Fuzzy clustering applied to a demand response model in a smart grid contingency scenario

This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.

Fuzzy clustering applied to a demand response model in a smatr grid contingency scenario

This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.

Work-related stress according to the demand-control model and minor psychic disorders in nursing workers

This was a cross-sectional study that aimed to assess the association between work-related stress according to the Demand-Control Model, and the occurrence of Minor Psychic Disorder (MPD) in nursing workers. The participants were 335 professionals, out of which 245 were nursing technicians, aged predominantly between 20 and 40 years. Data were collected using the Job Stress Scale and the Self-Reporting Questionnaire-20. The analysis was performed using descriptive and analytical statistics. The prevalence of suspected MPD was 20.6%. Workers classified in the quadrants active job and high strain of the Demand-Control Model presented higher potential for developing MPD compared with those classified in the quadrant low strain. In conclusion, stress affects the mental health of workers and the aspects related to high psychological demands and high control still require further insight in order to understand their influence on the disease processes of nursing workers.

Accuracy improvement of a demand forecasting model

This research concerns different statistical methods that assist to increase the demand forecasting accuracy of company X’s forecasting model. Current forecasting process was analyzed in details. As a result, graphical scheme of logical algorithm was developed. Based on the analysis of the algorithm and forecasting errors, all the potential directions for model future improvements in context of its accuracy were gathered into the complete list. Three improvement directions were chosen for further practical research, on their basis, three test models were created and verified. Novelty of this work lies in the methodological approach of the original analysis of the model, which identified its critical points, as well as the uniqueness of the developed test models. Results of the study formed the basis of the grant of the Government of St. Petersburg.

Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers' consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed. (C) 2016 Elsevier Ltd. All rights reserved.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.

The moderating role of task characteristics in determining responses to a stressful work simulation

Two experimental studies were conducted to examine whether the stress-buffering effects of behavioral control on work task responses varied as a function of procedural information. Study 1 manipulated low and high levels of task demands, behavioral control, and procedural information for 128 introductory psychology students completing an in-basket activity. ANOVA procedures revealed a significant three-way interaction among these variables in the prediction of subjective task performance and task satisfaction. It was found that procedural information buffered the negative effects of task demands on ratings of performance and satisfaction only under conditions of low behavioral control. This pattern of results suggests that procedural information may have a compensatory effect when the work environment is characterized by a combination of high task demands and low behavioral control. Study 2 (N = 256) utilized simple and complex versions of the in-basket activity to examine the extent to which the interactive relationship among task demands, behavioral control, and procedural information varied as a function of task complexity. There was further support for the stress-buffering role of procedural information on work task responses under conditions of low behavioral control. This effect was, however, only present when the in-basket activity was characterized by high task complexity, suggesting that the interactive relationship among these variables may depend on the type of tasks performed at work. Copyright (C) 1999 John Wiley & Sons, Ltd.

Urban water demand model: the case study of Emilia Romagna (Italy)

Water is the driving force in nature. We use water for washing cars, doing laundry, cooking, taking a shower, but also to generate energy and electricity. Therefore water is a necessary product in our daily lives (USGS. Howard Perlman, 2013). The model that we created is based on the urban water demand computer model from the Pacific Institute (California). With this model we will forecast the future urban water use of Emilia Romagna up to the year of 2030. We will analyze the urban water demand in Emilia Romagna that includes the 9 provinces: Bologna, Ferrara, Forli-Cesena, Modena, Parma, Piacenza, Ravenna, Reggio Emilia and Rimini. The term urban water refers to the water used in cities and suburbs and in homes in the rural areas. This will include the residential, commercial, institutional and the industrial use. In this research, we will cover the water saving technologies that can help to save water for daily use. We will project what influence these technologies have to the urban water demand, and what it can mean for future urban water demands. The ongoing climate change can reduce the snowpack, and extreme floods or droughts in Italy. The changing climate and development patterns are expected to have a significant impact on water demand in the future. We will do this by conducting different scenario analyses, by combining different population projections, climate influence and water saving technologies. In addition, we will also conduct a sensitivity analyses. The several analyses will show us how future urban water demand is likely respond to changes in water conservation technologies, population, climate, water price and consumption. I hope the research can contribute to the insight of the reader’s thoughts and opinion.

The hotelling model with multiple demands

The purpose of this chapter is to provide an elementary introduction to the non-renewable resource model with multiple demand curves. The theoretical literature following Hotelling (1931) assumed that all energy needs are satisfied by one type of resource (e.g. ‘oil’), extractible at different per-unit costs. This formulation implicitly assumes that all users are the same distance from each resource pool, that all users are subject to the same regulations, and that motorist users can switch as easily from liquid fossil fuels to coal as electric utilities can. These assumptions imply, as Herfindahl (1967) showed, that in competitive equilibrium all users will exhaust a lower cost resource completely before beginning to extract a higher cost resource: simultaneous extraction of different grades of oil or of oil and coal should never occur. In trying to apply the single-demand curve model during the last twenty years, several teams of authors have independently found a need to generalize it to account for users differing in their (1) location, (2) regulatory environment, or (3) resource needs. Each research team found that Herfindahl's strong, unrealistic conclusion disappears in the generalized model; in its place, a weaker Herfindahl result emerges. Since each research team focussed on a different application, however, it has not always been clear that everyone has been describing the same generalized model. Our goal is to integrate the findings of these teams and to exposit the generalized model in a form which is easily accessible.

Does Final Energy Demand in Portugal Exhibit Long Memory? A Fractional Integration Analysis

In this paper, we measure the degree of fractional integration in final energy demand in Portugal using an ARFIMA model with and without adjustments for seasonality. We consider aggregate energy demand as well as final demand for petroleum, electricity, coal, and natural gas. Our findings suggest the presence of long memory in all of the components of energy demand. All fractional-difference parameters are positive and lower than 0.5 indicating that the series are stationary, although with mean reversion patterns slower than in the typical short-run processes. These results have important implications for the design of energy policies. As a result of the long-memory in final energy demand, the effects of temporary policy shocks will tend to disappear slowly. This means that even transitory shocks have long lasting effects. Given the temporary nature of these effects, however, permanent effects on final energy demand require permanent policies. This is unlike what would be suggested by the more standard, but much more limited, unit root approach, which would incorrectly indicate that even transitory policies would have permanent effects

Stressful working conditions and poor self-rated health among financial services employees

OBJECTIVE: To assess the association between exposure to adverse psychosocial working conditions and poor self-rated health among bank employees. METHODS: A cross-sectional study including a sample of 2,054 employees of a government bank was conducted in 2008. Self-rated health was assessed by a single question: "In general, would you say your health is (...)." Exposure to adverse psychosocial working conditions was evaluated by the effort-reward imbalance model and the demand-control model. Information on other independent variables was obtained through a self-administered semi-structured questionnaire. A multiple logistic regression analysis was performed and odds ratio calculated to assess independent associations between adverse psychosocial working conditions and poor self-rated health. RESULTS: The overall prevalence of poor self-rated health was 9%, with no significant gender difference. Exposure to high demand and low control environment at work was associated with poor self-rated health. Employees with high effort-reward imbalance and overcommitment also reported poor self-rated health, with a dose-response relationship. Social support at work was inversely related to poor self-rated health, with a dose-response relationship. CONCLUSIONS: Exposure to adverse psychosocial work factors assessed based on the effort-reward imbalance model and the demand-control model is independently associated with poor self-rated health among the workers studied.

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.

Siltanosturin mallinnusmenetelmien kehittäminen

Työn tarkoituksena oli selvittää kaupallisen dynamiikan simulointiohjelmiston (Adams) soveltuvuus siltanosturin mallintamiseen. Työn kohteena oli kaksipalkkinen siltanosturi, joka sijaitsi KCI:n tiloissa Hyvinkäällä. Nosturin jänneväli oli noin 19.5 metriä ja nostokyky 16 tonnia. Mallintamisessa keskityttiin nosturin dynamiikkaan sekä ohjausvoimiin nosturin kantopyörissä. Simulointitulokset verifioitiin mittauksin. Koska mallista haluttiin mahdollisimman yksinkertainen, mallinnettiin ainoastaan pääkannattajat ja köydet joustavina. Muut osat mallinnettiin jäykkinä. Yksinkertaisuuteen pyrittiin sen vuoksi, että mallia oli tarkoitus käyttää perustana komponenttikirjaston luomiseksi myöhempää käyttöä varten. Tuloksista todettiin mallin soveltuvan hyvin nosturin dynamiikan mallintamiseen. Mallista saatavat tulokset vastasivat hyvin mitattuja liikkeitä. Ohjausvoimia ei kuitenkaan saatu verifioitua. Käytetty mittausmenetelmä osoittautui sopimattomaksi.