Day-ahead energy production in small hydropower plants: uncertainty-aware forecasts through effective coupling of knowledge and data

Motivated by the challenges induced by the so-called Target Model and the associated changes to the current structure of the energy market, we revisit the problem of day-ahead prediction of power production from Small Hydropower Plants (SHPPs) without storage capacity. Using as an example a typical run-of-river SHPP in Western Greece, we test alternative forecasting schemes (from regression-based to machine learning) that take advantage of different levels of information. In this respect, we investigate whether it is preferable to use as predictor the known energy production of previous days, or to predict the day-ahead inflows and next estimate the resulting energy production via simulation. Our analyses indicate that the second approach becomes clearly more advantageous when the expert's knowledge about the hydrological regime and the technical characteristics of the SHPP is incorporated within the model training procedure. Beyond these, we also focus on the predictive uncertainty that characterize such forecasts, with overarching objective to move beyond the standard, yet risky, point forecasting methods, providing a single expected value of power production. Finally, we discuss the use of the proposed forecasting procedure under uncertainty in the real-world electricity market.

Directions and Extent of Flows Changes in Warta River Basin (Poland) in the Context of the Efficiency of Run-of-River Hydropower Plants and the Perspectives for Their Future Development

This paper presents changes in the flow of 14 rivers located in the Warta River basin, recorded from 1951 to 2020. The Warta is the third-longest river in Poland. Unfortunately, the Warta River catchment area is one of the most water-scarce regions. It hosts about 150 hydropower plants with a capacity of up to 5 kW. The catchment areas of the 14 smaller rivers selected for the study differ in location, size, land cover structure and geological structure. The paper is the first study of this type with respect to both the number of analyzed catchments, the length of the sampling series and the number of analyzed flow characteristics in this part of Europe. The analysis of changes in the river flows was performed with reference to low minimum, mean and maximum monthly, seasonal and annual flows. Particular attention was paid to 1, 3, 7, 30 and 90-day low flows and durations of the flows between Q50 and Q90%. In addition, the duration of flows between Q50 and Q90% were analysed. Analysis of the direction and extent of particular flow types was performed by multitemporal analysis using the Mann–Kendall (MK) and Sen (S) tests. The analysis of multiannual flow sequences from the years 1951–2020 showed that the changes varied over the time periods and catchments. The most significant changes occurred in the low flows, while the least significant changes occurred in the high flows. From the point of view of the operation of the hydropower sector, these changes may be unfavourable and result in a reduction in the efficiency of run-of-river hydropower plants. It was established that local factors play a dominant role in the shaping of river flows in both positive and negative terms, for the efficiency of the hydropower plants.

Performance Analysis of a Low Head Water Vortex Turbine

A small hydropower plant is an environment-friendly renewable energy technology. The run-of-river type gravitational water vortex turbine can be designed to produce electricity at sites with low water heads. In this study, an experimental investigation was undertaken on this type of turbine with a water tank and a runner which is connected to a shaft. At the end of the shaft, a rope brake was attached to measure the output power, torque and overall efficiency of the vortex turbine by varying flow rates. The designed vortex turbine can achieve an overall efficiency of . The experimental results were validated with available data in the literature and theories associated with the turbine. The results also showed that the flow rate plays a vital role in generating power, torque as well as overall efficiency. The project was completed using local resources and technologies. Moreover, as water is used as the input power, this project is eco-friendly which has no adverse effect on the environment.

Analyzing the Applicability of Random Forest-Based Models for the Forecast of Run-of-River Hydropower Generation

Analyzing the impact of climate variables into the operational planning processes is essential for the robust implementation of a sustainable power system. This paper deals with the modeling of the run-of-river hydropower production based on climate variables on the European scale. A better understanding of future run-of-river generation patterns has important implications for power systems with increasing shares of solar and wind power. Run-of-river plants are less intermittent than solar or wind but also less dispatchable than dams with storage capacity. However, translating time series of climate data (precipitation and air temperature) into time series of run-of-river-based hydropower generation is not an easy task as it is necessary to capture the complex relationship between the availability of water and the generation of electricity. This task is also more complex when performed for a large interconnected area. In this work, a model is built for several European countries by using machine learning techniques. In particular, we compare the accuracy of models based on the Random Forest algorithm and show that a more accurate model is obtained when a finer spatial resolution of climate data is introduced. We then discuss the practical applicability of a machine learning model for the medium term forecasts and show that some very context specific but influential events are hard to capture.

Run-Of-River Small Hydropower Plants as Hydro-Resilience Assets against Climate Change

Renewable energy sources, due to their direct (e.g., wind turbines) or indirect (e.g., hydropower, with precipitation being the generator of runoff) dependence on climatic variables, are foreseen to be affected by climate change. In this research, two run-of-river small hydropower plants (SHPPs) located at different water districts in Greece are being calibrated and validated, in order to be simulated in terms of future power production under climate change conditions. In doing so, future river discharges derived by the forcing of a hydrology model, by three Regional Climate Models under two Representative Concentration Pathways, are used as inputs for the simulation of the SHPPs. The research concludes, by comparing the outputs of short-term (2031–2060) and long-term (2071–2100) future periods to a reference period (1971–2000), that in the case of a significant projected decrease in river discharges (~25–30%), a relevant important decrease in the simulated future power generation is foreseen (~20–25%). On the other hand, in the decline projections of smaller discharges (up to ~15%) the generated energy depends on the intermonthly variations of the river runoff, establishing that runoff decreases in the wet months of the year have much lower impact on the produced energy than those occurring in the dry months. The latter is attributed to the non-existence of reservoirs that control the operation of run-of-river SHPPs; nevertheless, these types of hydropower plants can partially remediate the energy losses, since they are taking advantage of low flows for hydropower production. Hence, run-of-river SHPPs are designated as important hydro-resilience assets against the projected surface water availability decrease due to climate change.

Unruly Mountains: Hydropower assemblages and geological surprises in the Indian Himalayas

Despite a decades long push to develop what is seen as the vast untapped hydropower potential of the Indian Himalayas, hydropower capacity addition has been delayed and become increasingly expensive in India. Policy documents cite “poor” geology as a major reason for these delays. As hydropower in the form of run-of-river projects expand into the Himalayas, their construction activities encounter poor geology more frequently. This paper analyses hydropower development as an assemblage and examines how risk, especially geological risk, is negotiated to allow hydropower development to continue in the Indian Himalayas. We show how the category of “geological surprises” emerges as an institutional response to the problems of run-of-river based hydropower development in a seismically vulnerable landscape. We further show how “geological surprises” act as a boundary object between hydropower policy, project development, infrastructural finance, and hydropower knowledge, allowing for cooperation and negotiation, to allow hydropower development to continue in the geologically complex Himalayas.

The future of Swiss run-of-river hydropower production: climate change, environmental flow requirements and technical production potential

Run-of-river (RoR) hydropower is essential in Alpine energy production and highly sensitive to climate change, due to no or limited water storage capacity. Here, we estimate climate change impact on 21 RoR plants in Switzerland, where 60% of the annual electricity is produced by hydropower (30% by RoR). This is one of the first comprehensive, simulation-based studies on climate change impacts on Alpine RoR production, including effects of environmental flow requirements and technical production potential. We simulate three future periods under three emission scenarios (RCP2.6, RCP4.5, RCP8.5). The results show an increase of winter and a decrease of summer production, which in conjunction leads to an annual decrease. The simulated impacts strongly depend on the elevation and the plant-specific characteristics. A key result is that the climate induced reduction is not linearly related to the underlying streamflow reduction, but is modulated by environmental flow requirements, the design discharge and streamflow projections. Stronger impacts are expected if climate change affects streamflow in the range that is usable for production. This result is transferable to RoR production in similar settings and should be considered in future assessments. Future work could in particular focus on further technical optimisation potential, considering detailed operational data.

Investigation of climate change impacts on hydropower generation: the case of a run-of-river small hydropower plant in North Western Greece

Services and uses arising from surface water‘s availability, such as hydropower production, are bound to be affected by climate change. The object of the research is to evaluate climate change impacts on energy generation produced by run-of-river small hydropower plants with the use of future river discharges derived from two up-to-date Regional Climate Models. For doing so, the hydropower simulation model HEC-ResSim, calibrated and validated over real power data, was used to simulate the generated energy in the two future periods of 2031-2060 and 2071-2100. The future river discharges in the case study area are derived from the hydrological model E-HYPE that uses as forcing the climatic variables of the CSC-REMO2009-MPI-ESM-LR and KNMI-RACMO22E-EC-EARTH climate models under two Representative Concentration Pathways, namely RCP4.5 and RCP8.5. The research outputs demonstrate a decrease of the generated energy varying from 2.86% to 25.79% in comparison to the reference period of 1971-2000. However, in most of the simulated scenarios the decrease is less than 10.0%, while increased energy production is projected for one of the scenarios. Overall, it can be concluded that the case study run-of-river small hydropower plant will be marginally affected by climate change when the decrease of the relevant river discharges is up to 10-15%.