scholarly journals Study on Optimization of Active Control Schemes for Considering Transient Processes in the Case of Pipeline Leakage

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1692
Author(s):  
Wan Zhang ◽  
Ruihao Shen ◽  
Ning Xu ◽  
Haoran Zhang ◽  
Yongtu Liang
Keyword(s):  
Active Control ◽  
Programming Model ◽  
High Reliability ◽  
Control Measures ◽  
Transient Processes ◽  
Mixed Integer ◽  
Effective Control ◽  
Hydraulic Systems ◽  
Control Plan ◽  
Control Schemes

Pipeline leakage of crude oil, refined oil or other petroleum derivatives can cause serious damage to the environment, soil, and more importantly, pose a serious threat to personal safety. The losses can be minimized to a degree by active control. Therefore, timely and effective control measures should be taken to minimize the leak volume whenever a pipeline leaks. However, the complexity of pipeline hydraulic systems makes it difficult to optimize control schemes for pipeline hydraulic devices under leak conditions, and existing studies rarely consider complex transient processes. This paper aims to establish a mixed integer linear programming model considering transient processes, hydraulic constraints, equipment constraints and flow constraints, and develop a detailed control scheme of the devices by the branch and bound algorithm. Moreover, it is the objective of the model to figure out the most optimal control plan to minimize the leakage. Experiments on a real-world liquid pipeline have proved the practicability and high reliability of the model.

scholarly journals The Effect of Nonlinear Charging Function and Line Change Constraints on Electric Bus Scheduling

2021 ◽  
Vol 33 (4) ◽  
pp. 527-538
Author(s):  
Aijia Zhang ◽  
Tiezhu Li ◽  
Ran Tu ◽  
Changyin Dong ◽  
Haibo Chen ◽  
...  
Keyword(s):  
Real World ◽  
Control Method ◽  
Large Deviation ◽  
Programming Model ◽  
Piecewise Linear ◽  
Mixed Integer ◽  
Piecewise Linear Approximation ◽  
Effective Control ◽  
Electric Bus ◽  
Bus Schedule

The recharging plans are a key component of the electric bus schedule. Since the real-world charging function of electric vehicles follows a nonlinear relationship with the charging duration, it is challenging to accurately estimate the charging time. To provide a feasible bus schedule given the nonlinear charging function, this paper proposes a mixed integer programming model with a piecewise linear charging approximation and multi-depot and multi-vehicle type scheduling. The objective of the model is to minimise the total cost of the schedule, which includes the vehicle purchasing cost and operation cost. From a practical point of view, the number of line changes of each bus is also taken as one of the constraints in the optimisation. An improved heuristic algorithm is then proposed to find high-quality solutions of the problem with an efficient computation. Finally, a real-world dataset is used for the case study. The results of using different charging functions indicate a large deviation between the linear charging function and the piecewise linear approximation, which can effectively avoid the infeasible bus schedules. Moreover, the experiments show that the proposed line change constraints can be an effective control method for transit operators.

Mixing in regional-structure model about the influence of floating population and optimal control about TB in Guangdong province of China

2017 ◽  
Vol 10 (08) ◽  
pp. 1750106 ◽  
Author(s):  
Chuanqing Xu ◽  
Xiaoxiao Wei ◽  
Jingan Cui ◽  
Xiaojing Wang ◽  
Dashun Xu
Keyword(s):  
Deterministic Model ◽  
Reproduction Number ◽  
Programming Model ◽  
Vaccine Coverage ◽  
Local Population ◽  
Guangdong Province ◽  
Control Measures ◽  
Floating Population ◽  
Effective Control ◽  
Prevention Measures

In the last 60 years, great progress has been made in controlling and preventing tuberculosis in China. However, the number of tuberculosis cases has increased dramatically in the last 25 years, mainly due to the lack of effective control measures of immigrating populations with tuberculosis. In order to explore the effective control and prevention measures we propose a deterministic model to study the transmission dynamics of tuberculosis in Guangdong province of China in this paper. The model consists of susceptible, exposed and infectious recovered subpopulations of immigrating populations from other provinces and the local population of Guangdong. We obtain the effective reproduction number. Based on the analysis, we also establish an optimal immune programming model, and get the optimal proportion of vaccine coverage with control of the effective reproduction number. Simulation is used to determine the validation and reliability. Our study demonstrates that the immigrating population from different provinces needs to be vaccinated according to the incidence rate of TB in their original provinces, and it is an effective way to prevent the outbreak of tuberculosis in Guangdong.

Designing a drone assisted sample collection and testing system during epidemic outbreaks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sayan Chakraborty ◽  
Raviarun Arumugaraj Nadar ◽  
Aviral Tiwari
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Clinical Sample ◽  
Diagnostic System ◽  
Mixed Integer ◽  
Effective Control ◽  
Sample Collection ◽  
Two Phase ◽  
Content Type ◽  
Urban City

Purpose A major component in managing pandemic outbreaks involves testing the suspected individuals and isolating them to avoid transmission in the community. This requires setting up testing centres for diagnosis of the infected individuals, which usually involves movement of either patient from their residence to the testing centre or personnel visiting the patient, thus aggregating the risk of transmission to localities and testing centres. The purpose of this paper is to investigate and minimize such movements by developing a drone assisted sample collection and diagnostic system. Design/methodology/approach Effective control of an epidemic outbreak calls for a rapid response and involves testing suspected individuals and isolating them to avoid transmission in the community. This paper presents the problem in a two-phase manner by locating sample collection centres while assigning neighbourhoods to these collection centres and thereafter, assigning collection centres to nearest testing centres. To solve the mathematical model, this study develops a mixed-integer linear programming model and propose an integrated genetic algorithm with a local search-based approach (GA-LS) to solve the problem. Findings Proposed approach is demonstrated as a case problem in an Indian urban city named Kolkata. Computational results show that the integrated GA-LS approach is capable of producing good quality solutions within a short span of time, which aids to the practicality in the circumstance of a pandemic. Social implications The COVID-19 pandemic has shown that the large-scale outbreak of a transmissible disease may require a restriction of movement to take control of the exponential transmission. This paper proposes a system for the location of clinical sample collection centres in such a way that drones can be used for the transportation of samples from the neighbourhood to the testing centres. Originality/value Epidemic outbreaks have been a reason behind a major number of deaths across the world. The present study addresses the critical issue of identifying locations of temporary sample collection centres for drone assisted testing in major cities, which is by its nature unique and has not been considered by any other previous literature. The findings of this study will be of particular interest to the policy-makers to build a more robust epidemic resistance.

Implementation of Hamilton-Wentworth Region’s Pollution Control Plan

1996 ◽  
Vol 31 (3) ◽  
pp. 453-472 ◽  
Author(s):  
M. Stirrup
Keyword(s):  
Wastewater Treatment ◽  
Pollution Control ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Control Measures ◽  
Storm Events ◽  
Combined Sewer Overflows ◽  
Control Plan ◽  
Combined Sewer ◽  
Sewer Overflows

Abstract The Regional Municipality of Hamilton-Wentworth operates a large combined sewer system which diverts excess combined sewage to local receiving waters at over 20 locations. On average, there are approximately 23 combined sewer overflows per year, per outfall. The region’s Pollution Control Plan, adopted by Regional Council in 1992, concluded that the only reasonable means of dealing with large volumes of combined sewer overflow in Hamilton was to intercept it at the outlets, detain it and convey it to the wastewater treatment plant after the storm events. The recommended control strategy relies heavily on off-line storage, with an associated expansion of the Woodward Avenue wastewater treatment plant to achieve target reductions of combined sewer overflows to 1–4 per year on average. The region has begun to implement this Pollution Control Plan in earnest. Three off-line detention storage tanks are already in operation, construction of a fourth facility is well underway, and conceptual design of a number of other proposed facilities has commenced. To make the best possible use of these facilities and existing in-line storage, the region is implementing a microcomputer-based real-time control system. A number of proposed Woodward Avenue wastewater treatment plant process upgrades and expansions have also been undertaken. This paper reviews the region's progress in implementing these control measures.

Analysis on the Penetration Level of Wind Farm Considering Transient Stability Constraint and Uncertainty of Wind Power

2020 ◽  
Vol 13 (7) ◽  
pp. 1078-1086
Author(s):  
Bai Hao ◽  
Huang Andi ◽  
Zhou Changcheng
Keyword(s):  
Wind Power ◽  
Energy Function ◽  
Wind Farm ◽  
Transient Stability ◽  
Programming Model ◽  
Forecast Error ◽  
Credibility Theory ◽  
Mixed Integer ◽  
Stability Constraint ◽  
Level Problem

Background: The penetration level of a wind farm with transient stability constraint and static security constraint has been a key problem in wind power applications. Objective: The study explores maximum penetration level problem of wind considering transient stability constraint and uncertainty of wind power out, based on credibility theory and corrected energy function method. Methods: According to the corrected energy function, the transient stability constraint of the power grid is transferred to the penetration level problem of a wind farm. Wind speed forecast error is handled as a fuzzy variable to express the uncertainty of wind farm output. Then this paper builds a fuzzy chance-constrained model to calculate wind farm penetration level. To avoid inefficient fuzzy simulation, the model is simplified to a mixed integer linear programming model. Results: The results validate the proposed model and investigate the influence of grid-connection node, wind turbine characteristic, fuzzy reliability index, and transient stability index on wind farm penetration level. Conclusion: The result shows that the model proposed in this study can consider the uncertainty of wind power out and establish a quantitative transient stability constraint to determine the wind farm penetration level with a certain fuzzy confidence level.

Characterizing the effectiveness of COVID-19 mitigation measures: A data-centric approach (Preprint)

2020 ◽  
Author(s):  
Lukman Olagoke ◽  
Ahmet E. Topcu
Keyword(s):  
Control Measure ◽  
Control Measures ◽  
World Health ◽  
Mitigation Measures ◽  
Effective Control ◽  
The World ◽  
Decision Making Processes ◽  
And Performance ◽  
Health Organization ◽  
The Impact

BACKGROUND COVID-19 represents a serious threat to both national health and economic systems. To curb this pandemic, the World Health Organization (WHO) issued a series of COVID-19 public safety guidelines. Different countries around the world initiated different measures in line with the WHO guidelines to mitigate and investigate the spread of COVID-19 in their territories. OBJECTIVE The aim of this paper is to quantitatively evaluate the effectiveness of these control measures using a data-centric approach. METHODS We begin with a simple text analysis of coronavirus-related articles and show that reports on similar outbreaks in the past strongly proposed similar control measures. This reaffirms the fact that these control measures are in order. Subsequently, we propose a simple performance statistic that quantifies general performance and performance under the different measures that were initiated. A density based clustering of based on performance statistic was carried out to group countries based on performance. RESULTS The performance statistic helps evaluate quantitatively the impact of COVID-19 control measures. Countries tend show variability in performance under different control measures. The performance statistic has negative correlation with cases of death which is a useful characteristics for COVID-19 control measure performance analysis. A web-based time-line visualization that enables comparison of performances and cases across continents and subregions is presented. CONCLUSIONS The performance metric is relevant for the analysis of the impact of COVID-19 control measures. This can help caregivers and policymakers identify effective control measures and reduce cases of death due to COVID-19. The interactive web visualizer provides easily digested and quick feedback to augment decision-making processes in the COVID-19 response measures evaluation. CLINICALTRIAL Not Applicable

scholarly journals Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1452
Author(s):  
Cristian Mateo Castiblanco-Pérez ◽  
David Esteban Toro-Rodríguez ◽  
Oscar Danilo Montoya ◽  
Diego Armando Giral-Ramírez
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Power Balance ◽  
Continuous Version ◽  
Discrete Part

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

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