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SUPPORTING THE SMALL HYDROPOWER SYSTEMS MANAGEMENT THROUGH SEASONAL FORECAST OF RIVER STREAMFLOW
Eva Contreras Javier Herrero, Cristina Aguilar, María José Polo
Keywords: seasonal forecast, climate service, small hydropower plant, streamflow 1. Introduction
Hydroelectric power is one of the cheapest, reliable, sustainable, and renewable sources of energy (Yildiz, 2019). Small hydropower plants located in mountainous areas, with no dam or water storage, despite being one of the most cost-effective (with relatively low operational and maintenance costs) and environmentally benign energy technologies (Paish, 2002), has the disadvantage that the production is not constant and is subjected to the run-of-river flow, which is also depending on a high variability in precipitation and snow cover. When inflow drops below the minimum technical inflow of the turbines, the hydropower station does not have enough water to remain operational. Another drawback of these systems is that when inflows are extremely high, water will have to be “spilled”, which represents a lost opportunity for generation (IRENA, 2012). The management has to accomplish with some particular operation conditions of the plant but also some environmental flow requirements. The aim of this work is to propose and develop a climate service targeted at end-users, able to support small hydropower systems management to foresee the water availability for the energy production in the most efficient way, and to make it profitable.
2. Materials and methods
The pilot application of the climate service proposed consists in the assessment of a three small hydropower plants system located in Poqueira River (Southern Spain), with a generating capacity between 10 and 12 megawatts and managed by a leading company in the Spanish energy sector which normally takes decisions based on historical information of the inflows. The annual precipitation regime is highly variable, ranging from 200 to 1000 mm in dry and wet years, respectively (Pérez-Palazón et al., 2015). The mean annual fractional snow cover area for
2 −2 2 −2
the period 2000-2013 was 0.21 m ·m , ranging from 0.9 to 0.16 m ·m in wet/cold and
dry/warm years, respectively (Pimentel et al., 2017), which results in a very heterogeneous spatial distribution over the years,
In this regards, a new technological pilot tool was developed following a co-generation process involving data providers, service purveyors and end-users. Seasonal (6 months) forecast of daily river flow and precipitation were provided by the Swedish Meteorological and Hydrological Institute. These data were combined with historical and real time local data provided by the Andalusian Environmental Information Network to make the downscaling generation of local impact indicators (river flow in the uptake points, as an indicator of available water to generate electricity) to the point of interest. Then, a set of local specifications, such as indicator thresholds, turbine performance curve, specific consumption and environmental flow rules were defined by end-users. Finally, the on-line implementation of a data model and a web interface were carried out.
3. Results and conclusions
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