The aim of this thesis is to briefly introduce the reader to the problem of development of the electricity consumption, to show the possibilities of its prediction, and provide an example of electricity consumption analysis, which may serve as a basis for long-term forecast. The first part of this work is devoted to brief overview of the development of consumption of electrical energy in the Czech Republic and factors associated with that development. The main events of Czech electrification history are outlined, as well as factors influencing the magnitude of the demand for electricity in the recent times. There are described the possibilities of the influence of foreign exchange and price of the electricity, net losses, GDP, the consumption of gas, the number of inhabitants, or the structure of the economy. This work further describes the development of the consumption of electric energy abroad and comparison of the electricity consumption in the Czech Republic to its neighboring countries, in which there are apparently influence by variety of factors that affect the consumption development trend. For more complex overview, the electricity consumption of most of European states is being noted, and near the end of the chapter the development in poorest countries and in quickly growing economies is shown. The fourth chapter mentions methods for short and middle-term prediction of consumption of electricity. There also is more consistent description of possibilities useful for long-term prediction, for which the use of the results of statistics analysis is possible. The description of observed data that are used to find the dependences of different factors is made in the following part. Further the approach of the statistics analysis used in this thesis is shown, and the key terms are explained. The dates concerning the consumption of Czech Republic are analyzed, followed by the states with similar trend of the consumption and finally other European states. Sixth chapter examines the possible uses of the outcomes of statistical analyses for long-term prediction of electricity consumption. The conclusion sums up the knowledge acquired during the research concerning problem of electricity consumption and my own analysis of data.

Due to the growing share of renewable energy in countries' power systems, the need for precise forecasting of electricity consumption will increase. This paper considers two different approaches to time series forecasting, autoregressive moving average (ARMA) models and recurrent neural networks (RNNs). These are applied to Swedish electricity consumption data, with the aim of deriving simple yet efficient predictors. An additional aim is to analyse the impact of day of week and temperature on forecast accuracy. The models are evaluated on both long- and mid-term forecasting horizons, ranging from one day to one month. The results show that neural networks are superior for this task, although stochastic seasonal ARMA models also perform quite well. Including external variables only marginally improved the ARMA predictions, and had somewhat unclear effects on the RNN forecasting accuracy. Depending on the network model used, adding external variables had either a slightly positive or slightly negative impact on prediction accuracy.

Made available in DSpace on 2010-04-20T20:08:30Z (GMT). No. of bitstreams: 0 Previous issue date: 1995-11-23T00:00:00Z / A metodologia para a estimação por cenários alternativos com base na interação entre modelos subjetivos causais e técnicas analíticas para o dimensionamento de mercado representa uma proposta de tratamento sistemático dos problemas de análise e previsão, utilizado nas áreas de estratégia mercadológica e planejamento empresarial. A tese trata inicialmente de dois critérios para a classificação das técnicas de previsão e geração de cenários. No primeiro deles, são considerados os atributos que usualmente orientam a seleção dos métodos de previsão mais apropriados para cada caso. No segundo, é definido um referencial com base nas regras empregadas para identificar o modo de geração dos futuros alternativos. Em ambas situações, foram consultados trabalhos que incorporaram extensivamente os conceitos de interesse desta tese, com o propósito de apoiar a sua fundamentação teórica. Uma análise adicional mais detalhada se ateve às técnicas que propiciaram a base conceitual da metodologia, a exemplo da modelagem estrutural e das probabilidades subjetivas. Com o objetivo de testar a adequação da proposta ao estudo de caso, foi escolhido o mercado atendido pela indústria de energia elétrica. Este procedimento passou inicialmente por uma investigação a nível nacional com a intenção de: (i) observar aquelas técnicas e indicadores utilizados regularmente III pelas concessionárias; (ii) constatar e comparar situações que afetam a qualidade das previsões, a exemplo do tamanho da equipe e do grau de comunicação com as instituições externas. Em seguida, foi efetuada uma aplicação prática sobre o mercado regional de eletricidade do segmento residencial, na tentativa de validar empiricamente a metodologia proposta. Como particularidades, foram introduzidas as equações simultâneas do lado analítico, e a consulta aos especialistas, os quais foram aplicados na construção do modelo exploratório do lado subjetivo. A interação entre as técnicas resultou em alguns cenários para o mercado analisado. / The methodology for forecasting by means of alternative scenarios based on the interaction between causal subjective models and analytical techniques for market measurement establishes a new framework. It provides a systematic approach to the analysis and forecasting practices in areas such as marketing strategy and business planning. We begin this thesis with a presentation of two criteria aimed at classifying the forecasting and scenario-generating techniques. As for the former, we considered some attributes which are usually applied to the selection of a suitable method under particular market conditions. Concerning the latter, we based the tipology on some rules generally employed for the specification of alternative scenarios. In both cases, to support our teorethical foundation, the research was carried out by introducing some selected techniques which strongly embody the concepts used in this thesis. Further analysis of the issue brought on some methods that defined the conceptual model, as for instance, the structural modeling and subjective probabilities. To back up the feasibility of such proposal, we chose the market supplied by the electric industry. The first step of this procedure was a national survey among electric utilities whose main purposes were: (i) point out the techniques and indicators most commonly used; (ii) consider and compare some factors that influence the quality of forecasts, such as team size and the extent of communication with external agencies. Finally, we conducted a practical application of the methodology to the regional market, as regards residential demand for electricity. As for peculiar features, we introduced in our thesis the concepts of simultaneous equations in the analytical side and the consensus analysis technique, which were applied to an exploratory model in the subjective side. The link between such techniques was used to create the scenarios for the prospective demand.