Sökning: "Short-term electricity load forecasting"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden Short-term electricity load forecasting.

1. 1. What would be the highestelectrical loads with -20°C inStockholm in 2022 ? : A study of the sensitivity of electrical loads to outdoor temperature in Stockholm region.

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Magali Mellon; [2022]
   Nyckelord :Data-driven approach; Electrical load forecasting; Temperature sensitivity; Linear Regression; Time series analysis; SARIMAX;

   Sammanfattning :  In the last 10 years, no significant increase in the peak electricity consumption of the region of Stockholm has been observed, despite new customers being connected to the grid. But, as urbanization continues and with electrification being a decisive step of decarbonization pathways, more growth is expected in the future. LÄS MER

3. 2. Multivariate Short-term Electricity Load Forecasting with Deep Learning and exogenous covariates

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för tillämpad fysik och elektronik

   Författare :Nordström Oscar; [2021]
   Nyckelord :Machine learning; Time series; Deep learning; Forecasting; Short-term electricity load forecasting; Artificial Neural Network;

   Sammanfattning : Maintaining the electricity balance between supply and demand is a challenge for electricity suppliers. If there is an under or overproduction, it entails financial costs and affects consumers and the climate. To better understand how to maintain the balance, can the suppliers use short-term forecasts of electricity load. LÄS MER

4. 3. Machine Learning in Electricity Load Forecasting of Prosumer Buildings

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Lu Zhao; [2021]
   Nyckelord :;

   Sammanfattning : Short-term load forecasting plays a key role in energy optimizations such as peaking shaving and cost arbitrage. Forecasting the aggregated load of a city or region has been researched for years and produced accurate results with time lead ranging from an hour to a week. LÄS MER

5. 4. Short-term Power Load Forecasting Based on Machine Learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Yusen Wang; [2020]
   Nyckelord :;

   Sammanfattning : Short-term power load forecasting is an important part of power system management.It is the premise of network structure planing, electricity tradingand load scheduling. The accuracy of power load forecasting is directly relatedto power system security, stability and economic operation. LÄS MER

7. 5. Anomaly detection in electricity demand time series data

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Mahmood Bakhtawar Shah; [2019]
   Nyckelord :LSTM; FFNN; electricity load forecasting; anomaly detection;

   Sammanfattning : The digitalization of the energy industry has made tremendous energy data available. This data is utilized across the entire energy value chain to provide value for customers and energy providers. LÄS MER