Martín Gastón

A clustering approach for the analysis of solar energy yields: A case study for concentrating solar thermal power plants

The design of Concentrating Solar Thermal Power (CSTP) systems requires a detailed knowledge of the dynamic behavior of the meteorology at the site of interest. Meteorological series are often condensed into one representative year with the aim of data volume reduction and speeding-up of energy system simulations, defined as Typical Meteorological Year (TMY). This approach seems to be appropriate for rather detailed simulations of a specific plant; however, in previous stages of the design of a power plant, especially during the optimization of the large number of plant parameters before a final design is reached, a huge number of simulations are needed. Even with today’s technology, the computational effort to simulate solar energy system performance with one year of data at high frequency (as 1-min) may become colossal if a multivariable optimization has to be performed. This work presents a simple and efficient methodology for selecting number of individual days able to represent the electrical product...

A methodology for calculating percentile values of annual direct normal solar irradiation series

A detailed knowledge of the solar resource is a critical point in the performance of an economic feasibility analysis of solar thermal electricity plants. In particular, the Direct Normal solar Irradiance (DNI) is the most determining variable in its final energy yield. Inter-annual variations of DNI can be large and seriously compromise the viability of solar energy projects. In this work, a methodology for evaluating the statistical properties of annual DNI series is presented for generating inputs to risk assessments in an economic feasibility analysis of a solar power plant. The methodology relies on the construction of a cumulative distribution function of annual DNI values, which allows for the evaluation of both mean and extreme climate characterization at a particular location in the long term.

Increasing the temporal resolution of direct normal solar irradiance forecasted series

A detailed knowledge of the solar resource is a critical point in the design and control of Concentrating Solar Power (CSP) plants. In particular, accurate forecasting of solar irradiance is essential for the efficient operation of solar thermal power plants, the management of energy markets, and the widespread implementation of this technology. Numerical weather prediction (NWP) models are commonly used for solar radiation forecasting. In the ECMWF deterministic forecasting system, all forecast parameters are commercially available worldwide at 3-hourly intervals. Unfortunately, as Direct Normal solar Irradiance (DNI) exhibits a great variability due to the dynamic effects of passing clouds, 3-h time resolution is insufficient for accurate simulations of CSP plants due to their nonlinear response to DNI, governed by various thermal inertias due to their complex response characteristics. DNI series of hourly or sub-hourly frequency resolution are normally used for an accurate modeling and analysis of tran...

A combination of HARMONIE short time direct normal irradiance forecasts and machine learning: The #hashtdim procedure

The present work describes the first approach of a new procedure to forecast Direct Normal Irradiance (DNI): the #hashtdim that treats to combine ground information and Numerical Weather Predictions. The system is centered in generate predictions for the very short time. It combines the outputs from the Numerical Weather Prediction Model HARMONIE with an adaptive methodology based on Machine Learning. The DNI predictions are generated with 15-minute and hourly temporal resolutions and presents 3-hourly updates. Each update offers forecasts to the next 12 hours, the first nine hours are generated with 15-minute temporal resolution meanwhile the last three hours present hourly temporal resolution. The system is proved over a Spanish emplacement with BSRN operative station in south of Spain (PSA station). The #hashtdim has been implemented in the framework of the Direct Normal Irradiance Nowcasting methods for optimized operation of concentrating solar technologies (DNICast) project, under the European Union...

The temporal distortion index (TDI). A new procedure to analyze solar radiation forecasts

In this work a new point of view to evaluate prediction models is presented. It is captured by mean of a novelty dissimilarity measure among time series, the Temporal Distortion Index (TDI), which compiles a new methodology to evaluate and control the solar radiation prediction models. This methodology complements the traditional verification measures found in the literature by adding the evaluation of the impact that time misalignments produces in the forecast accuracy. This new measure of error will allow a deeper knowledge of the prediction model behaviour besides a bi-criteria perspective to the problem of comparing different forecasts. The information about temporal features of the forecasts could play a key role in tasks as combination of different prediction models, Concentrating Solar Power (CSP) plants operation or energy grid integration.

A methodology for probabilistic assessment of solar thermal power plants yield

A detailed knowledge of the solar resource is a critical point to perform an economic feasibility analysis of Concentrating Solar Power (CSP) plants. This knowledge must include its magnitude (how much solar energy is available at an area of interest over a long time period), and its variability over time. In particular, DNI inter-annual variations may be large, increasing the return of investment risk in CSP plant projects. This risk is typically evaluated by means of the simulation of the energy delivered by the CSP plant during years with low solar irradiation, which are typically characterized by annual solar radiation datasets with high probability of exceedance of their annual DNI values. In this context, this paper proposes the use meteorological years representative of a given probability of exceedance of annual DNI in order to realistically assess the inter-annual variability of energy yields. The performance of this approach is evaluated in the location of Burns station (University of Oregon Sol...