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The annual trading declaration of the electricity market for Kaidu River Cascade Hydropower Station depends on an accurate assessment of their power generation capacity. In order to fully tap the power generation dispatching potential of the hydropower station, rationally declare the annual power generation plan, and guarantee the economic benefits of the hydropower station, it is imperative to carry out research on the power generation dispatching potential of Kaidu River Cascade Hydropower Station. This study focused on Kaidu River Cascade Hydropower Station, aiming to minimize water shortage rates and maximize power generation. A multi-objective optimization dispatching model was created, and it was solved by using an improved NSGA-II algorithm. The model results were compared with simulated dispatching to tap the power generation of optimization dispatching. The results show that: ① Compared with simulation dispatching, optimization dispatching improves output reliability and increases power generation. Under simulation dispatching, the annual average power generation of Kaidu River Cascade Hydropower Station is 1.678 billion kW·h. Optimization dispatching obtains an additional 133 million kW·h (8% increase) in the annual average power generation; ② in different typical years, optimization dispatching has different effects on power generation dispatching potential exploitation of Kaidu River Cascade Hydropower Station, especially in extreme dry years, where the increase is 1.95 times that of normal years and 6.68 times that of extreme wet years. These results provide a decision-making basis for annual trading plan declarations of cascade hydropower stations and ensure the economic benefits of cascade hydropower stations.

Wind curtailment, caused by wind power uncertainty, has become a prominent issue with the large-scale grid connection of wind power. To fully account for the uncertainty of wind power output, a short-term hydro-wind-thermal operation method based on a wind power confidence interval is proposed. By utilizing the flexible start-stop and efficient ramp-up of cascade hydropower plants to smooth fluctuations in wind power output, a multi-objective optimal scheduling model that minimizes the cost of power generation and maximizes the consumption of clean energy is constructed. To reduce the solution's complexity, we chunk the model according to the energy type using a hierarchical solution. The overall solution framework, which integrates a nonparametric method, a heuristic algorithm, and an improved particle swarm algorithm, is constructed to solve the model rapidly. The simulation results of a regional power grid show that the proposed method can attain an efficient solution in 83.5 seconds. Furthermore, the proposed method achieves an additional 455,600 kWh of hydropower and a reduction of ¥233,300 in the cost of coal consumption. These findings suggest that the proposed method is a good reference for the short-term operation of a hydro-wind-thermal combination in large-scale wind power access areas. [ABSTRACT FROM AUTHOR]

The water consumption rate for hydropower station power generation is an important index of the economic operation of hydropower stations, which has been widely considered and applied in the production practice of hydropower stations and has great significance for the full utilization of hydroelectric resources. This paper takes A and B cascade hydropower stations as the research objects to study the variation patterns of the water consumption rate of hydropower stations under different conditions, which mainly includes the following: (1) in this study, the relationship curve of output–gross head–flow (NHgrossQ) of each unit was established based on the relationship curve of output–net head–flow (NHQ) and the flow–head loss curve of each unit; (2) the mirror vertical shift method was used to calculate and plot the relationship curve of gross head–flow for combinations of multiple units; (3) the outflow–water–output characteristic curve of the hydropower station under the conditions of different reservoir water levels, different discharge flow, or different power generation output under the optimal operation of the hydropower station were calculated and drawn; (4) the outflow–water level–output curve of the hydropower station under various conditions was converted into an outflow–water level–water consumption curve; (5) the variation characteristics of the water consumption rate of the hydropower station under different conditions were analyzed; (6) on the basis of the definition of the water consumption rate of cascade hydropower stations, the research on the variation in the water consumption rate of cascade hydropower stations was carried out under the conditions of different water levels of the A reservoir, different water levels of the B reservoir, different discharge, and different total output of the hydropower stations. The variation pattern of the water consumption rate of hydropower stations under different conditions obtained in this paper can provide technical support for the real-time economic operation of cascade hydropower stations. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The annual trading declaration of the electricity market for Kaidu River Cascade Hydropower Station depends on an accurate assessment of their power generation capacity. In order to fully tap the power generation dispatching potential of the hydropower station, rationally declare the annual power generation plan, and guarantee the economic benefits of the hydropower station, it is imperative to carry out research on the power generation dispatching potential of Kaidu River Cascade Hydropower Station. This study focused on Kaidu River Cascade Hydropower Station, aiming to minimize water shortage rates and maximize power generation. A multi-objective optimization dispatching model was created, and it was solved by using an improved NSGA-II algorithm. The model results were compared with simulated dispatching to tap the power generation of optimization dispatching. The results show that: ① Compared with simulation dispatching, optimization dispatching improves output reliability and increases power generation. Under simulation dispatching, the annual average power generation of Kaidu River Cascade Hydropower Station is 1.678 billion kW·h. Optimization dispatching obtains an additional 133 million kW·h (8% increase) in the annual average power generation; ② in different typical years, optimization dispatching has different effects on power generation dispatching potential exploitation of Kaidu River Cascade Hydropower Station, especially in extreme dry years, where the increase is 1.95 times that of normal years and 6.68 times that of extreme wet years. These results provide a decision-making basis for annual trading plan declarations of cascade hydropower stations and ensure the economic benefits of cascade hydropower stations.

With the proposal of the carbon peaking and carbon neutrality goals, China's energy structure is gradually shifting from relying on fossil fuels to relying mainly on renewable and clean energy systems. However, clean energy represented by wind and photovoltaic power generation is difficult to operate and consume separately due to output fluctuations and uncertainties. Hydropower stations have good regulation capabilities and can operate in conjunction with wind farms and photovoltaic power stations to alleviate the instability of new energy generation. The southwestern region of China is rich in hydropower resources, and a large number of cascade hydropower stations with regulatory reservoirs have been built. The complementary operation of cascade hydropower with wind power and photovoltaic resources around the watershed, and the full utilization of the regulating capacity of cascade hydropower to bundle and deliver high-quality electricity, is an important means of achieving energy transformation. To quantify the carrying capacity of cascade hydropower stations on wind power and photovoltaic resources, this paper proposes a nested calculation model for medium to long-term optimal scheduling of hydropower to short-term optimal allocation of hydro-wind-photovoltaic power. The short-term scheduling calculation boundary is determined based on the mid-term and long-term optimization scheduling calculation results of hydropower, the scale of wind and photovoltaic power during short-term scheduling is adjusted, and scheduling with the goal of maximizing source load matching, maximizing power generation, and minimizing abandoned power are optimized. Decoupling is carried out by using a hierarchical nested strategy to calculate the scale of wind and photovoltaic resources that can be carried by cascade hydropower stations. Applying this model to the cascade hydropower station group in the Yalong River Basin, the scale of wind and photovoltaic resources carried by the "three reservoirs and seven cascade" cascade hydropower stations in the Yalong River Basin is calculated. The research results show that considering the 2025 planning level year and 5% curtailment rate constraint, the cascade hydropower in the Yalong River basin can carry 1.396 million kW of wind power resources and 10.74 million kW of photovoltaic power resources. The research results have a certain reference value for the optimization of water solar energy complementary power generation systems in the watershed. [ABSTRACT FROM AUTHOR]

The objective of jointly optimizing the dispatching of cascade hydropower stations in the basin is to maximize economic benefits while ensuring the safe and stable operation constraints of power grids and hydropower stations. The existing joint optimization scheduling algorithms include dynamic programming algorithms and intelligent optimization algorithms. Among them, the progressive optimization algorithm (POA) as a representative of dynamic programming methods can effectively solve complex nonlinear constraint optimization problems. However, while it effectively addresses the issue of "dimensional disaster" in traditional dynamic programming, it also faces the challenge of "local convergence". Although the intelligent optimization algorithm such as the differential evolutionary algorithm (DE) and the genetic algorithm (GA) can effectively handle large-scale complex constraint optimization problems, these algorithms rely on their own group evolution mechanism and lack a search strategy tailored to the mathematical mechanism of the joint scheduling model of cascade hydropower stations. Starting with the theoretical analysis of the two-stage problem of optimizing and dispatching cascade hydropower stations, this paper deduces the monotonicity principle of the two-stage optimization problem for power generation dispatch and proposes a local search strategy based on the monotonicity principle. By using the cascade reservoir group in the lower reaches of JinSha River as an example, the local search strategy for the two-stage optimization problem of power generation dispatch in cascade hydropower stations is validated. This strategy improves the convergence rate and solution accuracy of the algorithm, thereby achieving an efficient solution to the joint optimization dispatch problem of cascade hydropower stations. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Pearl River is the property of Pearl River Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The optimal operation of cascade hydropower station is a hydropower system based on the optimal operation method of a single reservoir and considering the water relations between reservoirs. Based on the allocation capacity of the reservoir, Water resources are redistributed in cascade basins, so that the power generation can reach the maximum under the condition of limited water resources. The optimal operation of cascade hydropower stations is a nonlinear optimization problem with many variables and constraints. When solving nonlinear problems, this paper considers using interior point method, which has good robustness characteristics. In this paper, interior point method is used to solve the optimal operation of cascade hydropower stations with intermountain runoff flows into the reservoir. The method used in this paper can shorten the optimal operation calculation time of 24 h 4 reservoir cascade hydropower station to 0.16 s. Compared with the traditional manual operation calculation, the calculation in this paper can be used for online operation to realize real-time operation. The manually scheduled power generation and the calculated power generation are 4328MW and 4617.77MW. In the calculation result, the power generation is 6.7% more than that of the manual calculation result.

With the large-scale integration of new energy into the grid, there is an urgent demand for peak-shaving resources in the power system, and it is urgent to comprehensively improve the utilization level of flexible power sources in the power system to maintain the safe and stable operation of the power grid and improve the efficient of clean energy consumption. As a regional power grid with the highest proportion of new energy grid-connected in China, the Northwest Power Grid is affected by the factors of few newly installed coal power plants in recent years, the pumped storage power plant has not been put into operation on large scale, and the scale of electrochemical energy storage is insufficient. In a word, the insufficient flexible resources restrict the efficient use of new energy. In this paper, by exploiting the role of cascade reservoirs that have been put into operation on Upper Yellow River, and further excavating the peak regulation potential of cascade hydropower stations, it can achieve the effectiveness that is similar to energy storage and effectively save the construction cost of peak regulation resources. By establishing a comparison model, three scenarios of cascade hydropower not participating in peak shaving, direct hydropower participating in peak shaving, and cascade hydropower participating in peak shaving were analyzed, and the positive contribution to the grid peak shaving resources under the mode of participating in peak shaving was verified. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy,electricity demand has increased.As the largest clean energy in China,hydropower has been put into large-scale and centralized production,and the most complex large-scale hydropower system in the world is formed.However,short-term hydropower optimal scheduling faces the serious challenge of the curse of dimensionality due to massive cascade hydropower stations,numerous hydropower constraints,and time-sensitive scheduling requirements.Therefore,this paper proposes a short-term optimal scheduling method for cascade hydropower stations based on a segmented load construction strategy.First,the selection rules of the hydropower stations to be regulated are formulated from the perspective of the regulation performance,location,and task of the cascade hydropower stations.Then,a method is given to divide the complex original load into two sub-load processes,namely the segmented load process with time reduction scale and the residual load process with frequent fluctuations.Finally,the adjustment method is given,and the particle swarm algorithm is used for traversal and optimization at different stages,so as to find the load division process when the target is optimal.By taking seven cascade hydropower stations in a certain river basin in southwest China as research objects,a mature particle swarm algorithm is used to simulate the typical day during the flood and dry periods.The results show that the segmented load construction strategy proposed in this paper can effectively reduce the solution complexity,and the appropriate number of segments can improve the solution efficiency while ensuring the solution quality.In addition,this method greatly reduces the output fluctuation of auxiliary hydropower stations and helps to reduce the difficulty of scheduling and unit loss.Therefore,the method proposed in this paper can provide a reference for solving the short-term scheduling of large-scale cascade hydropower stations and is of good practical value.

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A data‐driven multi‐time scale robust scheduling model for a wind–hydro–thermal power system is presented in this study, according to the characteristic that wind power prediction accuracy increases with the decrease of the time scale. In day‐ahead scheduling, a generation plan is formulated with the target of minimising the total operating cost, and a data‐driven robust optimisation method based on the robust kernel density estimation (RKDE) is employed to deal with the uncertainty of wind power. That is, the distributional information of wind power is extracted by the RKDE from the big data, then the distributional information is incorporated into a data‐driven uncertainty set, and finally, a robust optimisation model is formed. During the intraday scheduling stage, the objective is to minimise the total water spillage in cascade hydropower stations and the adjustment cost of thermal units, and the task is to readjust the outputs of units based on the base outputs obtained by the day‐ahead scheduling, combined with the rolling forecast data of wind power and load. The real‐time scheduling is aimed at satisfying the power balance with minimum power adjustment. Finally, a test system is carried out to verify the efficiency and practicability of the proposed framework. [ABSTRACT FROM AUTHOR]

Abstract The intractable problem of the solar energy and wind energy are their discontinuity and instability cause by the environmental change. Hydropower was often chosen as the compensation of electric energy system for its celerity and low cost of adjustment and respond. This paper presents a long term multi-objective optimization model of hydro-photovoltaic(PV)-wind power system, in which, cascade hydropower station acts as the compensation of the power system. One objective of the model is maximizing the annual total power generation of the power system, and another objective is to smoothen the fluctuation of the power output of the system. This model calculates all the PV power and wind power at first, and then inputs the calculated results to the power grid as the boundary condition of the hydropower optimization. A modified version of non-dominated sorting whale optimization algorithm (modified NSWOA) is proposed to get a solution set of the proposed model. The results demonstrate that the modified NSWOA can provide decision maker a series of solutions for optimal selection and the hydropower can well compensate the PV power and wind power by its great adjusting ability. [ABSTRACT FROM AUTHOR]

Elevated levels of total dissolved gas (TDG) may occur downstream of dams during the spill process. These high levels would increase the incidence of gas bubble disease in fish and cause severe environmental impacts. With increasing numbers of cascade hydropower stations being built or planned, the cumulative effects of TDG supersaturation are becoming increasingly prominent. The TDG saturation distribution in the downstream reaches of the Jinsha River was studied to investigate the cumulative effects of TDG supersaturation resulting from the cascade hydropower stations. A comparison of the effects of the joint operation and the single operation of two hydropower stations (XLD and XJB) was performed to analyze the risk degree to fish posed by TDG supersaturation. The results showed that water with supersaturated TDG generated at the upstream cascade can be transported to the downstream power station, leading to cumulative TDG supersaturation effects. Compared with the single operation of XJB, the joint operation of both stations produced a much higher TDG saturation downstream of XJB, especially during the non-flood discharge period. Moreover, the duration of high TDG saturation and the lengths of the lethal and sub-lethal areas were much higher in the joint operation scenario, posing a greater threat to fish and severely damaging the environment. This work provides a scientific basis for strategies to reduce TDG supersaturation to the permissible level and minimize the potential risk of supersaturated TDG. [ABSTRACT FROM AUTHOR]

Power generation dispatching is a large complex system problem with multi-dimensional and nonlinear characteristics. A mathematical model was established based on the principle of reservoir operation. A large quantity of optimal scheduling processes were obtained by calculating the daily runoff process within three typical years, and a large number of simulated daily runoff processes were obtained using the progressive optimality algorithm (POA) in combination with the genetic algorithm (GA). After analyzing the optimal scheduling processes, the corresponding scheduling rules were determined, and the practical formulas were obtained. These rules can make full use of the rolling runoff forecast and carry out the rolling scheduling. Compared with the optimized results, the maximum relative difference of the annual power generation obtained by the scheduling rules is no more than 1%. The effectiveness and practical applicability of the scheduling rules are demonstrated by a case study. This study provides a new perspective for formulating the rules of power generation dispatching.

Toward solving the actual operation problems of cascade hydropower stations under hydrologic uncertainty, this paper presents the process of extraction of statistical characteristics from long-term optimal cascade operation, and proposes a monthly operation function algorithm for the actual operation of cascade hydropower stations through the identification, processing, and screening of available information during long-term optimal operation. Applying the operation function to the cascade hydropower stations on the Jinshajiang-Yangtze River system, the modeled long-term electric generation is shown to have high precision and provide benefits. Through comparison with optimal operation, the simulation results show that the operation function proposed retains the characteristics of optimal operation. Also, the inadequacies and attribution of the algorithm are discussed based on case study, providing decision support and reference information for research on large-scale cascade operation work.

[Display omitted] • A vibration avoidance strategy considering the multiple vibration factors is proposed. • The influences difference of wind and solar energy on hydropower units are analyzed. • The planned output schemes of cascade hydropower station are presented. The cascade hydro-wind-photovoltaic complementary generation system is considered to be an effective approach to solve the output fluctuation of renewable energy. However, for hydropower units, grid-connected operation results in frequent power adjustments and increases the risk of operating in vibration zones, which may lead to the low generation efficiency and hidden danger for the power plant. This study proposes a vibration avoidance strategy based on the unit commitment while considering multiple vibration factors. Multi-objective optimization is performed to minimize the water consumption, the number of times crossing the vibration zone and the number of units involved in regulation. Results for a case study located in the Southwest China, indicate that the proposed strategy avoids hydropower units operating in the vibration zone (the vibration rates decrease from 7.6%, 6.7%, 6.3% to 0 under three initial water levels). Comparing 9 scenarios with different meteorological conditions, indicates that photovoltaic power enables less hydropower units to complete the peak load regulation and to cross the vibration zone less frequently due to PV daily generation profile fitting better the load curve, unlike wind power. Finally, the operation schemes of cascade hydropower station in different periods are proposed. The suggested models are beneficial in reducing the impact of the vibration on hydropower units in hybrid power system and provide operation strategy for cascade hydropower station. [ABSTRACT FROM AUTHOR]

The uncertainty of electricity demands and reservoir inflows makes the optimal operation of hydropower stations extremely difficult. Therefore, it is very important to establish a multi-time-scale coupling model that not only reflects the current inflows of short-term strategies but also adapts to the mid-term and long-term optimal strategies. In this paper, using the Three Gorges and Gezhouba cascade hydropower stations as examples, the principles of the layered coupling on multiple time scales are proposed. The control strategies and mechanisms of information feedback for layered models are also presented. Based on these theories, this study establishes an optimal five-layered coupling operation model of the Three Gorges and Gezhouba cascade hydropower stations with the objective of maximizing the generated energy solved by Incremental Dynamic Programming (IDP). Data from 2009 is used as the case study for the optimization of the cascade system. The results show that the model can preferably take advantage of the forecasted inflows with different levels of precision and coordinate the "control and feedback" relationships between short-term and long-term strategies. [ABSTRACT FROM AUTHOR]

Yi, M.; Mo, L., and Shen, Q., 2020. Study on generation scheduling of cascade hydropower stations based on SAPSO. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 371–378. Coconut Creek (Florida), ISSN 0749-0208. With the reduction of energy and the reform of China's electric power system, it is of great help to develop clean energy such as hydropower to ease the lack of energy. Many methods are studied to solve the reservoir optimal scheduling problem, such as particle swarm optimization (PSO). In order to solve the premature problem and slow convergence of traditional PSO, simulated annealing particle swarm optimization (SAPSO) is proposed in this paper. The algorithm is improved by adding shrinkage factor and combining with simulated annealing algorithm. Establishing the maximum generation model, and SAPSO algorithm is used to optimize the power generation scheduling of four and ten hydropower stations. The case study shows that the application of SAPSO to solve the short-term optimal scheduling problem of cascade hydropower stations has achieved satisfactory results in effect and rationality. It provides a reliable method for the optimal operation of cascade hydropower stations. [ABSTRACT FROM AUTHOR]

Due to the volatility of natural resources, the power fluctuations of photovoltaic (PV) generation have serious negative impacts on the power quality. This paper reports a novel approach to resolve this problem in a combined cascade hydro-PV-pumped storage (CH-PV-PS) generation system through appropriate power distribution on a small time scale. According to the characteristics of power generation systems and multi-constraints, how to obtain the optimal smoothing effects with the small cost is a key challenge. For this purpose, wavelet packet decomposition is modified by constructing cost function and ideal power trajectory sequences to obtain a new adaptive power distribution method for the CH-PV-PS generation system considering the boundary conditions of the system in this paper. At the same time, to meet the real-time control requirements of actual systems, an additive function is presented to improve the optimization speed of the adaptive power distribution method. In the meantime, a fuzzy controller is designed to optimize the inevitable delay time of the power scheduling system, and the starting threshold is set to avoid the frequently mode conversion of pumped storage. Finally, the performance of the method is evaluated based on the PV station data in Xiaojin County, Sichuan Province, China. Simulation results based on Matlab-simulink indicate that the proposed method can effectively suppress PV power fluctuations and ensure normal operation of the CH-PV-PS generation system within the multiple constraints. [ABSTRACT FROM AUTHOR]