Optimization of Reservoir Operation using Linear Programming

,; Raju*, B C Kumar; Gowda C, Chandre; ,; B S, Karthika; ,

doi:10.35940/ijrte.e6174.018520

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…Linear programming optimization techniques are applicable for addressing operational challenges in reservoir management (Jamil et al, 2019). This approach encompasses three critical components: the objective function, decision variables, and constraint functions (Raju et al, 2020). The aim of the objective function in these optimization calculations is to achieve the highest possible annual cropping intensity (Maliwal et al, 2019).…”

Section: Optimization Of Single Reservoir Operationmentioning

confidence: 99%

Optimization of Pengga Reservoir in The Mandalika Special Economic Zone for Irrigation and Water Supply

Agastya,

I Wayan Yasa,

I Dewa Gede Jaya Negara

2024

J. civil eng. forum

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Mandalika Special Economic Zone is tourism area that is expected to improve the economy in West Nusa Tenggara Province. To support these activities, an allocation of domestic water needs of 200 liters second -1 is needed. The potential availability of water in the Pengga Reservoir is planned to be a source of domestic water needs in the Mandalika Special Economic Zone. Pengga Reservoir has an effective storage volume of 17.26 MCM. Potential water resources in Pengga Reservoir are obtained from reservoir outflow upstream and lateral inflow from several tributaries. The study was carried out to determine the reservoir storage capacity to meet domestic water needs and irrigation water needs covering an area 3189 ha. The cropping pattern used in the Pengga irrigation area is Paddy – Paddy/Secondary Crops – Paddy/Secondary Crops. To optimize the potential of water resources in the Pengga Reservoir, a linear programming optimization method is used. Indicators of the success of optimization calculations are indicated by the value of cropping intensity, k factor and reliability that have met the minimum limit value. The k factor value for irrigation water needs is 0.70 and domestic water needs is 0.85. Based on the optimization results, it is known the largest annual cropping intensity value occurs in the November I planting season. This conclusion can be seen from the comparison of annual cropping intensity values for the November I and November II planting schedules for the dry year inflow discharge scenario of 99.98% and 97.22% respectively. The cropping intensity value in the November I planting season is greater than November II, namely 100% and 97.25%, for the normal year discharge inflow scenario. This study provides an information for policy makers can use the November I planting schedule to obtain values for maximum cropping intensity and domestic water requirements.

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Section: Optimization Of Single Reservoir Operationmentioning

confidence: 99%

Optimization of Pengga Reservoir in The Mandalika Special Economic Zone for Irrigation and Water Supply

Agastya,

I Wayan Yasa,

I Dewa Gede Jaya Negara

2024

J. civil eng. forum

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“…These complex modeling tools, including optimization programming techniques, solution algorithms, and inference models, can be classified into five main categories as shown in Figure 6: (1) implicit stochastic optimization (ISO) models, (2) explicit stochastic optimization (ESO) models, (3) computational intelligence (CI) models, (4) multi-objective optimization (MLO) models, and (5) simulation-optimization (S-O) models. ISO is an optimization modeling technique that implicitly includes stochastic features of reservoir random variables (e.g., spatial and temporal variations of inflow discharges) using deterministic optimization programming techniques such as linear programming (LP) [40][41][42][43][44] and its extensions (binary LP (BLP), integer LP (ILP), mixed-integer LP (MILP), non-linear programming (NLP) [45][46][47][48][49] including the successive LP (SLP), sequential quadratic programming (SQP), generalized reduced gradient (GRG), deterministic dynamic programming (DDP) [50][51][52][53][54] and its modified models to solve its curse of dimensionality (dynamic programming successive approximation (DPSA), incremental DP (IDP), discrete differential DP (DDDP), and discrete-time optimal control theory (DOCT)) [55,56]. The deterministic optimization models can generate the optimal policies for several historical or synthetically time-series data for reservoir random variables (e.g., inflow).…”

Section: Topic 1: Optimization Modelsmentioning

confidence: 99%

Dam System and Reservoir Operational Safety: A Meta-Research

Badr,

Li,

El-Dakhakhni

2023

Water

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Dams are critical infrastructure necessary for water security, agriculture, flood risk management, river navigation, and clean energy generation. However, these multiple, and often conflicting, objectives introduce complexity in managing dam operations. In addition, dam infrastructure has been evolving as complex systems-of-systems with multiple interacting components and subsystems, all susceptible to a wide range of uncertainties. Such complexities and uncertainties have triggered extensive research initiatives focused on dam systems and reservoir operational safety. Focusing on the latter, this paper meta-researches (conducts research-on-research) previously published studies to identify the critical research gaps and propose future research directions. In this respect, this paper first performs a quantitative analysis of the pertinent literature, using text mining and subsequent topic modeling, to identify and classify major and uncover latent topics in the field. Subsequently, qualitative analysis is conducted to critically review the identified topics, exploring the concepts, definitions, modeling tools, and major research trends. Specifically, the study identified seven topics: optimization models; climate change; flood risk; inflow forecasting; hydropower generation; water supply management; and risk-based assessment and management. The study also presents three main research gaps associated with the limitations in modeling concepts, modeling tools capabilities, and the lack of resilience-guided management of dam operational safety. Overall, this study presents a road map of the currently available dam and reservoir operational safety research and associated knowledge gaps, as well as potential future research directions to ensure the resilience of such critically important infrastructure, especially in the age of climate change.

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“…One of the most important methods for optimization is Linear programming. It is an operation approach that universally preferred and has been widely used in managing water resource planning and problems [30].…”

Section: Linear Programmingmentioning

confidence: 99%

Fuzzy Logic Model for Optimal Operation of Darbandikhan Reservoir, Iraq

Faris¹,

Ibrahim²,

Abdulrahman³

et al. 2021

IJDNE

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The operating system of a reservoir is a significant contributor to its success in water resources management. For a multi-purpose reservoir, an ideal operating system determines output characteristics that take account of all objectives. In this study, a new model to optimize Darbandikhan reservoir system operation in Iraq is proposed, based on a fuzzy logic controller. The aim of the new system is to maximize hydropower production while satisfying all downstream water demands. The proposal was tested on flow and other data in 324 monthly time steps, from January 1992 to December 2018, using a simulation model based on the Simulink technique of MATLAB software. Trial and error showed that membership functions of the Gaussian shape were most appropriate. For comparison purposes, Discrete Differential Dynamic Programming (DDDP), Nonlinear Programming (NLP) and Linear Programming (LP) optimization models were developed and applied to operate the reservoir. The results for turbine operation show that, relative to actual power produced, average monthly hydropower generation is increased by 32.2% (fuzzy logic), 51.4% (DDDP), 29.3% (NLP), 27.4% (LP). Although the dynamic programming method generated more hydropower, the fuzzy logic controller avoided complex optimization procedures, making it more flexible and more acceptable to operators. Moreover, the fuzzy approach provides an opportunity for reservoir operators to develop and apply more convenient operating rules, which in itself is a valuable alternative to conventional optimization techniques.

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Optimization of Reservoir Operation using Linear Programming

Cited by 4 publications

References 3 publications

Optimization of Pengga Reservoir in The Mandalika Special Economic Zone for Irrigation and Water Supply

Optimization of Pengga Reservoir in The Mandalika Special Economic Zone for Irrigation and Water Supply

Dam System and Reservoir Operational Safety: A Meta-Research

Fuzzy Logic Model for Optimal Operation of Darbandikhan Reservoir, Iraq

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