Search results for "Electricity demand"
showing 3 items of 3 documents
Energy efficiency improvement in hospital buildings, based on the example of a selected type of hospital facility in Poland
2019
Abstract Energy demand in hospitals is of highly diverse nature: heat energy, cool energy and electricity. A guarantee of energy supply is required to ensure continuity of medical procedures. Taking care of the lowest possible costs of hospital operations, special attention should be paid to energy efficiency of the installations used in the hospital buildings. The paper presents an analysis of energy demand for heating, cooling, ventilation and lighting in an example hospital in Poland. The selected object was considered a reference as it was built according to a repetitive construction plan, according to which several dozen other hospitals were built in Poland. On the basis of data from 2…
Training Artificial Neural Networks With Improved Particle Swarm Optimization
2020
Particle Swarm Optimization (PSO) is popular for solving complex optimization problems. However, it easily traps in local minima. Authors modify the traditional PSO algorithm by adding an extra step called PSO-Shock. The PSO-Shock algorithm initiates similar to the PSO algorithm. Once it traps in a local minimum, it is detected by counting stall generations. When stall generation accumulates to a prespecified value, particles are perturbed. This helps particles to find better solutions than the current local minimum they found. The behavior of PSO-Shock algorithm is studied using a known: Schwefel's function. With promising performance on the Schwefel's function, PSO-Shock algorithm is util…
Exponential smoothing with covariates applied to electricity demand forecast
2013
Exponential smoothing methods are widely used as forecasting techniques in industry and business. Their usual formulation, however, does not allow covariates to be used for introducing extra information into the forecasting process. In this paper, we analyse an extension of the exponential smoothing formulation that allows the use of covariates and the joint estimation of all the unknowns in the model, which improves the forecasting results. The whole procedure is detailed with a real example on forecasting the daily demand for electricity in Spain. The time series of daily electricity demand contains two seasonal patterns: here the within-week seasonal cycle is modelled as usual in exponen…