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A hybrid model for short-term forecasting of aggregated thermal loads and their load control responses is studied in this paper using field test data. Inputs include temperature measurement and forecast, measured power and control signals. The hybrid model comprises 1) partly physically based forecasting of the responses of the controlled thermal loads and the non-controlled power, and 2) forecasting...
Time of use tariffs are in large scale use in Finland, but the electricity market prices do not any more follow such regular time pattern. Dynamic demand response is increasingly needed and dynamic retail tariffs are available. Heat pumps and solar panels affect electricity consumption of houses. This paper analyses and demonstrates the benefits of forecasting and optimisation in dynamic price control...
Short-term forecasting of electric loads is an essential function required by Smart Grids. Today increasing amount of smart metering data is available enabling the development of enhanced data-driven models for short-term load forecasting. Until now, a plethora of models have been developed ranging from simple linear regression models to more advanced models such as (artificial) neural networks (NNs)...
Accurate forecasting of loads is essential for smart grids and energy markets. This paper compares the performance of the following models in short-term load forecasting: 1) smart metering data based profile models, 2) a neural network (NN) model, and 3) a Kalman-filter based predictor with input nonlinearities and a physically based main structure. The comparison helps method selection for the development...
Performance of smart grids and energy markets depends on the accuracy of forecasted power balances and power flows. This document describes the following approach to predict daily energy consumption of large groups of small customers that have electrical heating and cooling. The model is divided into parallel submodels, such as transfer function models, for differently behaving load types. Each linear...
Flexibility of distributed energy resources is increasingly needed in the electricity markets and grids. But this dispersed flexibility can be used efficiently only if it is aggregated to wholesale market products. A set of software tools was developed for an actor or a company who aggregates flexible household demand for the electricity market and network operators. The tools comprise 1) short term...
During military service young men (age 19–21 years) are exposed to many predisposing factors for asthma. We aimed to study the short-term prognosis of asthma after the military service.All 216 men with verified asthma in 2004–2005 from the register of the Central Military Hospital were included in the study. A questionnaire was mailed to them in autumn 2007 and the 146 responders (68%) formed the...
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