TY - JOUR
T1 - A model-free optimal operation strategy of diversified demands-park integrated energy system considering energy cascade utilization
AU - Li, Peng
AU - Jiang, Lei
AU - Wang, Jiahao
AU - Yao, Liangzhong
AU - Li, Yuwei
AU - Wang, Zixuan
N1 - Publisher Copyright:
© 2023 The Author(s)
PY - 2024/1
Y1 - 2024/1
N2 - In order to improve the energy efficiency of park integrated energy system, this work proposes a model-free optimal operation strategy of diversified demands-park integrated energy system considering energy cascade utilization. First, by considering diversified demands of various users for energy, an energy cascade utilization mode and its corresponding multi-dimensional energy supply and demand balance equation is developed. Moreover, in view of the above structure, a model-free DD-PIES optimal operation strategy is further proposed. Among them, the model-free approach is realized on the basis of the interaction between agent and environment, combined with sufficient exploration and consequences learning of its behavior through experience. Compared to the previous works, this proposed strategy has good self-learning ability for multiple uncertainties of renewable energy and energy demand, and cuts down on inefficient exploration during the training process, while guarantee the security during the execution of actions by the agent. Finally, the rationality and validity of the proposed strategy in reducing operating cost and improving energy efficiency of the system are verified by a case study.
AB - In order to improve the energy efficiency of park integrated energy system, this work proposes a model-free optimal operation strategy of diversified demands-park integrated energy system considering energy cascade utilization. First, by considering diversified demands of various users for energy, an energy cascade utilization mode and its corresponding multi-dimensional energy supply and demand balance equation is developed. Moreover, in view of the above structure, a model-free DD-PIES optimal operation strategy is further proposed. Among them, the model-free approach is realized on the basis of the interaction between agent and environment, combined with sufficient exploration and consequences learning of its behavior through experience. Compared to the previous works, this proposed strategy has good self-learning ability for multiple uncertainties of renewable energy and energy demand, and cuts down on inefficient exploration during the training process, while guarantee the security during the execution of actions by the agent. Finally, the rationality and validity of the proposed strategy in reducing operating cost and improving energy efficiency of the system are verified by a case study.
KW - Diversified demands-park integrated energy system
KW - Energy cascade utilization
KW - Energy efficiency
KW - Improved soft actor-critic
KW - Model-free
UR - http://www.scopus.com/inward/record.url?scp=85172676654&partnerID=8YFLogxK
U2 - 10.1016/j.ijepes.2023.109518
DO - 10.1016/j.ijepes.2023.109518
M3 - Article
AN - SCOPUS:85172676654
SN - 0142-0615
VL - 155
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
M1 - 109518
ER -