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.

Short-term Load Forecasting Based on Load Profiling

Load forecasting has gradually becoming a major field of research in electricity industry. Therefore, Load forecasting is extremely important for the electric sector under deregulated environment as it provides a useful support to the power system management. Accurate power load forecasting models are required to the operation and planning of a utility company, and they have received increasing attention from researches of this field study. Many mathematical methods have been developed for load forecasting. This work aims to develop and implement a load forecasting method for short-term load forecasting (STLF), based on Holt-Winters exponential smoothing and an artificial neural network (ANN). One of the main contributions of this paper is the application of Holt-Winters exponential smoothing approach to the forecasting problem and, as an evaluation of the past forecasting work, data mining techniques are also applied to short-term Load forecasting. Both ANN and Holt-Winters exponential smoothing approaches are compared and evaluated.

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.

Determining the Adjustment Baseline Parameters to Define an Accurate Customer Baseline Load

Demand response is an energy resource that has gained increasing importance in the context of competitive electricity markets and of smart grids. New business models and methods designed to integrate demand response in electricity markets and of smart grids have been published, reporting the need of additional work in this field. In order to adequately remunerate the participation of the consumers in demand response programs, improved consumers’ performance evaluation methods are needed. The methodology proposed in the present paper determines the characterization of the baseline approach that better fits the consumer historic consumption, in order to determine the expected consumption in absent of participation in a demand response event and then determine the actual consumption reduction. The defined baseline can then be used to better determine the remuneration of the consumer. The paper includes a case study with real data to illustrate the application of the proposed methodology.

Voltage Magnitude Analysis Considering Load Curtailment Minimization in Sub-Transmission Networks with Distributed Generators

Most of distribution generation and smart grid research works are dedicated to the study of network operation parameters, reliability among others. However, many of this research works usually uses traditional test systems such as IEEE test systems. This work proposes a voltage magnitude study in presence of fault conditions considering the realistic specifications found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzyprobabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12 bus sub-transmission network.

An automatic tool to Extract, Transform and Load data from real electricity markets

The study of Electricity Markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring produced. Currently, lots of information concerning Electricity Markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge, to define realistic scenarios, essential for understanding and forecast Electricity Markets behaviour. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of Electricity Markets and the behaviour of the involved entities. In this paper we present an adaptable tool capable of downloading, parsing and storing data from market operators’ websites, assuring actualization and reliability of stored data.

Load Control Timescales Simulation in a Multi-Agent Smart Grid Platform

Environmental concerns and the shortage in the fossil fuel reserves have been potentiating the growth and globalization of distributed generation. Another resource that has been increasing its importance is the demand response, which is used to change consumers’ consumption profile, helping to reduce peak demand. Aiming to support small players’ participation in demand response events, the Curtailment Service Provider emerged. This player works as an aggregator for demand response events. The control of small and medium players which act in smart grid and micro grid environments is enhanced with a multi-agent system with artificial intelligence techniques – the MASGriP (Multi-Agent Smart Grid Platform). Using strategic behaviours in each player, this system simulates the profile of real players by using software agents. This paper shows the importance of modeling these behaviours for studying this type of scenarios. A case study with three examples shows the differences between each player and the best behaviour in order to achieve the higher profit in each situation.

Load Profiling Tool to Support Smart Grid Operation Scenarios

This paper presents the characterization of high voltage (HV) electric power consumers based on a data clustering approach. The typical load profiles (TLP) are obtained selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The choice of the best partition is supported using several cluster validity indices. The proposed data-mining (DM) based methodology, that includes all steps presented in the process of knowledge discovery in databases (KDD), presents an automatic data treatment application in order to preprocess the initial database in an automatic way, allowing time saving and better accuracy during this phase. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ consumption behavior. To validate our approach, a case study with a real database of 185 HV consumers was used.

Study of Load Curves Concerning the Influence of Socioeconomic and Cultural Issues

The increase of electricity demand in Brazil, the lack of the next major hydroelectric reservoirs implementation, and the growth of environmental concerns lead utilities to seek an improved system planning to meet these energy needs. The great diversity of economic, social, climatic, and cultural conditions in the country have been causing a more difficult planning of the power system. The work presented in this paper concerns the development of an algorithm that aims studying the influence of the issues mentioned in load curves. Focus is given to residential consumers. The consumption device with highest influence in the load curve is also identified. The methodology developed gains increasing importance in the system planning and operation, namely in the smart grids context.

Voltage Analysis and Load Curtailment Minimization in Sub-transmission Networks with Distributed Generation

Most of distributed generation and smart grid research works are dedicated to network operation parameters studies, reliability, etc. However, many of these works normally uses traditional test systems, for instance, IEEE test systems. This paper proposes voltage magnitude and reliability studies in presence of fault conditions, considering realistic conditions found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12-bus sub-transmission network.

Shoulder Kinematics Is Not Influenced by External Load During Elevation in the Scapular Plane

The current study aimed to compare the shoulder kinematics (3D scapular orientation, scapular angular displacement and scapulohumeral rhythm) of asymptomatic participants under unloaded and loaded conditions during unilateral shoulder elevation in the scapular plane. We used a repeated-measures design with a convenience sample. Eleven male participants with an age range of 21–28 years with no recent history of shoulder injury participated in the study. The participants performed isometric shoulder elevation from a neutral position to approximately 150 degrees of elevation in the scapular plane in intervals of approximately 30 degrees during unloaded and loaded conditions. Shoulder kinematic data were obtained with videogrammetry. During shoulder elevation, the scapula rotated upwardly and externally, and tilted posteriorly. The addition of an external load did not affect 3D scapular orientation, scapular angular displacement, or scapulohumeral rhythm throughout shoulder elevation (P > .05). In clinical practice, clinicians should expect to observe upward and external rotation and posterior tilt of the scapula during their assessments of shoulder elevation. Such behavior was not influenced by an external load normalized to 5% of body weight when performed in an asymptomatic population.

Robustness of timber structures in seismic areas

Some of the properties sought in seismic design of buildings are also considered fundamental to guarantee structural robustness. Moreover, some key concepts are common to both seismic and robustness design. In fact, both analyses consider events with a very small probability of occurrence, and consequently, a significant level of damage is admissible. As very rare events,in both cases, the actions are extremely hard to quantify. The acceptance of limited damage requires a system based analysis of structures, rather than an element by element methodology, as employed for other load cases. As for robustness analysis, in seismic design the main objective is to guarantee that the structure survives an earthquake, without extensive damage. In the case of seismic design, this is achieved by guaranteeing the dissipation of energy through plastic hinges distributed in the structure. For this to be possible, some key properties must be assured, in particular ductility and redundancy. The same properties could be fundamental in robustness design, as a structure can only sustain significant damage if capable of distributing stresses to parts of the structure unaffected by the triggering event. Timber is often used for primary load‐bearing elements in single storey long‐span structures for public buildings and arenas, where severe consequences can be expected if one or more of the primary load bearing elements fail. The structural system used for these structures consists of main frames, secondary elements and bracing elements. The main frame, composed by columns and beams, can be seen as key elements in the system and should be designed with high safety against failure and under strict quality control. The main frames may sometimes be designed with moment resisting joints between columns and beams. Scenarios, where one or more of these key elements, fail should be considered at least for high consequence buildings. Two alternative strategies may be applied: isolation of collapsing sections and, provision of alternate load paths [1]. The first one is relatively straightforward to provide by deliberately designing the secondary structural system less strong and stiff. Alternatively, the secondary structural system and the bracing system can be design so that loss of capacity in the main frame does not lead to the collapse. A case study has been selected aiming to assess the consequences of these two different strategies, in particular, under seismic loads.

Hepatitis C viral load does not predict disease outcome: going beyond numbers

The analysis of 58 patients with chronic hepatitis C without cirrhosis and treated with interferon-alpha demonstrated that hepatitis C viral (HCV) load does not correlate with the histological evolution of the disease (p = 0.6559 for architectural alterations and p = 0.6271 for the histological activity index). Therefore, the use of viral RNA quantification as an evolutive predictor or determinant of the severity of hepatitis C is incorrect and of relative value. A review of the literature provided fundamental and interdependent HCV (genotype, heterogeneity and mutants, specific proteins), host (sex, age, weight, etc) and treatment variables (dosage, time of treatment, type of interferon) within the broader context of viral kinetics, interferon-mediated immunological response (in addition to natural immunity against HCV) and the role of interferon as a modulator of fibrogenesis. Therefore, viral load implies much more than numbers and the correct interpretation of these data should consider a broader context depending on multiple factors that are more complex than the simple value obtained upon quantification.

The influence of task design on upper limb muscles fatigue during low-load repetitive work: A systematic review

Ergonomic interventions such as increased scheduled breaks or job rotation have been proposed to reduce upper limb muscle fatigue in repetitive low-load work. This review was performed to summarize and analyze the studies investigating the effect of job rotation and work-rest schemes, as well as, work pace, cycle time and duty cycle, on upper limb muscle fatigue. The effects of these work organization factors on subjective fatigue or discomfort were also analyzed. This review was based on relevant articles published in PubMed, Scopus and Web of Science. The studies included in this review were performed in humans and assessed muscle fatigue in upper limbs. 14 articles were included in the systematic review. Few studies were performed in a real work environment and the most common methods used to assess muscle fatigue were surface electromyography (EMG). No consistent results were found related to the effects of job rotation on muscle activity and subjective measurements of fatigue. Rest breaks had some positive effects, particularly in perceived discomfort. The increase in work pace reveals a higher muscular load in specific muscles. The duration of experiments and characteristics of participants appear to be the factors that most have influenced the results. Future research should be focused on the improvement of the experimental protocols and instrumentation, in order to the outcomes represent adequately the actual working conditions. Relevance to industry: Introducing more physical workload variation in low-load repetitive work is considered an effective ergonomic intervention against muscle fatigue and musculoskeletal disorders in industry. Results will be useful to identify the need of future research, which will eventually lead to the adoption of best industrial work practices according to the workers capabilities.

Effect of sialic acid loss on dendritic cell maturation

Sialic acids are key structural determinants and contribute to the functionality of a number of immune cell receptors. Previously, we demonstrated that differentiation of human dendritic cells (DCs) is accompanied by an increased expression of sialylated cell surface structures, putatively through the activity of the ST3Gal.I and ST6Gal.I sialyltransferases. Furthermore, DC endocytosis was reduced upon removal of the cell surface sialic acid residues by neuraminidase. In the present work, we evaluate the contribution of the sialic acid modifications in DC maturation. We demonstrate that neuraminidase-treated human DCs have increased expression of major histocompatibility complex (MHC) and costimulatory molecules, increased gene expression of specific cytokines and induce a higher proliferative response of T lymphocytes. Together, the data suggest that clearance of cell surface sialic acids contributes to the development of a T helper type 1 proinflammatory response. This postulate is supported by mouse models, where elevated MHC class II and increased maturation of specific DC subsets were observed in DCs harvested from ST3Gal.I(-/-) and ST6Gal.I(-/-) mice. Moreover, important qualitative differences, particularly in the extent of reduced endocytosis and in the peripheral distribution of DC subsets, existed between the ST3Gal.I(-/-) and ST6Gal.I(-/-) strains. Together, the data strongly suggest not only a role of cell surface sialic acid modifications in maturation and functionality of DCs, but also that the sialic acid linkages created by different sialyltransferases are functionally distinct. Consequently, with particular relevance to DC-based therapies, cell surface sialylation, mediated by individual sialyltransferases, can influence the immunogenicity of DCs upon antigen loading.