Operation Of Cascade Hydropower Stations Research Articles

Multi-objective integrated decision method of cascade hydropower stations based on optimization algorithm and evaluation model

The establishment and functioning of cascade hydropower stations have significantly altered the natural state of rivers, leading to increasingly severe ecological impacts downstream. To mitigate the adverse effects of cascade reservoir impoundment on river ecosystems and achieve the multi-objective goals of hydropower development and environment protection, this study presents an integrated decision model for optimizing the operation of cascade hydropower stations, utilizing the lower Jinsha River as a case illustration. The proposed model comprises three main components: ecological flow calculation, establishment of a multi-objective optimization model, and scheme evaluation. The ecological flow threshold for the river was determined using the Tennant method. The multi-objective optimization model was formulated with objectives including power generation, ecological flow shortage, and navigation disruption days. The NSGA-II algorithm was employed to resolve the optimization framework. The improved TOPSIS method was adopted for evaluating the operation schemes. The case study conducted in the downstream region of the Jinsha River revealed significant conflicts between the objectives of power generation and ecological conservation. Moreover, different typical years exerted a considerable influence on determining the optimal operation scheme. The proposed integrated decision model provides a scientific framework for guiding the water resource dispatching of cascade hydropower stations and achieving the harmonization of economic and ecological benefits. Overall, this research contributes to the academic field by addressing the complex difficulties related to optimizing the operation of cascade hydropower stations while considering ecological concerns. The findings underscore the importance of adopting a comprehensive decision-making approach that integrates multiple objectives and utilizes advanced algorithms for sustainable river management.

Analysis of the suitable ecological flow of benthic animals in the lower reaches of Xiangjiaba Reservoir in the upper reaches of the Yangtze River based on the physical habitat model

Abundant water resources have facilitated the completion and operation of numerous large-scale water conservation projects. However, the operation of cascade hydropower stations has changed the natural hydrological regime of rivers, thereby affecting the integrity and stability of downstream benthic animal habitats. To quantitatively evaluate the impact of infrastructure development, we proposed a coupling of hydrodynamic and habitat models, with benthic animals as indicator species (because they are highly sensitive to hydrological changes). This study established a physical habitat model of benthic animals in the upper reaches of the Yangtze River, from the Xiangjiaba to Zhutuo sections by coupling the MIKE21 hydrodynamic model with a habitat model. This model coupled the changes in hydrological conditions and ecological processes to quantitatively reflect the effects of flow changes on river habitat quality, which can be used to predict the effects of hydrological changes on water ecosystems and provide fundamental information for ecological flow and scheduling decisions. Our results showed that by jointly regulating the suitable outflow of the Xiangjiaba Reservoir and the inflow of the Tuojiang, Minjiang, and Hengjiang rivers (three tributaries with water conservancy projects), the minimum flow in the non-flood season and the maximum flow in the flood season could be controlled more precisely. This increases the suitable habitat area for benthic animals as well as improves the stability of their habitat. This study fills the gap in the physical habitat model of benthic animals in the upper reaches of the Yangtze River as well as enriches the research ideas of ecological flow regulation. Moreover, this indicates the first application of the physical habitat model to the joint ecological flow regulation of the main tributaries, thus opening new directions for the application of the physical habitat model.

Discussion on the monotonicity principle of the two-stage problem in joint optimal operation of cascade hydropower stations

The joint optimal dispatching of cascade hydropower stations aims to maximize economic benefits while satisfying various constraints. However, numerous studies have failed to acknowledge the significance of the intrinsic optimization principle and lack discussion on this issue. This study started with a mathematical principle analysis of the optimization problem and studied the optimality principle puzzle of the joint optimal dispatching of cascade hydropower stations. First, a two-stage optimization problem was constructed to describe the relationship between the variation in discharge and the incremental function of the total energy generation of the reservoir. Subsequently, the first and second derivatives of the cascade total generating capacity increment to cascade reservoir discharge variation were derived, and the existence condition of monotonically decreasing the first derivative was proposed. Moreover, the monotonicity principle was proven through numerical simulations by comparing the optimization results of POA and the monotonicity principle coupled IPOA in the cascade hydropower stations operation of the Jinsha River, it was found that in terms of power generation and computational efficiency, IPOA is superior to POA. Finally, using this optimization principle, the optimal operation mode of the two typical cascade reservoirs was analyzed in the case studies. The example results show that the proposed optimal principle can theoretically analyze and clarify the optimal operation mode of cascade reservoirs, and the operation modes of the two typical cascade reservoirs can provide guidance and reference for the operation modes of cascade reservoirs in real life.

Effect of the quality of streamflow forecasts on the operation of cascade hydropower stations using stochastic optimization models

Effect of the quality of streamflow forecasts on the operation of cascade hydropower stations using stochastic optimization models

Optimal operation of cascade hydropower station based on interior point method

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.

Operation Rule Derivation of Hydropower Reservoirs by Support Vector Machine Based on Grey Relational Analysis

In practical applications, the rational operation rule derivation can lead to significant improvements in the middle and long-term joint operation of cascade hydropower stations. The key issue of actual optimal operation is to select effective attributions from the deterministic optimal operation results, however, there is still no general and mature method to solve this problem. Firstly, the joint optimal operation model of hydropower reservoirs considering backwater effects are established. Then, the dynamic programming and progressive optimality algorithm are applied to solve the joint optimal operation model and the deterministic optimization results are obtained. Finally, the grey relational analysis method is applied to select more effective factors from the obtained results as the input of a support vector machine for further operation rule derivation. The Xi Luo-du and Xiang Jia-ba cascade reservoirs in the upper Yangtze river of China are selected as a case study. The results show that the proposed method can obtain better input factors to improve the performance of SVM, and smallest value of root mean square error by the proposed method of Xi Luo-du and Xiang Jia-ba are 94.33 and 21.32, respectively. The absolute error of hydropower generation for Xi Luo-du and Xiang Jia-ba are 2.57 and 0.42, respectively. Generally, this study provides a well and promising alternative tool to guide the joint operation of hydropower reservoir systems.

A long-term intelligent operation and management model of cascade hydropower stations based on chance constrained programming under multi-market coupling

Under the medium- and long-term electric markets, cascaded hydropower stations face a series of practical challenges due to the uncertainty of inflow and market price. For long-term dispatch scheduling, the allocation of power generation in multimarkets is critical, including clean energy priority consumption market, inter provincial market and intra provincial market in order to maximize the operator’s expected revenue and reduce the market operation risks. Based on the hydro-dominant electricity market structure and settlement rules, we propose a long-term optimal operation method for cascade hydropower stations considering the uncertainty of multiple variables. First, a seasonal autoregressive integrated moving average model is used to handle the time-varying and seasonal characteristics of inflow series by using a copula connect function to fit the joint distribution of the monthly inflow, the clearing price of the intra provincial market and the delivery volume of the inter provincial market. Then, uncertain chance-constrained programming is established. Finally, a developed particle swarm optimization algorithm embedded in a Monte Carlo simulation is solved for hydropower operation policies, and the maximum revenue, resource allocation and scheduling strategy are obtained under the corresponding risk tolerance. Taking the actual data of cascaded hydropower stations in Yunnan Province, China, as an example, a simulation analysis is carried out. The results show that the proposed method can reasonably describe the uncertainty and correlation between the variables, realizing the optimal allocation of resources among multimarkets, and provide references for the long-term optimal operation of cascade hydropower stations in a multimarket environment. The results also show that the decision strategies should be determined considering the decision-maker’s risk preference.

Daily peak shaving operation of cascade hydropower stations with sensitive hydraulic connections considering water delay time

The increasing peak-valley differences pose a major threat to safe operation of the thermal-dominant power grid in China. Cascade hydropower stations, especially for one-reservoir and multi-cascade hydropower stations (OMHS), as the second largest power supply in China form an important part of peak shaving operation. However, nonconvex and nonlinear constraints have made it deeply difficult to perform the daily peak shaving operation (DPSO) of OMHS. In this paper, an improved DPSO model of OMHS considering water delay time is formulated and solved. Firstly, the confluence coefficient method (CCM) is developed to accurately describe the water delay time of OMHS. Secondly, to reduce the errors and water spillage, aggregation of nonlinear constraints, selection of the linearized area and periodic hypothesis are performed. Finally, an MIQP model integrated CCM is established by considering one-reservoir and six-cascade hydropower stations from the Hongshui River of China as a case study. The optimization results demonstrate that the proposed model can accurately simulate real-world system, and the optimized peak-valley differences on typical days in dry season and wet season reduce by 25% and 33%, respectively. Moreover, the CCM can produce more realistic and executable generation scheduling than the state-of-the-art description method of water delay time.

Evolutionary Game Analysis of Tripartite Cooperation Strategy under Mixed Development Environment of Cascade Hydropower Stations

Joint operation of cascade hydropower stations maximizes the utilization rate of water resources of a river basin and the benefit of the entire river system. However, under mixed development environment of cascade hydropower stations, i.e. simultaneous existence of operating and under-construction hydropower stations, the difficulty of the joint operation is increased. Moreover, this difficulty is further enhanced due to the cooperation among multiple stakeholders and uncertain evolutionary characteristic of stakeholder’s strategy. To handle these problems, this paper takes two upstream operating hydropower stations and one downstream hydropower station under construction as research objects, where one of upstream hydropower station locates in a tributary. First, all possible strategy combinations among these three stakeholders are comprehensively analyzed, and the benefit of each stakeholder strategy under each strategy combination is respectively calculated. A tripartite evolutionary game model is then established. It aims at exploring directions and conditions of cooperative and non-cooperative strategies evolving into stable states. Finally, the exploration results find that the strategy evolution of a stakeholder relies on its partners’ behaviors and net benefit of self-behavior; the tripartite cooperation will eventually form four stable states; the conditions for cooperation between upstream and downstream hydropower stations are that the compensation paid by downstream hydropower station is greater than the loss of upstream power generation and downstream project benefit is greater than the sum of compensation expenditure and risk benefit.

Climatic and anthropogenic impacts on water and sediment generation in the middle reach of the Jinsha River Basin

AbstractResponse of water and sediment generation to climate change and anthropogenic activities is becoming a hot topic in the middle reach of the Jinsha River Basin. In this research, coefficients of variation and concentration degree (i.e., Cv and Cd) and double mass curve (DDC) were adopted to examine the changes in water and sediment discharge and their relationships with precipitation. The contribution rates of climatic and anthropogenic factors to water and sediment discharge were assessed through comparisons between the measured and predicted values in the baseline and postbaseline periods in the basin. The main results were: (a) the water and sediment discharges of the basin showed a decreasing trend from 2006 to 2014, with peak points of Cv and Cd of sediment discharge of the basin in 2009 and 2010, respectively; (b) the precipitation had a major influence on water discharge variations, and the peak point of the DDC of the cumulative precipitation and sediment discharge was consistent with the cumulative water and sediment discharge; and (c) under annual and flooding season scales, the contribution rates of anthropogenic factors to water discharge were 63.060% and 70.457%, respectively. The contribution rates of anthropogenic factors on sediment discharge were 84.790% and 85.541%, respectively. The impacts of anthropogenic factors on water and sediment discharge were more significant than the impacts of precipitation, in which the construction and operation of cascade hydropower stations (CHS) were believed to play a crucial role.

An Improved Slime Mold Algorithm and its Application for Optimal Operation of Cascade Hydropower Stations

A recently modern stochastic optimization algorithm has been developed by observing the life of slime mold physarum polycephalum in nature. The algorithm is called the slime mold algorithm (SMA) with an excellent exploratory capacity and exploitation inclination. Still, slipping into optimal local is easy to happen and slowly converges speed while dealing with complicated problems. This article proposes a new process of improving SMA (namely ISMA) by adapting the weight coefficient and cooperating the reverse learning strategy in the expression of agents updating locations to enhance the algorithm’s optimization performance. Many selected benchmark functions and the optimal operation of cascade reservoirs are applied to evaluate the performance of the proposed algorithm. Comparisons of the proposed approach’s results with the various algorithms under the case situations show that the recommended solution produces better performance than the different competing algorithms.

Long-term optimal operation of cascade hydropower stations based on the utility function of the carryover potential energy

Challenge remains to find the optimal carryover storage to balance the immediate and carryover utilities for long-term hydropower reservoir operation due to low forecast accuracy, limited foresight, and complex hydrologic, hydraulic and electric connections between cascade hydropower reservoirs. Thus, this paper proposes a long-term optimal operation model to dynamically control the optimal carryover storages for cascade hydropower reservoirs. First, the carryover utility of cascade hydropower stations is expressed as a function of the carryover potential energy rather than the carryover storage, thus decreasing the function parameters and using the limited prior knowledge. Then, the utility function of the carryover potential energy (UFCPE) is fitted by a quadratic function based on a successive iteration method, based on which a two-stage optimal operation model (TSOOM) is developed to guide the long-term optimal operation of cascade hydropower stations. The case study with five cascade hydropower stations in the Yalong River Basin shows that: 1) UFCPE can be well fitted by a quadratic function, and it increases linearly in the dry season, but monotonically at a decreasing rate in the flood season resulting from a large quantity of surplus water; and 2) The performance of UFCPE-based TSOOM is much superior to those of conventional rules and conventional optimization methods and quite close to that of dynamic programming successive approximation in guiding the long-term cascade hydropower reservoirs operation.

Influence of Power Operations of Cascade Hydropower Stations under Climate Change and Human Activities and Revised Optimal Operation Strategies: A Case Study in the Upper Han River, China

Climate change and human activities are two driving factors that affect the hydrological cycle of watersheds and water resource evolution. As a pivotal input to hydropower stations, changes in runoff processes may reduce the effectiveness of existing operation procedures. Therefore, it is important to analyze the influences of cascade hydropower stations under climate change and human activities and to propose revised optimal operation strategies. For the present study, three runoff series conditions including: Initial runoff, affected by only climate change, and affected by both climate change and human activities are examined by a simulation model to analyze the influence on power generation with four schemes. Additionally, an optimal operation model of cascade power stations is proposed based on the simulation model to generate single and joint optimal operation charts for future hydrological scenarios. The paper also proposes to change human activities based on optimizing operation rules to reduce its influence on downstream power stations. This procedure is theoretically applied and varied for three power stations in the upper Han River, China. The results show that the influence of climate change is greater than that of human activities in that power generation decreased by 17.95% and 12.83%, respectively, whereas combined, there is a reduction of 25.71%. Under existing hydrological conditions, the modified single and joint operation charts would increase power generation by about 32 million and 47 million kWh. Furthermore, after optimizing the upstream project, the abandoned water and power generation of these cascade power stations would reduce by 150 million m3 and 5 million kWh, respectively. This study has practical significance for the efficient operation of cascade hydropower stations and is helpful for developing reservoir operation theory under changing environments.

Optimal Operation of Cascade Hydropower Stations Based on Chaos Cultural Sine Cosine Algorithm

Due to the fact that Sine Cosine Algorithm(SCA) may easily premature convergence, by taking cultural algorithm as the framework of population space and using chaotic search to lead the evolvement of belief space, a new Chaos Cultural Sine Cosine Algorithm (CCSCA) was present in this paper. And the results of typical benchmark functions show that CCSCA has better global searching ability than SCA to avoid the premature phenomenon. Finally, CCSCA was employed for optimal operation of cascade hydropower stations (OOCHS), and case study showed that CCSCA could get satisfying results with high accuracy and fast efficient, thus providing a new efficient method to solve OOCHS.

Short-term hydro generation operation of cascade hydropower stations in Han River, China

Hydropower is a natural renewable energy with outstanding technological superiority in short-term operation. Short-term hydro generation operation (SHGO) requires not only lord dispatch in single station, but also the coordination of hydraulic and electric connection for different stations. In this paper, a coordinated peak shaving operation method of cascade hydropower stations is proposed. Firstly, regular pattern of peak load regulation is analyzed using the load characteristics of power grid. The daily power output of cascade hydropower stations should meet the needs of typical load pattern. In order to satisfy comprehensive utilizations of water resources, the outflow of each reservoir should be no less than the demand of water supply or irrigation. To verify the feasibility and effectiveness of the proposed method, an application of Pankou and Xiaoxuan cascade hydropower stations, located in Hanjiang River in China, is presented in this paper. Simulation results indicate that the proposed method can obtain the maximum peak shaving amplitudes and suggested peak shaving amplitudes at the same time, which satisfies different operation demands of cascade hydropower stations.

The optimal equilibrium operation between power generation and ecology of Qingjiang cascade hydropower stations

Ecological operation of cascade hydropower stations is one of the most important methods for the ecological restoration of a river system. In order to balance the benefits between power generation and ecology of Qingjiang cascade hydropower station, an optimal equilibrium operation method is proposed in this paper. Firstly, the range of ecological flow of the Qingjiang cascade is calculated by using ten-day frequency calculation method. Secondly, an optimal equilibrium operation model by considering the balance between power generation and ecology is established. And then, in order to solve this complex model, a particle swarm optimization based model solution method is proposed, and the evaluation index system of operation schemes is established. Finally, through operation calculation in 2008-2010 years, the results show that compared with the operation scheme considering only power generation benefit, the optimal equilibrium operation scheme increases the runoff ecological dispersion coefficient by 6.90%，reduces the cascade ecological overflow by 7.739 billion m3and the cascade ecological water shortage by 130 million m3, while the cascade power generation decreases slightly by 1.83%. This study provides an effective scientific method for the optimal operation of Qingjiang cascade under the background of Yangtze River protection.

Application of power matching deviation coefficient in drying stage production control of Dadu River cascade hydropower stations

The economic indicators of cascade hydropower stations are the main technical means in the current economic operation management, but there are management loopholes in various economic indicators. Aiming at the particularity of the operation of cascade hydropower stations in dry season and the new form of grid reform, combined with the characteristics of various economic indicators, the power matching deviation coefficient is proposed to hedge the loophole of comprehensive water consumption rate, and the price difference is used to balance the spread between cascade hydropower stations. This indicator can correctly guide production and operation personnel to tap potential and increase efficiency and ensure healthy competition while ensuring the overall economic operation. The evaluation system has a good effect in the actual use of the Dadu River cascade hydropower stations, and has obvious promotion effect on the production control of the cascade hydropower stations.

Research on Short-term Multi-objective Optimization Scheduling oriented Peak Regulation of Power Network

With the succession of river basins and inter-basin hydropower stations, the joint optimal operation of cascade hydropower stations in the river basin has large-scale, nonlinear, strong coupling, and multi-target characteristics, and must consider the effects of hydrometeorology, water demand, and power grid security. Focusing on the preparation of short-term power generation plans for cascade hydropower stations on the Qingjiang River, a comprehensive multi-objetive power generation planning model with the largest total power generation and the least load variance on the power grid is established. Based on the constraint processing method of multi-objective optimization scheduling in long-term, the optimal flow distribution technology is adopted to improve the accuracy of power generation planning. The above model is solved by using SMPSO. The results show that the improved algorithm can effectively overcome the shortcomings of slow convergence speed and easy convergence to local optimum. It can improve the power generation efficiency of the whole cascade while responding to the peaking demand of the power grid and provide a new solution to the short-term power generation planning ideas.

Study on optimization of the short-term operation of cascade hydropower stations by considering output error

The study of reservoir deterministic optimal operation can improve the utilization rate of water resource and help the hydropower stations develop more reasonable power generation schedules. However, imprecise forecasting inflow may lead to output error and hinder implementation of power generation schedules. In this paper, output error generated by the uncertainty of the forecasting inflow was regarded as a variable to develop a short-term reservoir optimal operation model for reducing operation risk. To accomplish this, the concept of Value at Risk (VaR) was first applied to present the maximum possible loss of power generation schedules, and then an extreme value theory-genetic algorithm (EVT-GA) was proposed to solve the model. The cascade reservoirs of Yalong River Basin in China were selected as a case study to verify the model, according to the results, different assurance rates of schedules can be derived by the model which can present more flexible options for decision makers, and the highest assurance rate can reach 99%, which is much higher than that without considering output error, 48%. In addition, the model can greatly improve the power generation compared with the original reservoir operation scheme under the same confidence level and risk attitude. Therefore, the model proposed in this paper can significantly improve the effectiveness of power generation schedules and provide a more scientific reference for decision makers.

A Real-Time Load Distribution Method of Hydro-Thermal Power Grid Based on Working Conditions Self-Matching

Short-term hydro-thermal power optimal dispatch is a classical problem. Traditional scheduling methods cannot meet the requirements of different dispatch periods separately, and can hardly ensure the safety operation of cascade hydropower stations and reduce wasting water. So the problem how to ensure the safety operation of power grid and the rational utilization of water resources should be settled urgently. In order to solve the problem, a real-time load distribution method of hydro-thermal power grid based on working conditions self-matching is proposed in this paper. In the proposed method, working conditions self-matching is proposed to meet the requirements of different dispatch periods separately for ensuring the efficiency and economy of the power grid. Finally, the proposed method is applied to Sichuan power grid to verify its feasibility and effectiveness. Compared to traditional scheduling methods, the proposed method not only has excellent performance in the utilization of water resources but also can meet all constrains of each scheduling period, which provides a new method to solve the real-time load distribution of hydro-thermal power grid.