Optimal Reservoir Operation Research Articles

Optimization of reservoir operating curves and hedging rules using genetic algorithm with a new objective function and smoothing constraint: application to a multipurpose dam in Morocco.

Long-term operation optimization of multipurpose reservoirs is highly important in arid and semi-arid countries challenged by climate change. This paper suggests an objective function combining two competitive shortage indicators for multi-objective reservoir operation optimization. An improved genetic algorithm including a smoothing constraint, reducing infeasible fluctuations of the operation policy, is developed to solve this problem. Operating curves were optimized jointly to hedging factors aiming at avoiding severe droughts and high damages for users. The proposed function was compared with the conventional objective function of minimizing the sum of squared deviations (SSD) between releases and demands. Different combinations of weights of the objectives linked to the Moroccan reservoir were studied. The proposed objective function yields to improved results in terms of computation requirements since it converges quicker and it leads to better supply performance. For drinking water use, the frequency of shortage was reduced by 66% and the maximum deficit by 14% whereas for irrigation the frequency of shortage was curtailed by 6%. The operating curves obtained by the developed optimization model were then compared with static operating rule curves simulated in RIBASIM. The superiority of variable optimized rule curves was proven compared with stable operating mode over time.

Inter‐model Comparison of Turbidity‐Discharge Rating Curves and the Implications for Reservoir Operations Management

AbstractThis study compares several statistical rating curve techniques to estimate turbidity, a proxy for suspended sediment concentration, in fluvial systems based on available discharge data. Seven models were tested, including variants of quadratic rating curves, quantile regression, local regression, dynamic linear models (DLMs), and Box‐Jenkins models. Two comparisons were conducted in a case study of the Esopus Creek watershed in New York, a major water source for the New York City Water Supply System (NYCWSS). First, the models were tested in their ability to forecast turbidity at 1–7 day lead times assuming perfect forecasts of discharge using two daily datasets of varying record lengths and resolution. Second, the models were used to gap‐fill turbidity data based on available discharge data, and the resulting continuous turbidity time series were used to assess optimal reservoir operations in the NYCWSS to manage water quality. Results suggest that DLMs coupled with additional time series modeling on the residuals produce the most robust forecasts across lead times for both high and low turbidity values. During average conditions, differences between rating curves have little impact on inferred reservoir operations due to the buffering effect of storage. But during extreme events, rating curve differences lead to large differences in inferred operations, suggesting that rating curve choice can play an important role in assessing the risk of reservoir‐based water quality management.

Research on Optimal Operation of Reservoirs in Shule River Irrigation District Based on Dynamic Programming with Successive Approximation Method

Reservoir operation is an important means to realize optimal allocation of water resources. In order to reasonably distribute water resources in Shule River irrigation area and improve the utilization rate of water resources, according to the actual situation of Shule River irrigation area, taking the minimum annual water shortage and the highest irrigation guarantee rate of the whole irrigation area as the objective function, the deterministic long-term optimal operation model of reservoir group in the irrigation area is established, and the successive approximation dynamic programming ( DPSA ) is used to solve the problem, so as to realize the joint operation of Changma Reservoir, Shuangta Reservoir and Chijinxia Reservoir, and provide the basis and reference for the comprehensive management and scientific allocation of water resources in Shule River basin.

Optimal Design and Operation of a Hydropower Reservoir Plant Using a WEAP-Based Simulation–Optimization Approach

Optimal design and operation of a hydropower reservoir is a complex optimization problem in terms of formulation and solution. In this study, a simulation–optimization model is developed for simultaneous design and operation of hydropower dams. WEAP (Water Evaluation and Planning) as the water resources planning simulation software is coupled with the Invasive Weeds Optimization (IWO) as the optimization routine. The developed simulation–optimization model is used for the Bakhtiari Dam hydropower plant in west of Iran. Two objectives for solving the problem are to maximize the energy generation and minimize the flood damage at a downstream target point. Two types of problems are investigated. The first problem only considers the optimal design of the hydropower plan, in which the decision variables include the storage capacity, minimum operation storage of the reservoir and the installed capacity of the power plant while the releases from the reservoir are determined using a predefined operation policy. In the second problem, simultaneous design and operation of the hydropower reservoir is examined where in addition to the design variables, the reservoir releases are also optimized as the operational variables. According to the results, although considering flood damage does not have much effect on design variables, but significantly affects the operation variables. Results show that the optimization of the design variables has more impact on the benefit gained from the system comparing the operational ones. Also, the standard operating policy (SOP) is an optimal or near-optimal operational solution for hydropower generation.

Modeling adaptation policies to increase the synergies of the water-climate-agriculture nexus under climate change

The water-climate-agriculture nexus quantifies synergies, trade-offs, advantages and disadvantages that arise between water management, food production, and climate change consequences taking into account the environmental impacts, economic conditions, and population growth. This work evaluates the water-climate-agriculture nexus in the Gharanghu basin, Iran, seeking to achieve sustainable management of its water system. An optimization model solves for water-release adaptive strategies corresponding to five nexus scenarios to cope with reduced water resources under climate change. The scenarios are as follows (Afshar et al., 2006): change in cropping pattern (Asadieh and Afshar, 2019), reduction of areas under cultivation (Asgari et al., 2015), reuse of agricultural wastewater in irrigated land (Ashofteh et al., 2017), combination of scenarios (Afshar et al., 2006) and (Asgari et al., 2015), namely change in cropping pattern and reuse of agricultural wastewater simultaneously, and (Bates et al., 2008) integration of scenarios (Asadieh and Afshar, 2019) and (Asgari et al., 2015) namely, reduction of areas under cultivation and reuse of agricultural wastewater simultaneously. The nexus scenarios are evaluated with the time reliability index (the ratio of the number of months in which water is supplied to the total months of reservoir operation) based on changes in water supply and agricultural water demand. Results show the time reliability index in the climate change interval (monthly time series for the period 2040–2069) without implementing any nexus scenario equals 28%, and it increases with the implementation of the water-climate-agriculture nexus scenarios. The time reliability of the system equals 85% implementing scenario (Bates et al., 2008) (reducing the area under cultivation and reusing agricultural wastewater in irrigated land). The authors' previous research projects that climate change impacts in the study region would be severe. This paper's findings provide water managers and planners with useful strategies for optimal reservoir operation that rely on decreasing water demand and increasing water supply. The approach introduced and applied in this study, which develops modeling adaptation policies to increase the synergies of the water-climate-agriculture nexus, is applicable to other basins.

Application of Marginal Rate of Transformation in Decision Making of Multi-Objective Reservoir Optimal Operation Scheme

For reservoirs with combined storage capacity for flood control and beneficial purposes, there tends to be potential benefit loss when the flood control limited water level is used in medium and small floods. How to find the optimal water level scheme for profit-making and pursue the optimization of comprehensive benefits has always been a difficult problem in multi-objective reservoir optimal operation. Based on the principle of the maximum benefit obtained by the product conversion curve and the isorevenue line in microeconomics, taking flood control and power generation as two products of a reservoir, a multi-objective optimal operation scheme decision-making model is established to seek the highest water level scheme that can produce the maximum comprehensive benefits of flood control and power generation. A case study of the Three Gorges reservoir in the early flood season of a dry year shows that on the one hand, under the condition of deterministic inflow, the model can work out the optimal water level and the corresponding best equilibrium point for both flood control and power generation, and it can increase the total power output by 4.48% without reducing the flood control benefits; on the other hand, it can also obtain the dynamic control area of the maximum allowable water level for power generation considering inflow forecast error, which provides a theoretical reference for determining the starting water level in medium and small floods and utilizing flood resources.

Optimizing reservoir operations for tradeoffs between economic objectives and legacy phosphorus management

Dam impoundment causes significant phosphorus (P) retention in reservoirs, leading to the emergence of legacy P release as a water quality threat under external pollution load reduction measures. Reservoir operations impact sediment P release through their complex influence on hydrodynamic and biogeochemical processes, but applicatory reservoir operation strategies for legacy P management have rarely been proposed. This study introduces a reservoir operation optimization approach for balancing economic objectives (i.e., water supply and hydropower generation) and P release mitigation. A coupled hydrodynamic-eutrophication-sediment model based on the Environmental Fluid Dynamics Code platform is used to simulate sediment P release under multiple reservoir operation scenarios. The resultant simulation data are used to train a dynamic artificial neural network (ANN) to model the response of P release to reservoir operations. By coupling the ANN with a reservoir operation model, we develop a multi-objective optimization model to refine reservoir operations for a three-tier tradeoff (i.e., water supply, hydropower generation and P release mitigation). China's Danjiangkou Reservoir is chosen as a case study to generate optimal operation rules. The optimal operation scheme decreases multi-year averaged annual P release by 19% (from 6688 tons to 5436 tons) while inversely increasing annual economic loss caused by water supply shortages by 14% and decreasing hydropower generation by 5%. Pareto-optimal solutions are subsequently generated to analyze tradeoffs between water supply/hydropower generation and P release mitigation. This study demonstrates the efficiency of using reservoir operations for legacy P management and offers an optimization tool for reservoir operation decision-making processes.

Comparison of meta-heuristic algorithms in optimum operation of a single-reservoir dam system

Multi-objective models must be built to optimise the use of water supplies. In this study, the performance of the farmland fertility algorithm (FFA) and that of the Harris hawks optimisation (HHO) algorithm were evaluated and compared with each other to solve the two-objective problem of optimal operation of the Golestan dam reservoir under baseline (April 2006 to October 2018) and climate change conditions (April 2021 to October 2033) in Golestan Province, Iran. The operation rules were extracted by minimising vulnerability and maximising reliability indices under both conditions. The results showed that when considering a constant value of the reliability index (i.e. 80%), the rate of vulnerability changes in the multi-objective FFA (Moffa) is lower than that of the multi-objective HHO (Mohho) algorithm. Therefore, Moffa has performed better than the Mohho algorithm in the optimal operation of the Golestan dam reservoir under both baseline and climate change conditions. On the other hand, the comparison of the optimum rules obtained under the baseline and climate change conditions showed that supplying the water demands would be more concordant with the optimum rules under climate change conditions in both optimisation algorithms. Therefore, the Golestan dam reservoir could perform better under climate change conditions in the case of using both the mentioned algorithms.

Optimization of reservoir operation at Klang Gate Dam utilizing a whale optimization algorithm and a Lévy flight and distribution enhancement technique

Development, operations and management of multi-objective reservoirs, is vital for timely water supply. Optimisation studies were done at the Klang Gate Dam (KGD) utilising standard optimisation and dynamic programming; according to the technology then. Taking it further, the KGD was studied using the nature-inspired meta-heuristic algorithms (MHAs). The Whale Optimisation Algorithm (WOA) solves complex technical issues. The Lévy flight and distribution (LFWOA) was incorporated to increase productivity at the KGD. The aim of this study to minimise KGD's water deficit with WOA and LFWOA. The study comprises of two sections. The first section examined observed monthly inflow, demand, and storage data from 2001 to 2019, whilst the second compares performances to established MHAs, from 1097 to 2008. In the first section, LFWOA and WOA reliability were 60.53 and 58.33 %,respectively. For 2010, both methods gave similar vulnerability value. The LFWOA scored 1.04 while the WOA scored 1. In second section, the LFWOA satisfied 69.70% of exact demand, while the WOA met 56.06%. LFWOA had attained the least shortage. The LFWOA algorithm was the most robust among the MHAs (1.88). In short, the LFWOA is better on the count of reliability, resilience, and scarcity scores.

Climate change impact on optimal reservoir operation and agricultural water allocation

Considering the need to supply water and food in future periods, this study assessed the effects of climate change on the water resource system of the Ballarood reservoir that located in the northwest of Khuzestan province, Iran. The outputs of ten general circulation models (GCMs) under two scenarios RCP8.5 and RCP4.5 have been used to simulate the effects of climate change. The results indicated an increase in average annual temperature by 2.34 (1.64)°C under RCP8.5 (RCP4.5). An increase in the amount of agricultural water requirement for downstream and decrease in the amount of runoff into the reservoir (31% under the RCP8.5 scenario and 11% under the RCP4.5) are other results of this study. Based on this results, the increase of vulnerability [46% (21%) under RCP8.5 (RCP4.5)] and decrease reliability [41% (18%) under RCP8.5 (RCP4.5)] of reservoir water supply system is simulated in the future period (2030-2055) relative to the basis period (1980-2005).

Performance Assessment of Cascaded Reservoirs Operation Under the Impact of Climate Change the Case of Lower and upper Dabus Reservoirs, UBN Basin, Ethiopia

Globally the impact of climate change affects many water resources projects, thus it is important to assess its impact on reservoir performance. This study mainly assesses the performance of Upper and Lower Dabus reservoirs under the impact of climate change using Reliability, Resilience and Vulnerability indices (RRV). The future climate variables were projected by General Circulation Model (GCM) and downscaled at the basin level for the A1B emission scenario using the Regional Climate Model (RCM). The trend of streamflow forecasted at outlet (merging to main Abbay River) was assessed and the inflow generated to reservoirs was used to determine reservoirs performance indices (RRV). Finally the inflow to the reservoirs with monthly evapotranspiration from the reservoirs was used as input to HEC-ResSim to simulate and optimize reservoir operation and Power production. The average annual inflow to the upper Dabus reservoirs shows an increasing of 3.17% for early century (2010-2040) and decreasing of 2.08% and 4.46% for mid (2040-2070) and late century (2070-2100) respectively. The average time base reliability of the reservoirs was less than 50% for no reservoir condition and greater than 90% for the other condition considered but volumetric reliability and resilience shows 100% for all conditions. According to the vulnerability result the reservoirs will face shortage of flow which ranges from 8.85% to 88.51%. The result of reservoir simulation shows that the power plant parameters does not shows much significant in all scenarios considered in this study. As a result of these the Dabus sub-basin reservoirs have sufficient potential to produce required power for the country according to reconnaissance level study of the basin demand requirement and even more power can be produced.

Climate change impact on optimal reservoir operation and agricultural water allocation

Considering the need to supply water and food in future periods, this study assessed the effects of climate change on the water resource system of the Ballarood reservoir that located in the northwest of Khuzestan province, Iran. The outputs of ten general circulation models (GCMs) under two scenarios RCP8.5 and RCP4.5 have been used to simulate the effects of climate change. The results indicated an increase in average annual temperature by 2.34 (1.64)°C under RCP8.5 (RCP4.5). An increase in the amount of agricultural water requirement for downstream and decrease in the amount of runoff into the reservoir (31% under the RCP8.5 scenario and 11% under the RCP4.5) are other results of this study. Based on this results, the increase of vulnerability [46% (21%) under RCP8.5 (RCP4.5)] and decrease reliability [41% (18%) under RCP8.5 (RCP4.5)] of reservoir water supply system is simulated in the future period (2030-2055) relative to the basis period (1980-2005).

Optimal Reservoir Operation of Multiple-purpose Reservoirs in the Tropic Monsoon Area

Optimal Reservoir Operation of Multiple-purpose Reservoirs in the Tropic Monsoon Area

Developing MSA Algorithm by New Fitness-Distance-Balance Selection Method to Optimize Cascade Hydropower Reservoirs Operation

Optimal operation of cascade hydropower reservoirs is a complex high-dimensional engineering problem. Developing an appropriate model to solve such problems requires an efficient search method proportional to the dimensions of the problem. Accordingly, this research employed the new fitness-distance-balance (FDB) selection method in the moth swarm algorithm (MSA) to achieve promoted FDB-MSA with a high performance in solving complex large-scale problems. To ensure the efficiency of the developed algorithm, five benchmark functions of Shekel, Six-Hump Camel, McCormick, Goldstein-Price and Rosenbrock were used. Then, the FDB-MSA was used for optimization of hydropower generation of a real five-reservoir system along Karun River at Iran. This is the largest cascade reservoir system in Iran, which supplies more than 90% of the country’s hydropower demand. The results of the developed algorithm were compared with those of genetic algorithm (GA) and particle swarm optimization (PSO) algorithm. It was found that the FDB-MSA could successfully increase the hydropower generation by 59.5% (6724 GW) compared to the actual generation of energy over a 180-months operational period. The corresponding values for PSO and GA algorithms were 54.3% and 9.2% respectively. In addition, the results revealed the superiority of FDB-MSA to GA and PSO, so that, it demonstrated the smallest difference (3.41%) between nominal and optimal power generation compared to the PSO (6.58%) and GA (33.89%).

Reservoir optimal operation to adapt the non-stationary hydrological series<sup>*</sup>

为完善变化环境下水库防洪调度方案，建立了集水文非一致性诊断、水文模型还现、设计洪水计算与水库调度规则优化于一体的水库适应性调控方法体系，并应用于沂沭泗水系仕阳水库.结果表明，仕阳水库入库洪水变异点发生在1975年；利用新安江模型对水文序列还现处理，得到满足一致性的设计洪水，其洪峰、最大24 h和最大72 h洪量均值，较原设计分别增大了19.7%、14.5%和10.0%；建立了以防洪效益最大为目标函数的水库优化调度模型，采用动态规划进行求解.提出的适应性调度方案在20年、100年、1000年和5000年一遇设计洪水条件下，较水库现行设计方案最高洪水位分别降低了0.32、0.11、0.19和0.11 m.;To improve reservoir operation rules under changing environment, this paper proposed adaptive operation methodologies that include the hydrological series inconsistent testing→backwards restore by hydrological model→design flood calculation→optimal operation of reservoir for flood control safety. The proposed methodologies were applied to the Shiyang Reservoir, which located at the Yi-Shu-Si river system. The results have shown that the change-point of this reservoir inflow flood is 1975. The inflow flood that satisfies the assumption of hydrological stationery were calculated by the Xin'anjiang model, and the hydrological consistent design floods acquired based on it. Compared with the original design, the mean values of flood peaks, maximum flood volume during 24 hours and 72 hours of the new design floods increased 19.7%, 14.5% and 10.0%, respectively. The optimal reservoir operation model based on the objective function of maximizing the flood control benefit is established and solved by dynamic programing. Under design flood with 20-year, 100-year, 1000-year and 5000-year return periods, the maximum flood level of Shiyang Reservoir decrease by 0.32, 0.11, 0.19 and 0.11 m, respectively, compared with the current design scheme.

Sustainable Multi-Objective Multi-Reservoir Optimization Considering Environmental Flow

Increasing demand for water from all sectors presents a challenge for policy makers to improve water allocation policies for storage reservoirs. In addition, there are many other organisms and species present in river waters that also require water for their survival. Due to the lack of awareness many times the minimum required quantity and quality of water for river ecosystem is not made available at downstream of storage reservoirs. So, a sustainable approach is required in reservoir operations to maintain the river ecosystem with environmental flow while meeting the other demands. Multi-objective, multi-reservoir operation model developed with Python programming using Fuzzy Linear Programing method incorporating environmental flow requirement of river is presented in this paper. Objective of maximization of irrigation release is considered for first run. In second run maximization of releases for hydropower generation is considered as objective. Further both objectives are fuzzified by incorporating linear membership function and solved to maximize fuzzified objective function simultaneously by maximizing satisfaction level indicator (λ). The optimal reservoir operation policy is presented considering constraints including Irrigation release, Turbine release, Reservoir storage, Environmental flow release and hydrologic continuity. Model applied for multi-reservoir system consists of four reservoirs, i.e., Jayakwadi Stage-I Reservoir (R1), Jayakwadi Stage-II Reservoir (R2), Yeldari Reservoir (R3), Siddheshwar Reservoir (R4) in Godavari River sub-basin from Marathwada region of Maharashtra State, India.

Review on Dam and Reservoir Optimal Operation for Irrigation and Hydropower Energy Generation Utilizing Meta-Heuristic Algorithms

In engineering and scientific disciplines, there are extensive Optimization Application Problems (OAPs) such as economic dispatch, structural design, and water resources. One of the major OAPs is the operation of dams and reservoirs to minimize the gap between water supply for irrigation and demand patterns such as hydropower generation. Drawing optimal operation for dams and reservoirs is often categorized as discontinuity, multimodality, non-differentiability and non-convexity. Classical mathematical programming-based methods for optimization might be inappropriate or unrealizable in drawing optimal operation rules for dam and reservoir operation. During the last two decades, new optimization methods-based on nature-inspired meta-heuristic algorithms (MHAs) have motivated hydrologists to investigate MHAs as better alternative optimization tools for identifying the optimal dam and reservoir operation rules. To solve the dam and reservoir-optimization applications better, this review presents the past, present, and prospective research directions using MHAs. The problem of dam and reservoir optimization requires a fundamental shift of focus towards enhancing not only the problem formulation and decomposition but also the computational efficiency of MHAs.

Use of a Multi-Objective Correlation Index to Analyze the Power Generation, Water Supply and Ecological Flow Mutual Feedback Relationship of a Reservoir

Hitherto, there has been insufficient work to quantify the degree of mutual feedback among the different objectives of multi-objective reservoir operation. The purpose of this study is to use a Multi-objective Correlation Index (MCI) to quantitatively analyze the complicated relationship of a multi-objective reservoir operation under changing inflow and water demands. First, an improved maximum probability density function method has been used to generate the adaptive ecological flow thresholds in long-term, wet-year, normal-year and dry-year inflow scenarios. Based on these ecological flow thresholds, a multi-objective reservoir optimal operation including the three objectives of power generation, water supply and ecology is constructed to research the tradeoff relationship among the objectives. Moreover, using the optimal solution set as determined by the Progressive Optimality Algorithm-Particle Swarm Optimization (POA-PSO) algorithm, the MCI is used to quantify the degree of the tradeoffs and their trends in responding to the changing conditions. The results show that the synergistic degree between the water supply and ecological objective decreases when the climatic condition changes from wet years to dry years, while the conflicting degree of power generation with respect to water supply or ecological objectives increases. Furthermore, the major degree of tradeoffs changes from the power generation-ecological flow objective pair to the power generation-water supply objective pair. In general, the MCI is able to quantify the extent and characteristics of the tradeoffs between different objectives. Hence, this index is useful for managers to make more informed and transparent decisions.

An improved particle swarm optimization algorithm for the three gorges project operation optimization

The paper presents an algorithm combining simplex downhill search particle swarm optimization (SDSPSO) for solving reservoir operation optimization (ROO) problems, with a new search strategy: reflecting the worst particle through the particle swarm centroid to generate a new particle and guiding the evolution direction of each particle. The ROO problem is a complicated dynamically constrained nonlinear, non-convex optimization problem that is important for reservoir operation system, consisting of continuous control variables. The proposed algorithm is examined on Three Gorges Project (TGP) that provided a better operational effect result with greater effectiveness and obtains more power generation with lower insurance rate reservoir sum runoff.

Stochastic Optimization of Reservoir Operation by Applying Hedging Rules

AbstractThe high percentage of reliability of water resources systems has always been considered as a positive advantage by users. However, in arid and semiarid areas in which the flow rate of the ...