Hybrid intervention scheme-based optimization algorithm for real-time management of reactive power resources

2017 ◽  
Vol 65 (11) ◽  
Author(s):  
Deesh Dileep ◽  
José Luis Rueda Torres ◽  
Sander Franke ◽  
Peter Palensky
Keyword(s):  
Power System ◽  
Real Time ◽  
Reactive Power ◽  
Transmission System ◽  
Mixed Integer ◽  
Base Case ◽  
System Control ◽  
Case Scenario ◽  
Base Case Scenario ◽  
Non Linear

AbstractThis article introduces a Hybrid Intervention Scheme Based Optimization (HIBO) algorithm solving an Optimal Reactive Power Management (ORPM) problem in real-time using a Mixed Integer Linear Programming (MILP) solver. The ORPM problem presented here contains a linear objective function containing four objectives separated using a set of static penalty factors for each area. The non-linear optimization problem has been assumed linear by localizing the search for solution, this is done by introducing a penalty on the change from the original state or the base case scenario. Thereby, optimizing the non-linear ORPM in linear steps makes it a fast solver for small changes in power system state. A contingency analysis (for N-1 voltage violations) is included for ensuring the safety and reliability of the power system. The results are used to update the ORPM problem or stop if the system is secure. The optimization variables used to represent transformer taps and shunt device switches are handled as discrete integers and remaining variables as continuous real numbers. The intervention scheme, objectives and constraints used in the HIBO have been derived through surveys conducted at a transmission system control center and are supported using literature. Validation of the HIBO algorithm was performed on the Dutch transmission network model after dividing it into four regional areas. Convergence characteristics of the HIBO algorithm are compared using results. From the results, it is concluded that the HIBO algorithm is a competitive optimization solver, suitable for deployment in the secondary voltage control scheme within system operations domain for transmission system operators.

Economic modeling of woody biomass utilization for bioenergy and its application in central Appalachia, USA

2011 ◽  
Vol 41 (1) ◽  
pp. 165-179 ◽  
Author(s):  
Jinzhuo Wu ◽  
Jingxin Wang ◽  
Joseph McNeel
Keyword(s):  
West Virginia ◽  
Programming Model ◽  
Woody Biomass ◽  
Economic Modeling ◽  
Mixed Integer ◽  
Base Case ◽  
Case Scenario ◽  
Base Case Scenario ◽  
Biomass Utilization ◽  
Price Demand

A mixed integer programming model was developed to estimate the delivered cost of woody biomass, including the costs associated with stumpage, bundling (if any), extraction, storage, loading and hauling, and chipping–grinding under different woody biomass handling systems. The model was designed to optimize a woody biomass based biofuel facility’s location with the objective of minimizing the total annual delivered cost of woody biomass under resource and operational constraints. The model was applied in the central Appalachian region within the state of West Virginia. Results showed that the optimal plant location would be at Addison or Grantsville in West Virginia, depending on the system used when daily demand is 900 tonnes of dry woody biomass. For that base-case scenario, the average delivered cost ranged from $2.30·GJ–1 to $3.02·GJ–1 across the systems. Extensive sensitivity analysis was performed under different scenarios, including biomass availability and purchase–stumpage price, demand, extraction distance, and fuel pricing. The delivered cost was mostly affected by woody biomass demand. Skidding distance had the least impact on the delivered cost. The results would be useful in facilitating the research and economic development of woody biomass utilization for bioenergy in the region.

scholarly journals Modelling and mitigating dose to firefighters from inhalation of radionuclides in wildland fire smoke

2015 ◽  
Vol 24 (5) ◽  
pp. 723 ◽  
Author(s):  
Brian J. Viner ◽  
Tim Jannik ◽  
Daniel Stone ◽  
Allan Hepworth ◽  
Luke Naeher ◽  
...  
Keyword(s):  
Environmental Conditions ◽  
Wildland Fire ◽  
Radioactive Material ◽  
Fuel Load ◽  
Base Case ◽  
Published Data ◽  
Case Scenario ◽  
Base Case Scenario ◽  
Fuel Loads ◽  
Radiological Dose

Firefighters responding to wildland fires where surface litter and vegetation contain radiological contamination will receive a radiological dose by inhaling resuspended radioactive material in the smoke. This may increase their lifetime risk of contracting certain types of cancer. Using published data, we modelled hypothetical radionuclide emissions, dispersion and dose for 70th and 97th percentile environmental conditions and for average and high fuel loads at the Savannah River Site. We predicted downwind concentration and potential dose to firefighters for radionuclides of interest (137Cs, 238Pu, 90Sr and 210Po). Predicted concentrations exceeded dose guidelines in the base case scenario emissions of 1.0 × 107 Bq ha–1 for 238Pu at 70th percentile environmental conditions and average fuel load levels for both 4- and 14-h shifts. Under 97th percentile environmental conditions and high fuel loads, dose guidelines were exceeded for several reported cases for 90Sr, 238Pu and 210Po. The potential for exceeding dose guidelines was mitigated by including plume rise (>2 m s–1) or moving a small distance from the fire owing to large concentration gradients near the edge of the fire. This approach can quickly estimate potential dose from airborne radionuclides in wildland fire and assist decision-making to reduce firefighter exposure.

scholarly journals Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm

2017 ◽  
Vol 7 (5) ◽  
pp. 2349 ◽  
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Scheduling Problem ◽  
Power Scheduling

<p>This paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature.</p>

scholarly journals Impact of changes in the methodology of external price referencing on medicine prices: discrete-event simulation

2020 ◽  
Author(s):  
Sabine Vogler ◽  
Peter Schneider ◽  
Lena Lepuschütz
Keyword(s):  
Cost Containment ◽  
Discrete Event ◽  
Real Life ◽  
Base Case ◽  
Case Scenario ◽  
Medicine Price ◽  
Base Case Scenario ◽  
The Real ◽  
Methodological Choices ◽  
Medicine Prices

Abstract Background: Several governments apply the policy of external price referencing (EPR), which considers the prices of a medicine in one or more other countries for the purpose of setting the price in the own country. Different methodological choices can be taken to design EPR. The study aimed to analyse whether, or not, and how changes in the methodology of EPR can impact medicine prices.Methods: The real-life EPR methodology as of Q1/2015 was surveyed in all European Union Member States (where applicable), Iceland, Norway and Switzerland through a questionnaire responded by national pricing authorities. Different scenarios were developed related to the parameters of the EPR methodology. Discrete-event simulations of fictitious prices in the 28 countries of the study that had EPR were run over 10 years. The continuation of the real-life EPR methodology in the countries as surveyed in 2015, without any change, served as base case.Results: In most scenarios, after ten years, medicine prices in all or most surveyed countries were – sometimes considerably – lower than in the base case scenario. But in a few scenarios medicine prices increased in some countries. Consideration of discounts (an assumed 20% discount in five large economies and the mandatory discount in Germany, Greece and Ireland) and determining the reference price based on the lowest price in the country basket would result in higher price reductions (on average -47.2% and -34.2% compared to the base case). An adjustment of medicine price data of the reference countries by purchasing power parities would lead to higher prices in some more affluent countries (e.g. Switzerland, Norway) and lower prices in lower-income economies (Bulgaria, Romania, Hungary, Poland). Regular price revisions and changes in the basket of reference countries would also impact medicine prices, however to a lesser extent.Conclusions: EPR has some potential for cost-containment. Medicine prices could be decreased if certain parameters of the EPR methodology were changed. If public payers aim to apply EPR to keep medicine prices at more affordable levels, they are encouraged to explore the cost-containment potential of this policy by taking appropriate methodological choices in the EPR design.

scholarly journals Skenario Pengembangan Untuk Meningkatkan Recovery Factor Pada Lapangan TR Lapisan X Dengan Menggunakan Simulasi Reservoir

PETRO ◽  
2018 ◽  
Vol 4 (4) ◽  
Author(s):  
Muhamad Taufan Azhari
Keyword(s):  
Reservoir Simulation ◽  
History Matching ◽  
Control Volume ◽  
Base Case ◽  
Case Scenario ◽  
Injection Wells ◽  
Base Case Scenario ◽  
Development Scenarios ◽  
Production Wells ◽  
Grid Construction

<p>Reservoir simulation is an area of reservoir engineering in which computer models are used to predict the flow of fluids through porous media. Reservoir simulation process starts with several steps; data preparation, model and grid construction, initialization, history matching and prediction. Initialization process is done for matching OOIP or total initial hydrocarbon which fill reservoir with hydrocarbon control volume with volumetric method.</p><p>To aim the best encouraging optimum data, these development scenarios of TR Field Layer X will be predicted for 30 years (from 2014 until January 2044). Development scenarios in this study consist of 4 scenarios : Scenario 1 (Base Case), Scenario 2 (Base Case + Reopening non-active wells), Scenario 3 (scenario 2 + infill production wells), Scenario 4 (Scenario 2 + 5 spot pattern of infill injection wells).</p>

Abstract T MP100: Improving Encounter Frequency, Physician Prescribing, or Patient Adherence - What Works Best for Controlling Blood Pressure? Results From a Validated Micro-Simulation Model

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
Valy Fontil ◽  
Kirsten Bibbins-Domingo ◽  
Dhruv Kazi ◽  
Pamela Coxson ◽  
Steve Sidney ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Clinical Trial ◽  
Patient Adherence ◽  
The United States ◽  
Control Model ◽  
Uncontrolled Hypertension ◽  
Base Case ◽  
Treatment Intensification ◽  
Case Scenario ◽  
Base Case Scenario

Background: Only half of hypertensive adults achieve blood pressure (BP) control in the United States. Methods: We developed the BP Control Model to simulate physician- and patient-level processes relevant in achieving BP control. We validated the model by simulating the intervention arm of a recent multicenter clinical trial and used the validated model to examine the effects of isolated improvements in three modifiable processes on BP control. Data from national surveys, cohort studies, and trials were used to parameterize the model. We simulated 5,000 hypothetical adult patients with uncontrolled hypertension (systolic BP≥ 140) using probability sampling of participants from the 2009-2010 National Health and Nutrition Examination Survey. We modeled 50% improvements and ideal scenarios for each process parameter. Outcome: We reported outcomes in terms of BP control (% with SBP < 140 mmHg), and average change in BP at 52 weeks. Results: In our validation analysis, the model-predicted BP control was similar to what was achieved in the VIPER-BP clinical trial (63.5% vs. 63.8%). In our base case scenario, 24% of the NHANES-derived cohort achieved BP control at 52 weeks. In scenarios with 50% improvements, the model predicted small increases in BP control, but substantially larger and more variable effects when processes were idealized (Table). Control was reached in 77% with ideal treatment intensification, 44% with ideal encounter frequency, only 32% with ideal adherence, and 97% when all three processes were idealized. Conclusion: While improving patient adherence to medications would improve BP control, healthcare systems can achieve similar or greater success by focusing on increasing the frequency of clinical encounters and improving physicians’ prescribing behavior. The BP Control Model can be used to predict how much improvement to expect from such interventions.

scholarly journals Security Constrained Unit Commitment in a Power System based on Benders Decomposition and Mixed Integer Non-linear Programming

2018 ◽  
Vol 7 (2.6) ◽  
pp. 283 ◽  
Author(s):  
Pranda Prasanta Gupta ◽  
Prerna Jain ◽  
Suman Sharma ◽  
Rohit Bhakar
Keyword(s):  
Linear Programming ◽  
Network Security ◽  
Power System ◽  
Optimal Power Flow ◽  
Benders Decomposition ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Reserve Requirement ◽  
Non Linear Programming ◽  
Non Linear

In deregulated power markets, Independent System Operators (ISOs) maintains adequate reserve requirement in order to respond to generation and system security constraints. In order to estimate accurate reserve requirement and handling non-linearity and non-convexity of the problem, an efficient computational framework is required. In addition, ISO executes SCUC in order to reach the consistent operation. In this paper, a novel type of application which is Benders decomposition (BD) and Mixed integer non linear programming (MINLP) can be used to assess network security constraints by using AC optimal power flow (ACOPF) in a power system. It performs ACOPF in network security check evaluation with line outage contingency. The process of solving modified system would be close to optimal solution, the gap between the close to optimal and optimal solution is expected to determine whether a close to optimal solutionis accepetable for convenientpurpose. This approach drastically betters the fast computational requirement in practical power system .The numerical case studies are investigated in detail using an IEEE 118-bus system. 

Optimizing Strategies for Chlamydia trachomatis and Neisseria gonorrhoeae Screening in Men Who Have Sex With Men: A Modeling Study

2019 ◽  
Vol 70 (9) ◽  
pp. 1966-1972
Author(s):  
Nicolas Voirin ◽  
Camille Allam ◽  
Caroline Charre ◽  
Christine Fernandez ◽  
Matthieu Godinot ◽  
...  
Keyword(s):  
Chlamydia Trachomatis ◽  
Neisseria Gonorrhoeae ◽  
Screening Strategy ◽  
Unprotected Sex ◽  
Base Case ◽  
Case Scenario ◽  
Base Case Scenario ◽  
Systematic Screening ◽  
Ct Screening ◽  
Sex With Men

Abstract Background International guidelines recommend the systematic screening for Neisseria gonorrhoeae (NG) and Chlamydia trachomatis (CT) infections in all men who have sex with men (MSM) who have engaged in unprotected sex. However, the optimal screening strategy remains unclear. We developed a modeling approach to optimize NG/CT screening strategy in MSM. Methods A compartmental model of NG/CT screening and infection was implemented. NG/CT anal, pharyngeal, and urine (APU) samples from MSM attending the sexually transmitted infections clinic were used to estimate the screening rate, prevalence, and incidence in a base case scenario. Different screening strategies (scenarios; S) were then evaluated: APU samples every 12 months (S1); APU samples every 3 months (S2); APU samples every 6 months (S3); anal and pharyngeal (AP) samples every 6 months (S4); and AP samples every 3 months (S5). Results We analyzed 2973 triplet APU samples from 1255 patients. We observed 485 NG and 379 CT diagnoses. NG/CT prevalence and incidence estimates were 12.0/11.1% and 40/29 per 100 person-years, respectively, in the base case scenario. As compared to S2, the reference strategy, the proportions of missed NG/CT diagnoses were 42.0/41.2% with S1, 21.8/22.5% with S3, 25.6/28.3% with S4, and 6.3/10.5% with S5, respectively. As compared to S2, S1 reduced the cost of the analysis by 74%, S3 by 50%, S4 by 66%, and S5 by 33%. The numbers needed to screen for catching up the missed NG/CT diagnoses were 49/67 with S1, 62/82 with S3, 71/87 with S4, and 143/118 with S5. Conclusions S5 appears to be the best strategy, missing only 6.3/10.5% of NG/CT diagnoses, for a cost reduction of 33%.

scholarly journals Cost-effectiveness of a Contact Intervention and a Psychotherapeutic Program for Post-discharge Suicide Prevention: Rentabilité D’une Intervention de Contact et d’un Programme de Psychothérapie Pour la Prévention du Suicide Après le Congé de L’hôpital

2020 ◽  
pp. 070674372098013
Author(s):  
Gonzalo Martínez-Alés ◽  
José B. Cruz Rodríguez ◽  
Pablo Lázaro ◽  
Arce Domingo-Relloso ◽  
María Luisa Barrigón ◽  
...  
Keyword(s):  
Health Care ◽  
Cost Effectiveness ◽  
Suicide Prevention ◽  
Cost Effective ◽  
Cost Data ◽  
Base Case ◽  
Case Scenario ◽  
Post Discharge ◽  
Base Case Scenario ◽  
Augmentation Strategies

Objective: To determine the cost-effectiveness of 2 strategies for post-discharge suicide prevention, an Enhanced Contact intervention based on repeated in-person and telephone contacts, and an individual 2-month long problem-solving Psychotherapy program, in comparison to facilitated access to outpatient care following a suicide attempt. Methods: We conducted a cost-effectiveness analysis based on a decision tree between January and December 2019. Comparative effectiveness estimates were obtained from an observational study conducted between 2013 and 2017 in Madrid, Spain. Electronic health care records documented resource use (including extra-hospital emergency care, mortality, inpatient admission, and disability leave). Direct cost data were derived from Madrid’s official list of public health care prices. Indirect cost data were derived from Spain’s National Institute of Statistics. Results: Both augmentation strategies were more cost-effective than a single priority outpatient appointment considering reasonable thresholds of willingness to pay. Under the base-case scenario, Enhanced Contact and Psychotherapy incurred, respectively, €2,340 and 6,260 per averted attempt, compared to a single priority appointment. Deterministic and probabilistic sensitivity analyses showed both augmentation strategies to remain cost-effective under several scenarios. Enhanced Contact was slightly cost minimizing in comparison to Psychotherapy (base-case scenario: €−196 per averted attempt). Conclusions: Two post-discharge suicide prevention strategies based on Enhanced Contact and Psychotherapy were cost-effective in comparison to a single priority appointment. Increasing contacts between suicide attempters and mental health-care providers was slightly cost minimizing compared to psychotherapy.

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