To coordinate the energy interaction and dispatch among multiple park-level integrated energy systems (IES)
this paper proposes an optimal dispatch strategy for a multi-park electricity and heat sharing IES that accounts for energy transmission losses. Firstly
a shared energy storage center is introduced to uniformly schedule the surplus electrical energy of each park
enabling cross-park allocation and efficient utilization of electricity. Secondly
the energy losses during the transmission of natural gas and heat are considered to accurately characterize the energy flow. Finally
with the objective of minimizing the total system operating cost
a dispatch model for the multi-park electricity and heat sharing IES (MPEHS-IES) is established and solved using the twin delayed deep deterministic policy gradient (TD3) algorithm. Simulation results demonstrate that the proposed strategy can fully leverage the advantages of coordinated complementarity of energy resources among parks
thereby enhancing the allocation efficiency of electricity and heat resources as well as the economic performance of system operation.
LIU S,DING K,XIA Y,et al. Optimal scheduling method of park integrated energy system based on improved particle swarm algorithm [C ] //2022 3rd International Conference on Advanced Electrical and Energy Systems(AEES).Lanzhou,China, IEEE,2022:1-6.
HU Y,YANG B,WU P,et al. Optimal planning of electric-heating integrated energy system in low-carbon park with energy storage system [J ] .Journal of Energy Storage,2024,99:113327.
WANG M,WANG R,LIU J,et al. Operation optimization for park with integrated energy system based on integrated demand response [J ] .Energy Reports,2022,8:249-259.
HUI H,BAO M,DING Y,et al. Probabilistic integrated flexible regions of multi-energy industrial parks:conceptualization and characte rization [J ] .Applied Energy,2023,349:121521.
MENG F,WANG H,XU L,et al. Optimal scheduling of integrated energy system based on multi-agent reinforcement learning [C ] //2022 China Automation Congress(CAC),Xiamen,China.IEEE,2022:1179-1184.
DAI B,WANG H,LI B,et al. Capacity model and optimal scheduling strategy of multi-microgrid based on shared energy storage [J ] .Energy,2024,306:132472.
LI C,PRASAD S,BAI Y,et al. A quasi-dynamic model and comprehensive simulation study of district heating networks considering temperature delay [J ] .Energy,2025,318:134855.
JAKUBEK D,OCLON P,NOWAK-OCLON M,et al. Mathematical modelling and model validation of the heat losses in district heating networks [J ] .Energy,2023,267:126460.
BIAN Y,XIE L,YE J,et al. Peer-to-peer energy sharing model considering multi-objective optimal allocation of shared energy storage in a multi- microgrid system [J ] .Energy,2024,288:129864.
KANG H,JUNG S,KIM H,et al. Multi-objective sizing and real-time scheduling of battery energy storage in energy-sharing community based on reinforcement learning [J ] .Renewable and Sustainable Energy Reviews,2023,185:113655.
SHUI C,ZHOU D,HAO J,et al. Mid-term energy consumption predicting model for natural gas pipeline considering the effects of operating strategy [J ] .Energy Conversion and Management,2022,274:116429.
WANG Z,ZHANG J,CHEN L,et al. Modeling of hydrate layer growth in horizontal gas-dominated pipelines with free water [J ] .Journal of Natural Gas Science and Engineering,2018,50:364-373.
LEE L,INGENHOVEN P,SAW W,et al. The effect of scale,storage capacity and thermal transmission losses on the techno-economics of supplying high-temperature industrial process heat with concentrated solar thermal energy [J ] .Solar Energy,2025,299:113849.
CERUTI A,LAMBERT J,SPLIETHOFF H. Integrating renewable energy and thermal storage in district heating networks:A design optimization approach [J ] .Energy Conversion and Management,2025,345:120323.
LEE J O,KIM Y S. Novel battery degradation cost formulation for optimal scheduling of battery energy storage systems [J ] .International Journal of Electrical Power & Energy Systems,2022,137:107795.