@article{Sun2026, 
author = {Jian Sun and Deping Ke and Jian Xu and Siyang Liao and Yuanzhang Sun and Liangzhong Yao},
title = {Stochastic Planning of Integrated Energy System with Low-grade Heat Based on a Novel Heat Pump Model Considering Multiple Uncertainties},
year = {2026},
journal = {CSEE Journal of Power and Energy Systems},
volume = {12},
number = {3},
pages = {1547-1561},
keywords = {Heat pump model, improved grey wolf optimization, integrated energy system, low-grade heat},
url = {https://www.sciopen.com/article/10.17775/CSEEJPES.2024.01440},
doi = {10.17775/CSEEJPES.2024.01440},
abstract = {Regional low-grade heat, such as ground source heat, domestic sewage waste heat, low-temperature industrial waste heat and data center waste heat, has considerable potential to contribute to the alleviation of energy crises and environmental pollution from a micro-grid perspective. To explore the method of park-level integrated energy systems (IES) that incorporates low-grade heat, a coordinated planning model is proposed in this paper. First, the working efficiency of heat pump (HP)is modeled using a combined method of thermodynamics and data regression. This HP model takes into consideration the heat upgrading process, which involves utilizing low-grade heat at various temperature levels. The conditional probability distribution of the HP model is also estimated according to the working temperature. Furthermore, the uncertainties arising from sources, loads, and HP models are addressed through chance constraints in a proposed stochastic planning model of IES. Specifically, the planning model is solved using an improved Grey Wolf Optimization (IGWO) algorithm, which enhances global search capability, local optimization accuracy, and stability. Simulation results show the advantage of integrating low-grade heat in IES with high-performance HP through multi-energy complementary mode. The planning model can coordinate multiple energy sources and provide a reference for decision-makers between risk and economy.}
}