Spatial electric load forecasting using an evolutionary heuristic
نویسندگان
چکیده
منابع مشابه
Spatial Electric Load Forecasting Using an Evolutionary Heuristic
A method for spatial electric load forecasting using elements from evolutionary algorithms is presented. The method uses concepts from knowledge extraction algorithms and linguistic rules’ representation to characterize the preferences for land use into a spatial database. The future land use preferences in undeveloped zones in the electrical utility service area are determined using an evoluti...
متن کاملElectric Load Forecasting Using An Artificial Neural Network
This paper presents an artificial neural network(ANN) approach to electric load forecasting. The ANN is used to learn the relationship among past, current and future temperatures and loads. In order to provide the forecasted load, the ANN interpolates among the load and temperature data in a training data set. The average absolute errors of the one-hour and 24-hour ahead forecasts in our test o...
متن کاملSpatial Load Forecasting
Load forecasting in power systems is an important subject and has been studied from different points of view in order to achieve better load forecasting results. ”Ius paper will address one of the challenges in spatial load forecasting area urban re-development, and present a theory and methodology to incorporate urban re-development into spatial load forecasting considerations.
متن کاملUrban Electric Load Forecasting Using Combined Cellular Automata
TAbstractT—With the high-speed economic development in China, the transition of structural function in the urban land system highly effects the development of the urban electric load. Forecasting the urban electric load accurately is the foundation of decision making scientifically for the development and planning of the urban power grid in China. This paper improves the decision method of Tran...
متن کاملMedium Term Electric Load Forecasting Using TLFN Neural Networks
This paper develops medium term electric load forecasting using neural networks, based on historical series of electric load, economic and demographic variables. The neural network chosen for this work is the Time Lagged Feedforward Network (TLFN), which combines conventional network topology (multilayer perceptron) with good handling of time dependencies by means of gamma memory. This is a ver...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Sba: Controle & Automação Sociedade Brasileira de Automatica
سال: 2010
ISSN: 0103-1759
DOI: 10.1590/s0103-17592010000400005