Tianjin University

Xiaolong Jin

Hongjie Jia

Yunfei Mu

Xiaodan Yu

Wei Wei

Xiandong Xu

Xiaoyu Wang

Shuo Liang

A collaborative optimization method for an Electric and Heating Networks (EHN) and a building user includes: establishing a coordinated optimization scheduling framework of the EHN and a building in a park; based on the coordinated optimization scheduling framework, constructing an optimal thermal power flow scheduling model of the EHN, and constructing a building model to simulate thermal characteristics and energy consumption of the building; based on the optimal thermal power flow scheduling model and the building model, taking the lowest operation cost of EHN and the lowest heat consumption of building user as a goal, constructing a collaborative optimization model of the EHN and the building user; outputting a collaborative optimization scheme of the optimal thermal power flow scheduling of the EHN and the heat consumption of the building user through the collaborative optimization model of the EHN and the building user.

Collaborative optimization method, system, equipment and storage medium for electric and heating networks and building user

The invention pertains to optimal scheduling and trading technology for microgrid systems, specifically focusing on a real-time peer-to-peer energy trading method involving time-varying virtual energy storage. This method predicts environmental information within a specified time domain and incorporates historical transaction data into virtual energy storage modeling and real-time energy trading. During the supply and demand energy extraction phase, it quantitatively extracts supply and demand energy and the marginal cost for trading using an autonomous energy management model for prosumers. In the transaction price optimization phase, it optimizes the transaction price based on historical data to maximize prosumers' income. The distributed transaction decision optimization method, utilizing a continuous double auction, enhances transaction matching decisions to maximize prosumers' income and accommodate multi-transaction preference levels. This approach leverages the complementary potential of energy resources to balance supply and demand within the system.

Real-time peer-to-peer energy trading method considering time-varying virtual energy storage

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Tianjin, China

Xiaolong Jin