Zbigniew Gontar

Short-Term Load Forecasting Using Radial Basis Function Networks

This paper presents results from the application of Radial Basis Function Networks (RBFNs) to Short-Term Load Forecasting. Short-term Load Forecasting is nowadays a crucial function, especially in the operation of liberalized electricity markets, as it affects the economy and security of the system. Actual load series from Crete are used for the evaluation of the developed structures providing results of satisfactory accuracy, retaining the advantages of RBFNs.

Short term load forecasting with radial basis function network

The paper presents experiments with application of radial basis function (RBF) network to short term load forecasting (STLF) problems. The proposed regression model is used to forecast forty-eight hours ahead electric load. The model has been implemented on real data: inputs to the RBF are past loads, weekday and special-day coding and the output is the load forecast for the given hour. Ordinary RBF was applied in the experiments. The centers of the Gaussian basis functions were selected on the base of the quasi-Newton algorithm. Mean absolute percentage error of about 4% is derived from the data from the power system in Crete. The performance of the proposed model has been compared with simulations performed by the MLP network, and former models developed for the distribution company in Poland.

Uncertainty of the short-term electrical load forecasting in utilities

This paper investigates the problem of the short-term electrical load forecasting (STLF) in medium size utility. The model consisted of ensemble of the neural predictors with special heuristic input selection procedure is presented. We also discuss the problem of uncertainties involved in load forecasts, and confidence intervals calculation methods for neural STLF predictors.

Deployment of smart city concept in Poland. Selected aspects

The concept of Smart City is concerned primarily with integration ICT with processes performed in the city. The paper identifies applications and requirements of Smart Cities grouped into two topics: Smart Grid and Smart Tourism and reviews selected projects implemented in these areas in Poland.

CLOUD COMPUTING MIGRATION BARRIERS AND ADVANTAGES IN MANUFACTURING – AN ANALYSIS OF AMBIGUITY AND DEPENDENCES IN THE ASSESSMENT CRITERIA

Abstract There is still many misunderstandings associated with the assessment of the barriers encountered in the process of IT solutions migration to the computational cloud and the benefits to be expected. The purpose of this paper is to organize the criteria used in this field, to analyze the dependencies between them. This will allow us to better understand the problem of migration to the cloud and to improve the decision-making processes related to it. A comprehensive survey was carried out, covering about 400 manufacturing enterprises in Poland using cloud-based IT solutions in various areas. The elements of the study were questions about the barriers and benefits encountered in this process. The paper analyzes the relationships between the obtained categories using diverse data mining methods: association rules mining and hierarchical agglomerative clustering. The obtained results allow to identify the conceptual structure and build a model of relationships inside the problem.