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.

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.

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 .

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

ANN based day-ahead spinning reserve forecast for electricity market simulation

Electricity market players operating in a liberalized environment require adequate decision support tools, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. This paper deals with short-term predication of day-ahead spinning reserve (SR) requirement that helps the ISO to make effective and timely decisions. Based on these forecasted information, market participants can use strategic bidding for day-ahead SR market. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Short- and medium-term effects of manual therapy on cervical active range of motion and pressure pain sensitivity in latent myofascial pain of the upper trapezius muscle: a randomized controlled trial

Objective: The purpose of this study was to investigate effects of different manual techniques on cervical ranges of 17 motion and pressure pain sensitivity in subjects with latent trigger point of the upper trapezius muscle. 18 Methods: One hundred seventeen volunteers, with a unilateral latent trigger point on upper trapezius due to computer 19 work, were randomly divided into 5 groups: ischemic compression (IC) group (n = 24); passive stretching group (n = 20 23); muscle energy technique group (n = 23); and 2 control groups, wait-and-see group (n = 25) and placebo group 21 (n = 22). Cervical spine range of movement was measured using a cervical range of motion instrument as well as 22 pressure pain sensitivity by means of an algometer and a visual analog scale. Outcomes were assessed pretreatment, 23 immediately, and 24 hours after the intervention and 1 week later by a blind researcher. A 4 × 5 mixed repeated- 24 measures analysis of variance was used to examine the effects of the intervention and Cohen d coefficient was used. 25 Results: A group-by-time interaction was detected in all variables (P b .01), except contralateral rotation. The 26 immediate effect sizes of the contralateral flexion, ipsilateral rotation, and pressure pain threshold were large for 3 27 experimental groups. Nevertheless, after 24 hours and 1 week, only IC group maintained the effect size. 28 Conclusions: Manual techniques on upper trapezius with latent trigger point seemed to improve the cervical range of 29 motion and the pressure pain sensitivity. These effects persist after 1 week in the IC group. (J Manipulative Physiol 301 Ther 2013;xx:1-10)

Short-term Wind Forecasting to Support Virtual Power Player Operation

This paper proposes a wind speed forecasting model that contributes to the development and implementation of adequate methodologies for Energy Resource Man-agement in a distribution power network, with intensive use of wind based power generation. The proposed fore-casting methodology aims to support the operation in the scope of the intraday resources scheduling model, name-ly with a time horizon of 10 minutes. A case study using a real database from the meteoro-logical station installed in the GECAD renewable energy lab was used. A new wind speed forecasting model has been implemented and it estimated accuracy was evalu-ated and compared with a previous developed forecast-ing model. Using as input attributes the information of the wind speed concerning the previous 3 hours enables to obtain results with high accuracy for the wind short-term forecasting.

Stochastic Framework for Strategic Decision-making of Load-serving Entities for Day-ahead Market

The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

Stochastic Short-term Incentive-based Demand Response Scheduling of Load-serving Entities

In competitive electricity markets it is necessary for a profit-seeking load-serving entity (LSE) to optimally adjust the financial incentives offering the end users that buy electricity at regulated rates to reduce the consumption during high market prices. The LSE in this model manages the demand response (DR) by offering financial incentives to retail customers, in order to maximize its expected profit and reduce the risk of market power experience. The stochastic formulation is implemented into a test system where a number of loads are supplied through LSEs.

Multiagent System Architecture for Short-term Operation of Integrated Microgrids

The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid’s internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

Frailty as a predictor of short-term adverse outcomes

The objectives of this study were to compare how different frailty measures (Frailty Phenotype/FP, Groningen Frailty Indicator/GFI and Tilburg Frailty Indicator/TFI) predict short-term adverse outcomes. Secondarily, adopting a multidimensional approach to frailty (integral conceptual model–TFI), this study aims to compare how physical, psychological and social frailty predict the outcomes. A longitudinal study was carried out with 95 community-dwelling elderly. Participants were assessed at baseline for frailty, determinants of frailty, and adverse outcomes (healthcare utilization, quality of life, disability in basic and instrumental activities of daily living/ADL and IADL). Ten months later the outcomes were assessed again. Frailty was associated with specific healthcare utilization indicators: the FP with a greater utilization of informal care; GFI with an increased contact with healthcare professionals; and TFI with a higher amount of contacts with a general practitioner. After controlling for the effect of life-course determinants, comorbidity and adverse outcome at baseline, GFI predicted IADL disability and TFI predicted quality of life. The effect of the FP on the outcomes was not significant, when compared with the other measures. However, when comparing TFI’s domains, the physical domain was the most significant predictor of the outcomes, even explaining part of the variance of ADL disability. Frailty at baseline was associated with adverse outcomes at follow-up. However, the relationship of each frailty measure (FP, GFI and TFI) with the outcomes was different. In spite of the role of psychological frailty, TFI’s physical domain was the determinant factor for predicting disability and most of the quality of life.

Use of a fluorescence-based approach to assess short-term responses of the alga Pseudokirchneriella subcapitata to metal stress

This work explores the use of fluorescent probes to evaluate the responses of the green alga Pseudokirchneriella subcapitata to the action of three nominal concentrations of Cd(II), Cr(VI), Cu(II) and Zn(II) for a short time (6 h). The toxic effect of the metals on algal cells was monitored using the fluorochromes SYTOX Green (SG, membrane integrity), fluorescein diacetate (FDA, esterase activity) and rhodamine 123 (Rh123, mitochondrial membrane potential). The impact of metals on chlorophyll a (Chl a) autofluorescence was also evaluated. Esterase activity was the most sensitive parameter. At the concentrations studied, all metals induced the loss of esterase activity. SG could be used to effectively detect the loss of membrane integrity in algal cells exposed to 0.32 or 1.3 μmol L−1 Cu(II). Rh123 revealed a decrease in the mitochondrial membrane potential of algal cells exposed to 0.32 and 1.3 μmol L−1 Cu(II), indicating that mitochondrial activity was compromised. Chl a autofluorescence was also affected by the presence of Cr(VI) and Cu(II), suggesting perturbation of photosynthesis. In conclusion, the fluorescence-based approach was useful for detecting the disturbance of specific cellular characteristics. Fluorescent probes are a useful diagnostic tool for the assessment of the impact of toxicants on specific targets of P. subcapitata algal cells.