Technical Report

PV LCOE in Europe 2014-30

Authors:
  • Becquerel Institute, Brussels, Belgium
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Abstract

It has been shown that the PV module price will most likely to be halved again and BoS price will decrease by more than 35% by 2030, leading to an overall PV system CAPEX reduction of about 45%. It must be noted that this development does not require any major technology breakthroughs but is a natural cause from continuing efforts in reducing materials use, impoving efficiency and developing manufacturing processes. At the same time, PV system OPEX is expected to decrease by 30%. PV LCOE will decrease by 30-50% from 2014 to 2030, depending on the volume growth and learning rate. Cost of capital is by far more significant than CAPEX or OPEX: a 8% percentage point increase in real WACC will double the LCOE. It is the most urgent task for the solar industry to improve the bankability of PV, but at the same time for the policy makers to create a stable environment for investments, in order to decrease the cost of capital and thus the LCOE of PV. 􀀘 Residential and commercial PV electricity is already competitive with retail market electricity in all selected countries. Parity with wholesale market electricity will be reached by 2030 almost everywhere. There is every reason to believe that this development will continue after 2030 because there is still a huge improvement potential in various PV technologies. Figure 13 gives the PV LCOE for a 1 p ground-mounted system until 2050 assuming that the annual market would stay at the 200 GWp level, learning rate at 20%, and module efficiency improves 0.4 percentage points per year from 2030 to 2050. This would mean that global cumulative PV capacity would be 5700 GWp in 2050 and average module efficiency about 30%. PV system price would decrease to about third from 2014 and OPEX is assumed to be halved. It can be seen that in Spain the LCOE in 2050 would be about 20 €/MWh and in the UK and Sweden below 40 €/MWh with a 5% real WACC, or about 60% less in 2050 compared with 2014. It can be concluded that PV will probably be the cheapest form of electricity generation in most countries in the coming decades.

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... Obviously, system size has an impact on the share of CAPEX and OPEX in the LCOE, which is shown for utility-scale PV in Section 4. The weighted average cost of capital (WACC) used in the LCOE calculation is the single most important input parameter, more important than CAPEX and comparable to yield. 25 In this paper, WACC is varied in order to evaluate the full range of PV LCOE with different kind of investors and projects. WACC for utility-scale PV can be as low as 2.5%, as reported for the case of Germany. ...
... In a previous paper by Vartiainen et al 25 Nominal WACC can be defined as ...
... Another challenge is that the solar PV industry is developing so fast that it is difficult to forecast even the near future price development. As an example, Figure 15 shows a comparison of a couple of fairly recent EUPVTP/ETIP PV 25 sensitivity analysis that the cumulative installed PV capacity in 2050 ...
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... These costs decrease with improvements in the efficiency of the modules. OPEX costs are expected to reduce by 15% by the year 2030 [7]. It has also been suggested that the standardization of manufacturing practices will further contribute a drop of 15% in the same year leading to a total decline of 30% in OPEX costs which further makes up $14/kW per annum for systems holding capacity up to 1 MW and $10.5/kW per annum for multi-megawatts systems [7]. ...
... OPEX costs are expected to reduce by 15% by the year 2030 [7]. It has also been suggested that the standardization of manufacturing practices will further contribute a drop of 15% in the same year leading to a total decline of 30% in OPEX costs which further makes up $14/kW per annum for systems holding capacity up to 1 MW and $10.5/kW per annum for multi-megawatts systems [7]. ...
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Cost of Energy Comparison, Including Levelized Cost of Energy (LCOE)—2020 Update
Article
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Power-to-green urea is the concept of urea production using hydrogen from photovoltaic (PV)-electrolysis; a promising option for remote area that do not have natural gas reserves. In this study techno-economic analysis of a small-scaled power-to-green urea plant is conducted with the purpose of obtaining energy efficiency of the system, specific energy consumption, and urea price. Process simulation is carried out by using Aspen Plus and green urea price is calculated using cash flow with 4 schemes. Scheme 1 uses investment cost of technology in 2019, scheme 2 is modification of scheme 1 with additional revenue through clean development mechanisms (CDM), scheme 3 uses investment cost of technology in 2030 and 2050, and scheme 4 is a combination of scheme 2 and 3. The obtained result shows the system efficiency of 7.9% and specific energy consumption of 109 GJ/MT urea. The price of green urea with Scheme 1, 2, 3, and 4 in order are 2342, 2320, 2026 and 1704, as well as 2004 and 1682 USD/MT urea, respectively. Power-to-green urea could not compete economically with conventional large-scale urea; however, due to its stable price and easily acquired raw material it is still highly relevant for remote areas in the future.
Conference Paper
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A chronological multi-area generation planning model is used to investigate the influence of low-cost batteries on the cost-optimal share of wind power and photovoltaics (PV) under varying assumptions about their future investment costs. The analysis is performed in two different geographic locations that have a large difference in the solar resource. The results from around 400 scenario runs demonstrate to what extent lower investment costs mitigate the resource variability. In this regard, PV is more sensitive than wind power. Given the assumptions utilized, the model starts to invests in PV at much higher cost levels in Iberia (~1050 €/kW) than in Northern Europe (~400 €/kW). Furthermore, in Iberia batteries benefit PV strongly (already at 300 €/kWh) while in Northern Europe batteries are not as relevant, since PV has a strong seasonal variation that cannot be economically mitigated with batteries and the region already has high amounts of flexible reservoir hydro power.
Technical Report
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This report investigates data supplied from installed operating PV plants in different countries in order to improve understanding of efficiency and reliability issues of current state-of-the-art PV systems. The first section describes the continued efforts to enrich and maintain the existing online performance database and to add new operational data from existing and new grid-connected PV systems. This activity deals with quality data only, selected and analyzed for usability by experts from each of the contributing countries. Currently (mid 2014), the PV online performance database contains operational data of nearly 600 PV systems in 13 countries. The spectrum ranges from small installations of less than 1 kWp to power plants of more than 2 MWp. The database includes datasets of PV systems with different cell technologies and type of mounting like flat roof, sloped roof, façade, ground mounted or PV sound barriers. An important function is the possibility to filter the available data within the database. This allows a comparison of the different plant data within the sorted arguments. It is possible to export the data to a spreadsheet application like Microsoft Excel. In this way, it is possible to create own graphs and to analyze the data in more detail. A complementary approach is described in the second section, attempting to answer the question “How well is PV serving the world”. Therefore, only two parameters from as many PV systems as possible are analyzed: Annual yield (kWh per installed kWp) Performance ratio PR Experts of Task 13 have attempted to collect appropriate data for a large amount of PV systems. Notably data from Italy, USA and Australia have been supplied for this. Limited data availability from other participating countries has been addressed by using so-called web scraping techniques that collect and organize performance data automatically in databases. In order to study correlation between performance and system size, data have been divided into system power classes ranging from <1 kWp to >10 MWp. In addition, performance data can be related to climate zones. It may be concluded that today’s PV systems are in general “delivering what the salesman says”, with country differences in annual yield that can well be explained by irradiation differences or climate zone differences. While the first two sections deal with the analysis of PV system efficiency, the third section aims at finding the root cause of faults that lead to system downtime or low efficiency, as expressed by a low overall Performance Ratio. A study has begun to find correlation between defined faults, either hardware failures or low efficiencies, and the system parameters immediately before the fault as compared to long before the fault. The systems under study were and will be monitored for efficiency. When the efficiency drops or a failure becomes apparent the system parameters will be examined and compared to periods of time past. It is assumed that a correlation between monitored system parameters and specific failures can be found and catalogued. If a statistical correlation can be found between the changing characteristics of specific parameters and specific fault types, these correlations could be used as signs for impending failure. Such correlations could then be used to alert the owner on faults when no Performance Ratio monitoring exists.
Technical Report
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This report focuses on the analytical assessment of photovoltaic (PV) plant performance on the overall PV system level. In particular, this report provides detailed guidelines and comprehensive descriptions of methods and models used when analyzing grid-connected PV system performance. The main objectives of this report are: to propose good practices for PV system monitoring today, to determine and understand PV system losses that cannot be assessed by direct measurements in commercial PV systems, to determine and understand the behavior of new PV technologies in long-term system operation, to learn from previous bad experiences and draw out lessons for new installations in the IEA PVPS member countries. In the starting section, “Photovoltaic System Monitoring”, best practices in PV monitoring are documented. In addition to describing general monitoring approaches and listing common reference documents, the section outlines peculiarities of different measurement equipment and highlights best practices for hardware configuration and installation. An overview of various interesting measurement quantities and related failure patterns is also provided. In the second section, “Understanding Photovoltaic System Operation through Monitoring”, comprehensive guidelines on how to analyze performance data are given, based on concrete examples using periodic linear regression. The section highlights the versatility of this linear-regression-based approach for PV performance analysis. The approach can, for example, be used to assess the influence of module temperature on array and system performance, the influence of wind speed, DC voltage deviations and their relation to module temperature, as well as the resilience of grid voltage to active power. The majority of presented methods and tools can be applied irrespective of particular module technologies. However, a number of special effects related to less common module technologies require some consideration, as outlined in a dedicated chapter on “new” technologies. In particular, CIGS and amorphous silicon modules have been analyzed in this study. Based on data from different experimental installations in the field, the specific behavior of the new modules was modeled and compared to classical crystalline silicon PV. The existing models for crystalline silicon require major modifications especially for modules involving amorphous silicon. This is detailed in the third chapter, “Understanding Effects Related to Special Technologies”. Finally, measures that can help improve the performance of PV systems are described in the fourth chapter, “PV System Performance Improvement”. This section outlines recommendations for improvement, based on lessons learned from PV system design over the past decade. To this end, a brief introduction to traditional performance indicators is given, along with an overview of the trends in PV system performance over the years. Key system design decisions, such as mounting angle and row distance, inverter to module power ratio, and cabling optimizations, are also addressed. Several examples on both shading losses and inverter to module power ratio are highlighted, providing deeper insight into the pitfalls and merits of various system design options. Finally, the basic approach of real-time data processing is described as a means to optimize system output by increased responsiveness to outages. The full report delivers a comprehensive set of practical guidelines for analytical PV system monitoring. Applied systematically, these guidelines will contribute to further increasing the performance of PV power plants.
Chapter
Likelihood of a 100% Renewable World Global Network or Local Autonomy? Timeline for a 100% Renewable World
Maintaining Returns: PV O&M Opportunities & Prices
BNEF, 2013. Maintaining Returns: PV O&M Opportunities & Prices. Bloomberg New Energy Finance report.
Personal communication with Pietro Radoia
BNEF, 2015. Personal communication with Pietro Radoia, 14 April 2015.
  • Ise Fraunhofer
Fraunhofer ISE, 2014. Photovoltaics Report (2014), updated 24 October 2014.
SEMI International Technology Roadmap for Photovoltaic, Sixth Edition, 2014 Results. PV Parity, 2013. Grid Integration Cost of Photovoltaic Power Generation
ITRPV, 2015. SEMI International Technology Roadmap for Photovoltaic, Sixth Edition, 2014 Results. PV Parity, 2013. Grid Integration Cost of Photovoltaic Power Generation, project report.
Global Market Outlook for Solar
SolarPower Europe, 2015. Global Market Outlook for Solar Power 2015-2019.
Statistical data on the German Solar power industry
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BSW-Solar, 2014. Statistical data on the German Solar power industry.
Grid Integration Cost of Photovoltaic Power Generation
ITRPV, 2015. SEMI International Technology Roadmap for Photovoltaic, Sixth Edition, 2014 Results. PV Parity, 2013. Grid Integration Cost of Photovoltaic Power Generation, project report.