Short-Term Flood Control and Long-Term Energy Maximization in Multi-reservoir Systems Using Improved Particle Swarm Optimization

Güvengir, Umut; Savaşaneril, Seçil; Altan-Sakarya, A. Burcu; Buhan, Serkan

doi:10.1007/s11269-021-02947-8

Cited by 6 publications

(4 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…through the algorithm. Furthermore, Güvengir et al [95] applied PSO for the first time to a large-scale problem in the context of flood prevention, demonstrating that the algorithm is capable of early warning and control of floods. To ensure the cost-effective operation of industrial production practices, a new deep learning-driven particle swarm optimization approach to optimize energy utility was proposed by Qin et al [96].…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

A Review of Optimal Design for Large-Scale Micro-Irrigation Pipe Network Systems

Wang,

Zhang,

Wang

et al. 2023

Agronomy

View full text Add to dashboard Cite

Micro-irrigation pipe network systems are commonly utilized for water transmission and distribution in agricultural irrigation. They effectively transport and distribute water to crops, aiming to achieve water and energy conservation, increased yield, and improved quality. This paper presents a model for the scaled micro-irrigation pipeline network system and provides a comprehensive review of the fundamental concepts and practical applications of optimization techniques in the field of pipeline network design. This paper is divided into four main sections: Firstly, it covers the background and theoretical foundations of optimal design for scaled micro-irrigation pipeline network systems. Secondly, the paper presents an optimal design model specifically tailored for scaled micro-irrigation pipeline networks. And then, it discusses various optimization solution techniques employed for addressing the design challenges of scaled micro-irrigation pipeline networks, along with real-world case studies. Finally, this paper concludes with an outlook on the ongoing research and development efforts in the field of scaled micro-irrigation pipeline network systems. In addition, this paper establishes a fundamental model for optimizing pipeline networks, to achieve minimum safe operation and total cost reduction. It considers constraints such as pipeline pressure-bearing capacity, maximum flow rate, and diameter. The decision-making variables include pipeline diameter, length, internal roughness, node pressure, future demand, and valve placement. Additionally, this paper provides an extensive overview of deterministic methods and heuristic algorithms utilized in the optimal design of micro-irrigation pipeline networks. Finally, this paper presents future research directions for pipeline network optimization and explores the potential for algorithmic improvements, integration of machine learning techniques, and wider adoption of EPANET 2.0 software. These endeavors aim to lay a strong foundation for effectively solving complex and challenging optimization problems in micro-irrigation pipeline network systems in the future.

show abstract

Section: Particle Swarm Optimizationmentioning

confidence: 99%

A Review of Optimal Design for Large-Scale Micro-Irrigation Pipe Network Systems

Wang,

Zhang,

Wang

et al. 2023

Agronomy

View full text Add to dashboard Cite

show abstract

“…On the contrary, parallel reservoirs do not have any hydraulic inter-relationship, where the safety of the downstream area is affected by the coordination in RFCO of the parallel reservoirs. Regarding the mixed reservoir systems, RFCO is more complicated, where the complexity of hydraulic connection for the cascading reservoirs and the coordination of asynchronous peak flows for the parallel reservoirs should be considered simultaneously (see [147][148][149][150][151][152]).…”

Section: Topic 3: Flood Riskmentioning

confidence: 99%

“…Therefore, advanced optimization and simulation methods (reviewed in topic 1) were adopted to provide optimal real-time RFCO operating rules under various operational conditions. These studies consider different aspects of the RFCO, including single and multiple reservoirs [147,[155][156][157], short-term and long-term scheduling [148,158,159], single and multi-objective approaches [144,[160][161][162][163][164], and multi-criteria decision-making models [93,94,165,166]).…”

Section: Topic 3: Flood Riskmentioning

confidence: 99%

Dam System and Reservoir Operational Safety: A Meta-Research

Badr,

Li,

El-Dakhakhni

2023

Water

View full text Add to dashboard Cite

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.

show abstract

“…Most recently, Chen et al (2020) used PSO with adaptive random inertia weights for multi-objective reservoir operation. Guvengir et al (2021) used an improved PSO for short-term flood control and long-term energy maximization in multi-reservoir systems. Although some techniques have been proposed to optimize a FCO model, solving multi-reservoir FCO problem is more difficult than a single reservoir (Li and Ouyang, 2015;Qi et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Flood Control Operation of Reservoir Group Using Yin-Yang Firefly Algorithm

Chen

Wang

Chau

et al. 2021

Water Resour Manage

View full text Add to dashboard Cite

Flood control operation (FCO) of a reservoir is a complex optimization problem with a large number of constraints. With the rapid development of optimization techniques in recent years, more and more research efforts have been devoted to optimizing FCO problems. However, for solving large-scale reservoir group optimization problem, this is still a challenging task. In this work, a reservoir group FCO model is established with minimum flood volume stored in each reservoir and minimum peak flow of downstream control point during the dispatch process. At the same time, a flood forecast model for FCO of a reservoir group is developed by coupling Yin-Yang firefly algorithm (YYFA) with ε constrained method. As a case study, the proposed model is applied to a three-reservoir flood control system in Luanhe River Basin consisting of reservoirs, river channels, and downstream control points.Results show that optimal operation of three reservoirs systems can efficiently reduce the occupied storage capacity for flood control and flood peaks at downstream control point of the basin. The proposed method can be extended to FCO of other reservoir groups with similar conditions.

show abstract

Short-Term Flood Control and Long-Term Energy Maximization in Multi-reservoir Systems Using Improved Particle Swarm Optimization

Cited by 6 publications

References 18 publications

A Review of Optimal Design for Large-Scale Micro-Irrigation Pipe Network Systems

A Review of Optimal Design for Large-Scale Micro-Irrigation Pipe Network Systems

Dam System and Reservoir Operational Safety: A Meta-Research

Flood Control Operation of Reservoir Group Using Yin-Yang Firefly Algorithm

Contact Info

Product

Resources

About