Investment in photovoltaic (PV) projects is a key driving force for the sustainable growth of the solar photovoltaic device market, and therefore an important factor in the energy transition of many countries. To ensure that the expected return on investment (ROI) is achieved, it is very important to establish a professional risk assessment, which helps reduce the risks associated with related investments.
Risk assessment is an active quality management process. All stakeholders in the photovoltaic project approval process try to identify potential legal, technical and economic risks throughout the project life cycle. These risks need to be quantitatively and qualitatively assessed, managed and controlled. Although this quality management process overlaps widely, the focus and evaluation criteria will vary from stakeholder to stakeholder.
Different stakeholders must use the four-step process of risk identification, risk assessment, risk management and risk control throughout the life cycle of a photovoltaic project to formulate their own risk management strategies. With the continuous improvement of the level of experience in the photovoltaic industry, best practice guidelines and specific tools are emerging to better manage technical risks throughout the life cycle of photovoltaic projects. The ultimate responsibility for project risks is still borne by the owner and operator of the photovoltaic power station. With the help of a professional risk management plan, they can significantly reduce and transfer the initial risks associated with photovoltaic projects.
With gaining more and more experience from more and more projects, a more mature and professional photovoltaic industry, and the establishment of professional and standardized processes, these residual risks can be reduced. This is further supported by the positive experience of many investors who successfully run the project. However, when studying the details carefully, this may have occurred due to external phenomena, such as increased irradiance levels that were not considered in the early stages of the project.
Therefore, this article introduces the updated method of key measures as part of the technical risk management of the photovoltaic project design and procurement phase, which helps to reduce the technical risk and increase the possibility of successful commercial investment.
Investors use yield assessment (YA) and long-term yield prediction (LTYP) to make business decisions about long-term investments. Investors know that past performance does not guarantee future results. Benefit evaluation is an important step for photovoltaic projects because it helps determine whether the system will receive funding. However, YA is not only related to the software used, it is mainly related to the user. YAs may not be as reliable as expected. For example, in the IEA PVPS Task 13 report "Yield Assessment and PV LCOE Uncertainty" [IEA2020], the author showed how seven highly skilled experts did not reach the same results, although They have provided the same detailed input.
Together with cost data (CAPEX, OPEX, and discount rate), the output of YA and LTYP (utilization rate, performance loss rate, and lifespan) provides financial investors with calculations of levelized cost of electricity (LCOE) and evaluation of relative internal rate of return ( IRR) and net present value (NPV) of the investment cash flow model.
The YA and LTYP outputs should provide the relative probability of exceedance. This provides stakeholders involved in photovoltaic projects with the right tools to make the best decisions in terms of risk aversion. For a given probability of excess, a reduction in uncertainty in energy production may result in higher values, resulting in a stronger business case.
The main challenge of yield assessment (YA) and long-term yield forecast (LTYP) is related to the credibility of specific location information. In the global market, the task of assessing the output of photovoltaic power plants is actually not uncommon. It is located in an area that is not familiar to the output assessors, so it is extremely important to obtain local knowledge.
The most important parameter that affects energy production evaluation is actually the sunshine at a specific location. Several aspects need to be considered: the reliability of the database, inter-annual changes and long-term trends. Therefore, verifying the availability of satellite data or ground measurement is an essential first step. In this regard, site adaptation technologies can improve the reliability of specific sunlight at selected sites because they combine short-term measurement data with satellite-derived data, which have a longer recording period, but do not necessarily have the characteristics of a specific site. After the measurement activity is completed (usually about six months/a year), different methods can be applied to reduce the deviation. Then use the deviation correction record of the satellite data in this relationship to predict the long-term solar energy resources of the target site.
Other parameters that directly affect the estimation of incident radiation are related to i) the irradiance calculation on the module plane and the model used to decompose and convert the global horizontal irradiance to the global oblique irradiance, and ii) shadow loss (near and far) , Iii) pollution loss, and iv) reflection loss. Shading and pollution losses also vary from site to site, and understanding local conditions can ensure that the loss is properly assessed.
Finally, all conversion steps from irradiance to electricity must be considered. The power calculation in PV modeling software not only depends on the algorithm of the software, but also requires that the components (modules, inverters) have been correctly characterized and can be used as input to the software. Although the modeler can enter or convert the data table values provided by the manufacturer, so far, most manufacturers do not guarantee the accuracy of these key inputs. Through the implementation of peer review methods, the uncertainty of (sub)components in the photovoltaic power modeling chain is usually relatively low. However, errors in the module or inverter documentation may lead to modeling risks, which will have a negative impact on the output, and in turn affect the financial viability of the photovoltaic power plant. Therefore, photovoltaic modules or inverters are additionally characterized by independent laboratories according to the instructions of investors to ensure that the power plant model can be financed, which is increasingly becoming a common industry standard. At this stage, special attention must be paid to the number of modules to be tested and the selection procedure to obtain a reliable average value of electrical parameters for power calculation.
In summary, the main risks associated with yield assessment are:
It is very important to invest resources in the design phase, because from the perspective of cost-benefit analysis, mitigation measures that prevent future failures on site and allow optimization of system design are the most effective. Some measures can be easily applied to reduce the risk of production assessment and long-term production forecasting:
The direct consequence of the deviations in yield estimates is that in addition to the additional modeling assumptions that can be used for LCOE calculations, the LCOE values will also differ. It will be important to determine the P50 and P90 values of the LCOE results and highlight the hypothesis/modeling chain. From an industry perspective, it would be beneficial to be able to conduct and publish more "real-time" post-analysis (ie comparison of LTYP and measurement data, such as system life every 5 years). These can then be used as important feedback and input for YA modelers, financiers, and insurance companies.
Appropriate quality assurance during the procurement phase ensures that the appropriate quality level is achieved and that the equipment meets the planned specifications. This sounds simple in theory, but in reality, there are many situations that indicate that this is not the case—that is, the components installed on-site do not meet the required standards.
For example: VDE Renewables evaluated a photovoltaic portfolio in Turkey with a total capacity of 230MWp. The system uses a combination of eight different photovoltaic module types, each of which has been certified by international standards. However, poorly performing photovoltaic modules were detected at the beginning of the operation of the photovoltaic system. The comprehensive quality assurance work carried out by VDE Renewables determined that two types of photovoltaic modules underperformed around -4%, which exceeded the tolerance limit considering the measurement uncertainty. These underperforming modules are used for 26% of the entire product portfolio. Based on a 4% underperformance rate, substandard photovoltaic modules will cause approximately US$200,000 in losses per year (or US$2,000,000 during a 10-year operation period). Quality assurance in the procurement stage can find problems before operation, strengthen the negotiation basis for the buyer, and save the cost and energy of claiming to the manufacturer.
However, so far, poor equipment performance is not the only problem with procurement. Other risks may also arise, such as:
In the procurement phase of photovoltaic projects, great attention has been paid to the quality of photovoltaic modules. The reason behind this is understandable: modules account for a large part of the total cost, which is difficult/impossible to repair, and quality assurance results are usually easy to explain and resolve. The coupling of performance and purchase price, and the opposite coupling of low performance and yield loss, are some of the strongest arguments that buyers can use with suppliers. However, problems with other components have also been reported in this area. In the procurement process for independent quality assurance, the inverter is undoubtedly a blind spot.
But at the same time, people's expectations are also increasing. In the past, inverters usually operated in protected and climate-controlled environments, such as in building structures (such as central inverters). Nowadays, more and more string inverters of 100 to nearly 200kVA are operating unprotected on site. This of course will increase the pressure on the inverter, thereby increasing the requirements for reliability and weather resistance. In addition, there will be more changes in operating conditions.
The production loss was mainly due to poor performance on site compared to the data sheet, but also due to downtime due to inverter failure. In [NREL2019], it is reported that most of the failures of photovoltaic power plants are caused by power electronic equipment. Only obtaining certification according to existing technical standards does not ensure that the specifications are met, and there will be no problems when the modules and inverters are operated in the field.
Procurement quality control and risk mitigation should start at a very early stage to reduce plant downtime and output loss. It also helps to avoid/reduce the time and effort to file warranty claims or even litigation against manufacturers and replace defective equipment.
Equipment buyers should even clarify their quality requirements and the quality assurance measures they plan to implement before they even start contacting manufacturers. For example, some photovoltaic module buyers failed to agree on the terms of taking samples from production and sending them to independent testing laboratories. It is important to spread the sample selection to different production lines/workshops and production shifts and dates to ensure proper representation during the testing process.
The manufacturer’s goal is usually to limit the sample selection to a few pallets to reduce the logistical work required. Therefore, if these conditions are agreed with the buyer in advance in the purchase contract, potential disputes with the manufacturer can be avoided.
Hiring independent quality assurance partners (such as VDE Renewables) is a best practice followed by many professional project developers. Buyers can take advantage of countless quality assurance measures, such as those listed below
The aforementioned quality assurance measures provide buyers with an opportunity to establish a "quality gate" in the procurement process. If the equipment supplier fails at any of these gates, the buyer can quickly request a batch of equipment to be replaced, and at the same time, due to early failure detection, the impact on the project schedule is minimized.
Buyers can further benefit from the neutral expertise of experienced professionals to help define their quality standards, analyze the results of inspections and tests, and explore corrective actions when any quality defects are discovered during the project.
[IEA2020] David Moser and others, "Earnings Assessment and the Uncertainty of PV LCOE", IEA-PVPS T13-18, 2020; https://iea-pvps.org/key-topics/uncertainties-yield-assessments/
[NREL2019] Nagarajan, Adarsh, Ramanathan Thiagarajan, Ingrid Repins and Peter Hacke. 2019. Reliability evaluation of photovoltaic inverters. Golden, Colorado: National Renewable Energy Laboratory. NREL/TP-5D00-74462. https://www.nrel.gov/docs/fy20osti/74462.pdf.
Boris Farnung is the global head of power plants and systems in the VDE Renewables GmbH division in Germany. Over the past 15 years, Boris has built relationships in the development, management and completion of complex technology projects and has won the trust of leading technology companies, utilities, and international financial institutions. He is the operational agent of IEA PVPS Task 13-PV System Performance and Reliability. In this position, he demonstrated his ability to manage and coordinate international and distributed technology experts and scientists. Throughout his career, Boris has proven his ability to develop and lead teams, change management, and cross-cultural skills. He has an extensive network in the renewable energy industry and has established relationships with international contacts.
Keith Punzalan is responsible for the strategic and business development of VDE Renewables, covering the fields of solar and wind energy and energy storage. Keith has spent his entire career in the field of renewable energy. During his tenure at the Solar Energy Research Institute of Singapore, he supported the early development of the institute and participated in solar power plant feasibility studies and other market research projects in Southeast Asia. During his career at VDE, Keith has also established and developed a series of global renewable energy activities with a focus on solving problems of bankability and quality in the industry. Through these activities and projects, he often deals with renewable energy manufacturers, project developers, banks, investors, insurance companies, government agencies, utilities, market researchers and consulting companies.
David Moser is the research group leader of the EURAC Research Renewable Energy Research Institute. His main research areas include the indoor and outdoor characteristics of photovoltaic modules, the monitoring of photovoltaic project performance, and the modeling and analysis of energy systems.