3 documents found, page 1 of 1
Use of Sensors and Analyzers Data for Load Forecasting: A Two Stage Approach
Ramos, Daniel; Teixeira, Brigida; Faria, Pedro; Gomes, Luis; Abrishambaf, Omid; Vale, ZitaThe increase in sensors in buildings and home automation bring potential information to improve buildings' energy management. One promissory field is load forecasting, where the inclusion of other sensors' data in addition to load consumption may improve the forecasting results. However, an adequate selection of sensor parameters to use as input to the load forecasting should be done. In this paper, a methodolo...
Wang and Mendel’s Fuzzy Rule Learning Method for Energy Consumption Forecasting...
Jozi, Aria; Pinto, Tiago; Praça, Isabel; Silva, Francisco; Teixeira, Brigida; Vale, ZitaReliable consumption forecasts are crucial in several aspects of power and energy systems, e.g. to take advantage of the full potential of flexibility from consumers and to support the management from operators. With this need, several methodologies for electricity forecasting have emerged. However, the study of correlated external variables, such as temperature or luminosity, is still far from adequate. This p...
Energy Consumption Forecasting based on Hybrid Neural Fuzzy Inference System
Jozi, Aria; Pinto, Tiago; Praça, Isabel; Silva, Francisco; Teixeira, Brigida; Vale, ZitaForecasting the electricity consumption is one of the most challenging tasks for energy domain stakeholders. Having reliable electricity consumption forecasts can help minimizing the cost of electricity and also enable a better control on the electricity tariff. This paper presents a study regarding the forecast of electricity consumption using a methodology based on Hybrid neural Fuzzy Inference System (HyFIS)...