A Model-Based Filtering Strategy to Reconstruct the Maximum Power Generation of Curtailed Photovoltaic Installations: application to forecasting

In this paper, we propose a model-based filtering strategy to reconstruct the maximum power production of a PV power plant thanks to integrating measurements of the PV cell temperature, system DC voltage and DC current. The filter relies on a reversed physical model of the targeted PV system and enables to, first, determine analytically the irradiance incident to the panels, and, second, estimate the DC power production as if the plant was operating in maximum power point tracking (MPPT) mode. We present how the approach can be used to reconstruct the maximum power value starting from a generic operating point. As an application, we show that the proposed strategy can improve time series-based solar power forecasting techniques, in particular when the production of the PV system is curtailed and thus the measured power does not correspond to the maximum available.

Local estimation of the global horizontal irradiance using an all-sky camera

Mario Paolone, Enrica Scolari, Fabrizio Sossan

Localised and high-frequency measurements of the global horizontal irradiance (GHI) are a key information to assess the level of power production of distributed photovoltaic generation. The paper presents a supervised machine learning-based procedure to estimate the GHI using images obtained from an all-sky camera installed at ground level. The training phase consists, at first, in extracting a large set of features from historical images and sub-selecting them using principal component analysis (PCA). The set of selected features is used to train an artificial neural network (ANN) considering the clear-sky index as the estimated variable and output of the ANN. Then, the same procedure is augmented by considering features from satellites images (i.e., SEVIRI thermal channels). The output of the proposed estimator is compared against ground truth measurements from a pyranometer located in the proximity of the camera and benchmarked against state-of-the-art Heliosat-2 estimations. The performance assessment is presented for four different periods of the year, and for three different time resolutions (i.e., 1, 5, and 15 min). Results show that the estimator based only on images features outperforms the others, and improves the Heliosat-2 estimations by 20-45% (relative improvement in terms of normalized root mean square error).

PERGAMON-ELSEVIER SCIENCE LTD2018

Thermo-Economic Optimisation of Solar Tower Thermal Power Plants

James Spelling

Amidst a backdrop of rapidly increasing world-wide electricity demand, solar thermal power generation shows great potential for supplying the electricity needs of numerous countries in the Sun-belt regions of the world. In these regions, the absence of significant biomass, hydrological or geothermal reserves makes solar thermal power the most promising solution for meeting that most fundamental of demands: energy. Amidst the different options available for harnessing the Sun’s power, solar thermal technologies have been shown capable of producing electricity at the most economically viable rates [32]. However, all currently existing solar thermal power plants have been based around the use of Rankine, or steam turbine, cycles which are limited in the efficiencies they can achieve. In order to make better use of the Sun’s energy, higher efficiency cycles should be used. With their high concentration ratios, solar thermal power tower systems are amongst the best options for making use of the Sun’s potential. As the energy delivery temperature of central receiver systems is higher, they harness the solar radiation at a higher exergy level [4]. This higher temperature also opens the road to the use of more advanced thermodynamic cycles. Hybrid fossil-fuel – solar systems are also imaginable [13], as the energy delivery temperature is compatible with standard gas turbine cycles. Hybrid systems can help mitigate the requirements of thermal energy storage, as well as reducing the perceived risk when investing in new solar technology, which stimulates research and development, as well as providing employment. Recent developments in the field of high temperature volumetric receivers [10] along with rock- based packed-bed storage systems have opened up an interesting possibility. High temperature receivers allow the use of higher-efficiency combined-cycle setups, whereas packed-bed units offer the possibility of cheap storage. Larger storage volumes allow pure-solar systems to extend their power production into the night, making hybrid options less attractive. This is compounded by the common practice of guaranteeing a preferred tariff for electricity sales from pure-solar sources With this in mind, a complete dynamic model of a power plant based on the pure-solar concept has been elaborated. The performance of the setup is evaluated over a range of days, using solar insolation profiles obtained from satellite data. In order to examine different design options and their impact on the performance of the power plant, a multi-objective, thermo-economic optimisation of both the power plant superstructure and operating conditions was performed using the new, dynamic models. By means of an evolutionary algorithm [17], a family of Pareto-optimal points were obtained, representing the trade-off between increased power plant efficiency, and lower levelised energy costs. Through use of optimisation, it was shown that exergetic efficiencies in the region of 21-27% can be achieved, for relatively low power outputs of between 3 and 11 MWe. These configurations correspond with levelised electricity costs in the region of 14-21 UScts/kWhe. In most regions, the use of solar power is encouraged by the guarantee of a preferential tariff for electricity sales from renewable sources. Sale of electricity at a price of around 24 UScts/kWhe [32] should therefore be imaginable, ensuring the economic viability of solar thermal power tower systems. It can be concluded that, when properly designed, solar thermal power plants based on combined cycles are both economically and thermodynamically promising. By raising the efficiency of the plant, the size of the solar collector field is diminished, increasing the otherwise low energy densities of solar power systems. By reducing the levelised electricity costs, solar thermal power plants become more economically viable, accelerating their construction and thus, hopefully, reducing our dependence on fossil-fuels.

2009

Thermo-Economic Optimisation of Solar Tower Thermal Power Plants

James Spelling

2009