Risk-Constrained Stochastic Scheduling of a Grid-Connected Hybrid Microgrid with Variable Wind Power Generation

This paper presents a risk-constrained scheduling optimization model for a grid-connected hybrid microgrid including demand response (DR), electric vehicles (EVs), variable wind power generation and dispatchable generation units. The proposed model determines optimal scheduling of dispatchable units, interactions with the main grid as well as adjustable responsive loads and EVs demand to maximize the expected microgrid operator’s profit under different scenarios. The uncertainties of day-ahead (DA) market prices, wind power production and demands of customers and EVs are considered in this study. To address these uncertainties, conditional value-at-risk (CVaR) as a risk measurement tool is added to the optimization model to evaluate the risk of profit loss and to indicate decision attitudes in different conditions. The proposed method is finally applied to a typical hybrid microgrid with flexible demand-side resources and its applicability and effectives are verified over different working conditions with uncertainties

Protocol Adherence for Severe Sepsis and Septic Shock Management in the Emergency Department; a Clinical Audit

Introduction: Although significant development in the field of medicine is achieved, sepsis is still a major issue threatening humans’ lives. This study was aimed to audit the management of severe sepsis and septic shock patients in emergency department (ED) according to the present standard guidelines.Method: This is a prospective audit on approaching adult septic patients who were admitted to ED. The audit checklist was created based on the protocols of Surviving Sepsis Campaign and British Royal College recommendations. The mean knowledge score and the compliance rate of studied measures regarding standard protocols were calculated using SPSS version 21.Results: 30 emergency medicine residents were audited (63.3% male). The mean knowledge score of studied residents regarding standard guidelines were 5.07 ± 1.78 (IQR = 2) in pre education and 8.17 ± 1.31 (IQR = 85) in post education phase (p < 0.001). There was excellent compliance with standard in 4 (22%) studied measures, good in 2 (11%), fair in 1 (6%), weak in 2 (11%), and poor in 9 (50%). 64% of poor compliance measures correlated to therapeutic factors. After training, score of 5 measures including checking vital signs in < 20 minute, central vein pressure measurement in < 1 hour, blood culture request, administration of vasopressor agents, and high flow O2 therapy were improved clinically, but not statistically.Conclusion: The protocol adherence in management of severe sepsis and septic shock for urine output measurement, central venous pressure monitoring, administration of inotrope agents, blood transfusion, intravenous antibiotic and hydration therapy, and high flow O2 delivery were disappointingly low. It seems training workshops and implementation of Clinical audit can improve residents’ adherence to current standard guidelines regarding severe sepsis and septic shock

Study of the Effect of Time-Based Rate Demand Response Programs on Stochastic Day-Ahead Energy and Reserve Scheduling in Islanded Residential Microgrids

In recent deregulated power systems, demand response (DR) has become one of the most cost-effective and efficient solutions for smoothing the load profile when the system is under stress. By participating in DR programs, customers are able to change their energy consumption habits in response to energy price changes and get incentives in return. In this paper, we study the effect of various time-based rate (TBR) programs on the stochastic day-ahead energy and reserve scheduling in residential islanded microgrids (MGs). An effective approach is presented to schedule both energy and reserve in presence of renewable energy resources (RESs) and electric vehicles (EVs). An economic model of responsive load is also proposed on the basis of elasticity factor to model the behavior of customers participating in various DR programs. A two-stage stochastic programming model is developed accordingly to minimize the expected cost of MG under different TBR programs. To verify the effectiveness and applicability of the proposed approach, a number of simulations are performed under different scenarios using real data; and the impact of TBR-DR actions on energy and reserve scheduling are studied and compared subsequently