Reservoir Operating Rule Curves Research Articles

两阶段优化在水库调度图中的应用研究

水库常规调度图按时段出水位确定该时段出力(或出流)决策一般不考虑径流预报，但在水库实际调度中则可利用入库径流预报来提高水库的运行效率。本文基于水库两阶段优化问题，在分析目标函数单调性的基础上，将两阶段优化的理论应用于水库调度图中，并以三峡水库为研究背景，按照原设计调度图和两天预报结果，进行水库调度的优化运行。结果表明：较原模拟结果，优化后可增加年均发电量19.47亿KW·h，显著提高了水库的运行效益。 Generally, inflow forecast is not concerned when using conventional operating rule curves to calculate the output (or outflow) based on initial water level. While in real reservoir operation, inflow forecast can be added to improve the operation efficiency. Based on the reservoir two-stage optimization problem and the analysis of the monotonous of the objective function, the two-stage optimization theory is applied to the reservoir operation rule curves in this paper. With the case study of Three Gorge Reservoir, in accordance with initial operating rule curves and two days inflow forecast, the optimal operation of the reservoir is obtained. It is shown that: compared with the initial simulation result, the proposed method improves the hydropower greatly.

Reservoir operating rules to sustain environmental flows in regulated rivers

Sustainable water resource developments require reservoir operations that provide environmental flows (e‐flows) to support the downstream riverine ecosystem by minimizing the degree of hydrologic alteration under given water supply constraints. The effective management of e‐flows below dams was explored by combining three e‐flow management strategies for “normal,” wet, and dry year situations, delivering a range of e‐flow regimes for different reservoir storage levels and different natural flow (reservoir inflow) conditions. We combined these into a single combined e‐flow strategy and coupled this with reservoir operating rule curves to form a reservoir operating approach that optimized e‐flow provision under given water supply constraints. We also explored constraints imposed by the dam's valve release capacity. To investigate the capability of the approach to minimize the degree of hydrologic alteration downstream from a reservoir, we presented a case study of the Tanghe Reservoir in China's Tang river basin. The approach triggered a preferred e‐flow strategy when the reservoir water level was high to better maintain the ecological functions within downstream riverine ecosystems, a basic e‐flow strategy when the water level was low to reduce the water supply risk, and an acceptable strategy under intermediate conditions. The approach effectively balanced human and ecosystem needs and demonstrated the minimum levels of flow regime alteration achievable within the regulated river.

Optimized reservoir operation to balance human and riverine ecosystem needs: model development, and a case study for the Tanghe reservoir, Tang river basin, China

AbstractReservoirs impose many negative impacts on riverine ecosystems. To balance human and ecosystem needs, we propose a reservoir operation method that combines reservoir operating rule curves with the regulated minimum water release policy to meet the environmental flow requirements of riverine ecosystems. Based on the relative positions of the reservoir and the water intakes, we consider three scenarios: water used for human needs (including industrial, domestic and agricultural) is directly withdrawn from (1) the reservoir; (2) both reservoirs and downstream river channels and (3) downstream river. The proposed method offers two advantages over traditional methods: First, it can be applied to finding the optimal reservoir operating rule curves with the consideration of environmental flow requirement, which is beneficial to the sustainable water uses. Second, it avoids a problem with traditional approaches, which prescribe the minimum environmental flow requirements as the regulated minimum environmental flow releases from reservoirs, implicitly giving lower priority to the riverine ecosystem. Our method instead determines the optimal regulated minimum releases of water to sustain environmental flows while more effectively balancing human and ecosystem needs. To demonstrate practical use of the model, we present a case study for operation of the Tanghe reservoir in China's Tang river basin for the three above‐mentioned scenarios. The results demonstrate that this approach will help the reservoir's managers satisfy both human and environmental requirements. Copyright © 2009 John Wiley & Sons, Ltd.

Single Reservoir Operating Policies Using Genetic Algorithm

To obtain optimal operating rules for storage reservoirs, large numbers of simulation and optimization models have been developed over the past several decades, which vary significantly in their mechanisms and applications. As every model has its own limitations, the selection of appropriate model for derivation of reservoir operating rule curves is difficult and most often there is a scope for further improvement as the model selection depends on data available. Hence, evaluation and modifications related to the reservoir operation remain classical. In the present study a Genetic Algorithm model has been developed and applied to Pechiparai reservoir in Tamil Nadu, India to derive the optimal operational strategies. The objective function is set to minimize the annual sum of squared deviation form desired irrigation release and desired storage volume. The decision variables are release for irrigation and other demands (industrial and municipal demands), from the reservoir. Since the rule curves are derived through random search it is found that the releases are same as that of demand requirements. Hence based on the present case study it is concluded that GA model could perform better if applied in real world operation of the reservoir.

Optimizing the reservoir operating rule curves by genetic algorithms

Genetic algorithms, founded upon the principle of evolution, are applicable to many optimization problems, especially popular for solving parameter optimization problems. Reservoir operating rule curves are the most common way for guiding and managing the reservoir operation. These rule curves traditionally are derived through intensive simulation techniques. The main aim of this study is to investigate the efficiency and effectiveness of two genetic algorithms (GAs), i.e., binary coded and real coded, to derive multipurpose reservoir operating rule curves. The curves are assumed to be piecewise linear functions where the coordinates of their inflection points are the unknowns and we want to optimize system performance. The applicability and effectiveness of the proposed methods are tested on the operation of the Shih-Men reservoir in Taiwan. The current M-5 operating curves of the Shih-Men reservoir are also evaluated. The results show that the GAs provide an adequate, effective and robust way for searching the rule curves. Both sets of operating rule curves obtained from GAs have better performance, in terms of water release deficit and hydropower, than the current M-5 operating rule curves, while the real-coded GA is more efficient than the binary-coded GA. Copyright © 2005 John Wiley & Sons, Ltd.

Dynamic operating rules for water supply reservoirs in La Paz

Dynamic operating rules have been applied to the drought-prone Andean water supply reservoirs near La Paz, Bolivia. The water supply reservoirs are not using conventional reservoir operating rule curves. Instead, dynamic operating rules opportunistically supply surplus water for soft demands, and proactively adjust the water supply before a drought causes a water shortage. The conventional approach of forcing water levels to follow a set rule curve is replaced with notions of tradeoffs between long-term reliability and short-term supply opportunities. Operators can customise the dynamic rules based on their tolerance of shortages, and can choose to operate more aggressively during wet periods. In this way, the dynamic rules offer a flexible tool for making short-term decisions while managing medium and long-term performance goals. In the case of La Paz, it is possible to utilise the water sources more efficiently in the short-term without significantly reducing the long-term water supply reliability. The dynamic rules will reduce the severity of future water shortages (if they occur) by 60%, and provide opportunities to increase the firm water supply by up to 8% without affecting the long-term reliability.

Network Flow Optimization Model for Basin-Scale Water Supply Planning

This paper develops a generalized network flow optimization model for long-term supply-demand analysis for basin-wide water resources planning. A set of nodes and arcs are used to form the network, and the decision variables are reservoir storage and water supply for public and agricultural uses. The objective function to be minimized is formed by summing the products of the decision variables multiplied by their corresponding cost coefficients. The constraints of the model include continuity equations, reservoir operation rule curves, reduced water supply due to water shortage, and evaporation losses from reservoirs. The formulated network model has losses in the transshipment and is solved by an efficient embedded generalized network solver (EMNET). The developed model is applied to a river basin located in the northern part of Taiwan. To analyze the characteristics of the model, the results obtained from the optimization model are compared with those obtained from a well-calibrated simulation model. The comparison shows that the water shortage computed by the optimization model is smaller than that computed by the simulation model. The developed model is then used to analyze future water supply-demand conditions for the area.