Development of a Neural Network-Based Renewable Energy Forecasting Framework for Process Industries
This paper presents a neural network-based forecasting framework for photovoltaic power (PV) generation as a decision-supporting tool to employ renewable energies in the process industry. The applicability of the proposed framework is illustrated by comparing its performance against other methodologies such as linear and nonlinear time series modelling approaches. A case study of an actual PV power plant in South Korea is presented.
- Research Organization:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1326726
- Report Number(s):
- NREL/CP-5D00-67176
- Resource Relation:
- Conference: Presented at the 26th European Symposium on Computer Aided Process Engineering, 12-15 June 2016, Portoroz, Slovenia
- Country of Publication:
- United States
- Language:
- English
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