Operating Rule Curves Research Articles

Synchronizing short-, mid-, and long-term operations of hydro-wind-photovoltaic complementary systems

Hydro-wind-photovoltaic (PV) complementary power systems (HWPCSs) offer a promising solution for integrating intermittent wind and PV power, leveraging the long-term energy storage capacity of reservoirs and the short-term flexible adjustability of hydro units. However, existing studies often neglect the reciprocal influences among short-, mid-, and long-term operations of HWPCSs, resulting in suboptimal operating strategies. To tackle this issue, the study proposes a generic framework for synchronizing operations of HWPCSs across multiple time scales. The framework simultaneously optimizes long-term operating rule curves, mid-term water consumption allocation, day-ahead power generation plan scheduling, and intraday economic operation of HWPCSs. A HWPCS located in the Yalong River Basin is selected as the case study. The results indicate that: (1) synchronized operation effectively reduces the output shortage risk (from 4.86 % to 0 %) and average absolute water consumption deviation (from 2.07 % to 0.09 %) compared to the conventional method; (2) synchronized operation provides more reasonable boundaries for short-term operations, reducing the average online time percentage (from 65.08 % to 63.57 %) and start-up/shut-down times (from 3185 to 2981) of hydro units, leading to an increase in the average hydropower efficiency (from 9.05 to 9.12). This study highlights the impracticality of the conventional method, underscoring the necessity of synchronized operation for HWPCSs. The proposed method provides a practical framework for the efficient operation of HWPCSs.

Operational analysis of lake Tana under climate change, Upper Blue Nile Basin, Ethiopia

The excessive abstraction of lake water affects its sustainability and is common in Lake Tana. Hence this study aims to develop operation rule curves for optimum operation of Lake Tana reservoir by considering the effects of small and large-scale irrigation water abstraction, Hydropower demand, and climate change. The data used in this study were produced by two Global Circulation Models (GCMs) (MIROC5 and MPI) under two Representative Concentration Pathways (RCP4.5 and RCP8.5) in the 2040s (2020–2049) and 2070s (2050–2079). For RCP4.5 and RCP 8.5 scenarios of the 2040s- and 2070s-time domains, lake temperature exhibits an upward trend. The lake rainfall also will show an increase for the 2040s and 2070s under both RCP scenarios. The outcome showed that in all future scenarios, lake evaporation under RCP4.5 of 2040s and 2070s rise between 3.6 % to 7 % and 4.6 % to 19, respectively, while for RCP8.5 of 2040s and 2070s increases between 4.6 % to 9.9 % and 9.2 % to 24.7 %. The surface water inflow increased for RCP4.5 (2070s) and RCP8.5 (2040s), whereas it declined for RCP4.5 (the 2040s) and RCP8.5 (2070s. Under both scenarios, the average value of the time-based and volumetric reliability in the 2040s and 2070s is less than 80 %. The reservoir will take a very long time to recover from the shortfall as the resilience levels are below 50 %. Additionally, the dimensionless vulnerability was less than 50 %, indicating that there won't be a shortage of inflow to meet demand at the reservoir. Based on evaluation, the reservoir will not probably perform well in any way because of the rise in upstream abstractions. To guide the operation of the reservoir, operation rule curves were developed using the Hec-ResSim model. Generally, the government, decisions, and policymakers should set a water resources management plan not trigger normal functioning of the Lake system.

Mitigating adverse impacts of reservoir impoundment on lake ecology: A case study of the Three Gorges Reservoir and Dongting Lake

Upstream reservoir impoundment has brought adverse impacts on the downstream river-connected lakes, including lower water levels, frequent droughts, and reduced biodiversity. Existing research on ecological reservoir operation focused more on the effectiveness of operation redesign for ecology improvement, but less discussion on why they are eco-friendly. In this paper, the reservoir operation mechanisms targeting lake ecology are explored from three perspectives: ecological impoundment strategy, dominant characteristics of ecology and conservation tradeoffs, and critical parameters of the rule curves. Therefore, a reservoir operation framework, which couples the lake hydrological response model and multi-objective optimization model, is developed in this study. This framework is to maximize the water conservation and lake ecology benefits, assessing the latter by ecological reliability and ecological water shortage rate. Taking the Three Gorges Reservoir and Dongting Lake as the case study, operation rule curves are optimized for different impoundment strategies. The results indicate that impoundment with early storage time and slow storage rate can improve the ecological reliability and ecological water shortage by 9.90 % and 16.39 % than conventional operation. The ecological objectives are weakly competitive or synergistic when impounding fast, but strong competitive when impounding slow. Meanwhile, as the storage rate declines, the ecological improvement causes a slight decrease in power generation and a significant decrease in water supply. Finally, the crucial parameters of the rule curves are explored and appropriate values are recommended for different ecological preferences.

An Alternative Approach Using the Firefly Algorithm and a Hybrid Method Based on the Artificial Bee Colony and Cultural Algorithm for Reservoir Operation

In reservoir operation rule curves, it is necessary to apply rule curves to guide long-term reservoir management. This study proposes an approach to optimizing reservoir operation rule curves (RORCs) using intelligent optimization techniques from the firefly algorithm (FA) and a unique combination method utilizing the artificial bee colony and cultural algorithm (ABC-CA). The aim is to establish a connection with the simulation model to determine the optimal RORCs for flood control. The proposed model was used to determine the optimal flood control RORC for the Nam-Oon Reservoir (NOR) in northeastern Thailand. A minimum frequency and minimum average of excess water were provided as an objective function for assessing the efficiency of the search process. The evaluation of the effectiveness of flood control RORCs involved expressing water scarcity and excess water situations in terms of frequency, magnitude, and duration using historical inflow data synthesized from 1000 events. The results demonstrated that when using the obtained RORC to simulate the NOR system for reducing flooding in long-term operations, excess water scenarios were smaller than those using the current RORC. The results showed that the excess water scenario using the RORC obtained from the proposed model can reduce the excess water better than the current RORC usage scenario. In decreasing flood situations, the newly acquired RORC from the suggested FA and ABC-CA models performed better than the current RORC.

Study on the Basic Form of Reservoir Operation Rule Curves for Water Supply and Power Generation

Reservoir operation rule curves are crucial for managing water supply and power generation in reservoirs. As the number of objectives and management requirements increase, there is a growing demand for optimized operation rule curves. The objective of this study is to explore the most effective forms of reservoir operation rule curves, focusing on the case of the Nierji Reservoir and considering the dual objectives of water supply and power generation. The parameter–simulation–optimization framework, specifically employing the NSGA-II algorithm, was used to analyze and compare two basic forms of operation rule curves: the shared type and independent type. The impact of these curves on water supply potential and multi-objective optimization results with various water demand scenarios was assessed. The analysis revealed that the choice of operation rule curve form can influence the maximum water supply potential of the reservoir to some extent. The independent type operation rule curve was significantly more effective in enhancing the water supply potential for industrial and domestic users, resulting in a notable increase of 3.5 × 108 m3. Additionally, it also proved beneficial for environmental users, with an increase of 1 × 108 m3. Conversely, the shared type operation rule curve demonstrated similar functionality to the independent type curve with fewer decision variables, particularly when the water demand was relatively low. In scenarios with high water demand, the independent type curve outperformed the shared type curve by generating 6549 superior, non-dominated solutions for multi-objective optimization, specifically focused on maximizing reservoir operation benefits. In conclusion, selecting the appropriate form of reservoir operation rule curve is crucial to balance different reservoir functional objectives and achieve optimal results. Further research could focus on quantifying the specific benefits and trade-offs associated with each type of curve in order to provide more robust evidence for the advantages of a complex reservoir system.

Climate-associated risks for reliability, resilience, vulnerability and sustainability of irrigation reservoirs in small ungauged watersheds

Climate change poses an existential threat to the functional integrity of the network of agricultural reservoirs responsible for sustaining rice production in South Korea. Anthropogenic interventions have triggered a cycle of droughts and floods by magnifying the already existing supply–demand gap, which is seriously hampering reservoir performance. The watersheds of most agricultural reservoirs in South Korea are ungauged, and inflow and outflow data are not measured. In this study, recorded volumetric water storage data from five reservoirs were used to derive observed inflow data based on the hydrological reasoning and reservoir operation rule curves. These data were then used to evaluate the performance of a lumped rainfall-runoff model in simulating the runoff generated in upstream ungauged watersheds. A water balance analysis was conducted for 400 major agricultural reservoirs spread throughout the country during 1973–2017. Performance indices were estimated based on inflow availability in the reservoirs and downstream irrigation demands. Empirical relationships were derived to predict performance indices by using the reservoirs’ physical characteristics as input variables. Generally, reservoirs received substantially higher inflows compared to irrigation demands, suggesting sufficient water availability during the rice growing season (Apr−Sep). An out-of-phase cycle of peak inflow generation and water demand periods induced frequent failure events during the rice nursery transplanting period (May−Jun), and reservoir sustainability was minimal in these months. Southern and southwestern major agricultural regions with a higher density of small- to medium-sized reservoirs would be at higher risk of climate-induced water scarcity. Upsizing storage capacity could alleviate the water deficit in reservoirs associated with watersheds featuring higher means and lower standard deviations of runoff. A watershed-to-irrigated area ratio > 5 indicated acceptable reservoir sustainability.

Optimal Rule Curves for Operation the Euphrates River Concerning Tharthar Reservoir as a Case Study

Optimal Rule Curves for Operation the Euphrates River Concerning Tharthar Reservoir as a Case Study

Design of optimal operating rule curves for hydropower multi-reservoir systems by an influential optimization method

Hydropower plants play an integral role in energy supply and are one of the main renewable energy sources. The efficiency of hydropower reservoir systems is controlled by operating rules that need to be optimized to maximize energy production. Here, a novel optimization algorithm, influential flower pollination algorithm (IFPA), is developed in this paper. IFPA has three enhancements: an efficient exploration mechanism based on an adaptive coefficient, a new exploitation mechanism around the best solution, and a rank-based strategy to smoothly transition from exploration to exploitation. IFPA is tested in two benchmark multi-reservoir systems and a real-world five-reservoir hydropower system in Iran. The results show IFPA outperforms other advanced methods in terms of convergence speed and preciseness to achieve the global solution. The tested algorithms include adaptive guided differential evolution (AGDE), composite DE (CODE), hybridizing sum-local search optimizer (HSLSO), improved teaching learning-based optimization (ITLBO), self-adapting control parameters in DE (jDE), self-adaptive TLBO (SATLBO), and a multi-strategy hybrid of DE and particle swarm optimization (MS-DEPSO). IFPA also achieved better total power production in the real-world case study compared to other algorithms. Overall, IFPA can provide better solutions with less power deficit and shows as a promising method for optimizing hydropower reservoir problems.

Extracting Optimal Operation Rule Curves of Multi-Reservoir System Using Atom Search Optimization, Genetic Programming and Wind Driven Optimization

This research aims to apply optimization techniques using atom search optimization (ASO), genetic programming (GP), and wind-driven optimization (WDO) with a reservoir simulation model for searching optimal rule curves of a multi-reservoir system, using the objective function with the minimum average quantity of release excess water. The multi-reservoir system consisted of five reservoirs managed by a single reservoir that caused severe problems in Sakon Nakhon province, Thailand, which was hit by floods in 2017. These included Huai Nam Bo Reservoir, the Upper Huai Sai-1 Reservoir, the Upper Huai Sai-2 Reservoir, the Upper Huai Sai-3 Reservoir, and the Huai Sai Khamin Reservoir. In this study, the monthly reservoir rule curves, the average monthly inflow to the reservoirs during 2005–2020, the water demand of the reservoirs, hydrological data, and physical data of the reservoirs were considered. In addition, the performance of the newly obtained rule curves was evaluated by comparing the operation with a single reservoir and the operation with a multi-reservoir network. The results showed situations of water shortage and water in terms of frequency, duration, average water, and maximum water. The newly obtained rule curves from the multi-reservoir system case showed an average water excess of 43.722 MCM/year, which was less than the optimal curves from the single reservoir case, where the average water excess was 45.562 MCM/year. An analysis of the downstream reservoir of the multi-reservoir system, which diverts water from the upstream reservoirs, was performed. The results showed that the new optimal rule curves of ASO, GP, and WDO operated as a multi-reservoir system performed better than when operated as a single reservoir. Therefore, this research is suitable for sustainable water management without construction.

Assessment of reservoir performance under climate change: A case study in Shumbrite reservoir, South Gojjam sub-basin, Ethiopia

Climate change has the potential to reduce the water resource availability and hence the amount of storage in reservoirs. In this study, we assessed the impact of climate change on the performance of the Shumbrite reservoir using outputs from the CORDEX-Africa project, MPI Global Circulation Model (GCM) under three Representative Concentration Pathways (i.e., RCP2.6, RCP4.5 and RCP8.5). The trend analysis of future precipitation shows a decrease in the range of 0.57%–4.2%, with a maximum decrease under RCP2.6, and temperature (both maximum and minimum) shows an increasing trend as compared to the baseline period. The HBV model simulated future mean annual flow volume shows a decrease (ranges 0.06% to 1.64%) for RCP2.6 and RCP4.5 and a significant increase of 5.03% for RCP8.5 compared to the baseline period. Mean annual irrigation water demand from CROPWAT shows an increase (0.74% to 8.4%) for all RCPs compared to the baseline period. The time-based reliability for the Shumbrite reservoir has an average value above 80%. The resilience values are below 50% for all RCPs and hence the reservoir will take an extended period to recover from an inability to achieve the target demand volume. The dimensionless vulnerability shows a value below 50% which indicates that the reservoir has no insufficient flow to meet the demand. Generally, the reservoir can be used sustainably with operation rule curves. Generally, this study adds a contribution to the evaluation of small-scale reservoirs under a changing climate and the preparation of guide curves for the respective release.

Conceptual Sim-Heuristic optimization algorithm to evaluate the climate impact on reservoir operations

This study covers the application of sim-heuristics to simulate and optimise the KLang Gate Dam (KGD) operating rule curve using the Coupled Model Intercomparison Project 5 (CMIP5) climate scenarios. This research aims to examine future climate change impacts on the KGD reservoir water resources. First, based on model institution location and data availability, a few General Circulation Models (GCMs) under the CMIP5 were chosen. Most earlier studies had solely examined the impact of climate change on future reservoir operations using a single GCM. The ensemble of GCMs for precipitation, temperature (Maximum, Minimum, and Mean), and solar radiation for the base period (1991–2005) and future climatic scenarios under the Representative Concentration Pathways, RCP 2.6, RCP 4.5, and RCP 8.5 were downscaled, trained, and tested using data-driven techniques namely; the Artificial Neural Network (ANN) and the Support Vector Regression (SVR). During the base period, the SVR (Poly function) achieved R performance values of 0.6201, 0.5743, 0.6926, and 0.6073 for the respective predictant variables. Upon addressing for rainfall-runoff, the Turc-radiation evaporation strategy was utilised at this study location since it was suitable for the tropical, humid, or sub-humid region. Few scenarios were developed to forecast water demand. Scenario 1 was based on the base period (1991–2005) of water demand, whereas Scenarios 2 and 3 were based on maximum and mean temperatures, respectively (2020–2099). The results were then evaluated in terms of storage failure, reliability, resilience, and vulnerability. Overall, Scenario 3 showed the greatest reliability in satisfying exact demand with 93.54 %, as well as the least shortage index and length of water deficit under RCP 4.5.

An optimisation approach for the operating rule curves of the A Vuong reservoir, Vietnam

AbstractThis paper proposes to optimise the operation of the A Vuong reservoir using the dynamic programming technique. The A Vuong is a large reservoir in Vietnam serving multiple purposes, including power generation, flood control, and downstream water supply. First, different flood control storage capacities (Vpl) are investigated, and the best one is chosen based on the criteria of power output and the reservoir's ability to fill up after each regulation cycle. That option is for Vpl to be 50, 30, and 10% of the active storage capacity in September, October, and November, respectively. The study also proposes new operating rule curves with various scenarios of different beginning water levels, ranging from 368 m to 380 m. The average lines of the operating rule curves are also suggested for easier and more efficient operation. Recommendations for using this operating rule curve, as well as its advantages compared to the current one, are also discussed. The results show that the proposed operating rule curves provide much better performance compared with the current in terms of increasing the power output, with a 3.1% increase, while also protecting other water uses.

Optimal Operation of Nashe Hydropower Reservoir under Land Use Land Cover Change in Blue Nile River Basin

Changes in LULC (land use land cover), which significantly influence the spatial and temporal distribution of hydrological processes and water resources in general, have a substantial impact on hydropower generation. The utilization of an optimization approach in order to analyze the operation of reservoirs is an important concern in the planning and management of water resources. The SWAT (Soil and Water Assessment Tool) and the HEC-ResPRM (Hydrologic Engineering Center reservoir evaluation system Prescriptive Reservoir Model) were combined to model and optimize the Nashe hydropower reservoir operation in the Blue Nile River Basin (BNRB). The stream flow into the reservoir was determined using the SWAT model, considering the current and future impacts of LULC changes. The HEC-ResPRM model has been utilized in order to generate the optimal hydropower reservoir operation by using the results of the SWAT calibrated and validated stream flow as input data. This study proposes a method for integrating the HEC-ResPRM and SWAT models to examine the effects of historical and future land use land cover change on the watershed’s hydrological processes and reservoir operation. Therefore, the study aimed to investigate the current and future optimal reservoir operation scenarios for water resources management concerning hydropower generation under the effect of LULC changes. The results reveal that both the 2035 and 2050 LULC change scenarios show the increased operation of hydropower reservoirs with increasing reservoir inflows, releases, storage, and reservoir elevation in the future. The effects of LULC change on the study area’s hydrological components reveal an increase in surface runoff until 2035, and its decrease from 2035 to 2050. The average annual reservoir storage and elevation in the 2050 LULC scenario increased by 7.25% and 2.27%, respectively, when compared to the current optimized scenario. Therefore, changes in LULC have a significant effect on hydropower development by changing the total annual and monthly reservoir inflow volumes and their seasonal distribution. Reservoir operating rule curves have been commonly implemented in the operation of hydropower reservoirs, since they help operators to make essential, optimal decisions with available stream flow. Moreover, the generated future reservoir rule curves can be utilized as a reference for the long-term prediction of hydropower generation capacity, and assist concerned authorities in the successful operation of the reservoir under the impact of LULC changes.

Hybrid methods for reservoir operation rule curve determination considering uncertain future condition

In this research, simple and practical methods have been proposed to determine the reservoir operation rule curves considering uncertain water inflow values at future conditions based on the concept of comparative reservoirs management. For this purpose, two methods are proposed. In the first method named His-Inf, by considering the historical water inflow values, a mathematical optimization model is proposed for defining the reservoir operation rule curves determination problem and solved using nonlinear programming (NLP) method. However, in the second method, three different approaches named Pre-Inf1, Pre-Inf2 and Pre-Inf3 are proposed. In the Pre-Inf1 method, at first, water inflow values into the dam reservoir are predicted using neural network (ANN) model. Then, the predicted water inflow values are used to determine and update the reservoir operation rule curves using NLP method. In the Pre-Inf2 method, the ANN model is used to simulate and update the constant coefficients of the reservoir operation rule curves considering the water demand, water inflow values into the reservoir, water release values form reservoir and time index (T) as data set. For this purpose, two different framework and structure are proposed for sorting and providing data set leading to two different cases. Finally, in the Pre-Inf3 method, at first, water inflow values, reservoir storage volumes, water demand values and time index (T) are used to simulate and predict water releases values from the reservoir. Then, the linear regression method is used to determine the reservoir operation rule curves and policies. Here, both static and dynamic ANN models are used for simulating and predicting the water inflow values and reservoir operation rule curves and policies. In order to investigate the performance of proposed methods, here, the Sefidrood dam reservoir is considered as a case study in which it is located at the intersection of the QezelOzan River and Shahroud River near the city of Manjil in the north of Iran. Finally, the obtained results are presented and compared by calculating the reliability, residency, vulnerability and sustainability indexes. Comparison of the result indicates the superiority of the proposed Pre-Inf3 method for determining the reservoir operation rule curves at uncertain future condition in which the results of the His-Inf, Pre-Inf1 and Pre-Inf2 methods are almost similar. In other words, the sustainability index of His-Inf, Pre-Inf1, Pre-Inf2 and Pre-Inf3 are 63%, 63%, 63% and 74%, respectively, in which the corresponding value of Pre-Inf3 is 17.5% bigger than other proposed methods.

Investigation of a composite two-phase hedging rule policy for a multi reservoir system using streamflow forecast

Long-term changes in reservoir inflow due to climate changes and human interference violate the assumptions of hydrologic stationarity especially in the reservoir design. Utilization of uncertain prediction into a reservoir operating rule curves somehow reflects the challenges that imposed by nonstationary conditions. This study proposes a hedging based policy incorporated forecast term to manage release decisions in two separate phases. Hedging is applied firstly regarding to reservoir water level similar to conventional hedging rules and secondary according to an extra simulation in the near future. To determine the time interval of future effects, an exterior optimization model is introduced to handle the trade-off between forecast uncertainty and future information which imposed by forecast horizon. Future inflows are forecasted introducing a model including a wrapper-based feature selection method and AdaBoost.RT as a learning algorithm. The results of applying the model to a real six reservoir system in IRAN showed that incorporating future inflows into the real time decisions significantly improves the total squared relative deficit about 20% and 10% compared to conventional hedging rule curve (CHRC) and standard operation policy as objective function. Also having a glance at the near future reduces the vulnerability of the system about 5% and 27% respectively against CHRC and SOP. The results also showed that, although the SOP reaches to a best reliability of satisfying water demands in total system as 31% and 27% better than CHRC and the proposed two-phase policy, but the number of intensified failures was higher than two others which somehow influences on volume-based indices like vulnerability.

Deriving reservoir operating rules considering ecological demands of multiple stations

Reservoirs play important roles in hydropower generation, flood control, water supply and navigation. However, the regulation of reservoirs is challenged due to their adverse influences on river ecosystems. In this study, ‘Ecoflow’ was used as an ecological indicator for reservoir operation to indicate the extent of natural flow alteration. Three reservoir optimisation models were established to derive ecological operating rule curves (ORCs). Model 1 only considers maximisation of average annual hydropower generation (AAHG) and the assurance rate (AR) of hydropower generation. Model 2 incorporates ecological objectives and constraints. Model 3 not only considers the hydropower objectives but also simulates runoff and calculates the ecological indicator values of multiple downstream stations. The three models were optimised using a simulation–optimisation framework. Reservoir ecological ORCs were derived for a case study of China's Three Gorges reservoir. The results provided feasible schemes for reservoir operation by considering both hydropower and ecological demands. The AAHG and AR of the preferred optimised scheme for model 3 were increased by 1.06% and 2.50%, respectively. Furthermore, the ecological benefits of three hydrologic stations were also improved. In summary, the ecological indicator Ecoflow and optimisation models could be helpful for reservoir ecological operations.

Optimization of the Operation Rule Curves for Cascade Reservoirs Using the Cuckoo Search Algorithm

Reservoir operation optimization models are based on the hydrological cycle principle. These models determine the inflow and outflow necessary to meet the demands for drinking water, irrigation water, etc. Rather than optimizing each reservoir separately in cascaded reservoir systems, more efficient results are obtained if the reservoirs are optimized as a whole. In this study, the optimal operation rule curves for cascaded reservoirs were obtained by using the cuckoo search algorithm, which is a soft computing method. Both the irrigation and flood control constraints of the Adiguzel and Cindere dams in Denizli (Turkey) were satisfied by utilizing these rule curves, and the total energy production was maximized. In addition, these rule curves considered turbine efficiency, which significantly contributes to published literature. The total energy obtained with the proposed operation rule curves was 14% higher than that currently produced by the Adiguzel and Cindere dams.

Derivation of operating rule curves for cascade hydropower reservoirs considering the spot market: A case study of the China's Qing River cascade-reservoir system

The spot price varies in deregulated markets, and is important for the revenue of cascade hydropower reservoirs. However, the conventional operating rules maximize hydropower generation without considering the spot price. To address this issue, this study focuses on deriving operating rule curves to maximize revenue by integrating reservoir operations and a spot market. Spot prices are simulated by aggregating supply bids and estimating demand. A parameter-simulation-optimization approach is then used to maximize the hydropower revenue and reliability, and minimize spill water simultaneously. With China's Hubei province as the market boundary, the Qing River cascade-reservoir system was selected as the case study. The spot price is significantly affected when the Qing River cascade-reservoir system participates, compared with the market without the cascade system. The spill water reduction (1.33%) and average water head increase (0.56%) contributes to the 1.74% hydropower generation increment of the derived rule curves compared with the conventional operating rules, resulting in hydropower revenue increase by 2.25% with the mean spot price raised by 0.36%. The firm-output operational zone is expanded during the refill period, compared with that derived in an independent pricing scenario. The derived operating rule curves are effective to maximize hydropower revenue for long-term operation.

Appropriate Operating Policy for a Reservoir System Based on Inflow States (Mosul Reservoir as a Case Study)

The present study has focused on the selection of appropriate operating policies for a reservoir system to maximize the hydropower generation through the derivation of operation rule curves for different states of the inflow into the reservoir. And in order to accomplish this task, 30 years of monthly observed inflow has been used and arranged into five intervals with lower and upper values of each interval. The Genetic Algorithms techniques were implemented to obtain the optimal operating policies for each of the proposed five categories of inflow. Furthermore, and in order to alleviate the adverse effects of trapping in local maxima, a hybrid method is suggested making use of the built-in functions of optimization available in the Matlab software. The non-linear optimization function used the values of the variables obtained by GA's as initial solutions required by the optimization process to reach global solutions. One of the main objectives of the current study was to build a simple mechanism to select the most appropriate operating policy which is compatible with the nature of the inflow state entering the reservoir during a certain period of time. Consequently, a simulation model was conducted using SIMULINK technique to mimic the Mosul reservoir system which is selected as a case study to test the proposed method. The results reveal an improvement by 10 % of hydropower generation over that produced over the 30 years of real operation using the current method.

Hybridizing ANN-NSGA-II model with genetic programming method for reservoir operation rule curve determination (Case study Zayandehroud dam reservoir)

Hybridizing ANN-NSGA-II model with genetic programming method for reservoir operation rule curve determination (Case study Zayandehroud dam reservoir)