Essays about: "energy consumption forecasting"
Showing result 1 - 5 of 40 essays containing the words energy consumption forecasting.
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1. Predicting Electricity Consumption with ARIMA and Recurrent Neural Networks
University essay from Uppsala universitet/Statistiska institutionenAbstract : 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). READ MORE
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2. Long-term Forecasting Heat Use in Sweden's Residential Sector using Genetic Algorithms and Neural Network
University essay from Högskolan i Halmstad/Akademin för företagande, innovation och hållbarhetAbstract : In this study, the parameters of population, gross domestic product (GDP), heat price, U-value, and temperature have been used to predict heat consumption for Sweden till 2050. It should be noted that the heat consumption has been considered for multi-family houses. Most multi-family houses (MFH) get their primary heat from district heating (DH). READ MORE
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3. COMPARATIVE ANALYSIS OF MACHINE LEARNING LOAD FORECASTING TECHNIQUES
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Load forecasting plays a critical role in energy management, and power systems, enabling efficient resource allocation, improved grid stability, and effective energy planning and distribution. Without accurate very short term load forecasting, utility management companies face uncertain load patterns, unrealistic prices, and poor infrastructure planning. READ MORE
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4. Forecasting the Temperatures of theWinter 2022/2023 using SARIMA Models
University essay from Uppsala universitet/Statistiska institutionenAbstract : In this paper the possibility and accuracy of forecasting weekly temperatures for one season,the winter of 2022/2023 is explored. By comparing the forecasted values with normal temper-atures a prediction of the severity of the coming winter can be attained. READ MORE
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5. Forecasting CO2 Emissions in Sweden with a Bayesian Neural Network
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : Carbon dioxide (CO2) is the main constituent of greenhouse gases whose increasing concentrations creates a multitude of different environmental problems. Developing an effective predictive modell for forecasting CO2 is therefore of great importance for future policymakers. READ MORE
