KONG Shiting,PING Jian,XU Xiaoyuan,et al.Trusted Collaborative Scheduling for Integrated Energy Systems of Industrial Parks Considering Energy Cascade Utilization[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250921003.
KONG Shiting,PING Jian,XU Xiaoyuan,et al.Trusted Collaborative Scheduling for Integrated Energy Systems of Industrial Parks Considering Energy Cascade Utilization[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250921003.DOI:
Trusted Collaborative Scheduling for Integrated Energy Systems of Industrial Parks Considering Energy Cascade Utilization
Multiple industrial enterprises within an industrial park exhibit complementary differences in their energy consumption demand. Energy cascade utilization can improve energy utilization efficiency and the economic performance of energy consumption in the park. However
as these industrial enterprises belong to various stakeholders
traditional collaborative optimization methods for cascade utilization may fail to guarantee the fairness and credibility of optimal scheduling results
or lead to leakage of private data of industrial enterprises. Therefore
this paper proposes a trusted collaborative scheduling method for the integrated energy system of industrial parks to support cross-enterprise energy cascade utilization. First
a day-ahead collaborative scheduling model for parks with multiple-type industrial enterprises considering energy cascade utilization is established. Then
a trusted collaborative optimization method for the integrated energy systems of industrial parks is proposed based on blockchain on-chain-off-chain collaboration. At the off-chain layer
the dimensionality reduction projection method is adopted to project the subsystem of each industrial enterprise into a low-dimensional convex hull
so as to construct an equivalent scheduling model concealing the parameter information of industrial enterprises. At the on-chain layer
the collaborative scheduling scheme of industrial parks is determined based on the proof-of-solution consensus algorithm. Accordingly
the idea of “off-chain dimensionality reduction
on-chain consensus” is adopted to realize the trusted privacy-preserving collaborative scheduling of multiple industrial enterprises. Case studies show that the proposed method helps realize privacy-preserving
high-efficiency and trustworthy collaborative optimization for integrated energy systems of industrial parks.
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