalline silicon (s-Si) cells, which are SP, BL, HC, TCT and three novel hybrid topologies proposed in the present work, which are CT-SP, CT-BL and CT-HC.

Methodology

The large amount of data generated from the experiment have been analyzed in the present work using combined Shannon's entropy and DEA for having deeper insights and to be able to draw meaningful conclusions. DEA was proposed by Charnes et al. [37] and is based on the original formulations of Farrell [38] as a tool to quantify relative efficiencies of a set of decision making units (DMUs) viz. power plants, manufacturing units, transmission networks, power distribution divisions etc.

Selection of input-output

Selection of input and output variables is a very crucial step in DEA studies, which depends on several factors like functional relation of the variables with the DMUs, technical requirement of the chosen model and reliability of available data as well. Generally, the input variables should reflect the resources utilised by the DMUs, whereas, production parameters of the DMUs are considered as output variables in DEA studies [46]. In the present work, choice of inputs and outputs has been made

Analysis of primary data generated from experiment

As discussed in Section 2, in the first step of the present work, performance of different PV arrays (A1, …,A7) has been experimentally studied by simulating changes in three environmental factors such as irradiance levels (Ir1,…,Ir3), aerosol types (T1, ,T4) and concentration of aerosols (W1, … W3). Current (I) vs. voltage (V) characteristics has been plotted by changing the resistance connected across the panels and following parameters are derived: open circuit voltage (Voc), short circuit

Conclusion

Partial shading and aerosol deposition are two most common detrimental environmental factors which impact the PV performance. Though quite large number of studies related to impact of either of these two factors in isolation are found in literature, studies on cumulative impact of both is absent. In this paper, the cumulative impact of partial shading and deposition of aerosols on seven PV array topologies have been experimentally investigated, which includes four conventional topologies such

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