Due to high need of available and reliable energy, renewable sources have aided the increasing diffusion of small plants and distributed generation, allowing the use of low-density distributed renewable sources and provision of self-sufficient energy for small communities in order to reduce transmission loss and grid congestion problems.
Various models used in analyzing energy systems despite their accuracy and complexity, focused less on model input data such as investment cost. There arises some situation in cases of hybrid energy system technology such as small hydropower plants as simplified models cannot accurately estimate investment costs.
Researchers from Department of Industrial Engineering, at University of Padova in Italy proposed a new approach for the estimation of cost of electro-mechanical equipment, where the final cost was decomposed in three terms, two of which represents the cost of mechanical equipment and one the cost of electrical equipment. The work is published in journal, Energy.
Cavazzini et al. (2016) proposed methodology decomposes cost of electro-mechanical equipment which includes ex-works market prices of turbine, automatic valve, regulation elements and alternator in three terms depending on net head, design flow rate and design power. The great diversity in the topology of turbines was taken into account by defining them for each type of turbine separately as regards to correlation constants. The constants were evaluated by applying a recent modified version of the Particle Swarm Optimization ASD-PSD algorithm.
When optimization procedure to determine correlation coefficients was applied to a data set of 13 small hydropower plants located in Italy and equipped with Pelton turbines, it was seen that correlation simulated with good agreement of the real costs of power plants with an average error equal to 6.4% and standard deviation of 6.5%.
For data set of 12 small hydropower plants located in Italy and in Guatemala equipped with Francis turbine, correlation also simulated with good agreement of the real costs of power plants with an average error equal to 10.6% and standard deviation of 4.4%. For Kaplan turbines, resulting correlation simulates with good agreement the real costs of power plants with an average error equal to 8.1% and a standard deviation of 8.8%.
In comparison with the most popular and accurate literature correlations, the proposed approach reached obtained mean errors of 9.2% for Pelton turbine, 9.8% for Francis turbine and 18.2% for Kaplan turbine which were all smaller than all the literature correlations and in particular than those of Ogayar and Vidal’s widely adopted method (10.2% for Pelton turbines, 11.5% for Francis turbine and 25.0% for Kaplan turbines).
It can be deduced that the researchers approach is capable of reaching good values of accuracy with a mean error smaller than all the literature correlations.
The proposed correlation structure with a direct dependency not only on power and net head, but also on design flow rates seems to generate a better approximation of the real cost trend of the electro-mechanical equipment of small hydropower plants.
Giovanna Cavazzini , Alberto Santolin , Giorgio Pavesi , Guido Ardizzon. Accurate estimation model for small and micro hydropower plants costs in hybrid energy systems modelling, Energy, Volume 103, 2016, Pages 746–757.
Department of Industrial Engineering, University of Padova, Via Venezia 1, 35131, Padova, Italy
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