Xie, M.; Lin, S.; Dong, K.; Zhang, S. Short-Term Prediction of Multi-Energy Loads Based on Copula Correlation Analysis and Model Fusions. Entropy2023, 25, 1343.
Xie, M.; Lin, S.; Dong, K.; Zhang, S. Short-Term Prediction of Multi-Energy Loads Based on Copula Correlation Analysis and Model Fusions. Entropy 2023, 25, 1343.
Xie, M.; Lin, S.; Dong, K.; Zhang, S. Short-Term Prediction of Multi-Energy Loads Based on Copula Correlation Analysis and Model Fusions. Entropy2023, 25, 1343.
Xie, M.; Lin, S.; Dong, K.; Zhang, S. Short-Term Prediction of Multi-Energy Loads Based on Copula Correlation Analysis and Model Fusions. Entropy 2023, 25, 1343.
Abstract
To improve the accuracy of short-term multi-energy load prediction models for integrated energy systems, the historical development law of the multi-energy loads must be considered. Moreover, understanding the complex coupling correlation of the different loads in the multi-energy systems and accounting for other load-influencing factors, such as weather, may further improve the forecasting performance of such models. In this study, a two-stage fuzzy optimization method is proposed for the feature selection and identification of the multi-energy loads. To enrich the information content of the prediction input feature, we introduced a copula correlation feature analysis in the proposed framework, which extracts the complex dynamic coupling correlation of multi-energy loads and applies Akaike information criterion (AIC) to evaluate the adaptability of the different copula models presented. Furthermore, we combined a NARX neural network with Bayesian optimization and an extreme learning machine model optimized using a genetic algorithm to effectively improve the feature fusion performances of the proposed multi-energy load prediction model. The effectiveness of the proposed short-term prediction model was confirmed by the experimental results obtained using the multi-energy load time-series data of an actual integrated energy system.
Keywords
feature identification and extraction; Copula analysis; multi-energy loads; model fusion
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
