Hydropower Operation Research Articles

Review on assessing climate-change-induced risks to run-of-river hydropower infrastructure in Nepal

Abstract. Nepal annually invests millions of dollars in hydropower development, with a substantial portion of these funds allocated to civil infrastructure. Climate change, which impacts geological and hydrological conditions, poses a threat to civil components throughout hydropower project construction and operation. This causes budget overruns, project delays, and adverse consequences for society and the environment, ultimately resulting in multimillion-dollar losses. The identification of risk factors and their underlying causes, stemming from the impacts of climate change, constitutes a fundamental aspect of this study. This critical analysis primarily draws upon extensive literature reviews to pinpoint these factors (risk factors arising from climate change), emphasizing their economic and human impacts. This paper highlights the risks to run-of-river hydropower infrastructures in Nepal. The findings of the study can be used to develop and implement adaptation strategies to mitigate the risks posed by climate change to Nepal's vital hydropower sector.

Measurement of the Macro-Efficiency of Hydropower Plants in Nigeria Using Transfer Functions and Data Envelopment Analysis

Persistent power challenges plague Nigeria, with hydropower constituting a vital component of the country's energy mix. This study assessed the macro efficiency of three operational hydropower plants in Nigeria using three distinct methods: Constant Return to Scale Method of Data Envelopment Analysis (DEA-CRS), Input-oriented Variable Return to Scale Method of Data Envelopment Analysis (DEA-VRS), and System's Coefficient of Performance Methodology (SCOPM) employing transfer functions. Input factors included man-hours, plant capacity, and water flow, while energy generation was the output. DEA-VRS revealed Shiroro and Jebba as the most efficient, while Kainji was the least. DEA-CRS indicated Shiroro as the most efficient and Kainji as the least. SCOPM indicated Jebba as the most efficient and Shiroro as the least. SCOPM's higher standard deviation suggests better discrimination among plants. DEA-VRS result showed that the scale of the biggest power plant, Kainji, has some effects on its efficiency. The study recommends the adoption of SCOPM by electricity utility operators and regulators for performance improvement due to its robust results. The contributions of the research are significant because of the novel application of DEA and SCOPM to measure the efficiency of power plants in Nigeria, and SCOPM for measurement of macro efficiency of power plants.

The impact of hydroclimate-driven periodic runoff on hydropower production and management

This study evaluates the impact of hydroclimate-driven periodic runoff on hydropower operations and production, with a focus on how the forecasted biennial periodicity of runoff time series could affect the efficiency of hydropower generation. Hydrologic stochastic processes are utilized to forecast long-term runoff, and seven hydroclimate scenarios are developed to be input into a production management model, allowing for an analysis of how periodic hydroclimate variations influence hydropower management and output. The results reveal that the biennial alternation between wet and dry years is a key factor affecting hydropower operations in the Dalälven River Basin. Notable differences between wet- and dry-year scenarios were observed in terms of power efficiency, production output, and forecasting accuracy. Operating hydropower systems based on dry-year runoff forecasts in wet years results in a 1.63% decrease in production efficiency and a reduction of 9,104 MWh in power generation. Conversely, applying wet-year forecasts in dry years slightly boosts production efficiency by 0.31% and increases power generation by 7,832 MWh. Scenarios that adhere to biennial periodicity offer the highest forecasting accuracy, particularly when applying dry-year forecasts in dry years in winter and spring, which produce the most precise predictions. In contrast, using dry-year forecasts in wet years results in the lowest forecasting accuracy.

Defining and Mitigating Flow Instabilities in Open Channels Subjected to Hydropower Operation: Formulations and Experiments

A thorough literature review was conducted on the effects of free surface oscillation in open channels, highlighting the risks of the occurrence of positive and negative surge waves that can lead to overtopping. Experimental analyses were developed to focus on the instability of the flow due to constrictions, gate blockages, and the start-up and shutdown of hydropower plants. A forebay at the downstream end of a tunnel or canal provides the right conditions for the penstock inlet and regulates the temporary demand of the turbines. In tests with a flow of 60 to 100 m3/h, the effects of a gradually and rapidly varying flow in the free surface profile were analyzed. The specific energy and total momentum are used in the mathematical characterization of the boundaries along the free surface water profile. A sudden turbine stoppage or a sudden gate or valve closure can lead to hydraulic drilling and overtopping of the infrastructure wall. At the same time, a PID controller, if programmed appropriately, can reduce flooding by 20–40%. Flooding is limited to 0.8 m from an initial amplitude of 2 m, with a dissipation wave time of between 25 and 5 s, depending on the flow conditions and the parameters of the PID characteristics.

Environmental flows in a future climate: Balancing hydropower production and ecosystem rehabilitation in the Ume River system, Sweden

Hydropower is central to renewable electricity systems, but degrades ecosystems, calling for environmental flow schemes to enhance the ecological status of river systems. Environmental flow assessments need to account for climate change, since climate-driven changes in runoff affect both hydropower operation and riverine ecosystems. Here, we quantify expected changes in hydropower production and environmental benefits of introducing environmental flows in a large regulated river system in northern Sweden in a future climate. Compared with the hydrology of 1981–2010, runoff is projected to increase with climatic conditions projected for 2040, leading to a 2.2 % increase in hydropower production with present rules for turbine and reservoir operation. Implementing environmental flows will result in lower hydropower production losses in with the 2040 climate than at present: Introducing restrictions against zero flow events, discharge to technical fishways and bypassed reaches throughout the year (with seasonal flow variation), as well as having more natural water-level variation in all run-of-river impoundments, would reduce annual hydropower production with 3.5 % with present conditions, and by 3.3 % in 2040. At the same time, the net effect of higher runoff and introducing environmental flows means that the annual hydropower production in the 2040 climate would be only 0.8 % lower compared to 1981–2010. In all scenarios, reservoir filling degree in 2040 was projected to increase compared to scenarios for 1981–2010, and flow requirements were met for both environmental flows and hydropower production over an 83-year scenario-based time series. This study demonstrates the feasibility of introducing environmental flow actions in Sweden, and other regions where increases in runoff are projected, with sustained hydropower production, having large benefits for riverine biodiversity and enhancing resilience of riverine ecosystems to climate change. For this to be successful, collaboration among stakeholders in riverine management is needed.

The role of hydropower in decarbonisation scenarios

An increased penetration of renewable energy sources is essential for the energy transition. A major role will be played by wind and solar, as they are widely available. Hydropower is another crucial resource, currently covering large shares of power generation (e.g., Norway, Italy, Brazil). Despite little expected growth, in a context of increasing electrification, improved integration of hydropower can play a critical role thanks to programmable operation. This work addresses the modelling of hydropower flexibility in energy system models and analyses the impact of hydropower operation on CO2 emission-constrained scenarios. To implement the study, a detailed dataset of the Italian programmable hydroelectric plants is created, using open-source information, covering location, rated power, and storage capacity. Inflow timeseries are derived from historical operational data. These new sets of data are employed in OMNI-ES (a multi-node, multi-sector, and multi-vector energy system model) to study optimal configurations and operation of the Italian energy system in decarbonisation scenarios, such as net-zero-CO2 and Fit-for-55 targets. Considering different operational strategies and multiple historical reference years (impacting the inflow), results demonstrate significant changes in hydropower behaviour and highlight its relevance as zero-carbon resource in terms of both power and energy output, influencing the installation of other technologies.

Climate-driven shifts in freshwater biodiversity will impact mitigation costs for hydropower

Climate change is forecasted to drastically alter freshwater fish and mussel species distribution. Hydropower dam reservoirs, which modify downstream thermal regimes, may interact with climate change's impact on species distribution. This distribution shift may feedback, affecting hydropower operation costs through environmental compliance. We investigated how freshwater species distribution will shift due to climate change and hydropower reservoirs in the conterminous United States (CONUS), and how this will affect biodiversity mitigation costs for privately-owned hydropower plants. In general, using environmental niche modeling, we found that climate change increased the range of both freshwater fish and mussel species on average. For fish, this was mainly due to the expanded habitat for warm-water and cool-water fish species despite the diminish in habitat for cold-water species. Compared to climate change, thermal stratification of hydropower reservoirs had a small impact on the future range changes of these species in the tailwaters but showed an interaction with the effect of climate change on species range. Geographically, we projected an increase of species richness in the west and a decrease in the central and east of CONUS for fish, while projecting uniform increase for mussels. With this shift in species distribution, we estimated that the Northwest region will face the largest increase in mitigation cost, while the majority of plants in the Southeast will experience a decrease in cost.

Large-scale hydropower dispatching system based on cloud platform and its key technologies

In the past decade, the rapid expansion of hydropower capacity in China brings challenges to hydropower dispatching in data management and operation scheduling. In data management, the scale of hydropower operation data increases explosively, presenting typical big data features. In operation scheduling, the optimization of hydropower system operations is a high-dimension, nonconvex, and nonlinear problem. Conventional optimization methods encounter the “dimensionality disaster”, and cannot solve the scheduling problem efficiently. To deal with these challenges, by analyzing the data characteristics and operation scheduling requirements, this paper develops a large-scale hydropower dispatching system based on the cloud platform. The dispatching system consists of four layers: data access layer, cloud platform layer, data sharing layer, and application layer, which has good scalability and flexibility in data management and operation scheduling. In the application layer, key technologies based on the big data and cloud computing resources of the dispatching system are proposed to carry out the optimal operation of hydropower systems, including distributed parallel dynamic programming (DPDP) for long-/medium-term scheduling and data mining-based method (DMM) for short-term scheduling. Finally, the dispatching system is applied to the operation of hydropower systems in southwest China. Results indicate that: 1) The developed dispatching system is capable of processing 18 million data records per day, with a peak processing speed of 10,000 data requests per second, fulfilling the requirements for hydropower dispatching. 2) In long-term generation scheduling, under varying levels of runoff and plant scales, DPDP has demonstrated a remarkable reduction in computing time compared to dynamic programming, obtaining the same optimal solution with over 90 % less computational time. 3) In short-term peak shaving operation, on typical dry and wet days, the computing time of DMM is 7.2 s and 7.5 s, respectively, far less than the time of mixed-integer linear programming, and the maximum residual load obtained by DMM is lower than historical observations, indicating its effectiveness.

Modelling long-term operational dynamics of grid-connected hydro- photovoltaic hybrid systems

The development of variable renewable energy sources (VRESs), such as wind and solar photovoltaic (PV), has become a strategic choice for ensuring the security of electricity supplies and the decarbonization of power systems. The hybridization of hydropower with VRESs is an important measure for guaranteeing the smooth and cost-effective integration of VRESs into the power system. However, the highly variable weather- and climate-driven spatial and temporal fluctuations in VRES performance have significant potential to affect the optimal trajectory of hydropower operations. Therefore, it is essential to understand how hydropower responds to VRESs over long-term horizons, thereby allowing informed operation decisions to be made for hybrid generation systems (HGSs). In this study, a long- and short-term nested operation model is developed for hydropower operations considering PV integration. Specifically, the long-term model determines the day-by-day hydropower production over many years, and the short-term model simulates the day-ahead generation scheduling and real-time operation processes of the HGS. Performance metrics are established for evaluating the complementary operation in comparison with separate operation of hydropower and PV plants. China's two representative hydro-PV HGSs (Zhongyu and Longyangxia) are selected as case studies. The results indicate that the hybrid generation of hydropower and PV could, on average, increase total electricity generation by 11.33 %, reduce the load loss rate by 9.31 %, and decrease the PV curtailment rate by 36.60 %. However, hydro-PV hybridization may lead to an increase of 9.22 % in the water spillage rate and a decrease of 0.094 kWh/m3 in the water–electricity conversion coefficient. Therefore, hybrid generation of hydropower and PV could further enhance energy yield and supply reliability. Also, the importance of improving hydropower flexibility is highlighted.

Assessing the social life cycle impacts of the Spanish electricity mix: A decadal analysis

Power generation systems are crucial to national energy transitions, such as Spain's, which stands as a notable example. However, this profound transformation could have multifaceted implications, leading to unintended consequences on society. The present work is the first to understand the social impacts of the Spanish power sector and their technology supply chains using the social life cycle sssessment methodology. The functional unit is 1 kWh of electricity produced by the technologies in the Spanish electricity mix. A cradle-to-gate approach is taken using a supply chain protocol to complete the system boundaries. The social life cycle inventory, comprising data on national suppliers, working hours and social flows, was integrated into the PSILCA database to derive the social profile of each power technology and, consequently, to obtain a comprehensive view of the Spanish power sector. The results reveal that social impact associated with the Spanish electricity mix has increased or remained stable from 2010 to 2022. Analysis of four indicators (child labour, contribution of the sector to the economic development, frequency of forced labour and women in the sectoral labour force) reveals significant differences, highlighting three main social hotspots: i) solar PV panel production in East and Southeast Asia, particularly China, ii) natural gas extraction and refining in North Africa, concentrated in Algeria, for natural gas combined cycle and cogeneration plants, and iii) construction and operation of hydropower and nuclear plants in Spain. This study demonstrates that current strategies for Spain's power sector transition may not guarantee a favourable social performance, emphasizing the need for balanced environmental and social considerations in energy policy making, aligned with the Sustainable Development Goals.

New Technique to enhance Hybrid Renewable Energy Resources Operational Flexibility and Reliability

In this research four integrated strategies proposed and discussed for increasing the flexibility of hydropower operations. This initiative seeks to understand, enable, and improve the contribution of hydropower, including pumped storage hydropower (PSH) to reliability, resilience, and integration in the rapidly evolving U.S. electricity system. Hydropower’s flexibility is central to enhancing all these contributions. Four KFA (key focus areas) listed below to maintain and reliable operations. These KFAs will develop a suite of advancements that improve hydropower flexibility at multiple scales: improved components within the plant, improved hybridized capabilities at the plant interconnection, and improved operations across the fleet.[1],[2],[3] 1. HSE in Hydropower Hybrids 2. Reliable productivity 3. Technologies to Increase Flexibility 4. Operational Flexibility Key words. Novelty, Corrective Maintenance and Preventive maintenance and Intelligent module.

Distributed economic model predictive control for the joint energy dispatch of wind farms and run-of-the-river hydropower plants

This study addresses the energy dispatch problem of a virtual power plant (VPP) acting as a price-tacker in the day-ahead electricity market. The VPP comprises wind farms and a cascade of run-of-the-river hydropower plants. Even if the storage capacity of the cascade is limited, it can still be exploited to compensate the variability of wind. This implies dispatching the water reservoirs near to real-time, while accounting for complex constraints and various sources of uncertainty. To this aim, we present a control strategy based on economic model predictive control (MPC), which is then decomposed using the auxiliary problem principle. As a distinctive feature, the proposed algorithm is fully-distributed, i.e. no central coordinator is required. Compared to centralized MPC, the distributed algorithm brings a ∼10% reduction in the average execution time of the controller. Moreover, the joint operation of hydropower and wind is shown to enhance the economic value of both assets.

Research on the starting-up process of a prototype reversible pump turbine with misaligned guide vanes: An energy loss analysis

With fossil fuel depletion and rising demand for renewable energy, reversible pump turbines (RPTs) are crucial for balancing energy supply. Understanding the dynamics of RPTs during starting-up is essential for optimal performance and stability in renewable energy systems. The unique “S" curve of RPTs can lead to instability under transient conditions. This study aimed to investigate the impacts of misaligned guide vanes (MGV) devices on prototype RPT stability, pressure pulsation, and performance improvement during the starting-up process. Using CFD simulation, flow characteristics and energy loss during start-up were analyzed and validated against experimental data. The results show that MGV enhances stability but induces significant energy loss. The analysis of entropy production, vorticity transport, and pressure fluctuation revealed high energy loss regions and the evolution of vortices during the starting-up process. This study provides new insights into hydrodynamic challenges and energy loss with MGV in prototype RPT start-up, with implications for optimizing pumped storage hydropower operations. Overall, this study has valuable engineering significance for the development and application of RPT in renewable energy systems.

Hydrogen production to combat power surpluses in hybrid hydro–wind–photovoltaic power systems

The complementary operation of hydropower, photovoltaic, and wind power can promote the integration of renewable energy resources into the grid. However, the competition of power transmission channels among multiple energy raises surpluses significantly. This study equips a hydrogen production plant for the hydro–wind–PV hybrid system to utilize the power surplus. First, a multi-scale nested joint operation model that considers both long-term and short-term operation strategies is proposed to simulate the operation process of the hybrid system. Then, the potential surplus of the system is evaluated and used as the power source of the hydrogen production plant. Lastly, the optimal hydrogen production plant size is determined based on economic and technical analysis. A case study is performed with the Yalong River basin of China. The results show that (McElroy and Chen, 2017 (1)) The deployment of a 260 MW hydrogen production system has the potential to boost the annual power generation benefit of the hybrid system by 610 million CNY； (2) The fluctuation of hydropower station output is effectively reduced, subsequently mitigating operational risks. Especially during flood season, the power variation coefficient experiences a notable decrease of approximately 75%； Liu and Xu (2022) (3) The deployment of hydrogen production plants is more economically feasible than expanding power transmission channels, particularly when considering long-distance power transmission. Furthermore, given that hydrogen production plants frequently operate under fluctuating power conditions, the electrolyzers and compressors must exhibit prompt responsiveness to these power variations.

Forecasting daily rainfall in a humid subtropical area: an innovative machine learning approach

ABSTRACT Hydrological modeling is one of the most complicated tasks in sustainable water resources management, particularly in terms of predicting rainfall. Predicting rainfall is critical to build a sustainable society in terms of hydropower operations, agricultural planning, and flood control. In this study, a hybrid model based on the integration of k-nearest neighbor (KNN), XGBoost (XGB), decision tree (DCT), and Random Forest (RF) has been developed and implemented for forecasting daily rainfall for the first time at Sydney airport, Australia. Daily rainfall, temperature, evaporation, and humidity have been selected as input parameters. Three statistical measurements, namely, root mean square error (RMSE), coefficient of determination (R2), mean absolute error (MAE), and Normalized Root Mean Square Error (NRMSE) have been utilized in order to check the accuracy of the proposed model. A sensitivity analysis was conducted, and the results indicated that for the purpose of prediction, the temperature, humidity, and evaporation were highly sensitive to the rainfall data. According to the results, the developed hybrid model was capable of predicting daily rainfall with high performance for both training and testing parts with RMSE = 0.124, R2 = 0.999, MAE = 0.007, NRMSE = 0.04 and RMSE = 1.246, R2 = 0.991, MAE = 0.109, NRMSE = 0.339, respectively.

Optimal Scheduling of a Cascade Hydropower Energy Storage System for Solar and Wind Energy Accommodation

The massive grid integration of renewable energy necessitates frequent and rapid response of hydropower output, which has brought enormous challenges to the hydropower operation and new opportunities for hydropower development. To investigate feasible solutions for complementary systems to cope with the energy transition in the context of the constantly changing role of the hydropower plant and the rapid evolution of wind and solar power, the short-term coordinated scheduling model is developed for the wind–solar–hydro hybrid pumped storage (WSHPS) system with peak shaving operation. The effects of different reservoir inflow conditions, different wind and solar power forecast output, and installed capacity of pumping station on the performance of WSHPS system are analyzed. The results show that compared with the wind–solar–hydro hybrid (WSH) system, the total power generation of the WSHPS system in the dry, normal, and wet year increased by 10.69%, 11.40%, and 11.27% respectively. The solar curtailment decreased by 68.97%, 61.61%, and 48.43%, respectively, and the wind curtailment decreased by 76.14%, 58.48%, and 50.91%, respectively. The high proportion of wind and solar energy connected to the grid in summer leads to large net load fluctuations and serious energy curtailment. The increase in the installed capacity of the pumping station will promote the consumption of wind and solar energy in the WSHPS system. The model proposed in this paper can improve the operational flexibility of hydropower station and promote the consumption of wind and solar energy, which provides a reference for the research of cascade hydropower energy storage system.

River systems under peaked stress

The change in the global energy production mix towards variable renewable energy sources requires efficient utilization of regulated rivers to optimise hydropower operations meet the needs of a changing energy market. However, the flexible operation of hydropower plants causes non-natural, sub-daily fluctuating flows in the receiving water bodies, often referred to as ‘hydropeaking’. Drastic changes in sub-daily flow regimes undermine attempts to improve river system health. Environmental decision makers, including permitting authorities and river basin managers facing the intense and increasing pressure on river environments, should consider ecosystem services and biodiversity issues more thoroughly. The need for research innovations in hydropeaking operation design to fulfil both the water and energy security responsibilities of hydropower is highlighted. Our paper outlines optimized hydropeaking design as a future research direction to help researchers, managers, and decision-makers prioritize actions that could enable better integration of river science and energy system planning. The goal of this is to find a balanced hydropower operation strategy.

Value of long-term inflow forecast for hydropower operation: A case study in a low forecast precision region

Many studies have evaluated the value of long-term inflow forecast for hydropower operation in high-precision watersheds and explored the impact of forecast uncertainty on hydropower benefits. However, few of them focuses on the low-accuracy regions and the specific impact of forecast errors on hydropower benefits. Taking Hunjiang cascaded system in China as an example, this study investigated the value of low accuracy long-term inflow forecast for hydropower operation, revealed the influence mechanism of forecast errors on hydropower benefits, and determined the critical threshold for accuracy of beneficial forecast. Results show that low accuracy forecast but higher than critical threshold can increase hydropower generation. Hunjiang has a low accuracy long-term forecast with qualified rate being 30–40 %, but annual hydropower generation can be increased by 14.86–29.58 million kWh. The influence mechanism of forecast errors on hydropower operation presents three typical scenarios, two of which are harmless. One is that the error tolerance of operation rules can avoid some decision-making errors; the other one is that when current misreporting is consistent with the inflow in a longer lead time, the misreporting may instead be beneficial. We conclude that low accuracy long-term forecast is valuable but higher accuracy brings higher benefits.

Analysis of Surrounding Rock Stability and Supporting Structure Effect Based on a Hydropower Station Underground Cavern

The surrounding rock stability is a main difficult problem in the hydropower station construction and operation. Taking one hydropower station as object, FLAC 3D numerical simulation software was used to calculate the changes in surrounding rock failure zone distribution, surrounding rock strain, and block safety factor before and after supporting. The stability of the surrounding rock after excavation was analyzed and effect of the supporting structure was also evaluated. Finding that: the supporting structure can effectively improve the stability of surrounding rock. After supporting, the failure zone range, the deformation of surrounding rock, and the internal force of the supporting structure all reduced, while the safety factor of the block improved. Due to the effect of bolt, the deformation of the surrounding rock transformed from plastic to elastic, and the rebound zone of the surrounding rock increased, while the plastic and failure zone reduced. The depth of the failure zone on the downstream side is greater than that on the upstream side, and a large number of cracking zones are distributed on the downstream side. At the same time, due to the influence of cracks and geological fracture, the failure of surrounding rock around the main powerhouse is higher than that around the tailgate chamber higher than that in the main transformer chamber. The safety factor of the key blocks distributed around the main transformer chamber and the main power house improved, the sliding form of some blocks transformed from collapse to single-surface sliding.

Assessment of Fish Habitats and Suitable Ecological Flow under Hydropower Operation

Hydropower operations significantly alter the natural hydrological conditions of rivers, exerting adverse effects on riverine ecosystems. Accurate identification of fish habitats under hydropower operation and maintaining suitable ecological flow are crucial for riverine ecological conservation and water resource management. Coreius guichenoti was selected as the target species and the Yibin reach of the downstream Jinsha River was selected as the studied river reach. Subsequently, Weighted Usable Area (WUA) and Habitat Connectivity Index (HCI) were employed to comparatively analyze the habitat quantity and quality before and after the construction and operation of the Xiangjiaba hydropower station, namely the natural period (1991–2005), construction period (2006–2014), and operation period (2015–2020). Finally, correlations between WUA, HCI, and flow were established to determine the optimal ecological flow corresponding to optimal fish habitats. The results indicate that the average WUA and HCI during the construction period are similar to the natural period. In comparison to the natural period, the average WUA decreases by 9.2%, and the average HCI decreases by 0.05 during the operation period. It is determined that the habitat conditions are optimal when the flow is between 3000 and 5000 m3/s. After further refining the flow scenarios, the suitable ecological flow is determined to be 3500 m3/s. This study can provide a scientific basis for the water resources management in the Jinsha River and contribute to the field of riverine ecological conservation and restoration.