Abstract
Hydropower is the most widely used renewable power source worldwide. The current work presents a methodological tool to determine the hydropower potential of a reservoir based on available hydrological information. A Bayesian analysis of the river flow process and of the reservoir water volume is applied, and the estimated probability density function parameters are integrated for a stochastic analysis and long-term simulation of the river flow process, which is then used as input for the water balance in the reservoir, and thus, for the estimation of the hydropower energy potential. The stochastic approach is employed in terms of the Monte Carlo ensemble technique in order to additionally account for the effect of the intermediate storage retention due to the thresholds of the reservoir. A synthetic river flow timeseries is simulated by preserving the marginal probability distribution function properties of the observed timeseries and also by explicitly preserving the second-order dependence structure of the river flow in the scale domain. The synthetic ensemble is used for the simulation of the reservoir water balance, and the estimation of the hydropower potential is used for covering residential energy needs. For the second-order dependence structure of the river flow, the climacogram metric is used. The proposed methodology has been implemented to assess different reservoir volume scenarios offering the associated hydropower potential for a case study at the island of Crete in Greece. The tool also provides information on the probability of occurrence of the specific volumes based on available hydrological data. Therefore, it constitutes a useful and integrated framework for evaluating the hydropower potential of any given reservoir. The effects of the intermediate storage retention of the reservoir, the marginal and dependence structures of the parent distribution of inflow and the final energy output are also discussed.
Highlights
Hydropower is a clean, renewable source of energy that significantly contributes to the reduction of greenhouse gas emissions; global warming is expected to have an impact on water availability and on hydropower management
A Bayesian analysis of the river flow and available water volume in the reservoir is applied, and the estimated probability density function parameters are integrated for a stochastic analysis and longterm simulation of the river flow process, which is used as input for the water balance in the reservoir, and for the estimation of the hydropower residential energy potential
Following the methodology described in the previous section, the hydropower potential for the case study reservoir is calculated using the average supply volume of the reservoir that corresponds to 6.127 hm3 or 17.8 m of water level as a pilot example
Summary
Hydropower is a clean, renewable source of energy that significantly contributes to the reduction of greenhouse gas emissions; global warming is expected to have an impact on water availability and on hydropower management. Several Mediterranean islands are not connected to the main electricity grid (e.g., [1]), meaning that independent local grids cater for their power requirements, mainly using imported fossil fuels, contributing to global warming. The exploitation of the hydroelectric potential, respecting the islands’ water needs and a multipurpose use of the reservoirs, has been a topic of investigation as it could contribute to a sustainable energy system and support the implementation of the revised Renewable Energy Directive (2018/2001/EU).
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