Development of reservoir operation rules using seasonal climate forecasts

ABSTRACT This study verified the suitability of using precipitation forecasts in defining operation rules for the Cruzeta reservoir in Rio Grande do Norte, Brazil. The operation rules were developed through reservoir operation simulation–optimization, using a genetic algorithm. The performance indicators were analyzed in five operation scenarios: standard operating policy (SOP), current reservoir rationing rule (C), rationing without forecast (R), rationing with forecast (RF), and rationing with perfect forecast (RPF). The SOP scenario better met the total demand but made the system very susceptible to supply collapse. The results of the RF and RPF scenarios showed better compliance with the priority demands and the total demand during the dry periods. Changing from RF to RPF scenario, there is a small improvement in the evaluation indexes. The use of rules integrating the seasonal weather forecast is thus recommended.

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Faculty Opinions recommendation of Malaria early warnings based on seasonal climate forecasts from multi-model ensembles.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.9199.467505 ◽

2006 ◽

Author(s):

Sari Kovats

Keyword(s):

Seasonal Climate ◽

Climate Forecasts ◽

Model Ensembles ◽

Seasonal Climate Forecasts ◽

Early Warnings

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Constraints and Suggestions in Adopting Seasonal Climate Forecasts by Farmers in South India

The Journal of Agricultural Education and Extension ◽

10.1080/1389224x.2011.544456 ◽

2011 ◽

Vol 17 (2) ◽

pp. 153-163 ◽

Cited By ~ 8

Author(s):

K. Ravi Shankar ◽

K. Nagasree ◽

B. Venkateswarlu ◽

Pochaiah Maraty

Keyword(s):

South India ◽

Seasonal Climate ◽

Climate Forecasts ◽

Seasonal Climate Forecasts

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Combined Aggregated Sampling Stochastic Dynamic Programming and Simulation-Optimization to Derive Operation Rules for Large-Scale Hydropower System

Energies ◽

10.3390/en14030625 ◽

2021 ◽

Vol 14 (3) ◽

pp. 625

Author(s):

Xinyu Wu ◽

Rui Guo ◽

Xilong Cheng ◽

Chuntian Cheng

Keyword(s):

Dynamic Programming ◽

Stochastic Dynamic Programming ◽

Large Scale ◽

Simulation Optimization ◽

Optimal Operation ◽

Stochastic Dynamic ◽

Operation Model ◽

Two Stage ◽

Operation Rules ◽

Reservoir Systems

Simulation-optimization methods are often used to derive operation rules for large-scale hydropower reservoir systems. The solution of the simulation-optimization models is complex and time-consuming, for many interconnected variables need to be optimized, and the objective functions need to be computed through simulation in many periods. Since global solutions are seldom obtained, the initial solutions are important to the solution quality. In this paper, a two-stage method is proposed to derive operation rules for large-scale hydropower systems. In the first stage, the optimal operation model is simplified and solved using sampling stochastic dynamic programming (SSDP). In the second stage, the optimal operation model is solved by using a genetic algorithm, taking the SSDP solution as an individual in the initial population. The proposed method is applied to a hydropower system in Southwest China, composed of cascaded reservoir systems of Hongshui River, Lancang River, and Wu River. The numerical result shows that the two-stage method can significantly improve the solution in an acceptable solution time.

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A Reservoir Operation Policy Using Inter-Basin Water Transfer for Maximizing Hydroelectric Benefits in Brazil

Energies ◽

10.3390/en13102564 ◽

2020 ◽

Vol 13 (10) ◽

pp. 2564 ◽

Cited By ~ 2

Author(s):

Anderson Passos de Aragão ◽

Patrícia Teixeira Leite Asano ◽

Ricardo de Andrade Lira Rabêlo

Keyword(s):

Reservoir Operation ◽

Network Flow ◽

Water Transfer ◽

Energy Deficit ◽

Generation System ◽

Operation Rules ◽

First Case ◽

Basin Water ◽

Hydroelectric Plants

The Hydrothermal Coordination problem consists of determining an operation policy for hydroelectric and thermoelectric plants within a given planning horizon. In systems with a predominance of hydraulic generation, the operation policy to be adopted should specify the operation of hydroelectric plants, so that hydroelectric resources are used economically and reliably. This work proposes the implementation of reservoir operation rules, using inter-basin water transfer through an optimization model based on Network Flow and Particle Swarm Optimization (PSO). The proposed algorithm aims to obtain an optimized operation policy of power generation reservoirs and consequently to maximize the hydroelectric benefits of the hydrothermal generation system, to reduce the use of thermoelectric plants, the importation and/or energy deficit and to reduce the cost associated with meeting the demand and reduce CO2 emissions from combustion of fossil fuels used by thermoelectric plants. In order to illustrate the efficiency and effectiveness of the proposed approach, it was evaluated by optimizing two case studies using a system with four hydroelectric plants. The first case study does not consider transfer and water and the second case study uses water transfer between rivers. The obtained results illustrate that the proposed model allowed to maximize the hydroelectric resources of a hydrothermal generation system with economy and reliability.

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