Статті в журналах: "Cascaded hydropower"

1

Xu, Zhanxing, Qiang Liu, Lingjun Xu, Li Mo, Yongchuan Zhang, and Xin Zhang. "Optimal Dispatching Rules for Peak Shaving of Cascaded Hydropower Stations in Response to Large-Scale New Energy Integration." Processes 13, no. 3 (February 21, 2025): 612. https://doi.org/10.3390/pr13030612.

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Fully tapping into the load regulation capacity of cascade hydropower stations on a river, in coordination with wind and photovoltaic power stations, can effectively suppress power fluctuations in new energy and promote grid integration and the consumption of new energy. To derive the peak shaving dispatching rules for cascaded hydropower stations in provincial power systems with a high proportion of new energy integration, a short-term peak shaving dispatching model for cascaded hydropower stations was first established considering large-scale new energy consumption; secondly, based on statistical learning methods, the peak shaving and dispatching rules of cascade hydropower stations in response to large-scale new energy integration were derived. Finally, taking wind farms, photovoltaic power stations, and the Qingjiang cascade hydropower stations in the power grid of Hubei Province, China, as research objects, the compensation effect of Qingjiang cascade hydropower stations on new energy output and the peak shaving performance for the power grid load were verified. The research results indicate that cascade hydropower can effectively reduce the peak valley load difference in provincial power grids and improve the overall smoothness of power grid loads while suppressing fluctuations in new energy output. After peak regulation by cascade hydropower, the residual load fluctuation indices of the power grid are improved by more than 20% compared to those after the integration of new energy. The probabilistic dispatching decisions for the facing period’s output through the optimal dispatching rules of cascade hydropower stations can provide dispatchers with richer decision-making support information and have guiding significance for the actual peak shaving dispatch of cascade hydropower stations.

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2

Wang, Xiang, Le Guo, Jianjian Shen, Meiyan Kong, and Xu Han. "Issues and Strategies for the Dispatching and Trading of the Three Gorges Large Hydropower System." Energies 16, no. 18 (September 18, 2023): 6683. http://dx.doi.org/10.3390/en16186683.

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China’s electricity market reform has posed a real challenge to the large-scale hydropower system. Taking the world’s largest watershed hydropower system, the Three Gorges large hydropower system (TGLHS), as the engineering background, this study analyzes the issues and strategies of dispatching and trading in the electricity market. The analysis indicates that the TGLHS exhibits unique difficulties because of transprovincial and transregional power transmission. Major issues including the multi-dimensional and multi-time-scale nested allocation of hydropower energy, the bidding and performance of cascaded hydropower plants in multiple electricity markets, as well as multiple uncertainties in the runoff; electricity prices in multiple markets are also elaborated upon. The corresponding suggested strategies are proposed to cope with the aforementioned issues: (1) for multi-dimensional and multi-scale nested allocation problems, it is necessary to comprehensively consider monthly market transactions and priority generation plans, and establish a profit maximization model; (2) propose a bidding decision-making linkage and segmented bidding optimization model for cascades upstream and downstream hydropower stations; (3) construct a model for decomposing the annual and monthly planned electricity consumption curves and developing operational plans for giant cascade power stations that are suitable for cross-provincial and cross-regional power transmission and transformation; (4) a runoff, electricity price, and market distribution model has been proposed, laying the foundation for further research on multi-scale optimization models for hydropower. Finally, prospects for research on the participation of large-scale hydropower systems in the electricity market are summarized, expecting to promote the marketization of large cascaded hydropower systems. The dispatching and trading of the TGLHS implies that it is important and necessary to explore market theories and methods considering hydropower characteristics and operation needs.

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3

Chen, Yang, Yong Zhao, and Jing Rui Zhang. "Analysis on Electricity Pricing Mechanism for Cascade Hydropower Stations in China." Applied Mechanics and Materials 94-96 (September 2011): 2200–2203. http://dx.doi.org/10.4028/www.scientific.net/amm.94-96.2200.

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For the large cascaded hydropower stations, an electricity pricing mechanism of cascade hydropower stations on large basins is proposed. The main idea is that the electricity generated by different hydropower stations on the same river can be sold to the Grid Corporation with the same price. Using five hydropower stations on the middle and lower reaches of some river in China's south-western region as a case, the pricing methods based on the Operation-period pricing method are studied. The changes of hydropower stations' earnings are analyzed through the cascade hydropower stations optimal scheduling model and simulation analysis. The results show that the mechanism is conducive to hydropower development and the comprehensive utilization of water resources, which provides an alternative of electricity market reform strategy for the national energy departments.

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4

Shao, Qizhuan, Mingbo Wang, and Shuangquan Liu. "A Two-stage Successive Approximation Method of Dynamic Programming for Operations of Cascaded Hydropower Plants with Navigation Demand." Journal of Physics: Conference Series 2224, no. 1 (April 1, 2022): 012136. http://dx.doi.org/10.1088/1742-6596/2224/1/012136.

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Abstract The operations of cascaded hydropower plants have always been recognized as a complex system optimization problem. The difficulty of modelling and optimization solution is further aggravated when comprehensive water demands for power generation, navigation and ecology are considered. This study develops an optimization model for operations of cascaded hydropower plants with navigation demands, and proposes a two-stage successive approximation method of dynamic programming. In the model, the navigation demand is considered as a constraint. The first stage is to optimize the operation of cascaded hydropower plants with no consideration of navigation demand. The optimized result is taken as an initial solution of the last stage. Moreover, the navigation constraint is introduced in the solution procedure to obtain a reasonable operation scheme. The method is implemented on operations of a cascaded hydropower plants with navigation task in Southwest China. The results show that the navigation demand can be satisfied by coordination of cascaded hydropower plants. Moreover, this constraint has an effect on the monthly distribution of total energy production during one year. In addition, the computing efficiency and solution accuracy are analysed by using different discrete steps.

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5

Wu, Zhong Qun. "How to Apply Dynamic Optimization into Intertemporal Investment." Applied Mechanics and Materials 63-64 (June 2011): 930–35. http://dx.doi.org/10.4028/www.scientific.net/amm.63-64.930.

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The most important feature of cascaded hydropower investment, intertemporal optimization, is neglected to some extent. This paper focuses on how to make an optimal decision on intertemporal investment based on the case of cascaded hydropower. I incorporated intertemporal investment and financing constraints in dynamic programming, and proposed a new objective function. As a result, an intertemporal optimal dynamic model is established. The model highlights the fundamental framework of dynamic programming on cascaded hydropower development. The framework is robustly suitable to improve investment efficiency with respect to intertemporal optimization.

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6

Liu, Shuangquan, Jingzhen Luo, Hui Chen, Youxiang Wang, Xiangyong Li, Jie Zhang, and Jinwen Wang. "Third-Monthly Hydropower Scheduling of Cascaded Reservoirs Using Successive Quadratic Programming in Trust Corridor." Water 15, no. 4 (February 11, 2023): 716. http://dx.doi.org/10.3390/w15040716.

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The third-monthly (about 10 days in a time-step) hydropower scheduling, typically a challenging nonlinear optimization, is one of the essential tasks in a power system with operational storage hydropower reservoirs. This work formulates the problem into quadratic programming (QP), which is solved successively, with the linearization updated on the nonlinear constraint of the firm hydropower yield from all the cascaded hydropower reservoirs. Notably, the generating discharge is linearly concaved with two planes, and the hydropower output is defined as a quadratic function of reservoir storage, release, and generating discharge. The application of the model and methods to four cascaded hydropower reservoirs on the Jinsha River reveals several things: the successive quadratic programming (SQP) presented in this work can derive results consistent with those by the dynamic programming (DP), typically with the difference in water level within 0.01m; it has fast convergence and computational time increasing linearly as the number of reservoirs increases, with the most significant improvement in the objective at the second iteration by about 20%; and it is capable of coordinating the cascaded reservoir very well to sequentially maximize the firm hydropower yield and the total hydropower production.

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7

Zheng, Hao, Xuhan Luo, and Jinwen Wang. "A monthly hydropower scheduling of cascaded reservoirs based on a three-triangle linear concaving method." Journal of Physics: Conference Series 2306, no. 1 (November 1, 2022): 012010. http://dx.doi.org/10.1088/1742-6596/2306/1/012010.

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Abstract Hydropower is one of the most critical renewable energy resources in reducing carbon emissions and alleviating global warming. The energy production efficiency can be improved with hydropower scheduling, which, however, is a challenging optimization problem mainly attributable to the nonlinear and nonconvex hydropower output function (HOF). This work applies a new method to linearly concave the nonlinear HOF without introducing any integer variables, ensuring a very fast solution to a long-term hydropower scheduling of cascaded reservoirs. The Lancang River, which involves four cascaded reservoirs, is studied with the model and method, which takes only 34 seconds to secure the optimum monthly hydropower scheduling over five years.

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8

Zhou, Binbin, Suzhen Feng, Zifan Xu, Yan Jiang, Youxiang Wang, Kai Chen, and Jinwen Wang. "A Monthly Hydropower Scheduling Model of Cascaded Reservoirs with the Zoutendijk Method." Water 14, no. 23 (December 6, 2022): 3978. http://dx.doi.org/10.3390/w14233978.

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A monthly hydropower scheduling determines the monthly flows, storage, and power generation of each reservoir/hydropower plant over a planning horizon to maximize the total revenue or minimize the total operational cost. The problem is typically a complex and nonlinear optimization that involves equality and inequality constraints including the water balance, hydraulic coupling between cascaded hydropower plants, bounds on the reservoir storage, etc. This work applied the Zoutendijk algorithm for the first time to a medium/long-term hydropower scheduling of cascaded reservoirs, where the generating discharge capacity is handled with an iterative procedure, while the other head-related nonlinear constraints are represented with exponential functions fitting to discrete points. The procedure starts at an initial feasible solution, from which it finds a feasible improving direction, along which a better feasible solution is sought with a one-dimensional search. The results demonstrate that the Zoutendijk algorithm, when applied to six cascaded hydropower reservoirs on the Lancang River, worked very well in maximizing the hydropower production while ensuring the highest firm power output to be secured.

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9

Zou, Jin, and Feng Pan. "A Fuzzy-Dynamic-Programming Approach to the Scheduling of Cascaded Hydropower Plants." Advanced Materials Research 760-762 (September 2013): 2028–36. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.2028.

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An optimization-based algorithm is presented for the optimal operation of hydropower systems with cascaded hydro-plants. Continuous reservoir dynamics and constraints, discrete operating states, and hydraulic coupling of cascaded hydro-plants are considered in an integrated way. The main idea is to decompose the cascaded hydro-plants into individual plants, and then use Fuzzy Dynamic Programming (FDP), rather traditional Dynamic Programming (DP), to solve the subproblem of each plant while considering the hydraulic coupling of the plants. Numerical test shows that this method converges very fast, and is efficient and effective to deal with hydropower system with cascaded hydro-plants.

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10

Liu, Shuangquan, Guoyuan Qian, Zifan Xu, Hua Wang, Kai Chen, Jinwen Wang, and Suzhen Feng. "A Special Ordered Set of Type 2 Modeling for a Monthly Hydropower Scheduling of Cascaded Reservoirs with Spillage Controllable." Water 15, no. 17 (August 31, 2023): 3128. http://dx.doi.org/10.3390/w15173128.

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This study introduces a novel approach for optimizing the monthly hydropower scheduling of cascaded reservoirs by employing a special ordered set of type 2 (SOS2) formulation within a mixed integer linear programming (MILP) model. The proposed method linearizes the relationships between hydropower output, spillage, storage, and outflow, enabling controllable spillage. The objective is to minimize spillage, maximize firm hydropower output, and maximize energy production, all in priority while considering complex constraints such as reservoir storage and discharge bounds, upstream–downstream relationship, and water balance. The approach is applied to four cascaded reservoirs on the Lancang River. Results indicate that the SOS2 formulation effectively minimizes spillage, maximizes hydropower generation, and ensures maximum firm power output. Comparisons across different gridding resolutions reveal that more grid points yield greater benefits but with a longer solution time. Furthermore, a comparison with the Successive Quadratic Programming (SQP) method highlights the superior performance of the SOS2 model in terms of objective improvement and solution efficiency. This research offers valuable insights into optimizing monthly hydropower scheduling for cascaded reservoir systems, enhancing operational efficiency and decision-making in water resources management.

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11

Parvez, Iram, Jianjian Shen, Ishitaq Hassan, and Nannan Zhang. "Generation of Hydro Energy by Using Data Mining Algorithm for Cascaded Hydropower Plant." Energies 14, no. 2 (January 7, 2021): 298. http://dx.doi.org/10.3390/en14020298.

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The thirst of the Earth for energy is lurching towards catastrophe in an era of increasing water shortage where most of the power plants are hydroelectric. The hydro-based power systems are facing challenges in determining day-ahead generation schedules of cascaded hydropower plants. The objective of the current study is to find a speedy and practical method for predicting and classifying the future schedules of hydropower plants in order to increase the overall efficiency of energy by utilizing the water of cascaded hydropower plants. This study is significant for water resource planners in the planning and management of reservoirs for generating energy. The proposed method consists of data mining techniques and approaches. The energy production relationship is first determined for upstream and downstream hydropower plants by using multiple linear regression. Then, a cluster analysis is used to find typical generation curves with the help of historical data. The decision tree algorithm C4.5, Iterative Dichotomiser 3-IV, improved C4.5 and Chi-Squared Automatic Interaction Detection are adopted to quickly predict generation schedules, and detailed comparison among different algorithms are made. The decision tree algorithms are solved using SIPINA software. Results show that the C4.5 algorithm is more feasible for rapidly generating the schedules of cascaded hydropower plants. This decision tree algorithm is helpful for the researchers to make fast decisions in order to enhance the energy production of cascaded hydropower plants. The major elements of this paper are challenges and solution of head sensitive hydropower plants, using the decision-making algorithms for producing the generation schedules, and comparing the generation from the proposed method with actual energy production.

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12

Parvez, Iram, Jianjian Shen, Ishitaq Hassan, and Nannan Zhang. "Generation of Hydro Energy by Using Data Mining Algorithm for Cascaded Hydropower Plant." Energies 14, no. 2 (January 7, 2021): 298. http://dx.doi.org/10.3390/en14020298.

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Анотація:

The thirst of the Earth for energy is lurching towards catastrophe in an era of increasing water shortage where most of the power plants are hydroelectric. The hydro-based power systems are facing challenges in determining day-ahead generation schedules of cascaded hydropower plants. The objective of the current study is to find a speedy and practical method for predicting and classifying the future schedules of hydropower plants in order to increase the overall efficiency of energy by utilizing the water of cascaded hydropower plants. This study is significant for water resource planners in the planning and management of reservoirs for generating energy. The proposed method consists of data mining techniques and approaches. The energy production relationship is first determined for upstream and downstream hydropower plants by using multiple linear regression. Then, a cluster analysis is used to find typical generation curves with the help of historical data. The decision tree algorithm C4.5, Iterative Dichotomiser 3-IV, improved C4.5 and Chi-Squared Automatic Interaction Detection are adopted to quickly predict generation schedules, and detailed comparison among different algorithms are made. The decision tree algorithms are solved using SIPINA software. Results show that the C4.5 algorithm is more feasible for rapidly generating the schedules of cascaded hydropower plants. This decision tree algorithm is helpful for the researchers to make fast decisions in order to enhance the energy production of cascaded hydropower plants. The major elements of this paper are challenges and solution of head sensitive hydropower plants, using the decision-making algorithms for producing the generation schedules, and comparing the generation from the proposed method with actual energy production.

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13

Li, Yang, Feilong Hong, Xiaohui Ge, Xuesong Zhang, Bo Zhao, and Feng Wu. "Optimal Capacity Configuration of Pumped-Storage Units Used to Retrofit Cascaded Hydropower Stations." Energies 16, no. 24 (December 13, 2023): 8049. http://dx.doi.org/10.3390/en16248049.

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As flexible resources, cascaded hydropower stations can regulate the fluctuations caused by wind and photovoltaic power. Constructing pumped-storage units between two upstream and downstream reservoirs is an effective method to further expand the capacity of flexible resources. This method transforms cascaded hydropower stations into a cascaded pumped-hydro-energy storage system. In this paper, a flexibility reformation planning model of cascaded hydropower stations retrofitted with pumped-storage units under a hybrid system composed of thermal, wind, and photovoltaic power is established with the aim of investigating the optimal capacity of pumped-storage units. First, a generative adversarial network and a density peak clustering algorithm are utilized to generate typical scenarios to deal with the seasonal fluctuation of renewable energy generation, natural water inflow, and loads. Then, a full-scenario optimization method is proposed to optimize the operation costs of multiple scenarios considering the variable-speed operation characteristics of pumped storage and to obtain a scheme with better comprehensive economy. Meanwhile, the proposed model is retransformed into a mixed-integer linear programming problem to simplify the solution. Case studies in Sichuan province are used to demonstrate the effectiveness of the proposed model.

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14

Wu, Xinyu, Ruixiang Cheng, and Chuntian Cheng. "A Simplified Solution Method for End-of-Term Storage Energy Maximization Model of Cascaded Reservoirs." Energies 15, no. 12 (June 20, 2022): 4503. http://dx.doi.org/10.3390/en15124503.

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In medium-term scheduling, the end-of-term storage energy maximization model is proposed to create conditions for the safety, stability and economic operation of the hydropower system after control term, which satisfies the system load demand undertaken by the cascaded system in a given scheduling period. This paper presents a simplified solution method based on the Lagrangian relaxation method (LR) to solve the end-of-term storage energy maximization model. The original Lagrange dual problem with multiple Lagrange multipliers is converted to that with only one Lagrange multiplier by an entropy-based aggregate function method, which relaxes the complex cascaded hydropower system load balance constraints. The subgradient method and successive approximation of dynamic programming (DPSA) are adopted to update the Lagrange multiplier iteratively and solve the subproblem of the Lagrange dual problem, respectively. The Wujiang cascaded hydropower system is studied, and the result shows that the simplified solution method for the end-of-term storage energy maximization model both improves solving efficiency and ensures solving accuracy to a great extent.

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15

Ha, Phu Trieu, Dao Trong Tran, Tan Minh Phan, and Thang Trung Nguyen. "Maximization of Total Profit for Hybrid Hydro-Thermal-Wind-Solar Power Systems Considering Pumped Storage, Cascaded Systems, and Renewable Energy Uncertainty in a Real Zone, Vietnam." Sustainability 16, no. 15 (August 1, 2024): 6581. http://dx.doi.org/10.3390/su16156581.

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The study maximizes the total profit of a hybrid power system with cascaded hydropower plants, thermal power plants, pumped storage hydropower plants, and wind and solar power plants over one operation day, considering the uncertainty of wind speed and solar radiation. Wind speed and solar radiation in a specific zone in Vietnam are collected using the wind and solar global atlases, and the maximum data are then supposed to be 120% of the collection for uncertainty consideration. The metaheuristic algorithms, including the original Slime mould algorithm (SMA), Equilibrium optimizer, and improved Slime mould algorithm (ISMA), are implemented for the system. ISMA is a developed version of SMA that cancels old methods and proposes new methods of updating new solutions. In the first stage, the cascaded system with four hydropower plants is optimally operated by simulating two cases: simultaneous optimization and individual optimization. ISMA is better than EO and SMA for the two cases, and the results of ISMA from the simultaneous optimization reach greater energy than individual optimization by 154.8 MW, equivalent to 4.11% of the individual optimization. For the whole system, ISMA can reach a greater total profit than EO and SMA over one operating day by USD 6007.5 and USD 650.5, equivalent to 0.12% and 0.013%. The results indicate that the optimization operation of cascaded hydropower plants and hybrid power systems can reach a huge benefit in electricity sales

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16

Yang, Ying, Weibin Huang, Guangwen Ma, Shijun Chen, Gang Liu, and Yue Liu. "Combined Bidding Strategy of Multi-owner Cascaded Hydropower Stations in Day-Ahead Market." MATEC Web of Conferences 246 (2018): 02036. http://dx.doi.org/10.1051/matecconf/201824602036.

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Under the background of the electricity market reform, if the multi-owner cascade hydropower stations bid separately, the overall competitive advantages of river basin cannot be exerted, and the overall benefits cannot achieve the maximization. Based on the operation characteristics of cascade hydropower stations and the rule of competitive bidding, this paper established a bi-level optimal model for bidding game in day-ahead market, and used the Nash equilibrium principle of the game theory and genetic algorithm to solve this model, the optimal bidding strategies of the multi-owner cascade hydropower stations have been solved under the circumstances of bidding by oneself and alliance. The results from the calculating examples showed that the unified price declaration of the multi-owner cascade hydropower stations in day-ahead market can improve the overall and individual generation efficiency, and proved the effectiveness and feasibility of the combined bidding strategy in power market.

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17

Rathnayake, Namal, Upaka Rathnayake, Tuan Linh Dang, and Yukinobu Hoshino. "A Cascaded Adaptive Network-Based Fuzzy Inference System for Hydropower Forecasting." Sensors 22, no. 8 (April 10, 2022): 2905. http://dx.doi.org/10.3390/s22082905.

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Hydropower stands as a crucial source of power in the current world, and there is a vast range of benefits of forecasting power generation for the future. This paper focuses on the significance of climate change on the future representation of the Samanalawewa Reservoir Hydropower Project using an architecture of the Cascaded ANFIS algorithm. Moreover, we assess the capacity of the novel Cascaded ANFIS algorithm for handling regression problems and compare the results with the state-of-art regression models. The inputs to this system were the rainfall data of selected weather stations inside the catchment. The future rainfalls were generated using Global Climate Models at RCP4.5 and RCP8.5 and corrected for their biases. The Cascaded ANFIS algorithm was selected to handle this regression problem by comparing the best algorithm among the state-of-the-art regression models, such as RNN, LSTM, and GRU. The Cascaded ANFIS could forecast the power generation with a minimum error of 1.01, whereas the second-best algorithm, GRU, scored a 6.5 error rate. The predictions were carried out for the near-future and mid-future and compared against the previous work. The results clearly show the algorithm can predict power generation’s variation with rainfall with a slight error rate. This research can be utilized in numerous areas for hydropower development.

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18

Liu, Shuangquan, Xuhan Luo, Hao Zheng, Congtong Zhang, Youxiang Wang, Kai Chen, and Jinwen Wang. "Investigation on Water Levels for Cascaded Hydropower Reservoirs to Drawdown at the End of Dry Seasons." Water 15, no. 2 (January 16, 2023): 362. http://dx.doi.org/10.3390/w15020362.

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Operators often have a dilemma in deciding what water levels the over-year hydropower reservoirs should drawdown at the end of dry seasons, either too high to achieve a large firm hydropower output during the dry seasons in the current year and minor spillage in coming flood seasons, or too low to refill to the full storage capacity at the end of the flood seasons and a greater firm hydropower output in the coming year. This work formulates a third-monthly (in an interval of about ten days) hydropower scheduling model, which is linearized by linearly concaving the nonlinear functions and presents a rolling strategy to simulate many years of reservoir operations to investigate how the water level at the end of dry seasons will impact the performances, including the energy production, firm hydropower output, full-refilling rate, etc. Applied to 11 cascaded hydropower reservoirs in a river in southwest China, the simulation reveals that targeting a drawdown water level between 1185–1214 m for one of its major over-year reservoirs and 774–791 m for another is the most favorable option for generating more hydropower and yielding larger firm hydropower output.

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Huang, Shuo, Xinyu Wu, Yiyang Wu, and Zheng Zhang. "Mid-Term Optimal Scheduling of Low-Head Cascaded Hydropower Stations Considering Inflow Unevenness." Energies 16, no. 17 (September 2, 2023): 6368. http://dx.doi.org/10.3390/en16176368.

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China has a vast scale of hydropower, and the small hydropower stations account for a large proportion. In flood season, the excessive inflow keeps these stations at a high reservoir level, leading to a worse condition of hindered power output and a great error in the calculation of power generation. Therefore, this paper proposes a mid-term optimal scheduling model for low-head cascaded hydropower stations considering inflow unevenness, in which the power output is controlled by the expected power output curve and daily inflow–maximum power output curve. A case study of nine hydropower stations on the Guangxi power grid shows that, regardless of considering the fitted curve or not, there are different degrees of error between the planned and actual situations. However, the error and power generation are decreased when considering the fitted curve, which reflects the impact of hindered power output. Meanwhile, according to the comparison, the weekly plan is more in line with the real condition when using this model to solve the problem. The results indicate that this model improves the accuracy of power output calculation for low-head hydropower stations with uneven inflow, playing a key role in the process of scheduling.

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20

Feng, Zhong-Kai, Wen-Jing Niu, Jian-Zhong Zhou, and Chun-Tian Cheng. "Multiobjective Operation Optimization of a Cascaded Hydropower System." Journal of Water Resources Planning and Management 143, no. 10 (October 2017): 05017010. http://dx.doi.org/10.1061/(asce)wr.1943-5452.0000824.

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21

Ogunbiyi, Olalekan, Cornelius T. Thomas, Oludare Y. Ogundepo, Isaac O. A. Omeiza, Jimoh Akanni, and B. J. Olufeagba. "A steepest descent algorithm for the optimal control of a cascaded hydropower system." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 4 (August 1, 2020): 4136. http://dx.doi.org/10.11591/ijece.v10i4.pp4136-4144.

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Optimal power generation along the cascaded Kainji-Jebba hydroelectric power system had been very difficult to achieve. The reservoirs operating heads are being affected by possible variation in impoundments upstream, stochastic factors that are weather-related, availability of the turbo-alternators and power generated at any time. Proposed in this paper, is an algorithm for solving the optimal release of water on the cascaded hydropower system based on steepest descent method. The uniqueness of this work is the conversion of the infinite dimensional control problem to a finite one, the introduction of clever techniques for choosing the steepest descent step size in each iteration and the nonlinear penalty embedded in the procedure. The control algorithm was implemented in an Excel VBA® environment to solve the ormulated Lagrange problem within an accuracy of 0.03%. It is recommended for use in system studies and control design for the optimal power generation in the cascaded hydropower system.

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Guo, Yuxue, Guohua Fang, Xin Wen, Xiaohui Lei, Yu Yuan, and Xiaoying Fu. "Hydrological responses and adaptive potential of cascaded reservoirs under climate change in Yuan River Basin." Hydrology Research 50, no. 1 (March 5, 2018): 358–78. http://dx.doi.org/10.2166/nh.2018.165.

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Abstract The ongoing cascading hydropower exploitation in southwestern China has been the subject of debate and conflict in recent years. This study aims to assess the climate change impacts on the hydropower system of Yuan River and to quantify the future potential in operation optimization of Gasa-Madushan (GS-MDS) Reservoir system. The Community Climate System Model version 4 (CCSM4) projections are bias-corrected and downscaled to drive the Soil and Water Assessment Tool hydrological model, aiming to predict the climate and runoff changes for the future. Then, an adaptive operation chart model of cascaded reservoirs is established to balance hydropower generation and ecological requirements under climate change. In the future, the decadal average temperature and annual average precipitation will possibly increase by 0.80–2.22 °C and 2.56–4.65%, respectively; the monthly average runoff may increase by 6.89%, 6.17%, and 18.26% for GS Reservoir Basin, and by 8.89%, 8.14%, and 23.14% for MDS Reservoir Basin under Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5, respectively. The adaptive operation chart results in a reduction of 52.66–70.77% in the total water shortage at a cost of 2.09–4.54% decrease in total power generation of the GS-MDS cascaded hydropower system compared to that of non-adaptive operation chart.

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23

Shen, Jianjian, Chuntian Cheng, Jun Zhang, and Jianyu Lu. "Peak Operation of Cascaded Hydropower Plants Serving Multiple Provinces." Energies 8, no. 10 (October 13, 2015): 11295–314. http://dx.doi.org/10.3390/en81011295.

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24

Zeng, Yun, Xinyu Wu, Chuntian Cheng, and Yuqian Wang. "Chance-Constrained Optimal Hedging Rules for Cascaded Hydropower Reservoirs." Journal of Water Resources Planning and Management 140, no. 7 (July 2014): 04014010. http://dx.doi.org/10.1061/(asce)wr.1943-5452.0000427.

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25

Li, Yang, Feng Wu, Xudong Song, Linjun Shi, Keman Lin, and Feilong Hong. "Data-Driven Chance-Constrained Schedule Optimization of Cascaded Hydropower and Photovoltaic Complementary Generation Systems for Shaving Peak Loads." Sustainability 15, no. 24 (December 17, 2023): 16916. http://dx.doi.org/10.3390/su152416916.

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The coordinated scheduling of cascade hydropower with photovoltaic (PV) power stations can significantly improve the utilization rate of delivery transmission lines. However, the inherent uncertainty associated with photovoltaic (PV) forecasts challenges the reliable and economic operation of the complementary energy system. Against this background, in this paper, a day-ahead, chance-constrained scheduling for cascaded hydro–photovoltaic complementary generation systems (CHPSs) considering the transmission capacity is proposed. Firstly, the uncertainty of PV forecast errors is simulated by a probability density function fitted using kernel density estimation with historical sampling data. Then, a chance-constrained optimization model considering peak-shaving demands of the receiving-end power grid is developed to determine the day-ahead optimal schedules of CHPSs. Also, complex hydraulic coupling and unit operation constraints of cascade hydropower are considered in the proposed model. To deal with the nonlinear and stochastic constraints, an efficient linearization method is adopted to transform the proposed model into a mixed-integer linear programming (MILP) problem. Finally, the effectiveness and feasibility are verified by case studies. The results show that the day-ahead schedule optimized by the proposed method can fully balance peak-shaving and photovoltaic accommodation while considering photovoltaic output uncertainty.

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26

Wu, Xinyu, Yiyang Wu, and Qilin Ying. "Research on Dynamic Programming Game Model for Hydropower Stations." Mathematical Problems in Engineering 2022 (August 17, 2022): 1–11. http://dx.doi.org/10.1155/2022/1458388.

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In the condition of the electricity market, the benefit is the result of market gaming for hydropower stations with price-making ability. The traditional energy maximization model is not appropriate in this circumstance. To study long-term operation variation in the market, a dynamic programming game model of hydropower stations is proposed to obtain a Nash equilibrium solution in long-term time series. A dynamic programming algorithm iteratively solves the model. The proposed approach is applied to hydropower stations of Longtan, Xiaowan, and Goupitan in a hypothetical pure hydropower market. The results show that the dynamic programming game model clearly outperforms the energy maximization model in terms of hydropower station benefit, and the operation results differences using the game model and optimization model are analyzed. For the studied cascaded reservoirs, the benefit increasing percentages can be 4.1%–8.2% with 0.2%–3.8% energy loss in this hypothetical electricity market, comparing the game model to the energy maximization model.

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27

Song, Heng Li, and Chao Yuan Yue. "A Dynamic Game Approach for Analyzing the Coalitional Stability of Cascaded Hydropower Stations." Advanced Materials Research 562-564 (August 2012): 1544–48. http://dx.doi.org/10.4028/www.scientific.net/amr.562-564.1544.

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A game model is proposed to discuss the possible coalition structures of hydropower stations. The stable coalition structures in different contexts of electricity markets are derived on basic of numerical simulation using the raw data of three hydropower stations on the middle and lower reaches of some river in China's south-western region as a case. The coalitional stability is analyzed by a dynamic cooperation game approach using the conception of LCS and EPCS. The total purchase power fees of the grid in three coalition structures are calculated and compared to analyze the effects of coalition structures on the social benefit.

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28

Lu, Ying, Jiaping Gu, Liang Li, Jia Zhou, and Shikai Zhang. "Research on the capacity allocation of basin hydropower-photovoltaic-storage hybrid power generation system based on flexibility of hydropower and pumped storage power stations." Journal of Physics: Conference Series 2427, no. 1 (February 1, 2023): 012011. http://dx.doi.org/10.1088/1742-6596/2427/1/012011.

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Abstract The development and utilization of basin hydropower-photovoltaic-storage integrated energy system aim to smooth out the fluctuation of new energy generation capacity with the regulating ability of hydropower and pumped-storage power station, thus promoting the large-scale consumption of new energy. For regions rich in water, wind, solar, and pumped-storage resources, the main problem is how to allocate a reasonable scale of photovoltaic and wind power projects according to the scale of regional hydropower and pumped-storage power stations and realize the integrated development of multi-energy complementary. In this paper, based on the complementary power output characteristics of cascaded hydropower stations and regional photovoltaic power stations, and the good energy storage regulation of pumped-storage power stations, a capacity optimization model of basin hydropower-photovoltaic-storage hybrid power generation system with the goal of economic optimization under multiple constraints is constructed. It was applied to the planning and construction of the clean energy base in the Tibet-Sichuan section upstream of the Jinsha River, and the combined operation of the hydropower-photovoltaic-storage hybrid power generation system was analyzed to verify its feasibility.

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29

Mahmoud, M., K. Dutton, and M. Denman. "Dynamical modelling and simulation of a cascaded reserevoirs hydropower plant." Electric Power Systems Research 70, no. 2 (July 2004): 129–39. http://dx.doi.org/10.1016/j.epsr.2003.12.001.

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30

Xu, Wei, Xiaoli Zhang, Anbang Peng, and Yue Liang. "Deep Reinforcement Learning for Cascaded Hydropower Reservoirs Considering Inflow Forecasts." Water Resources Management 34, no. 9 (June 27, 2020): 3003–18. http://dx.doi.org/10.1007/s11269-020-02600-w.

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31

Marcial, Alexander Svensson, and Magnus Perninge. "Production Planning of Cascaded Hydropower Stations using Approximate Dynamic Programming." IFAC-PapersOnLine 56, no. 2 (2023): 10069–76. http://dx.doi.org/10.1016/j.ifacol.2023.10.876.

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32

Li, Yang, Ni Fang, Shengming He, Feng Wu, Outing Li, Linjun Shi, and Renshan Ding. "Two-Stage Stochastic Scheduling of Cascaded Hydropower–Wind–Photovoltaic Hybrid Systems Considering Contract Decomposition and Spot Market." Sustainability 16, no. 3 (January 27, 2024): 1093. http://dx.doi.org/10.3390/su16031093.

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With the advancement of China’s electricity markets and the continuous development of renewable energy sources (RESs), it is of great importance to investigate the strategic behavior of RESs in electricity markets. In this paper, a two-stage stochastic optimization model is proposed for a hybrid energy system composed of cascade hydropower plants, wind farms, and photovoltaic stations. Firstly, typical scenarios are generated based on Latin hypercube sampling (LHS) and the K-means clustering algorithm to represent uncertainties of wind–photovoltaic power outputs. Then, with an analysis of China’s electricity market structure, a two-stage coordinated scheduling model of hydropower–wind–photovoltaic hybrid systems in electricity markets is established with the objective of maximizing total revenues considering bilateral contract decomposition, the day-ahead energy market, and the real-time balance market. In addition, the proposed model is transformed into a mixed-integer linear programming (MILP) problem for computational convenience. As shown in an analysis of case studies, cascade hydropower plants can compensate for the fluctuation in wind and photovoltaic power outputs to reduce financial risks caused by uncertainties of wind and photovoltaic power generation. Simulation results show that compared with uncoordinated operation, the coordinated operation of hydropower–wind–photovoltaic hybrid systems increases total revenue by 1.08% and reduces the imbalance penalty by 29.85%.

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33

Wu, Yang, Wang Xia, Jinwen Wang, Shuangquan Liu, Binbin Zhou, Zhenyu Zhao, and Cheng Chen. "Comparison of Procedures to Combine Operating Zones of Multiple Units into Plant-Based Operating Zones." Energies 16, no. 3 (February 1, 2023): 1435. http://dx.doi.org/10.3390/en16031435.

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The hydropower unit commitment (HUC) is often indirectly considered by combining individual units in a hydropower plant into a plant-based generator to alleviate the dimensional difficulty in short-term hydropower scheduling of cascaded reservoirs. This work presents three procedures to combine operating zones of units in a hydropower plant into the plant-based operating zones, including an exhaustive method (M01) that enumerates all the possible combinations, a discrete method (M03) that investigates discrete values to see if they are in an operating zone, and a bound oriented method (M04) that explores new operating zones with an optimization solver. The procedures are compared with a previous one (M02) that merges the operating zones of a unit one by one in order. The experiments of the methods in 11 case studies involving a variety of hydropower plants reveal that the second method (M02) should always be recommended due to its strength, which is even more prominent than any other methods in dealing with large-scale problems, and errors occur when using interpolation to estimate the plant-based operating zones at a water head between two sampling water heads.

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34

Zhang, Shuai, Jingxian Yang, Hongjun Gao, Jichun Liu, and Junyong Liu. "Probabilistic Chronological Production Simulation-Based Coordinated Dispatching for Cascaded Hydro-PV-PSH Combined Power Generation System." Mathematical Problems in Engineering 2020 (December 29, 2020): 1–14. http://dx.doi.org/10.1155/2020/6677301.

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The comprehensive and effective utilization of multiple renewable sources involving water, solar, and other energies have been receiving more and more attention, and the coordinated dispatching considering multiple uncertainties has become one of the research focuses currently. To cope with the stochastic dispatching of cascaded hydro-PV-PSH (pumped storage hydropower, PSH) complementary power generation system, this paper has proposed a two-stage optimized dispatching method combining uncertainties simulation and complementary dispatching schemes optimization. Firstly, a modified PCPS (probabilistic chronological production simulation) method is proposed to simulate the uncertain power output of each energy type, and thus the complementary dispatching schemes and performance parameters are obtained. In the simulation process, a special treatment method combining overall uncertainties, overall dispatching measures, and interstage distribution for cascaded hydropower stations is given out. Secondly, a dual-objective optimized model considering reliability and economic performance and MOQPSO algorithm is introduced to calculate the optimal Pareto solution set of stochastic dispatching schemes. The results of the case study verified the feasibility and calculating performance of the proposed method in developing optimized dispatching schemes.

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35

Liao, Shengli, Yan Zhang, Benxi Liu, Zhanwei Liu, Zhou Fang, and Shushan Li. "Short-Term Peak-Shaving Operation of Head-Sensitive Cascaded Hydropower Plants Based on Spillage Adjustment." Water 12, no. 12 (December 8, 2020): 3438. http://dx.doi.org/10.3390/w12123438.

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There are many cascaded hydropower plants with poor regulation performance and sensitive water heads accompanied by water spillage during the wet season. Faced with the increasing load peak–valley differences, it is necessary to tap the peak-shaving potential of such head-sensitive cascaded hydropower plants (HSCHPs) because relying solely on hydropower plants with better regulation performance for peak shaving is inadequate. To address the modeling, solving, and water spillage treatment difficulties posed by HSCHPs, a new short-term peak-shaving method based on spillage adjustment is introduced. First, fuzzy cluster analysis is used to determine when to release more water spillage by automatically identifying valley periods of the daily load curve. Furthermore, a spillage adjustment strategy, implemented through an easy gate operation, is adopted to readjust the water release during each period of the load curve. The ratio of the water spillage released in advance in a certain period to its total water spillage is defined as the water spillage ratio (WSR) of the period. Finally, a mixed-integer linear programming model linearized by special ordered sets of type two is solved to determine the optimal WSRs, which achieves the optimal peak-shaving effect. HSCHPs in the Hongshui River Basin during the wet season were selected as case studies. The results demonstrate that the proposed method can achieve a good peak-shaving effect without significantly reducing the power generation and adding additional water spillage.

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36

Fekete, Krešimir, Srete Nikolovski, Zvonimir Klaić, and Ana Androjić. "Optimal Re-Dispatching of Cascaded Hydropower Plants Using Quadratic Programming and Chance-Constrained Programming." Energies 12, no. 9 (April 27, 2019): 1604. http://dx.doi.org/10.3390/en12091604.

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Stochastic production from wind power plants imposes additional uncertainty in power system operation. It can cause problems in load and generation balancing in the power system and can also cause congestion in the transmission network. This paper deals with the problems of congestion in the transmission network, which are caused by the production of wind power plants. An optimization model for corrective congestion management is developed. Congestions are relieved by re-dispatching several cascaded hydropower plants. Optimization methodology covers the optimization period of one day divided into the 24 segments for each hour. The developed optimization methodology consists of two optimization stages. The objective of the first optimization stage is to obtain an optimal day-ahead dispatch plan of the hydropower plants that maximizes profit from selling energy to the day-ahead electricity market. If such a dispatch plan, together with the wind power plant production, causes congestion in the transmission network, the second optimization stage is started. The objective of the second optimization stage is the minimization of the re-dispatching of cascaded hydropower plants in order to avoid possible congestion. The concept of chance-constrained programming is used in order to consider uncertain wind power production. The first optimization stage is defined as a mixed-integer linear programming problem and the second optimization stage is defined as a quadratic programming (QP) problem, in combination with chance-constrained programming. The developed optimization model is tested and verified using the model of a real-life power system.

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37

Wang, Sen, Jianjian Shen, and Shanzong Li. "A Load-Based Method for Peak Operations of Cascaded Hydropower Stations." IOP Conference Series: Earth and Environmental Science 690, no. 1 (March 1, 2021): 012013. http://dx.doi.org/10.1088/1755-1315/690/1/012013.

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38

Shen, Jianjian. "A Two-Stage Approach for Large-Scale Cascaded Hydropower System Operations." Journal of Water Resource and Protection 06, no. 16 (2014): 1553–60. http://dx.doi.org/10.4236/jwarp.2014.616142.

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39

Shen, Keyan, Hui Qin, and Jianzhong Zhou. "Multi-time-scale nested optimal scheduling model for cascaded hydropower reservoirs." IOP Conference Series: Earth and Environmental Science 768, no. 1 (May 1, 2021): 012012. http://dx.doi.org/10.1088/1755-1315/768/1/012012.

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40

Wu, Xinyu, Chuntian Cheng, Yun Zeng, and Jay R. Lund. "Centralized versus Distributed Cooperative Operating Rules for Multiple Cascaded Hydropower Reservoirs." Journal of Water Resources Planning and Management 142, no. 11 (November 2016): 05016008. http://dx.doi.org/10.1061/(asce)wr.1943-5452.0000685.

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41

Wu, Xinyu, Rui Guo, Xilong Cheng, and Chuntian Cheng. "Combined Aggregated Sampling Stochastic Dynamic Programming and Simulation-Optimization to Derive Operation Rules for Large-Scale Hydropower System." Energies 14, no. 3 (January 26, 2021): 625. http://dx.doi.org/10.3390/en14030625.

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Simulation-optimization methods are often used to derive operation rules for large-scale hydropower reservoir systems. The solution of the simulation-optimization models is complex and time-consuming, for many interconnected variables need to be optimized, and the objective functions need to be computed through simulation in many periods. Since global solutions are seldom obtained, the initial solutions are important to the solution quality. In this paper, a two-stage method is proposed to derive operation rules for large-scale hydropower systems. In the first stage, the optimal operation model is simplified and solved using sampling stochastic dynamic programming (SSDP). In the second stage, the optimal operation model is solved by using a genetic algorithm, taking the SSDP solution as an individual in the initial population. The proposed method is applied to a hydropower system in Southwest China, composed of cascaded reservoir systems of Hongshui River, Lancang River, and Wu River. The numerical result shows that the two-stage method can significantly improve the solution in an acceptable solution time.

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42

Feng, Suzhen, Hao Zheng, Yifan Qiao, Zetai Yang, Jinwen Wang, and Shuangquan Liu. "Weekly hydropower scheduling of cascaded reservoirs with hourly power and capacity balances." Applied Energy 311 (April 2022): 118620. http://dx.doi.org/10.1016/j.apenergy.2022.118620.

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43

Hongjiang, Liu, Xie Hongzhong, Chen Lihui, Gan Shu, Zhang Jun, and Wei Fangqiang. "Monitoring of land-cover dynamic change in Lancangjiang River cascaded Hydropower Area." Wuhan University Journal of Natural Sciences 11, no. 4 (July 2006): 1015–20. http://dx.doi.org/10.1007/bf02830203.

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44

Zhou, Shuchan, Tao Tang, Naicheng Wu, Xiaocheng Fu, Wanxiang Jiang, Fengqing Li, and Qinghua Cai. "Impacts of cascaded small hydropower plants on microzooplankton in Xiangxi River, China." Acta Ecologica Sinica 29, no. 1 (June 2009): 62–68. http://dx.doi.org/10.1016/j.chnaes.2009.04.008.

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45

武, 新宇. "A Fast Algorithm for Short Term Scheduling of Cascaded Hydropower Reservoir Systems." Journal of Water Resources Research 07, no. 03 (2018): 236–50. http://dx.doi.org/10.12677/jwrr.2018.73026.

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46

Shen, Jianjian, Chuntian Cheng, Xiufei Zhang, and Binbin Zhou. "Coordinated operations of multiple-reservoir cascaded hydropower plants with cooperation benefit allocation." Energy 153 (June 2018): 509–18. http://dx.doi.org/10.1016/j.energy.2018.04.056.

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47

Kang, Chuanxiong, Cheng Chen, and Jinwen Wang. "An Efficient Linearization Method for Long-Term Operation of Cascaded Hydropower Reservoirs." Water Resources Management 32, no. 10 (April 28, 2018): 3391–404. http://dx.doi.org/10.1007/s11269-018-1997-2.

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48

Zhang, Chun-ze, Yong-guang Cheng, Jia-yang Wu, and Wei Diao. "Lattice Boltzmann simulation of the open channel flow connecting two cascaded hydropower stations." Journal of Hydrodynamics 28, no. 3 (June 2016): 400–410. http://dx.doi.org/10.1016/s1001-6058(16)60643-1.

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49

CHENG, ChunTian, Xiong CHENG, XinYu WU, and JianJian SHEN. "A hybrid nonlinear optimization method for operation of large-scale cascaded hydropower plants." SCIENTIA SINICA Technologica 44, no. 3 (March 1, 2014): 306–14. http://dx.doi.org/10.1360/092013-1195.

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50

CHENG, ChunTian, XinYu WU, BaoJian LI, and Sen WANG. "Parallel stochastic dynamic programming for long-term generation operation of cascaded hydropower stations." SCIENTIA SINICA Technologica 44, no. 2 (February 1, 2014): 209–18. http://dx.doi.org/10.1360/092013-800.

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