Abstract
The global energy system is in a phase of change for power generation technologies which involve traditional fossil fuel-based technologies to renewable energy-based systems, thanks to lower construction costs, mainly for photovoltaic energy, and changes in countries’ energy policies. In the case of Spain, both factors have led to a reactivation of renewable technologies, which can be found from the data on requests for access and connection to the electricity transmission network that are being processed in Red Eléctrica de España (REE). The requests that were granted access to the network exceeded 100 GW of power in November 2019 alone, and the companies which made the requests must commence electricity production by 2025. During the early stage of approval considerations, it is necessary to carry out an influence study of the risks that can already be identified, as this would enable determining the effects of these risks on the project’s main financial parameters. Based on a risk identification for similar prior projects, experts are typically asked to make their judgments on the influence of such risks on the main economic variables of a project, focusing on the project’s cost, time, and scope. By applying the fuzzy sets, these judgments can be transformed into triangular values that, through Monte Carlo simulation, allow us to assess the influence of these risks on the main financial parameters: the net present value (NPV), internal rate of return (IRR), and payback (PB); as a result of obtaining these parameters, a response to project risks can be planned. To check the functionality of the model, it was applied to a case study involving a construction project for a 250 MW photovoltaic plant located in Murcia (Spain). The application of this methodology allowed us to determine which evaluation criteria are most appropriate based on the philosophy of the PMO (Project Management Office) and the data that were obtained.
Highlights
We are currently in a global situation that favors the use of various forms of renewable energy, the decarbonization of energy production, and the promotion of electric vehicles, with the aim of reducing pollutant emissions and protecting the environment
To study the influence of risks on the project parameters, we worked with the range of values with respect to the mode, the results of the sensitivity analysis with Monte Carlo simulations conducted with 10,000 iterations for each of the 100 simulations, the basic parameters of economic analysis (NPV, PB, and internal rate of return (IRR)), and the resulting influence of the identified risks on the investment items
This paper presents a methodology that allows for analyzing the effect of risks on the profitability of photovoltaic solar plant construction projects based on probabilistic analyses using Monte Carlo simulation, risk identification, and expert judgment
Summary
We are currently in a global situation that favors the use of various forms of renewable energy, the decarbonization of energy production, and the promotion of electric vehicles, with the aim of reducing pollutant emissions and protecting the environment. The expectations created for renewable generation have been so great that, for solar photovoltaic energy alone, there are more than 100 GW of renewable projects in the pipeline, a figure that is well above the 37 GW that was envisaged in the Plan Nacional Integrado de Energía y Clima (PNIEC) 2021–2030. During this phase of the process, as work progresses, more data and information about projects become available, which allows for a quantitative evaluation to be made. It becomes possible to conduct a study on the influence of the risks identified at an early stage to determine their effects on the main financial parameters of each project
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