Abstract
The photovoltaic (PV) power plants installed in the northwest and northeast areas of China have a serious dust pollution problem. In this paper, a model for optimizing the cleaning cycle of module dust and evaluating the cost for the PV power plants in China was proposed by the use of dust deposition monitoring with image recognition and two cleaning technologies. Outdoor experimental results showed that the degradation of power conversion efficiency changed linearly with increasing the image gray value and the dust deposition density had an asymptotic relationship with dust deposition time. Based on the proposed model and corresponding dry and wet cleaning technologies, the optimal cleaning cycles for a PV power plant in northeast China were approximately 10.1 and 22.8 days when the power conversion efficiency was reduced by 4.5% and 10.2%, respectively. The annual cost resulting from dust on the PV power modules in China was estimated to be $0.0161–0.0222 million per MW with current fixed cleaning cycle and wet cleaning technology. However, the annual cost could be reduced to 36.5–50.3% by using the optimized cleaning cycle and applying dry cleaning technology.
Graphic abstract
Similar content being viewed by others
Abbreviations
- C e :
-
Grid-connected price ($/kWh)
- E :
-
Annual total cost caused by dust ($)
- E c :
-
Cleaning and maintenance cost in a single cleaning cycle ($)
- E d :
-
Power loss cost in a single cleaning cycle ($)
- E m :
-
Residual dust cost in a single cleaning cycle ($)
- Gray i :
-
Image gray value of a point
- Gray a :
-
Average image gray value of dirty PV modules
- P :
-
Installed capacity of PV power plant (kW)
- P max :
-
Maximum power output (Wp)
- T b :
-
Average temperature of PV module array (°C)
- T s :
-
Normal operating cell temperature (°C)
- c f :
-
Fuel consumption cost ($/MW)
- c l :
-
Staff cost per unit capacity ($/MW)
- c m :
-
Annual maintenance cost of the cleaning equipment ($)
- c s :
-
Annual depreciation cost of the cleaning equipment ($)
- e d :
-
Daily power loss cost ($/day)
- e m :
-
Daily residual dust cost ($/day)
- k :
-
Power temperature coefficient (%/°C)
- n c :
-
Cleaning frequency (time)
- n d :
-
Useful life of the cleaning equipment (year)
- t :
-
Dust deposition time (day)
- t ci :
-
Cleaning interval (day)
- t cp :
-
Cleaning time (day)
- v d :
-
Original value of the cleaning equipment ($)
- η :
-
Power conversion efficiency (%)
- η clean :
-
Power conversion efficiency of PV modules in clean condition (%)
- η dust :
-
Power conversion efficiency of PV modules in dust condition (%)
- η d :
-
Estimated net residual rate of the cleaning equipment (%)
- η m :
-
Maintenance rate of the cleaning equipment (%)
- η pl :
-
Loss ratio of power output (%)
- τ :
-
Annual operation period (day)
References
Al Hanai T, Hashim RB, El Chaar L, Lamont LA (2011) Environmental effects on a grid connected 900 W photovoltaic thin-film amorphous silicon system. Renew Energy 36:2615–2622
Alam MJE, Muttaqi KM, Sutanto D (2014) A novel approach for ramp-rate control of solar PV using energy storage to mitigate output fluctuations caused by cloud passing. IEEE Trans Energy Convers 29:507–518
Costa S, Diniz AS, Kazmerski LL (2016) Dust and soiling issues and impacts relating to solar energy systems: literature review update for 2012–2015. Renew Sustain Energy Rev 63:33–61
Cuddihy E, Coulbert C, Gupta A, Liang R (1986) Electricity from photovoltaic solar cells, Flat-Plate Solar Array Project, Final Report. Jet Propulsion Laboratory, Pasadena
El-Shobokshy MS, Hussein FM (1993) Degradation of photovoltaic cell performance due to dust deposition on to its surface. Renew Energy 3:585–590
Ghazi S, Sayigh A, Ip K (2014) Dust effect on flat surfaces—a review paper. Renew Sustain Energy Rev 33:742–751
Hassan AH, Rahoma UA, Elminir HK (2005) Effect of airborne dust concentration on the performance of PV modules. J Astron Soc 13:24–38
Jiang H, Lu L, Sun K (2011) Experimental investigation of the impact of airborne dust deposition on the performance of solar photovoltaic (PV) modules. Atmos Environ 45:4299–4304
Jiang Y, Lu L, Lu H (2016) A novel model for estimate the cleaning frequency for dirty solar photovolatic (PV) modules in deserts environment. Sol Energy 140:236–240
Kern DQ, Seaton RA (1959) A theoretical analysis of thermal surface fouling. Br Chem Eng 4:258–262
Mani M, Pillai R (2010) Impact of dust on solar photovoltaic (PV) performance: research status, challenges and recommendations. Renew Sustain Energy Rev 14:3124–3131
Müller-Steinhagen H (2011) Heat transfer fouling: 50 years after the Kern and Seaton model. Heat Transf Eng 32:1–13
Rehman S, El-Amin I (2012) Performance evaluation of an off-grid photovoltaic system in Saudi Arabia. Energy 46:451–458
Sakarapunthip N, Chenvidhya D, Chuangchote S, Kirtikara K, Chenvidhya T, Onreabroy W (2017) Effects of dust accumulation and module cleaning on performance ratio of solar rooftop system and solar power plants. Jpn J Appl Phys 56:08ME02
Sioshansi FP (2010) Generating electricity in a carbon-constrained world. Elsevier, Burlington
Sundareswaran K, Peddapati S, Palani S (2014) MPPT of PV systems under partial shaded conditions through a colony of flashing fireflies. IEEE Trans Energy Convers 29:463–472
Thackery PA (1980) The cost of fouling in heat exchanger plant. Effl Water Treat J 20:111–115
Van Nostrand WL, Leach SH, Haluska JL (1981) Economic penalties associated with the fouling of refinery heat transfer equipment. Fouling Heat Transf Equip 619–643
Wright S, Andrews G, Sabir H (2009) A review of heat exchanger fouling in the context of aircraft air-conditioning systems, and the potential for electrostatic filtering. Appl Therm Eng 29:2596–2609
Zaihidee FM, Mekhilef S, Seyedmahmoudian M, Horan B (2016) Dust as an unalterable deteriorative factor affecting PV panel’s efficiency: why and how. Renew Sustain Energy Rev 65:1267–1278
Acknowledgements
This study was supported by the National Natural Science Foundation of China (51606035) and the Science and Technology Development Plan of Jilin Province (20190302079GX and 20190201098JC). The authors gratefully acknowledge the contributions of G. Wang, X. M. Gao, R. M. Bao, and J. Wu for their work on the field test of MDCA.
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Conflict of interest
The authors declare that there is no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Zhao, B., Zhang, S., Cao, S. et al. Cleaning cycle optimization and cost evaluation of module dust for photovoltaic power plants in China. Clean Techn Environ Policy 21, 1645–1654 (2019). https://doi.org/10.1007/s10098-019-01731-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10098-019-01731-y