Hydropower System Research Articles

Modelling and Simulation of 100 kW Pumped Storage Hydro Power System

Renewable energy sources are an attractive alternative option for augmenting the supply that comes from the utility Grid. This is because they are environmentally friendly. However Photovoltaic power generation is intermittent in nature. Hence, it is usually combined with energy storage systems such as batteries. In this study, pumped hydroelectric energy storage is used for supplementing the power produced from the Solar Photovoltaic system especially during peak demands and when the solar irradiance is low especially at night. Thus, the objective of this study is to model and simulate a pumped energy storage hydro system that can provide power supply of up to approximately 100 kW for a 10 hour period to service the night time. The proposed system is modeled using MATLAB Simulink. A total volume of 91836.7 m3 of storage water was calculated to achieve this purpose. Maximum torque of about 90 N/m was attainable when the angular speed of the water turbine was between 1100 and 1200 rpm. Recommendation for further works can be considered to maintain the angular speed of the turbine within this range.

Operational Robustness Assessment of the Hydro-Based Hybrid Generation System under Deep Uncertainties

The renewable-dominant hybrid generation systems (HGSs) are increasingly important to the electric power system worldwide. However, influenced by uncertain meteorological factors, the operational robustness of HGSs must be evaluated to inform the associated decision-making. Additionally, the main factors affecting the HGS’s robustness should be urgently identified under deep uncertainties, as this provides valuable guidance for HGS capacity configuration. In this paper, a multivariate stochastic simulation method is developed and used to generate uncertain resource scenarios of runoff, photovoltaic power, and wind power. Subsequently, a long-term stochastic optimization model of the HGS is employed to derive the optimal operating rules. Finally, these operating rules are used to simulate the long-term operation of an HGS, and the results are used to evaluate the HGS’s robustness and identify its main sensitivities. A clean energy base located in the Upper Yellow River Basin, China, is selected as a case study. The results show that the HGS achieves greater operational robustness than an individual hydropower system, and the robustness becomes weaker as the total capacity of photovoltaic and wind power increases. Additionally, the operational robustness of the HGS is found to be more sensitive to the total capacity than to the capacity ratio between photovoltaic and wind power.

Cascaded Fractional-Order Controller-Based Load Frequency Regulation for Diverse Multigeneration Sources Incorporated with Nuclear Power Plant

To sustain a system frequency within acceptable limits, it is widely conceded that retaining a power balance between generation and demand is necessary. In order to regulate the frequency of power systems (PSs) this article proposes a novel cascaded based fractional-order controller termed as fractional-order integer- (FOI-) fractional-order proportional integral with double derivative (FOPIDD2). In addition to redox flow batteries and capacitive energy storage, the recommended control strategy has been validated with gas, thermal reheat, hydro, and nuclear power systems. Additionally, a newly designed algorithm known as squid game optimizer (SGO) optimizes the gains of the new FOI-FOPIDD2 controller. The squid game optimizer technique is inspired by the fundamental principles of a conventional Korean sport. It employs a population of candidate solutions and iteratively adjusts the control parameters to discover the optimal set that reduces frequency abnormalities and improves system stability. A comparison is also made between the controller’s performance and benchmarks, including the jellyfish search algorithm, the firefly algorithm, the grey wolf optimizer, and the particle swarm algorithm. The proposed algorithms reduced peak overshoot as compared to grey wolf optimizer algorithm by 35.34%, 46.78%, and 76.89%; jellyfish search optimization algorithm by 34.76%, 77.22%, and 82.56%; and firefly algorithm by 82.67%, 89.23%, and 29.67% for frequency variations in area 1, area 2 and tie line power, respectively. Furthermore, SGO-FOI-FOPIDD2 controllers under different loading circumstances and conditions were evaluated and endorsed for their ability to withstand uncertainties in power system parameters.

Multi-timescale analysis and quantification of dynamic regulation characteristics of DFIM-based variable-speed pumped storage units in alleviating wind power fluctuations

To comprehensively clarify the regulating role of variable-speed pumped storage system (VSPS) in alleviating wind power fluctuations, this paper quantitatively evaluates the multi-timescale frequency regulation performance of VSPS in a typical wind-hydro-pumped storage hybrid system (WHPHS). Firstly, the flexible equivalent frequency response models of VSPS and WHPHS are established. Then, the effectiveness of fixed-speed pumped storage system (FSPS) and VSPS in enhancing the stability of dominant hydropower system (HS) in WHPHS is compared, and the dynamic regulation behaviors between VSPS and FSPS are quantitatively evaluated. Based on the operational characteristics, the differences in the allocation of regulation responsibilities between VSPS/FSPS and HS for frequency regulation are clarified. The results indicate that VSPS contributes to an exhaustive improvement in HS stability, reduces the power fluctuation and frequency deviation of WHPSHS. Specifically, in the established simulation scenarios, WHPSHS with VSPS outperforms an equivalent FSPS in reducing frequency deviation frms by 20 %, power fluctuation Is by 40 %, and complementarity Ic by 50 %. Particularly effective in suppressing power fluctuations in range of 0.01 Hz to 0.8 Hz, which decreases the resonant peak of frequency deviation by 61.3 % compared to FSPS. It further highlights the regulatory advantages of VSPS in responding to low-amplitude high-frequency power variations. These findings can provide novel insights into the role of VSPS in mitigating RES fluctuations and energy management strategies in multi-type hybrid systems.

Stochastic Flow Analysis for Optimization of the Operationality in Run-of-River Hydroelectric Plants in Mountain Areas

The highly temporal variability of the hydrological response in Mediterranean areas affects the operation of hydropower systems, especially in run-of-river (RoR) plants located in mountainous areas. Here, the water flow regime strongly determines failure, defined as no operating days due to inflows below the minimum operating flow. A Bayesian dynamics stochastic model was developed with statistical modeling of both rainfall as the forcing agent and water inflows to the plants as the dependent variable using two approaches—parametric adjustments and non-parametric methods. Failure frequency analysis and its related operationality, along with their uncertainty associated with different time scales, were performed through 250 Monte Carlo stochastic replications of a 20-year period of daily rainfall. Finally, a scenario analysis was performed, including the effects of 3 and 30 days of water storage in a plant loading chamber to minimize the plant’s dependence on the river’s flow. The approach was applied to a mini-hydropower RoR plant in Poqueira (Southern Spain), located in a semi-arid Mediterranean alpine area. The results reveal that the influence of snow had greater operationality in the spring months when snowmelt was outstanding, with a 25% probability of having fewer than 2 days of failure in May and April, as opposed to 12 days in the winter months. Moreover, the effect of water storage was greater between June and November, when rainfall events are scarce, and snowmelt has almost finished with operationality levels of 0.04–0.74 for 15 days of failure without storage, which increased to 0.1–0.87 with 3 days of storage. The methodology proposed constitutes a simple and useful tool to assess uncertainty in the operationality of RoR plants in Mediterranean mountainous areas where rainfall constitutes the main source of uncertainty in river flows.

Integration and performance analysis of optimal large-scale hybrid PV and pump hydro storage system based upon floating PV for practical application

The widespread use of green energy sources creates a significant demand for energy storage. Hybrid floating photovoltaic (FPV) and pumped hydro storage (PHS) represent one of the most dependable and cost-effective solutions, which uses the PV system on the water body combined with a pair of lakes with different heights. This study focuses on the load side as well as the PHS capacity factor and aims to lower the cost of energy (COE) by raising the PHS capacity factor. Since building a PHS requires a significant upfront investment, doing so will also lower the COE and enable the acquisition of PHS for large-scale power production, which will guarantee power access in large cities. To simulate the FPV-PHS system, the multi-objective genetic algorithm (MOGA) is employed. Sufficient power management is a prerequisite for achieving system reliability in the best possible hybrid energy system design and implementation. Considering the 60-year system lifespan, the net present cost (NPC) analysis shows that, out of all the communities evaluated, the FPV-PHS system has the lowest NPC and COE. For the optimal configuration (FPV (Block A) 105 MW, PHS 80 MW, FPV (Block B) 357 MW, and the current hydropower plant), the expected NPC and energy costs for implementing the hybrid energy system (HRS) at the chosen location are $44,737,613 and $40/MWh, respectively. The existing FPV system spans 4.65 km2 and lowers the evaporation fraction by 17,279,400 m3. The hybrid FPV-PHS system reduces annual CO2 emissions by 581,830 tons. Our research reveals that a hybrid floating PV and pump storage hydropower system offers more steady clean electricity, implying a great significance for power grid infrastructure.

A high-precision transient state prediction framework for ageing hydropower systems: Refined model, two-stage parameter identification and impact analysis

Ageing has adverse effects on the hydraulic-mechanical characteristics of hydropower systems (HPSs). It leads to parameter uncertainty both in the hydropower generating units (HGUs) and pipeline systems, further resulting in more severe transient conditions. Existing studies on transient state prediction of HPSs mostly do not consider the parameter uncertainty caused by HPS ageing, especially in the hydro-turbine model. This omission significantly reduces the accuracy. Therefore, a novel framework is proposed to achieve a high-precision transient state prediction of ageing HPSs. The framework includes: a refined HPS model to consider the uncertain ageing of HPSs through its uncertain parameters; a two-stage parameter identification strategy to enhance the prediction accuracy iteratively; and a parameter impact analysis which quantifies the contribution of identifying parameters to the precision improvement. Note that a comprehensive hydro-turbine model with six uncertain parameters is proposed to account for both the hydraulic-mechanical characteristic and uncertain ageing, and a fuzzy analytic hierarchy process is applied to quantify the precision. Comparative studies with on-site measurement show that: (1) The proposed framework demonstrates a 13.24% improvement in prediction performance compared to existing methods; (2) The parameters associated with HGU (especially those related to the hydro-turbine model) contribute significantly more to prediction precision, surpassing those related to the pipeline by an average factor of 9.27; (3) The contribution ranking of HGU parameters to the precision improvement is GD2＞ kf＞ μQ0＞kyd＞kq ＞kn ＞ηc. Overall, this study effectively improves the transient state prediction for ageing HPSs considering the uncertain parameters related to HGU and pipeline systems.

Stochastic multi-criteria decision-making for scheduling of wind–photovoltaic–hydropower systems

Abstract The decision-making process of wind–photovoltaic–hydropower systems involves knowledge from many fields. Influenced by the knowledge level of the decision-maker and the attribute information of the scheme set, there exists a certain uncertainty in the indicator weights. In view of this, this paper proposes a stochastic multi-criteria decision-making framework for scheduling of wind–photovoltaic–hydropower systems, which overcomes the difficulty of uncertainty in indicator weights or even completely unknown information about indicator weights at the time of decision-making. The Stochastic Multi-criteria Acceptability Analysis (SMAA) theory and the VIKOR model are introduced, and the proposed SMAA–VIKOR model makes the indicator weight space explicit. The study shows that the proposed SMAA–VIKOR model can overcome the obstacle of decision-makers’ lack of information on indicator weights. The ranking acceptability indicators calculated by the model show a more obvious trend of advantages and disadvantages, which gives full confidence to the decision-making group to formulate a plan to be implemented. It breaks through the bottleneck of group decision-making, which is difficult to make effective decisions due to the condition of incomplete information, and enriches the library of stochastic multi-criteria decision-making methods for the scientific formulation of scheduling schemes of wind–photovoltaic–hydropower systems under uncertainty conditions.

Design and performance analysis of hydro and wind-based power and hydrogen generation system for sustainable development

Renewable energy sources have significance in combating global challenges. In this developed paper, the integration of the hydropower and wind turbine energy conversion system is designed and proposed. The foremost focus of this combined plant is to simultaneously generate clean power, hydrogen, and freshwater through a sustainable way. The developed innovative plant embraced a hydropower plant, wind turbines, a Proton Exchange Membrane unit, and a Reverse osmosis desalination unit. To determine the system performance, detailed thermodynamic performance modeling and sustainability index evaluation are fulfilled on the plant’s indicators. In light of this purpose, several parameters are used to conduct the irreversibility rate, energetic and exergetic efficiency, and other calculations. Along with the examination results, the electricity production rate is calculated as 81591 kW. Moreover, the developed combined system has 61.29 % energetic performance and 57.14 % exergetic performance. The sustainability index value is figured out as 2.33 for the entire system.

The Potential of Hydro Energy as the Renewable Energy Alternatives in the Rural Area

Hydro energy systems are broadly used around the world as renewable energy. The concept of hydro energy becomes the major energy alternative for fulfilling the energy demand, especially in the remotes area. The type of micro-hydro power was the most applicable to meet electricity purposes. Micro hydropower system proposes an environment friendly used because of easy to operate and low operation cost, especially in the area which high water availability. This review paper focuses on the potential of hydro energy systems that are built in remote areas. This review revealed three types of hydropower systems, namely mini-hydropower, small hydro power, and micro hydro power. Out of these three types, micro hydro power can become the solution for electrification in remote areas. Micro hydro power installation was built with many types of technological approaches. Nevertheless, considering geographical purposes, the capacity of energy production, and sustainability of resources. Yet, several obstacles should be aware of such as power availability in remote areas. The technical issue and government support become the key to success in applying hydropower in the site of installation. Otherwise, conventional fossil fuel-based systems which are costly and unsustainable may require due to the operating system of micro-hydro power as well

Improving the Management of the Hydropower System as Clean Energy in Mosul Dam According to Water Storage Fluctuation

Improving the Management of the Hydropower System as Clean Energy in Mosul Dam According to Water Storage Fluctuation

Application of Three-Dimensional CFD Model to Determination of the Capacity of Existing Tyrolean Intake

CFD models of intakes in high-head hydropower systems are rare due to the lack of geometric data and cost of modeling. This study tests two different types of software to see how modeling can be performed in a cost-effective way with scarce input data and still have sufficient accuracy. The volume of fluid (VoF) model simulations are conducted using both ANSYS Fluent and OpenFOAM. The geometry is modelled from Google Earth satellite images, drone scanning data, and design drawings from the construction period and supported by field observations for extra quality control. From the model, both capacity parameters and flow pattern are calculated. For capacity, the Cd factor is calculated and compared with the literature. The simulations are conducted for a Tyrolean weir with rectangular bars (flat steel) in the rack. Simulated flow patterns through the rack with ANSYS Fluent and OpenFOAM are compared. OpenFOAM simulations yielded 15% to 20% higher water levels compared to the VOF model applied in Ansys Fluent. Also, when the flow rate was high, the water capture capacity calculated with ANSYS Fluent was 10% higher than that obtained with OpenFOAM. However, considering the total simulation times, modeling with OpenFOAM offered approximately 11% faster results.

Short-term optimization scheduling method of cascade hydropower and photovoltaic complementary system based on pumping station operation strategy

With the rapid development of photovoltaic power generation, how to improve the photovoltaic grid connection rate is an urgent problem to be solved. This article proposes an optimized scheduling method for the water and photovoltaic complementary system, taking into account the operation strategy of pump stations to improve the photovoltaic grid connection rate. Firstly, a multi-objective optimization scheduling model is constructed to consider both power generation and output fluctuation, and the uncertainty of photovoltaic power generation is analyzed from multiple perspectives. Then, taking the cascade hydropower stations and surrounding photovoltaic power stations in a river basin in Sichuan as an example, the operation strategy of pump stations is introduced into the water and photovoltaic complementary system, considering different weather scenarios, to reduce the photovoltaic curtailment rate. The study verifies that the introduction of pump stations can effectively increase the photovoltaic grid connection rate, and quantitatively analyzes the pump station capacity configuration under different photovoltaic penetration rates.

Single-level reduction of the hydropower area Equivalent bilevel problem for fast computation

For inclusion in large-scale power system models, various aggregations and simplifications in the modeling of relevant actors are needed. This paper focuses on reduced models of hydropower, so called area Equivalent models. They use a simplified topology but are not a direct aggregation of the real hydropower system. Instead, the area Equivalent is constructed to mimic the simulated power production of a more detailed hydropower reference model. Here, this goal is fulfilled by formulating a bilevel problem minimizing the difference in simulated power production between the area Equivalent and its reference. Solving this can be computationally heavy. Thus, for a fast solution of this bilevel problem, a single-level reduction is done, which is then solved using two methods. The first method includes McCormick envelopes to form a linear single-level problem. Second is a modified Benders with a relaxed sub-problem to handle the non-convex single-level. These are then also compared to Particle Swarm Optimization. Moreover, six new upper-level objective functions are investigated for a case study of hydropower in northern Sweden. The method using McCormick envelopes is fast (2–5 min), but the area Equivalent shows lower average performance. The modified Benders finds a solution in 5–31 min with good performance.

Effect of turbine's torque and speed variation on hydraulic vibration analysis during transient processes

AbstractWith the rapid development of large‐capacity hydraulic turbines and pumped‐storage power stations, hydraulic vibration analysis attracts increasing attention nowadays. To explore the influence of torque and speed variation on hydraulic vibration characteristics during transient processes and ensure the stability of hydropower stations, an improved analytical formula of turbine impedance involving the torque and speed variation was then derived. The free vibration analysis and forced vibration analysis using the transfer matrix method and the hydraulic impedance method were carried out. According to the numerical simulations, the obtained attenuation factors show differences in magnitude which illustrates that the torque variation and speed variation in transients do affect the damping rate of the vibration. In addition, the results indicated the natural angular frequencies of hydropower system were mainly dependent on the length of water conveyance system and pipe characteristics. It can be inferred form vibration mode shapes that for some specific frequencies, the magnitude of oscillatory pressure head and flow rate along the downstream tail tunnel are influenced by the hydraulic turbine. The correlation between the turbine impedance and guide vane openings tells that the hydraulic impedance is getting smaller as the opening increases. What's more, the corresponding free vibration analysis shows that the absolute value of the damping rate is closely related to the value of the flow rate.

Integrating Hydrological and Machine Learning Models for Enhanced Streamflow Forecasting via Bayesian Model Averaging in a Hydro-Dominant Power System

Streamflow forecasting plays a crucial role in the operational planning of hydro-dominant power systems, providing valuable insights into future water inflows to reservoirs and hydropower plants. It relies on complex mathematical models, which, despite their sophistication, face various uncertainties affecting their performance. These uncertainties can significantly influence both short-term and long-term operational planning in hydropower systems. To mitigate these effects, this study introduces a novel Bayesian model averaging (BMA) framework to improve the accuracy of streamflow forecasts in real hydro-dominant power systems. Designed to serve as an operational tool, the proposed framework incorporates predictive uncertainty into the forecasting process, enhancing the robustness and reliability of predictions. BMA statistically combines multiple models based on their posterior probability distributions, producing forecasts from the weighted averages of predictions. This approach updates weights periodically using recent historical data of forecasted and measured streamflows. Tested on inflows to 139 reservoirs and hydropower plants in Brazil, the proposed BMA framework proved to be more skillful than individual models, showing improvements in forecasting accuracy, especially in the South and Southeast regions of Brazil. This method offers a more reliable tool for streamflow prediction, enhancing decision making in hydropower system operations.

A System and Method for Retrieving Energy Potential through Irrigation Gate of an Agricultural Dependent Hydro Power Plant

The modern economics depends on the electrical energy and the share of decarburized electrical energy is the base of 2050 net zero emission targets. Non-fossil fuel and fossil fuel energy resources are the integral part of net zero energy system. The net zero emission activities are affected by increasing demand of electricity and its related CO2 emission in 2021. The contribution of 41.4% of renewable energy as compared to 56.8% of non-renewable energy in the year of 2023 at national level necessities attention of green sources of energy like solar, wind, hydro, waste to energy, small hydropower, etc. Hydropower is one of the reliable backbones of clean energy system which should be used effectively for power generation. The turbine dependent hydropower plant of 45-60 years old requires renovation, modernization, uprating and digitization (RMUD) to resolve socio-economic concerns and increasing demands. This scenario imposes the need of finding solution in existing hydropower plant than investing on new unit. Both high and low discharge should be potentially used for power generation to improve the capacity factor of the plant. Therefore, present work focusses on improving capacity factor of an existing agricultural dependent hydro power plants having reaction type turbine. Reaction turbines operates at high flow and low/medium head conditions. The operational conditions of low flow and low head for reaction turbines may lead to noise, vibration and directed to major catastrophic failure of turbines. There is a need of utilizing the energy potentials balancing power generation and irrigation even during low flow releases. Thus, this paper is an attempt to a design and develop a modified irrigation gate with sliding gate and mini hydropower system at the inlet of existing irrigation diversion gate. Stochastic nature of flows through different hydraulic structures is to be addressed by this modification. A case study of an irrigation dependent hydropower plant Dhom (2X1 MW), MAHAGENCO, Satara, Maharashtra having TWO irrigation gates have been considered. In addition to 2MW, the suggested design can generate 680kW by average irrigation releases of 2.47m3/sec through each gate. The suggested model can be used on any hydropower plant and canal locations.

Fast Coordinated Predictive Control for Renewable Energy Integrated Cascade Hydropower System Based on Quantum Neural Network

The increasing penetration of renewable energy poses intractable uncertainties in cascade hydropower systems, such that excessively conservative operations and unnecessary curtailment of clean energies can be incurred. To address these challenges, a quantum neural network (QNN)-based coordinated predictive control approach is proposed. It manipulates coordinated dispatch of multiple clean energy sources, including hydro, wind, and solar power, leverages QNN to conquer intricate multi-uncertainty and learn intraday predictive control patterns, by taking renewable power, load, demand response (DR), and optimal unit commitment as observations. This enables us to exploit the stability and exponential memory capacity of QNN to extrapolate diversified dispatch policies in a reliable manner, which can be hard to reach for traditional learning algorithms. A closed-loop warm start framework is finally presented to enhance the dispatch quality, where the decisions by QNN are fed to initialize the optimizer, and the optimizer returns optimal solutions to quickly evolve the QNN. A real-world case in the ZD sub-grid of the Sichuan power grid in China demonstrates that the proposed method hits a favorable balance between operational cost, accuracy, and efficiency. It realizes second-level elapsed time for intraday predictive control.

System Power Quality Analysis under Wind–Hydro Complementary Generation Mode

The highly random and characteristics of wind power generation challenge the power quality of the wind–hydro complementary generation system (WHCGS). Herein, the transient characteristics of power quality under the complementary generating mode are studied. First, a nonlinear hydropower system (HPS) model is innovatively established considering the dynamic characteristics of hydrounits under part load operation, and then a wind power system model including wind speed model, wind turbine and its controller, generator and converter is established. Finally, the applicability of WHCGS model in power quality evaluation is established and verified by IEEE‐9 node model. Combined with active power, frequency, and voltage power quality indicators, the effects of wind–hydro capacity ratio and voltage sag on the system are quantified. The results show that the increase in wind power penetration will deteriorate the power quality of WHCGS. Moreover, when the wind power capacity reaches 60 MW, it will damage the voltage and frequency stability of HPS. Besides, the larger the voltage sag amplitude, the worse the power quality of WHCGS. The longer the voltage sag lasts, the higher the risk of WHCGS instability. This article provides a technical reference for the safe and stable operation of WHCGS.

Technical, Economic, and Environmental Investigation of Pumped Hydroelectric Energy Storage Integrated with Photovoltaic Systems in Jordan

In this study, the technical and economic feasibility of employing pumped hydroelectric energy storage (PHES) systems at potential locations in Jordan is investigated. In each location, a 1 MWp off-grid photovoltaic (PV) system was installed near the dam reservoir to drive pumps that transfer water up to an upper reservoir at a certain distance and elevation. PVsyst (Version 7.3.4) is implemented to simulate the water flow rate pumped to the upper reservoir at each location. The water in the upper reservoir is presumed to flow back into the dam reservoir through a turbine during peak hours at night to power a 1 MW load. Based on the water volume in the upper reservoir, the power generated through the turbine was estimated using HOMER Pro® (Version 3.15.3), and the power exported to the grid (when the power generated from the turbine is more than the power required by the driven load) was also determined. It is worth mentioning that scaling up the size of PV and hydropower systems is a straightforward approach considering the modular nature of such systems. However, the quantity of water in the dam reservoir that is allowed to be pumped is the main determinant for the size of a PHES system. The technical and economic results show that the potential of employing these locations to implement PHES systems is great. In addition, a study was conducted to estimate how much CO2 emissions were reduced by generating renewable energy compared to generating the same amount of energy from fossil fuels. These systems increase renewable energy in the energy mix in Jordan, stabilize the grid, and balance the loads, especially during peak periods. More importantly, PHES systems contribute to making the energy sector in Jordan more sustainable.