•Propose operation strategies of the hybrid pumped storage-wind-photovoltaic system.•Analyze the additional benefits of the pumping station to the hybrid system.•Evaluate the system performance under ...different inflows and electricity prices.
The integration of the pumping station between conventional cascade hydropower stations to form the hybrid pumped storage has the potential to increase the hydropower’s flexibility and promote the consumption of renewable energy into the power grid. However, the conversion of electricity and water potential energy between the pumping station, hydropower, wind power, and photovoltaic poses challenges to the operation of the multi-energy sources. This study explores the complementary operation of the hybrid pumped storage-wind-photovoltaic system at different time scales and evaluates the economic benefits and energy efficiency of the system. 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 different operation strategies are set considering the operation time scale of the pumping station. The case study in the Wujiang River, China, demonstrates that the hybrid pumped storage can increase power generation profit and decrease energy curtailment, and consideration of long-term scale and short-term scale nested operation can further increase the system’s profit. The pumping station can increase the amount of available water during the dry season on a long-term scale and store excess electricity from renewables and the grid on a short-term scale. The benefits of hybrid pumped storage are further validated under different reservoir inflows and electricity prices.
Abstract
The relationship between aquatic and avian predators and prey is a fundamental process that influences the ecological dynamics of freshwater communities; a landscape of fear underpins ...spatial and temporal habitat use of prey, i.e., non‐consumptive predation effects. For example, complex marginal vegetation and other natural in‐river refuges are known to be important for prey to manage predation risk and predators must alter their behaviour in response to habitat patches prey occupy. However, it is unclear how prey respond to predators, and vice versa, in heavily modified degraded lowland rivers with a high degree of river maintenance measures; a component critical for flood risk management globally. Such modifications could lead to prey seeking refuge at hazardous anthropogenic infrastructure, but a robust quantification of predator–prey interactions in this context is required to develop this understanding.
Using multi‐beam sonar (Dual‐Frequency Identification Sonar), we non‐invasively and simultaneously quantified the temporal rate of predator–prey interactions, the attack behaviour of predators, and the refuge seeking behaviour of prey at a pumping station intake during winter in a heavily modified lowland river.
Prey fish experienced temporally dynamic, density‐dependant, and species‐specific predation risks from two dissimilar predators (i.e., aquatic vs. avian); pike (
Esox lucius
) and cormorant (
Phalacrocorax carbo
). Generalised linear modelling revealed that prey refuge use was positively associated with predator attack rate. Non‐consumptive effects were evidenced by quantified changes to shoal structure (density, area), shoaling (group aggregation), and schooling (coordinated directional movement), including diurnal migrations to and from the pumping station intake for refuge.
Our results show that in the absence of natural refuge habitats the natural landscape of fear shifted and speculate that prey fish were paradoxically dependant on hazardous anthropogenic infrastructure, i.e., a pumping station intake, for refuge from predators in a degraded lowland river.
These findings strongly enhance our understanding of the impact of anthropogenic infrastructure on predator–prey interactions by demonstrating how flood risk management, including river maintenance measures, and associated anthropogenic infrastructure can impact the behavioural game played between aquatic and avian predators and their prey.
The aim of this work is to analyze the applicability of a convex hyperbola chart’s methodology to determine how many pumps should be working in a pumping station of a real case study to consume the ...least amount of energy. The applicability of the convex hyperbola charts is demonstrated, its effectiveness is shown, and a step-by-step exemplification is presented. Moreover, the order in which pumps should be activated is analyzed and discussed. The pumping station of the optimization is located in Tres Cantos, Madrid, Spain; it consists of a pumping station of four (+1 reserved) hydraulic pumps that take water from a reservoir and distribute it through a branched pipeline. The geometric height difference Hg of the case study is variable. This article also shows how the variability of Hg plays a major role in the optimal configuration of the pumping station. This paper also proves how the number of pumps to activate or disactivate does not necessarily need to be consecutive, meaning that activating or disactivating pumps one by one may not be the best solution. The convex hyperbola charts show how there can be circumstances in which skipping a certain number of pumps is the best solution. How the pump efficiency is distributed along the commercial pump plays a major role in determining which is the best configuration of active pumps. A straightforward and inexpensive optimization methodology for the optimization of the energy in a water supply system was proved and exemplified. This simple methodology can be applied by engineers in the operation of a water supply system when pumping is required, e.g., in agricultural systems or in underdeveloped areas where energy expenses need to be considered.
China's hydropower, with a total installed capacity of over 390 GW, is currently considered to be the most reliable flexibility resources to support the grid integration of wind and solar power with ...a total planned capacity of over 1200 GW. Fully exploiting hydropower flexibility is of great practical significance to China. This paper preliminarily evaluates the feasibility of transforming cascade hydropower stations to a large-scale cascade hydropower energy storage system (LCHES) via adding a pumping station between two adjacent upstream and downstream reservoirs. The pumping station can utilize excess electricity to recycle water potential energy between the two linked reservoirs. Taking cascade hydropower stations of a large hydro-wind-solar clean energy base (HWSCEB) in China as the case study, a simulation model is developed to simulate annual operation of LCHES at hourly resolution. The simulation results for the multi-year average representative year (2017) indicate that LCHES can effectively reduce the energy loss of HWSCEB, and store excess electricity of power grid during valley-electricity-price periods to realize price arbitrage; the overall efficiency of LCHES is approx.65%; LCHES is economically feasible only when the pumping station efficiency is greater than 55%. The performances of LCHES are further verified in different typical years.
•Energy storage of cascade hydropower stations achieved via a pumping station.•Feasibility of the large-scale cascade hydropower energy storage system is evaluated.•Excess electricity can be effectively utilized to recover water potential energy.•Pumping station efficiency is critical to the economic feasibility.
The Roof-attached Vortex (RAV), Floor-attached Vortex (FAV) and Combined Submerged Vortices (CSV) induced by the closed sump of a tidal pumping station have become an intricate problem that urgently ...needs to be clarified in expanding the stable operation range of units. This work reveals the dynamic evolution laws of various vortices and their typical forms under different flow conditions based on a combination of high-speed visualization and scale-resolving simulation methods. The results show that the RAV is a single spiral vortex structure under low flow rates and a main-secondary vortex double spiral structure under high flow rate conditions. The increase in flow rate has a positive promoting effect on the growth of the FAV. The RAV and FAV frequency values of occurrence are in the range of 0.001–0.1 Hz and 0.007–0.06 Hz, respectively. The maximum frequency of the CSV is 0.03 Hz. In the symbiotic stage of the CSV, there is an interaction between RAV and FAV. The suction of the surrounding low-pressure system affects the FAV, with vertical vorticity propagating towards the side of the RAV. In addition, the tangential velocity distribution of RAV and FAV exhibit rigid-like rotation characteristics consistent with the Burgers vortex model.
•Typical morphology and evolution characteristics of various vortices in a closed sump have been revealed.•The frequency of multiple vortices occurring is statistically analyzed.•The instantaneous characteristics of dynamic parameters of the combined submerged vortices are explored.•The roof-attached and floor-attached vortex exhibit tangential velocity distribution characteristics like rigid-body rotation.
Highly degraded lowland river ecosystems are of global concern to restoration practitioners. Hazardous anthropogenic structures, such as those used for water level management (i.e. pumping stations), ...present a mortality risk to fish and associated channelization, dredging, and removal of in‐channel and riparian vegetation during winter dramatically reduces habitat availability. Paradoxically, fish seeking habitat for predator refuge in these systems can lead to ecological traps, that is, the undesired occupation of pumping stations. Artificial habitats installed upstream could provide safe alternative refuge, but the effectiveness of this restoration technique is poorly understood. Here, we uniquely quantified habitat occupancy and preference of a ubiquitous European freshwater fish (Rutilus rutilus) between an artificial reed bed and pumping station habitat, with access to open water in a tank experiment. Generalized linear mixed models revealed that fish preferred the pumping station when the artificial habitat was absent (baseline) and when it was introduced (pre‐exclusion). Habitat management (exclusion from pumping station) was performed, during which artificial habitat occupancy was highest. When the pumping station was reintroduced (post‐exclusion), pumping station occupancy probability decreased from 87.5% (pre‐exclusion) to 3.7%, while artificial habitat occupancy probability increased from 18.4 to 87.9%. Therefore, our results demonstrate a preferential change in habitat occupancy of R. rutilus and suggest introducing artificial habitat alone may lead to restoration failures and ecological traps, stressing the need for habitat management to accompany artificial habitat restoration plans which aim to provide a safe alternative refuge for fish which occupy hazardous anthropogenic structures.
The operational efficiency error of a pumping station unit is affected by several factors, resulting in a large error between the theoretical and actual pumping efficiencies. To solve the problem of ...accurately simulating the operating efficiency of the pumping station unit, this study conducted research on efficiency simulation models of pumping based on data-driven from three aspects: ①model algorithm, ②feature input and ③response output. In this study, eight machine learning models were introduced to establish pumping unit efficiency simulation models and they were compared with the traditional polynomial regression models, and the models with better performance were selected. Then the experiment proposed using “upstream water level + downstream water level” (UWL + DWL) instead of the traditional “head” (H) as feature input to train the models, and discussed the effects on efficiency simulation accuracy with direct fitting efficiency and fitting power then calculate the efficiency through formula. An example analysis was carried out using the historical data of eight units at Pizhou Station and Suining 2nd Station on the East Line of the South-to-North Water Diversion Project. The experimental results show that ① among all methods, the models based on Gaussian Process Regression (GPR) has the most accurate in ERMS, EMA, R², and EMI indicators, R² is close to 0.92. ②After UWL + DWL was used to train the models, all the test set indicators of the GPR models improved, and the EMA indicator decreased from an average of 0.39% to 0.26%. ③ The study found that the fitting efficiency directly is better than the calculation efficiency after fitting the power, but the R² of fitting the power is better than the efficiency, which may provide another idea for the optimal goal of economic operation of pumping stations. ④ On the whole, trainning the GPR models with UWL + DWL to simulate efficiency has the highest precision, for example the EMA and EMI indicators of No.4 unit in Pizhou station can be reduced from 16.49% and 20.40% to 0.18% and 1.55% respectively. The research results have practical significance and can provide strong support for the economical operation of pump stations.
The determination of optimal parameters is of great importance to ensure the operability of a district heating system. Solving this problem entails providing the necessary network transmission ...capacity by determining pipe diameters, sites and parameters of pumping stations. The Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences has proposed methods to solve problem. A significant feature of these methods lies in that they make it possible to use complex mathematical models of the equipment used and flexibly adjust the computational procedure to the specific features of the system to be modelled. Normally, district heating systems have several heat sources. The practical problems for such systems have been solved by a technique based on the decomposition of the model of a district heating system according to heat source service areas. The decomposition breaks the unity of the computational process. As a result, the solution obtained is not optimal for the original district heating system model. The paper presents a methodological approach to determining optimal parameters of district heating systems with several heat sources. The approach employs a modified dynamic programming optimization method that provides an optimal solution without decomposition into the heat source service areas.
•Optimization of district heating system parameters is considered.•A modified dynamic programming optimization method is developed.•A methodological approach and algorithms are presented.•The approach is applied to district heating systems with several heat sources.•The approach has been demonstrated on a real district heating system.
Trash rack blockage significantly affects the water levels and velocity distributions near trash racks, influencing the performance of subsequent hydraulic systems. An experiment was conducted where ...alligator weeds, green grasses, woven bags, denim, and cotton fabrics were used as typical trash. Under different amounts of trash, approach velocities and water depths, the movement and aggregation characteristics of the trash were observed and measured. The water level difference and the velocity distributions of cross-sections near trash racks were measured and analysed. A general dimensionless expression was advanced to calculate the head loss coefficient of the trash rack. We introduced the local head loss formula of trash rack blockage based on measured velocity distributions. The results indicate that the water level difference is related to blocked trash characteristics and the approach velocity. The velocity distributions are determined by the blocked location and blocked area on the rack surface. Backflow occurs in severe blockage, which makes the velocity distribution uneven and increases the local head loss.
•The search ability of the BAS algorithm is improved by increasing the search direction and introducing the optimal individual and levy flight.•The IBAS algorithm is used to optimize the weight and ...bias of ELM to improve the prediction accuracy.•The data are divided into regulated and unregulated periods for water level prediction according to whether the unit is regulated or not.•Model input in the regulated period is improved considering the regulation time and the discharge of the pumping station.
It is necessary but difficult to accurately predict the water levels in front of pumping stations of an open-channel water transfer project because of the complex interactions among hydraulic structures. In this study, an improved beetle antennae search - extreme learning machine (IBAS-ELM) water level prediction model is proposed by combining the improved beetle antennae search (IBAS) algorithm with extreme learning machine (ELM). First, the water level data is divided into regulated and unregulated periods according to whether the pump unit is regulated or not. Second, the model inputs in the regulated period are improved by taking into account the regulation time of pumping units and the flow before and after regulation. Then, the beetle antennae search (BAS) algorithm is improved by increasing the search direction and introducing the optimal individual and levy flight. Finally, the IBAS-ELM model is established to predict water levels in front of Huibu and Dongsong pumping stations of the Jiaodong Water Transfer Project, China. The results show that: (1) the values of mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) of all models under group prediction are 15.60–24.65%, 10.18–23.86%, and 14.81–26.96% lower than those under direct prediction, respectively, and the values of Nash efficiency coefficient (NSE) are 0.33–2.14% higher; (2) the MAE, RMSE and MAPE values after improvement of model inputs are 27.03–38.85%, 24.64–43.12% and 28.44–40.58% lower than those without improvement of model inputs, respectively, and the NSE values are 4.20–8.84% higher; (3) the MAE, RMSE and MAPE values of the IBAS-ELM model are 0.66–28.50%, 1.07–30.18% and 0–27.10% lower than those of other models, respectively, and the NSE value is 0.09–3.05% higher. Therefore, the proposed model has higher prediction accuracy and can provide support for the operation of water transfer projects.