Rolling Scheduling Method considering Shiftable Demand Respond Resources

In order to deal with the fluctuation of the renewable energy, this paper proposes rolling scheduling strategy taking into account the capacity of load-side resources. By considering the energy characteristics of shiftable loads, an improved rolling scheduling model is proposed by adopting a full-cycle scheduling and adding periodic power constraints. By this way, the accuracy of the scheduling can be improved. The testing examples verified that the proposed rolling scheduling method can reflect the long-time benefit and therefore result in better performance.

Optimal Cleaning Cycle Scheduling under Uncertain Conditions: A Flexibility Analysis on Heat Exchanger Fouling

Fouling is a substantial economic, energy, and safety issue for all the process industry applications, heat transfer units in particular. Although this phenomenon can be mitigated, it cannot be avoided and proper cleaning cycle scheduling is the best way to deal with it. After thorough literature research about the most reliable fouling model description, cleaning procedures have been optimized by minimizing the Time Average Losses (TAL) under nominal operating conditions according to the well-established procedure. For this purpose, different cleaning actions, namely chemical and mechanical, have been accounted for. However, this procedure is strictly related to nominal operating conditions therefore perturbations, when present, could considerably compromise the process profitability due to unexpected shutdown or extraordinary maintenance operations. After a preliminary sensitivity analysis, the uncertain variables and the corresponding disturbance likelihood were estimated. Hence, cleaning cycles were rescheduled on the basis of a stochastic flexibility index for different probability distributions to show how the uncertainty characterization affects the optimal time and economic losses. A decisional algorithm was finally conceived in order to assess the best number of chemical cleaning cycles included in a cleaning supercycle. In conclusion, this study highlights how optimal scheduling is affected by external perturbations and provides an important tool to the decision-maker in order to make a more conscious design choice based on a robust multi-criteria optimization.

Adaptive Power Control and Fuzzy Based Duty Cycle Scheduling in Under Water Sensor Network (UWSN)

In Under Water Sensor Network (UWSN), power control algorithm should consider channel condition and frame loss probability. Also the queue length variations or traffic load should be considered for fixing the sleep duty cycle. In this paper, we propose to design an Adaptive Power Control and Fuzzy based Duty Cycle Scheduling (APC-FDS) algorithm for clustered UWSN. In the adaptive power control algorithm, the sender node will fix the minimum transmit power such that the energy consumption and frame loss probability are minimized. In adaptive duty cycle scheduling, the duty cycle is adaptively adjusted by considering the connection value and traffic load using fuzzy logic technique. The connectivity between a cluster and its neighboring cluster is estimated using the connection value. The cluster head collects the traffic information from its members. Experimental results show that the APS-FDS algorithm reduces the average energy consumption and frame loss probability.

Effect of Oral Contraceptive Pill Pretreatment on Pregnancy Rates in Patients Stimulated with GnRH Antagonists and rFSH for ICSI

Background: After the recent introduction of GnRH antagonists in ovarian stimulation, OCP has been used for cycle scheduling purposes. Cycle programming has become more difficult with the use of GnRH antagonists, as stimulation initiation is dependent on the occurrence of menstruation. To overcome this limitation in the GnRH antagonist protocol, patients can be offered the use of pretreatment with oral contraceptive pills (OCP). Objective: To evaluate the effect of oral contraceptive pills (OCP) pretreatment on pregnancy rate in GnRH antagonist cycles. Design: Observational cohort study. Setting: Observational study performed at Sri Ramachandra institute of higher education & research Chennai. Patients: Total 115 patients included in the study from January 2019 to December 2019. All patients divided into two groups, oral contraceptives pretreated group (n-64) and oral contraceptives non treated group (n-51). Results: All oral contraceptives pretreated patients required significantly higher dose of gonadotropins (4745±1476 versus 3659±1230;P <0.0005) and significantly longer days of stimulations (12.2±1.2 versus 10.5±0.8;P <0.0005) in comparison to non-oral contraceptives treated group. There were no difference in total oocytes retrieved and fertilization rate. There were no other differences in cycle characteristics between groups. Implantation and pregnancy rates were not affected by OCP pretreatment. Conclusions: OCP pretreatment use for synchronization of follicles and cycle scheduling in GnRH-antagonist protocol, though it may be associated with longer stimulation and higher gonadotropin consumption but similar pregnancy rates.

DDS: A Delay-Constrained Duty-Cycle Scheduling Algorithm in Wireless Sensor Networks

Since sensor nodes usually have a large duty cycle interval to prolong network lifetime, duty-cycled wireless sensor networks (WSNs) can suffer from a long end-to-end (E2E) delay. Because delay-sensitive applications have a certain E2E delay requirement, a lot of studies have tried to tackle the long E2E delay problem. However, most existing studies focused on simply reducing the E2E delay rather than considering the delay bound requirement, which makes it hard to achieve balanced performance between E2E delay and energy efficiency. Although a few studies took into consideration both the delay bound requirement and energy consumption, they required specific node deployment or strict time synchronization between nodes in the network. In order to address the limitations of the existing studies, we propose a delay-constrained duty-cycle scheduling (DDS) algorithm. The objective of DDS is to achieve low energy consumption while satisfying the delay bound requirement in various node deployment scenarios depending on user demands. First, based on network topology information collected by the sink, one-hop delay distribution is derived as a function of the duty cycle interval. Then, the E2E delay distribution is estimated using the Lyapunov central limit theorem, which allows each node group to have a different delay distribution. Finally, the duty cycle interval is determined using the estimated E2E delay distribution such that energy consumption is minimized while meeting the delay bound requirement. Practical WSN deployment scenarios are considered to evaluate the proposed algorithm. The simulation results show that DDS can guarantee the given delay bound requirement and outperform existing algorithms in terms of energy efficiency.