Adaptive Algorithms for Estimating Betweenness and k -path Centralities

International audienc

Optimal Operation of Climate Control Systems of Produce Storage Facilities in Smart Grids

(© 2015 IEEE) Bozchalui, M. C., Canizares, C. A., & Bhattacharya, K. (2015). Optimal operation of climate control systems of produce storage facilities in smart grids. IEEE Transactions on Smart Grid, 6(1), 351–359. https://doi.org/10.1109/tsg.2014.2325553This paper presents mathematical optimization models of produce storage facilities to optimize the operation of their energy systems in the context of smart grids. In the storage facilities, climate control of the storage rooms consumes considerable energy; thus, in this paper, a mathematical model of storage facilities appropriate for their optimal operation is developed, so that it can be implemented as a supervisory control in existing climate controllers. The proposed model incorporates weather forecasts, electricity price information, and the end-user preferences to optimally operate existing climate control systems in storage facilities. The objective is to minimize total energy costs and demand charges while considering important parameters of storage facilities, i.e., inside temperature and humidity should be kept within acceptable ranges. The performance of the proposed model for various electricity prices and weather conditions and their variations are studied via Monte Carlo Simulations (MCS). The presented simulation results show the effectiveness of the proposed model to reduce total energy costs while maintaining required operational constraints

Optimal Energy Management of Greenhouses in Smart Grids

(© 2015 IEEE) Bozchalui, M. C., Canizares, C. A., & Bhattacharya, K. (2015). Optimal Energy Management of greenhouses in smart grids. IEEE Transactions on Smart Grid, 6(2), 827–835. https://doi.org/10.1109/tsg.2014.2372812This paper presents a novel hierarchical control approach and new mathematical optimization models of greenhouses, which can be readily incorporated into energy hub management systems (EHMSs) in the context of smart grids to optimize the operation of their energy systems. In greenhouses, artificial lighting, CO2 production, and climate control systems consume considerable energy; thus, a mathematical model of greenhouses appropriate for their optimal operation is proposed, so that it can be implemented as a supervisory control in existing greenhouse control systems. The objective is to minimize total energy costs and demand charges while considering important parameters of greenhouses; in particular, inside temperature and humidity, CO2 concentration, and lighting levels should be kept within acceptable ranges. Therefore, the proposed model incorporates weather forecasts, electricity price information, and the end-user preferences to optimally operate existing control systems in greenhouses. Effects of uncertainty in electricity price and weather forecast on optimal operation of the storage facilities are studied through Monte Carlo simulations. The presented simulation results show the effectiveness of the proposed model to reduce total energy costs while maintaining required operational constraints.Ontario Centres of Excellence || Hydro One Networks, Inc. || Milton Hydro Distribution, Inc. || Energent, Inc. || 10.13039/501100004526-Ontario Power Authority

Evaluation of the comparative effectiveness of three therapeutic drug regimens in the treatment of medication overuse headache in the patients with headache

Background and Aim: Medication overuse headache (MOH) is the second leading cause of chronic headaches. This study aimed to compare the efficacy of three medication regimens in the treatment of MOH in the patients referring to the neurology clinic of Imam Khomeini Hospital in Urmia in 2018. Material and Methods: This was a randomized clinical trial. Participants in this study selected from MOH patients referring to neurology clinic of Imam Khomeini Hospital in Urmia from Feb to Aug 2018. Our study included 60 patients. Patients were randomly assigned to one of the following 3 groups; prednisolone, celecoxib or a combination of both medications. The duration of treatment was 15 days for all the patients. At the end of the study period, the patients provided the information in regard to the severity, duration, and the number of headache days. Results: The mean duration of headache was 3.55 ± 1.58 months. Gender had no significant relationship with age and the duration of headache. The mean values for severity of headache were 8.2 ±0.71, 2.33 ± 0.84 and 2.3 ±0.95 at the first, second and third visits respectively. The mean values for severity of headache at first visit was higher in the patients receiving celecoxib compared to those in the other two treatment groups. At the second and third visits, the mean values for severity of headache were lower in the patients receiving combination therapy. Difference between the scores of severity of headache at the first visit was higher than those at the second and third visits in the combination group which indicated greater effect of this treatment regimen on reducing the severity of the headache compared to the other treatment groups. Conclusion: All three-treatment regimens were effective in reducing headaches, but the combination regimen was more effective. Both celecoxib and prednisolone had beneficial effects on reducing the severity of headache, but celecoxib was more effective. © 2018 the Author (s)

Optimal Operation of Residential Energy Hubs in Smart Grids

(© 2012 IEEE) Bozchalui, M. C., Hashmi, S. A., Hassen, H., Canizares, C. A., & Bhattacharya, K. (2012). Optimal operation of residential energy hubs in smart grids. IEEE Transactions on Smart Grid, 3(4), 1755–1766. https://doi.org/10.1109/tsg.2012.2212032This paper presents mathematical optimization models of residential energy hubs which can be readily incorporated into automated decision making technologies in smart grids, and can be solved efficiently in a real-time frame to optimally control all major residential energy loads, storage and production components while properly considering the customer preferences and comfort level. Novel mathematical models for major household demand, i.e., fridge, freezer, dishwasher, washer and dryer, stove, water heater, hot tub, and pool pumps are formulated. Also, mathematical models of other components of a residential energy system including lighting, heating, and air-conditioning are developed, and generic models for solar PV panels and energy storage/generation devices are proposed. The developed mathematical models result in Mixed Integer Linear Programming (MILP) optimization problems with the objective functions of minimizing energy consumption, total cost of electricity and gas, emissions, peak load, and/or any combination of these objectives, while considering end-user preferences. Several realistic case studies are carried out to examine the performance of the mathematical model, and experimental tests are carried out to find practical procedures to determine the parameters of the model. The application of the proposed model to a real household in Ontario, Canada is presented for various objective functions. The simulation results show that savings of up to 20% on energy costs and 50% on peak demand can be achieved, while maintaining the household owner's desired comfort levels