Sensitivity analysis and optimal operation control for large-scale waterflooding pipeline network of oilfield

2017 ◽  
Vol 154 ◽  
pp. 38-48 ◽  
Author(s):  
Haoran Zhang ◽  
Yongtu Liang ◽  
Xingyuan Zhou ◽  
Xiaohan Yan ◽  
Chen Qian ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Large Scale ◽  
Optimal Operation ◽  
Pipeline Network ◽  
Operation Control

Optimal Operation Control for Multiple BESSs of a Large-Scale Customer Under Time-Based Pricing

2018 ◽  
Vol 33 (1) ◽  
pp. 803-816 ◽  
Author(s):  
Seul-Ki Kim ◽  
Jong-Yul Kim ◽  
Kyeong-Hee Cho ◽  
Gilsung Byeon
Keyword(s):  
Large Scale ◽  
Optimal Operation ◽  
Operation Control

scholarly journals The research on the operation mode and parameter selection method of large-scale water injection pipeline network

2021 ◽  
Author(s):  
Yan Ruan ◽  
Huan Liu ◽  
Jiaona Chen
Keyword(s):  
Large Scale ◽  
Effective Means ◽  
Operation Mode ◽  
Water Injection ◽  
Selection Method ◽  
Optimal Operation ◽  
Injection System ◽  
Operating Parameters ◽  
Pipe Network ◽  
Pipeline Network

AbstractDue to the complexity of the large-scale water injection pipe network system and the difficulty of manual analysis, it is impossible to guarantee the optimal operation mode scheme selected. At present, there are still gaps in the research on the judgment of its optimal operation mode. Through the calculation and evaluation of a large amount of water injection system data, the selection method of the optimal operation mode of the water injection system is determined, and it is found that the selection of the optimal operation mode is closely related to the pressure distribution characteristics of the individual wells of the entire water injection system, and five discriminant rules for the optimal operation mode of the water injection system are formed based on these characteristics; the mathematical model for determining the mode and the optimal method of operating parameters is given, and the pipeline network simulation system automatically generates the pipe network topology diagram; the optimal operation mode of the water injection system is developed; Intelligent judgment software can modify its operating parameters according to needs, change operating modes, easily simulate the energy consumption in various modes of operation, adjust and find the optimal operation plan of the water injection pipe network. Application examples show that the judgment rules of the optimal operation mode of the water injection system and the optimization method of operating parameters can be used as an effective means for selecting the optimal operation plan for a large-scale water injection pipeline network.

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

Energies ◽  
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.

Parameter Sensitivity Analysis of a Large-Scale System With Several Components Interacting in Series

1989 ◽  
Author(s):  
H. Torab
Keyword(s):  
Sensitivity Analysis ◽  
Large Scale ◽  
Optimization Problems ◽  
Parameter Sensitivity ◽  
Engineering Optimization ◽  
Parameter Sensitivity Analysis ◽  
Large Scale Systems ◽  
In Series ◽  
Special Case ◽  
Engineering Optimization Problems

Abstract Parameter sensitivity for large-scale systems that include several components which interface in series is presented. Large-scale systems can be divided into components or sub-systems to avoid excessive calculations in determining their optimum design. Model Coordination Method of Decomposition (MCMD) is one of the most commonly used methods to solve large-scale engineering optimization problems. In the Model Coordination Method of Decomposition, the vector of coordinating variables can be partitioned into two sub-vectors for systems with several components interacting in series. The first sub-vector consists of those variables that are common among all or most of the elements. The other sub-vector consists of those variables that are common between only two components that are in series. This study focuses on a parameter sensitivity analysis for this special case using MCMD.

A Novel Approach for Two-Stage UAV Path Planning in Pipeline Network Inspection

2020 ◽  
Author(s):  
Rui Qiu ◽  
Yongtu Liang
Keyword(s):  
Path Planning ◽  
Large Scale ◽  
Flight Path ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Two Stage ◽  
Calculation Time ◽  
Pipeline Network ◽  
Second Stage ◽  
Computational Performance

Abstract Currently, unmanned aerial vehicle (UAV) provides the possibility of comprehensive coverage and multi-dimensional visualization of pipeline monitoring. Encouraged by industry policy, research on UAV path planning in pipeline network inspection has emerged. The difficulties of this issue lie in strict operational requirements, variable flight missions, as well as unified optimization for UAV deployment and real-time path planning. Meanwhile, the intricate structure and large scale of the pipeline network further complicate this issue. At present, there is still room to improve the practicality and applicability of the mathematical model and solution strategy. Aiming at this problem, this paper proposes a novel two-stage optimization approach for UAV path planning in pipeline network inspection. The first stage is conventional pre-flight planning, where the requirement for optimality is higher than calculation time. Therefore, a mixed integer linear programming (MILP) model is established and solved by the commercial solver to obtain the optimal UAV number, take-off location and detailed flight path. The second stage is re-planning during the flight, taking into account frequent pipeline accidents (e.g. leaks and cracks). In this stage, the flight path must be timely rescheduled to identify specific hazardous locations. Thus, the requirement for calculation time is higher than optimality and the genetic algorithm is used for solution to satisfy the timeliness of decision-making. Finally, the proposed method is applied to the UAV inspection of a branched oil and gas transmission pipeline network with 36 nodes and the results are analyzed in detail in terms of computational performance. In the first stage, compared to manpower inspection, the total cost and time of UAV inspection is decreased by 54% and 56% respectively. In the second stage, it takes less than 1 minute to obtain a suboptimal solution, verifying the applicability and superiority of the method.

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