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Electricity transmission in a grid-connected system provides an effective solution to promoting clean energy accommodation. However, with arbitrary determination in current operation models, the clean energy utilization ratio (CEUR) is not satisfactory largely due to the lack of electricity curtailment (the electricity equivalent of clean energy curtailment) cost-dependent optimization. In this study, a curtailment cost-dependent multi-objective operation (CCMO) model was proposed to complementarily operate a grid-connected hybrid energy system, identify optimal CEUR, and thus maximally reduce electricity curtailment. The CCMO model centers on coupling the punishment cost of electricity curtailment with the multi-objective function defined as the total cost of each grid component. The CCMO model was solved to derive the optimal equilibrium solution determined based on multiple non-dominated solutions. A grid-connected hybrid energy system including the Yunnan, Guangdong, and Guangxi Power Grids was used to test the model performance. The results showed that the CCMO model’s CEUR was up to 100% at hourly scale and 96.9% on daily average, which were both significantly higher than those in the current operation models. Furthermore, the CCMO’s optimal equilibrium solution, i.e., respective minimum total cost of each grid component, can also identify optimal transmission schemes of the daily channel utilization to make the peak utilization hours largest.

A new improved shuffled frog leaping algorithm (SFLA), the chaos catfish effect SFLA (CCESFLA), is proposed by coupling a local “refine search” mechanism and a “global incentive adjustment” mechani...

Power generation plan formulated based on the forecasted runoff is an important basis for the actual operation of hydropower station. However, due to the forecast error, the load adjustment is necessary in the actual operation, and how to find out the most satisfactory load adjustment scheme from the scheme set is an important topic. So, in order to comprehensively reflect the risk and benefit state of hydropower station operation, a risk-benefit collaborative evaluating indicator system of load adjustment scheme is established firstly in this paper, and aim at the strong subjectivity of present evaluation methods, an improved grey target decision model based on moment estimation method is proposed, and the combinatorial weight integration technology and the Mahalanobis distance are coupled in this model. Taking the cascade hydropower stations of Yalong River in China as an instance, six schemes are evaluated by the proposed model, and the results are compared and analyzed with another six evaluation models. Results show that the proposed model can effectively coordinate different weighting methods and overcome the shortcomings of traditional grey target decision model about the insufficient consideration on the importance and correlation of evaluating indicators, and it has a good value of popularization and application.

With the rapid development of cascade reservoirs, the joint operation chart of cascade reservoirs and its optimization methods have been widely researched. Aimed at the defects of the conventional two-stage Progressive Optimality Algorithm (POA) in the optimization of energy storage operation chart, this paper proposed a new multi-stage POA optimization model. It took the traditional reverse calculation result as the initial solution, and expanded the two-stage optimization mode of conventional POA to three-stage mode, four-stage mode, or higher stages mode, and implemented the iterative calculation by taking the result of lower stages POA as the input of higher stages POA, until the result converged. In addition, enumeration method was used to iterate over all the possible combinations in local optimization to improve the efficiency of local search. In order to test and verify the rationality and validity of the proposed model, two cascade reservoirs had been taken as the instances of case study, compared with conventional two-stage POA, results showed that the power generation of Li Xianjiang and Three Gorges cascade reservoirs by the proposed multi-stage POA can respectively increase by 0.055% ($32000) and 0.077% ($3900000). So the economic benefits are remarkable, and the proposed model is reasonable and effective.

Difficulty remains to represent water propagation impact to construct water balance constraints for the Short-Term Cascade Reservoirs Optimal Operation (SCROO), due to the complex water propagation mechanism existing between cascade reservoirs. The imprecise representation of water propagation impact hinders the implementation of hydropower generation schemes and leads to operational risks. Thus, a modified SCROO model considering water propagation impact was proposed in this study to improve the accuracy of cascade operation. Specifically, water propagation is expressed using the Muskingum method in the modified SCROO model, and characterized by two variables, including propagation time related to the magnitude of the upstream reservoir’s outflow and flow attenuation related to the propagation time, which were identified using the successive approximation method under water balance constraints within the modified SCROO model. Subsequently, this research applied the Nested Progressive Optimality Algorithm (NPOA) in the model calculation innovatively, in which the stage benefit function and nest computation could be improved. The modified model and algorithm developed herein were applied and validated on cascade reservoirs along the Yalung River in China by comparing it with traditional methods and algorithms. The results show that: 1) Compared to traditional methods, considering water propagation within water balance constraints as a dynamic parameter can calculate the inflow of downstream reservoir more accurately and mitigate risks in the actual operation of cascade reservoirs. Besides, the reservoir inflow calculated by traditional methods will lead to different magnitudes of benefit loss; and 2) the NPOA can significantly reduce dimensionality problems caused by the water propagation impact and greatly improve the actual hydropower generation than that of a traditional optimal algorithm, Multi-Stage Dynamic Programming (MSDP). Compared to the MSDP, the NOPA is more applicable in a cascade system with a larger number of reservoirs. The modified model and algorithm can significantly improve the effectiveness of cascade reservoir optimal operation schemes and provide more information for decision-makers.

The uncertainty of streamflow forecast will cause the ineffectiveness on the short-term hydropower station optimal operation (SHSOO) and lead to the risk of producing less hydropower than planned. Traditionally, stochastic optimal theory represented by the stochastic dynamic programming model (SDPM) is commonly used for SHSOO, which is focus on the uncertainty during a single lead time and lack of an overall consideration of multiple independent lead times of differing length. Thus, this paper proposes a short-term hydropower station optimal operation model based on mean-variance theory (MV-SHSOOM) for reducing operational risk. The proposed multi-step model considers the forecasting uncertainty of different lead times as an integral component to guide a station’s optimal operation. Specifically, the forecast uncertainty was integrated by the joint probability distribution of forecast error using a multivariate hydrologic uncertainty processor (HUP) at first. Then, possible observed streamflow sequences were obtained using the joint probability distribution of forecast error and taken as input to the short-term optimal operation model of the hydropower station. Finally, the mean-variance theory was applied to construct the optimal operation model for balancing the power generation and operational risk. The proposed model was applied to the Jinxi hydropower station, China, to determine its performance. The results show that: 1) the dependent structure among the forecast errors at different lead times is significant in terms of Spearman correlation, and the joint probability distribution of forecast error can be effectively described by a multivariate HUP; 2) the proposed MV-SHSOOM is superior to the traditional deterministic dynamic programming model (DDPM) and SDPM, and can more effectively reduce operational risk while increasing power generation.

In order to allocate the raw water of the complex water supply system in Shenzhen reasonably, this paper studied the complex network relationship of this large-scale urban water supply system, which consists of 46 reservoirs, 67 waterworks, 2 external diversion water sources, 14 pumping stations and 9 gates, and described each component of the system with the concepts of point, line and plane. Using the topological analysis technology and graph theory, a generalized model of the network topological structure of the urban water allocation system was established. On this basis, combined with the water demand prediction and allocation model of waterworks, a water resources allocation model was established, aiming at satisfying the guaranteed rate of the water supply. The decomposition and coordination principle of the large-scale system and the dynamic simulation technology of the supply-demand balance were adopted to solve the model. The forward calculation mode of controlling waterworks and pumps, and the reverse calculation mode of controlling reservoirs and waterworks were designed in solving the model, and a double-layer feedback mechanism was formed, which took the reverse calculation mode as outer feedback and the reservoir water level constraint or pipeline capacity constraint as inner feedback. Through the verification calculation of the case study, it was found that the proposed model can deal well with the raw water allocation of a large-scale complex water supply system, which had an important application value and a practical significance.

Summary The dynamic control operation of reservoir flood limited water level (FLWL) can solve the contradictions between reservoir flood control and beneficial operation well, and it is an important measure to make sure the security of flood control and realize the flood utilization. The dynamic control bound of FLWL is a fundamental key element for implementing reservoir dynamic control operation. In order to optimize the dynamic control bound of FLWL by considering flood forecasting error, this paper took the forecasting error as a fuzzy variable, and described it with the emerging credibility theory in recent years. By combining the flood forecasting error quantitative model, a credibility-based fuzzy chance constrained model used to optimize the dynamic control bound was proposed in this paper, and fuzzy simulation technology was used to solve the model. The FENGTAN reservoir in China was selected as a case study, and the results show that, compared with the original operation water level, the initial operation water level (IOWL) of FENGTAN reservoir can be raised 4 m, 2 m and 5.5 m respectively in the three division stages of flood season, and without increasing flood control risk. In addition, the rationality and feasibility of the proposed forecasting error quantitative model and credibility-based dynamic control bound optimization model are verified by the calculation results of extreme risk theory.

An efficient reservoir operation technique plays a very important role in improving the water resources and energy efficiency of reservoirs. In order to effectively avoid or alleviate the “curse of dimensionality” of Multi-dimensional Dynamic Programming (MDP) in the application of cascade reservoirs operation optimization (CROO) and keep a global convergence at the same time, two dimension reduction methods are proposed in this paper. One is a hybrid algorithm of MDP and a Progressive Optimality Algorithm (POA), named MDP-POA, which combines the global convergence of MDP and the strong local search ability of POA. MDP-POA first takes the global optimal trajectory of MDP in a low discrete degree as the initial trajectory of the POA, and then implements further optimization to the obtained initial trajectory by the POA with a high discrete degree, so as to avoid the “curse of dimensionality” of MDP in high discrete degree and the dependency of the POA for the initial trajectory. The other is an improved MDP (IMDP), which first constructs a corridor by the optimal trajectory of MDP in a lower discrete degree, and then implements further optimization in the corridor by MDP with a relatively high discrete degree, so as to avoid a large number of unnecessary calculations, and shorten the run-time effectively. In a case study, the results of MDP-POA, IMDP, and MDP are compared and analyzed from the aspects of power generation and run-time. The analysis indicates that the proposed MDP-POA and IMDP both have a good application effect and are worthy of further promotion.

With the rapid development of cascade hydropower stations in recent decades, the cascade system composed of multiple reservoirs needs unified operation and management. However, the output distribution problem has not yet been solved reasonably when the total output of cascade system obtained, which makes the full utilization of hydropower resources in cascade reservoirs very difficult. Discriminant criterion method is a traditional and common method to solve the output distribution problem at present, but some shortcomings cannot be ignored in the practical application. In response to the above concern, this paper proposes a new total output operation chart optimization model and a new optimal output distribution model, the two models constitute to a double nested model with the goal of maximizing power generation. This paper takes the cascade reservoirs of Li Xianjiang River in China as an instance to obtain the optimal total output operation chart by the proposed double nested model and the 43 years historical runoff data, progressive searching method and progressive optimality algorithm are used in solving the model. In order to take the obtained total output operation chart into practical operation, mean value method and stepwise regression method are adopted to extract the output distribution ratios on the basis of the optimal simulation intermediate data. By comparing with discriminant criterion method and conventional method, the combined utilization of total output operation chart and output distribution ratios presents better performance in terms of power generation and assurance rate, which proves it is an effective alternative method to deal with the cascade reservoirs joint operation problem.

Ji, C. and Wu, H., 2019. Medium and long term optimal scheduling of cascade hydropower stations based on topological parallel computing. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 572–577. Coconut Creek (Florida), ISSN 0749-0208.In order to shorten the calculating time effectively for solving the medium-and-long term optimal scheduling model of cascade hydropower stations, based on the decomposition and coordination method of large-scale system, topological parallel computing is proposed in this paper. Then, taking the cascade hydropower station system located in one watershed of Southwest China as an example, the decomposition and coordination topology parallel computing method is validated in its medium-and-long term optimal scheduling of power generation. It provides a new research direction for improving the calculating efficiency of the optimal scheduling model of giant hydropower stations, the purpose of which is to make full use of water resources.

To narrow the gap between theoretical research and practical application of short-term optimal reservoir power generation operation under uncertain conditions, a comprehensive study is conducted on the formulation, evaluation, and implementation of operation schemes throughout the entire procedure of optimal operation. Firstly, the three implementation modes of the optimal operation scheme are assessed with the post-evaluation method. After the optimal implementation mode is determined, the formulation and implementation of optimal operation schemes are improved by combining the advantages of conventional and optimal operation and using the concept of warning water level in operation rules. Finally, the Xiaoxuan Reservoir is taken as an example for simulation calculation under different operating conditions. The results show that the operation model integrated with operation rules has both the security of conventional operation and the profitability of optimal operation. The accordingly-formulated optimal operation schemes, when implemented with the output control mode, can provide valuable guidance for the actual operation of hydropower stations.

The multidimensional dynamic programming (MDP) algorithm is a traditional method used to solve cascade reservoir operation optimization (CROO) problems, but the high dimensionality called the curse of dimensionalitycannot be ignored. In order to alleviate this problem, this paper proposes a new MDP algorithm named multilayer nested multidimensional dynamic programming (MNDP), which is based on a multilayered, nested structure. MNDP is mainly used to deal with computer memory space and computation complexity problems of MDP in CROO, and its recursive equation of reverse recursion calculation and specific calculation steps are presented in detail. This paper takes the cascade reservoirs of the Li Xianjiang River in China as an example to solve the CROO problem with the proposed MNDP. By comparing with the dynamic programming with successive approximations (DPSA) method, MNDP presents better performance in terms of power generation and the assurance rate in wet, normal, dry, and average years. The gl...

Traditional leveling optimization algorithms are confined to such simple situations as single-mode activities and start-to-finish precedence relations with zero time-lag between a pair of activities. However, they are not correspondent with the practical working mode. In this paper, according to the analysis on practical working mode, types of generalized precedence relations between a pair of activities and characteristics of multi-mode activities are studied, and constraints between a pair of activities with generalized precedence relations are established, and an leveling optimization model for multi-mode activities with generalized precedence relations is also constructed. It is proved by examples and comparative analysis that this optimization model is good in effectiveness and practicality.

Niche evolutionary strategy and chaotic searching were introduced into PSO, called as Chaotic Particle Swarm Optimization Algorithm with Niche (CNPSO) in this thesis. Restricted competition selection method was used to establish niche, in which each species excluded each other and dynamically formed their own searching spaces, effectively maintain the diversity of the species, so as to avoid local convergence. The chaotic searching further improved the global optimization searching precision. CNPSO was programmed to do the optimization regulation of 14 cascade hydropower stations with giant reservoirs by 48-year run-off series. With the result showing that CNPSO is highly efficient in optimization searching, capable of solving the complicated multi dimensional, strong-constraint, multi-states, multi-stages and non-linear problems such as optimization regulation of cascade hydropower stations with giant reservoirs.

Stochastic dynamic programming in solving large-scale cascade reservoirs regulation may lead to the curse of dimensionality. This paper applies to system identification theory, by which large-scale cascade reservoirs operation problem is described as an identification system, then select the appropriate equivalence criterion, identify the most similar model to the tested system according to the samples of deterministic optimization progress so as to set up the reservoirs optimal regulation functions to simulate the regulation. Identified reservoirs optimal regulation functions combine the strength of operation chart and optimal algorithm and can overcome the curse of dimensionality. This paper took advantage of 48-year long series of run-off, simulated and calculated the power generation of 14 cascade hydropower stations. With a good simulation result, simulation program can represent the characteristics of optimal regulation of cascade reservoir, which proves compensation benefits of the upstream reservoir to the downstream cascade reservoirs.

The bid evaluation of construction project is a multivariate evaluation. Based on the principal component analysis which is included in multivariate statistical analysis, this paper establishes the multi-index comprehensive bid evaluation model of construction project, and proposes that how to calculate the evaluation index weight by introducing the variance contribution ratio, and that how to determine the number of principal components by making comprehensive consideration with an introduction of accumulated contribution ratio and factor load. Finally, an example is given to prove the convenience and feasibility of this bid evaluation method. This method has some characteristics: It overcomes deficiencies like large number of evaluation indexes, the overlap of the information that contained in evaluation indexes, and the determination of weight is artificial. The results of bid evaluation are objective and reasonable, which are suit for the evaluation of multi-index systems of large construction projects.