HS5.3.3

The design of hydropower works typically follows a top-down approach, starting from a macroscopic screening of the broader region of interest, to select promising clusters for hydroelectric exploitation, based on easily retrievable information. Manual approaches are very laborious and may fail to detect sites of significant hydropower potential. In order to facilitate this kind of studies, we provide a novel geomorphological approach to assess the hydropower potential across river networks. The method is based on the discretization of the stream network into segments of equal length, thus providing a background layer of head differences between potential abstraction and power production sites. Next, at each abstraction point, we estimate the so-called unit geo-hydro-energy index (UGHE), which is a key concept of our approach. UGHE is defined as the ratio of annual potential energy divided by the upstream catchment area, the head difference, and the unit annual runoff of the catchment, which is set equal to 1000 mm. The method is further expanded, to estimate the actual hydropotential, if spatially distributed runoff data are available. All analyses are automatized by taking advantage of the high-level interpreted programming language Python and the open-source QGIS tool. The proposed framework is demonstrated at the regional scale, involving the siting of run-of-river hydroelectric works in the Peneios river basin.

How to cite: Risva, K., Sakki, G. K., Efstratiadis, A., and Mamassis, N.: Hydropower potential assessment made easy via the unit geo-hydro-energy index, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4462, https://doi.org/10.5194/egusphere-egu21-4462, 2021.

Hydropower is a comparatively cheap, reliable, sustainable, and renewable
source of energy. Run of River (RoR) hydropower plants are characterised by a
negligible storage capacity and by generation almost completely dependent on the
timing and size of river flows. Their environmental footprint is minimal compared to that
of reservoir-powered plants, and they are much easier to deploy.
This work uses and extends HYPER, a state-of-the-art toolbox that finds the
design parameters that maximise either the RoR plant’s power production or its net
economic profit. Design parameters include turbine type (Kaplan, Francis, Pelton and
Crossflow), configuration (single or two in parallel), and design flow, along with
penstock diameter and thickness, admissible suction head, and specific and rotational
speed.
This work extends HYPER to realise hydropower system design that is robust
to climate variability and change and to changing economic conditions. It uses the many
objective robust decision making (MORDM) approach through the following steps: (1)
an explicit three objective formulation is introduced to explore how design parameter
choices balance investment cost, average annual revenue, and drought year (first
percentile) revenue, (2) coupling of a multi-objective evolutionary algorithm (here,
AMALGAM) with HYPER to solve the problem using 1,000 years of synthetic
streamflow data obtained with the Hirsch-Nowak streamflow generator, (3) sampling
of deeply uncertain factors to analyse robustness to climate change as well as financial
conditions (electricity prices and interest rates), (4) quantification of robustness across
these deeply uncertain states of the world. We also extend HYPER by adding the
possibility to consider three-turbine RoR plants.
The HYPER-MORDM approach is applied to a proposed RoR hydropower plant
to be built on Mukus River in Van province which is located in Eastern Anatolia region
of Turkey. Preliminary results suggest that applying MORDM approach to RoR
hydropower plants provides insights into the trade-offs between installation cost and
hydropower production, while supporting design with a range of viable alternatives to
help them determine which design and RoR plant operation is most robust and reliable
for given site conditions and river stream characteristics. Results confirm earlier
findings that installation of more than one turbine in a hydropower plant enhances
power production significantly by providing operational flexibility in the face of variable
streamflows. When contrasting robustness of a design with its benefit / cost ratio, a
classic measure of performance of hydropower system design which accounts only for
annual revenues and cost, designs with the highest benefit / cost ratios do not
necessarily perform well in terms of dry year revenue. They also show less robustness
to both climate change (and associated drying) and to evolving financial conditions
than the designs that do better balance average annual revenue with dry year revenue

How to cite: Yildiz, V., Rougé, C., and Brown, S.: Application Multi-Objective Robust Decision-Making to the Design of Run-ofRiver Hydropower Plants, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12887, https://doi.org/10.5194/egusphere-egu21-12887, 2021.

Small hydropower plants (SHPPs) are subject to multiple uncertainties and complexities, despite their limited scale. These uncertainties are often ignored in the typical engineering practice, which results in risky design. As this type of renewable energy rapidly penetrates the electricity mix, the impacts of their uncertainties, exogenous and endogenous, become critical. In this vein, we develop a stochastic simulation-optimization framework tailored for small hydropower plants. First, we investigate the underlying multicriteria design problem and its peculiarities, in order to determine a best-compromise performance metric that ensures efficient and effective optimizations. Next, we adjust to the optimal design problem a modular uncertainty assessment procedure. This combines statistical and stochastic approaches to quantify the uncertainty of the inflow process per se, the associated input data, the initial selection of efficiency curves for the turbine mixing in the design phase, as well as the drop of efficiency due to aging effects. Overall, we propose a holistic framework for the optimal design of SHPPs, highlighting the added value of considering the stochasticity of input processes and parameters. The novelty of this approach is the transition from the conventional to the uncertainty-aware design; from the unique value to Pareto-optimality, and finally to the reliability of the expected performance, in terms of investment costs, hydropower production, and associated revenues.

How to cite: Sakki, G.-K., Tsoukalas, I., Kossieris, P., and Efstratiadis, A.: A dilemma of small hydropower plants: Design with uncertainty or uncertainty within design?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2398, https://doi.org/10.5194/egusphere-egu21-2398, 2021.

The functionality of a renewable electricity system in Europe depends on long-term climate variations, uneven spatiotemporal distribution of renewable energy, and constraints of storage and electric transmission. In particular, hydropower offers a large capacity for energy storage and production flexibility, but only stands for a minor part of the total energy potential. Here we explored the spatial and temporal power variance of a combined system consisting of wind-, solar- and hydropower availability for a 35-year period based on historical hydro-meteorological data from large parts of Europe. A spectral analysis of these historical time-series shows that spatiotemporal coordination within the power system can potentially contribute with a “virtual” energy storage capacity that is many times higher than the actual energy storage capacity contained in the existing hydropower reservoirs in Europe. Such virtual energy storage capacity implies reduced water storage demand, hence, indirectly contributes to reduced constraints of the food-water-energy nexus also in a wider system perspective. This study focused on the theoretical maximum potential for virtual energy storage, but the feasibility of this potential is limited by the uncertainty associated with production optimization and the meteorologic forecasts of future energy availability.

How to cite: Wörman, A., Mewes, D., Riml, J., Bertacchi-Uvo, C., and Pechlivanidis, I.: Virtual energy storage-gain due to spatiotemporal coordination of wind-, solar- and hydropower over Europe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14118, https://doi.org/10.5194/egusphere-egu21-14118, 2021.

Multi-sector modelling frameworks are fundamental platforms for exploring the complex interactions between the water and energy sectors. While acknowledging the pivotal role of hydropower within the energy system, it is essential to understand the feedback mechanisms between power and water systems to guide the design of hydropower operations and enhance water-energy management strategies. With this in mind, we developed a modelling framework hinged on a bidirectional coupling between water and power system models. We simulate the constraints imposed by water availability on grid operations as well as the feedback between the state of the energy and water systems. For example, the framework explicitly accounts for conditions of hydropower oversupply, during which part of the water could be stored in reservoirs or allocated to other sectors. The flexibility added to the system gives operators control over desired reservoirs, and allows the system to exploit the benefits warranted by a more efficient use of renewable energy. We evaluate the framework on a real-world case study based on the Cambodian grid, which relies on hydro, solar, and thermoelectric resources. In our analysis, we demonstrate that managing hydropower reservoirs with the feedback mechanism in mind allows us to improve system’s performance—evaluated in terms of power production costs and CO₂ emissions. Overall, our work contributes a novel modelling tool for climate-water-energy nexus studies, working towards an optimal integration of hydropower and other renewable energy sources into power systems.

How to cite: Koh, R., Kern, J., Chowdhury, A. K., and Galelli, S.: Valuing feedback mechanisms between water and energy systems in hydropower networks, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9919, https://doi.org/10.5194/egusphere-egu21-9919, 2021.

The Western U.S. relies heavily on hundreds of water-dependent power plants, with hydropower and fresh surface water dependent thermo-electric plants accounting for over 60% of generating capacity.  The Western Interconnect overlays 11 States, over three different electricity market areas, and 9 large river basins with tens of unconnected watersheds as well as tens of coordinated watersheds. Such complexity requires computational tradeoffs for the representation of the water-energy dependencies, including a centrally controlled unit commitment and economic dispatch as well as an offline representation of hydropower’s availability and operations. Benchmark hydropower representations for application to resource adequacy studies include i) fixed daily time series and ii) a parameterized monthly representation involving three constraints: a monthly energy target, and hourly minimum and maximum generation. The representations are derived for one year and under average water conditions. We propose a large-scale approach to represent medium-term (weekly) hydropower flexibility for grid-scale reliability studies, as driven by weekly water availability. Using a combination of hydrological models, reservoir operation schemes, and statistical tools, we develop datasets of hydropower plant-specific weekly energy targets, with weekly minimum and maximum hourly generation, for multiple years with varying water conditions. The assumption – and computational tradeoff - is that water availability guides the weekly operations and range of daily operations, leaving enough flexibility for the power system optimization to accommodate intra-day, week days and weekends load variations. We present the hydropower datasets and evaluate how this new representation influences the simulated contribution of hydropower to grid operations as part of resource adequacy and reliability studies.

How to cite: Voisin, N., Oikonomou, K., Turner, S., Clement, M., Magee, T., Zagona, E., Ploussard, Q., and Veselka, T.: A new representation of conventional hydropower in unit commitment economic dispatch models to support resource adequacy and reliability studies, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1843, https://doi.org/10.5194/egusphere-egu21-1843, 2021.

The evaluation of the stakeholders’ perception of new hydropower projects is essential for assessing public acceptance, ensuring local involvement, and identifying feasible and desirable changes towards sustainable development. This study uses the concept of causal diagrams (CD) to identify the individual perspectives of stakeholders of two new hydropower projects, one in Switzerland (Val d’Ambra project) and one in Iceland (Hvammvirkjun project). For this purpose, semi-structured interviews with relevant stakeholders were conducted, which were then categorized into 5 interest groups. Using the software Atlas.ti, we identified and sequenced the perceived causality of impact pathways of the two projects. The results are exposed in two series of 10 topical causal networks, and two aggregated diagrams. For each case, CDs expose the complexity of multi-sequenced causalities between elements of a very heterogeneous nature, as expected and reported by stakeholders. This approach enables the identification of inter- and intra-group conflicting perspectives, and perceived uncertainties, concerning both subjectives matters along with much more tangible and predictable aspects. Our method enables the identification of areas where further research or better transfer of information between stakeholders is required. It also exposes how hydropower impacts can differ in time and space, when in one case study, intracommunity tensions and conflicts were identified at the earliest project stage, along with psychological distress of some local residents. Based on the presented CD, we conclude that this method can facilitate communication and problem-solving in complex social-environmental situations amid multiple stakeholder categories, which heterogeneity should not be underestimated.

This research has been published in Energy Research and Social Science:

https://www.sciencedirect.com/science/article/pii/S2214629620304473

How to cite: Voegeli, G. and Finger, D. C.: Conflicting interests over hydropower: Identifying and representing stakeholder perspectives on new projects using causal mapping., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16362, https://doi.org/10.5194/egusphere-egu21-16362, 2021.

Hydropower provides a low-carbon solution to a large portion of Sweden’s energy demand, which is increasingly important in order to combat climate change. However, associated flow regulations introduce variability of the flow on the daily, weekly and seasonal time scales, driven by the varying energy demand. Additional variability is introduced when compensating for the shifting wind energy production. The Water framework directive requires all EU member states to evaluate the ecological impact from anthropogenic activities, such as hydropower. Ecological impacts must also be assessed when all hydropower permissions in Sweden are renewed over the coming 20 years. Because different species are sensitive to different longevity of high- and low-flow periods, it is important to understand the introduced variability of flow in terms of its dominant periods, and how quickly these perturbations are attenuated downstream of regulations.

In this work, time-series of flow from hydrological simulations with HYPE are analyzed with the Fourier transform to examine the amplitudes of perturbations of different periods, and their decay downstream of hydropower stations. HYPE is a catchment-based model that simulates rainfall-runoff as well as water quality processes. The Swedish model application has been developed over the past decade and covers all of Sweden. Seasonal regulations are modeled with calibrated input parameters, whereas short-term regulations are introduced with station updates from observations that are available at or close to the majority of hydropower regulations. Very high accuracy has been proven between the updated sub-catchments. This, together with a verified model for natural flow, gives us a unique opportunity to study the impact of hydropower on dominant periods and their decay over the entire country, as well as the mechanisms that govern this decay.

In many sub-catchments, especially in large regulated rivers in northern Sweden, Fourier analysis of daily time series results in dominance of the 7-day period. The exponential decay rate of this and other modes is presented for all Sweden and analyzed in terms of land use and other parameters. Short periods decay faster than long ones. Periods of one month or longer are amplified in the downstream direction in most of Sweden.

Apart from aid in ecological assessments, our analysis can be used to introduce short-term regulations in hydrological simulators, for either deterministic forecasts (the 7-day mode typically has a minimum value on Sundays) or for stochastic seasonal forecasts where it will impact indicators such as the number of days below or above a threshold.

How to cite: Elenius, M. and Lindström, G.: Introduced flow variability and its propagation downstream of hydropower stations in Sweden, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14166, https://doi.org/10.5194/egusphere-egu21-14166, 2021.

The penetration of intermittent renewable energy sources (RES) such as solar PV and wind is rapidly growing in many countries. Due to the RES intermittency, it is becoming increasingly difficult to manage the balance between energy generation and demand at any time. In this context, it is necessary to use other energy generation technologies, such as hydropower, a controllable renewable source that may already be available as a means to provide energy balance. Hydropower, through hydropeaking, is considered a flexible solution to this challenge as it can quickly help manage the fluctuations in the generation-demand balance due to the highly RES intermittency. Hydropeaking plants usually supply energy at maximum capacity during on-peak periods, whereas they run at low power output during off-peak periods. However, this operating scheme leads to heavy hydrological alteration downstream of the hydropower plants because of short-term fluctuations in turbined flows motivated by the integration of intermittent RES. In this work, an integrated and spatially distributed river-basin and energy system co-simulation model is used to evaluate the hydrological alteration produced by varying penetration levels of intermittent RES in Ghana's national power system. Results show that the spatial and temporal distribution of hydrological alteration, correlated with intermittent RES penetration levels, varies according to the hydropower plants' location within the power system and the intermittent renewable resources seasonality throughout the year.

How to cite: Gonzalez, J. M., Tomlinson, J., Martínez-Ceseña, E. A., Obuobie, E., Panteli, M., and Harou, J.: Risk of increased hydrological alteration due to penetration of intermittent renewable energy generation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8543, https://doi.org/10.5194/egusphere-egu21-8543, 2021.

The quest for a lower operational cost of daily scheduling cascade hydropower generation is subject to imperfections in the representation of reality due to it multiple uncertainties. One way to reduce uncertainties is to improve the representation of the hydrological processes and the operation of the electrical components of the system. A complementary strategy to deal with the difficulty of representing hydrological processes is to move from a deterministic approach to a probabilistic approach considering scenarios. These two proposals usually lead to high-dimensional problems that require Mixed Integer Nonlinear Programming for solving. This work proposes the use of simple Constructive Heuristics to solve this kind of problem guarding the non-linear formulations. The GAMS software was used to represent a hydropower cascade with individualized turbine with multiple inflow scenarios as presented in the formulation bellow. For each scenario s:

Z is the objective function. a is a coefficient considered in the proposed Constructive Heuristic. Q is the outflow of the turbine. H is the set of hydropower plants. U is the set of turbines. t is the set of hours considered in the problem. s is the set of considered scenarios. α is a conversion term. τ is the time delay of the hydropower plants. β is the set of hydropower plants located upstream of a hydropower plant. I is the incremental flow. V is the volume of the reservoir. D is the power demand. Pg is power generated per turbine. Pmin and Pmax are the thresholds of power of the turbine. Pst is the net power generated by the turbine. Pgg are the electrical losses of the generator. Pmt are the mechanical losses of the generator. f1, f2, f3, f4, f5, f6, f7 and f8 are functions. HH is the hydraulic net head. UP is the upstream level. Down is the downstream level. Lo are the hydraulic and mechanical losses. ρ is the turbine efficiency curve. The CONOPT solver was selected for it resolution. The  Constructive Heuristic scheme considers a continuous variable “a” to represent if the turbine is opened or closed. After the first resolution of the problem with Nonlinear Programming, the integer part number of turbines for each power plant is fixed. The fractional part is tested for all the possible configurations and the best outcome is chosen. The results of the Constructive Heuristic were compared with other similar works with perfect correspondence. The system was tested for 51 ECMWF precipitation forecast scenarios as input of the hydrologic model MGB (Large Basin Model) with coherent results. The proposal is a feasible approach to reach unique optimal solutions for high-dimensional non-linear problems considering integer variables.

How to cite: Firmo Kazay, D. and Mendonça da Rocha, C. R.: A Constructive Heuristic approach for solving Mixed Integer Nonlinear cascade optimization considering an hydrological uncertainty model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2903, https://doi.org/10.5194/egusphere-egu21-2903, 2021.