Reduced resting skeletal muscle protein synthesis is rescued by resistance exercise and protein ingestion following short-term energy deficit

The myofibrillar protein synthesis (MPS) response to resistance exercise (REX) and protein ingestion during energy deficit (ED) is unknown. We determined, in young men (n=8) and women (n=7), protein signaling, resting post-absorptive MPS during energy balance [EB: 45 kcal∙(kg FFM∙d)-1] and after 5d of ED [30 kcal∙(kg FFM∙d)-1] as well as MPS while in ED after acute REX in the fasted state and with the ingestion of whey protein (15 and 30 g). Post-absorptive rates of MPS were 27% lower in ED than EB (P<0.001), but REX stimulated MPS to rates equal to EB. Ingestion of 15 and 30 g of protein after REX in ED increased MPS ~16 and ~34% above resting EB, (P<0.02). p70 S6Kthr389 phosphorylation increased above EB only with combined exercise and protein intake (~2-7 fold; P<0.05). In conclusion, short-term ED reduces post-absorptive MPS, however, a bout of REX in ED restores MPS to values observed at rest in EB. The ingestion of protein after REX further increases MPS above resting EB in a dose-dependent manner. We conclude that combining REX with increased protein availability after exercise enhances rates of skeletal muscle protein synthesis during short term ED and could, in the long term, preserve muscle mass.

Short-term energy forecasting using time series techniques: Chile, a case study

Includes bibliography

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Design of a renewable - hybrid energy storage power scheme for short-term power dispatch

A hybrid energy storage system (HESS) consisting of battery and supercapacitor (SC) is proposed for use in a wind farm in order to achieve power dispatchability. In the designed scheme, the rate of charging/discharging powers of the battery is controlled while the faster wind power transients are diverted to the SC. This enhances the lifetime of the battery. Furthermore, by taking into consideration the random nature of the wind power, a statistical design method is developed to determine the capacities of the HESS needed to achieve specified confidence level in the power dispatch. The proposed approach is useful in the planning of the wind farm-HESS scheme and the coordination of the power flows between the battery and SC.

Some behaviours of strongest short-term coastal change induced by cross-shore wave energy flow and corresponding theoretical consideration

There is a number of famous theoretical and experimental works that oriented themselves to solve actual problem of coastal change, including the change of coastline, under versatile influence of oceanic wind waves. In this paper the author would like to give supplementally a few new behaviours of that phenomena observed along the coasts of Vietnam, such as coastal collapse & primitive on-the-spot accumulation, material hurl, etc. Most simple theoretical explanation of them grounding on the Newton's second law has been presented and as results of that there appeared such notion as indicator and criterion which could be used for demarcation of different behaviours in initial stage of general coastal changing processes.

Real-time energy resources scheduling considering short-term and very short-term wind forecast

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process it is necessary the update of generation and consumption operation and of the storage and electric vehicles storage status. Besides the new operation condition, it is important more accurate forecast values of wind generation and of consumption using results of in short-term and very short-term methods. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

Combined Pool/Bilateral Short-Term Hydrothermal Scheduling Model for Day-Ahead Energy Markets

This paper proposes a combined pool/bilateral short term hydrothermal scheduling model (PDC) for the context of the day-ahead energy markets. Some innovative aspects are introduced in the model, such as: i) the hydraulic generation is optimized through the opportunity cost function proposed; ii) there is no decoupling between physical and commercial dispatches, as is the case today in Brazil; iii) interrelationships between pool and bilateral markets are represented through a single optimization problem; iv) risk exposures related to future deficits are intrinsically mitigated; v) the model calculates spot prices in an hourly basis and the results show a coherent correlation between hydrological conditions and calculated prices. The proposed PDC model is solved by a primal-dual interior point method and is evaluated by simulations involving a test system. The results are focused on sensitivity analyses involving the parameters of the model, in such a way to emphasize its main modeling aspects. The results show that the proposed PDC provides a conceptual means for short term price formation for hydrothermal systems.

Energy supply and demand in the short term, 1979 and 1980 : analysis report /

"AR/ES/79-28"

Combined effects of short-term exposure to elevated CO2 and decreased O2 on the physiology and energy budget of the thick shell mussel Mytilus coruscus

Hypoxia and ocean acidification are two consequences of anthropogenic activities. These global trends occur on top of natural variability. In environments such as estuarine areas, short-term acute pH and O2 fluctuations are occurring simultaneously. The present study tested the combined effects of short-term seawater acidification and hypoxia on the physiology and energy budget of the thick shell mussel Mytilus coruscus. Mussels were exposed for 72 h to six combined treatments with three pH levels (8.1, 7.7 and 7.3) and two dissolved oxygen (DO) levels (2 mg/L, 6 mg/L). Clearance rate (CR), food absorption efficiency (AE), respiration rate (RR), ammonium excretion rate (ER), O:N ratio and scope for growth (SFG) were significantly reduced, and faecal organic dry weight ratio (E) was significantly increased at low DO. Low pH did not lead to a reduced SFG. Interactive effects of pH and DO were observed for CR, E and RR. Principal component analysis (PCA) revealed positive relationships among most physiological indicators, especially between SFG and CR under normal DO conditions. These results demonstrate that Mytilus coruscus was sensitive to short-term (72 h) exposure to decreased O2 especially if combined with decreased pH levels. In conclusion, the short-term oxygen and pH variation significantly induced physiological changes of mussels with some interactive effects.

Does metabolic compensation explain the majority of less-than-expected weight loss in obese adults during a short-term severe diet and exercise intervention?

Objective: We investigated to what extent changes in metabolic rate and composition of weight loss explained the less-than-expected weight loss in obese men and women during a diet-plus-exercise intervention. Design: 16 obese men and women (41 ± 9 years; BMI 39 ± 6 kg/m2) were investigated in energy balance before, after and twice during a 12-week VLED (565–650 kcal/day) plus exercise (aerobic plus resistance training) intervention. The relative energy deficit (EDef) from baseline requirements was severe (74-87%). Body composition was measured by deuterium dilution and DXA and resting metabolic rate (RMR) by indirect calorimetry. Fat mass (FM) and fat-free mass (FFM) were converted into energy equivalents using constants: 9.45 kcal/gFM and 1.13 kcal/gFFM. Predicted weight loss was calculated from the energy deficit using the '7700 kcal/kg rule'. Results: Changes in weight (-18.6 ± 5.0 kg), FM (-15.5 ± 4.3 kg), and FFM (-3.1 ± 1.9 kg) did not differ between genders. Measured weight loss was on average 67% of the predicted value, but ranged from 39 to 94%. Relative EDef was correlated with the decrease in RMR (R=0.70, P<0.01) and the decrease in RMR correlated with the difference between actual and expected weight loss (R=0.51, P<0.01). Changes in metabolic rate explained on average 67% of the less-than-expected weight loss, and variability in the proportion of weight lost as FM accounted for a further 5%. On average, after adjustment for changes in metabolic rate and body composition of weight lost, actual weight loss reached 90% of predicted values. Conclusion: Although weight loss was 33% lower than predicted at baseline from standard energy equivalents, the majority of this differential was explained by physiological variables. While lower-than-expected weight loss is often attributed to incomplete adherence to prescribed interventions, the influence of baseline calculation errors and metabolic down-regulation should not be discounted.