Integrated energy system operation optimization considering edge computing and demand response

Yuqiang Yang; Qiming Zhao; Lei Li; Pengfei Lu

doi:10.1117/12.3024238

13 May 2024 Integrated energy system operation optimization considering edge computing and demand response

Yuqiang Yang, Qiming Zhao, Lei Li, Pengfei Lu

Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 131592E (2024) https://doi.org/10.1117/12.3024238
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China

Abstract

Driven by the dual-carbon targets, the application of integrated energy stations is becoming increasingly widespread. A core aspect of these stations is the utilization of various energy sources and storage devices to meet a variety of load demands. This study delves into the characteristics of an integrated energy microgrid, encompassing aspects such as energy storage properties, time-of-use electricity pricing, and electric-thermal load. Under the premise of fully considering demand response, we construct a dual-layer operation optimization model, implemented via edge computing technology. An integrated energy station equipped with a combined heat and power system, an electric boiler, a fuel cell, and electricity and heat storage systems is used as a simulation example to study the response models of different electricity and thermal energy demands. We analyze and compare four different application scenarios, and perform simulation calculations of the economic benefits of the model. The research results reveal the superiority and effectiveness of the demand response model based on edge computing in achieving real-time demand response. This validates the feasibility and rationality of executing the comprehensive energy demand response on the edge side.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuqiang Yang, Qiming Zhao, Lei Li, and Pengfei Lu "Integrated energy system operation optimization considering edge computing and demand response", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 131592E (13 May 2024); https://doi.org/10.1117/12.3024238

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