AUTHOR=Xu Yurui , Deng Youjun , Guo Xiangwei , Wang Jiarui , Zhang Jiajun 

TITLE=Economic-environmental dispatch for the integrated energy system considering off-design conditions

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.1020607

DOI=10.3389/fenrg.2022.1020607

ISSN=2296-598X

ABSTRACT=The integrated energy system (IES) is recognized as a promising energy utilization way enabled to both improve energy efficiency and reduce pollutant emissions. Although the economic-environmental dispatch (EED) problem of the IES has been widely studied, the fact that the IES is operated with the off-design conditions having a significant influence on the efficiency of energy devices is neglected usually, resulting in the scheduled operations for the IES could not be accurate enough in many actual situations. This paper investigates the EED problem of the IES under off-design conditions. Technically, by integrating an efficiency correction process into the traditional energy hub (EH) model, a dynamic energy hub (DEH) model is firstly formulated for adapting itself to variable energy conversion efficiency. Then, a deep neural network (DNN) - based efficiency correction method is proposed to predict and correct the time-varying efficiency of energy devices, based on three main off-design conditions including load rate, air temperature and pressure. A multi-objective EED model is finally formulated for the IES with the framework of the DEH model, aiming at establishing a trade-off between operational cost and emitted pollutants. Case studies show that the proposed approach is help of enhancing the accuracy of IES dispatch while having a good performance in both the operational cost and pollutant emissions reduction.