Journal
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 14, Issue 1, Pages 97-110Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2022.3203160
Keywords
Alternating direction method of multipliers; decentralized optimization; distributed energy systems; district heating networks; renewable energy sources
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In this article, a new model for distributed energy systems (DES) is proposed, which takes into account the delay and storage features of pipeline heat migration and heat transfer between fluids. A dispatch problem considering hybrid regulation of fluid flow rates and temperatures is established, and a decentralized gradient descent method with the Alternating Direction Method of Multipliers (ADMM) is proposed to optimize the DES in a fully decentralized manner. Case studies on two test systems validate the effectiveness of the proposed model and method in reducing renewable energy curtailment by 17.3% and 27.0% respectively.
Distributed Energy Systems(DES) interconnected with Electric Power Network(EPN) and District Heating Network(DHN) have drawn great attention recently as they promote user-side coordination of multi-energy flows. However, the difference in physical nature between electric power transmission and heat transport has brought difficulties to the modelling and decentralized optimization. In this article, a new DHN model considering delay and storage features of pipeline heat migration and heat transfer between fluids is proposed through trigonometric expansion of the decision series and the heat current method. The model comprehensively characterizes the heat transport in the system and a dispatch problem considering hybrid regulation of fluid flow rates and temperatures in DHN is then established. A primal-decomposition-based decentralized gradient descent method in accompany with Alternating Direction Method of Multipliers(ADMM) is proposed to optimize the DESs in a fully decentralized manner. Case study on two test systems validates the effectiveness of the proposed model and method to further harness the potential of DHN, which reduce renewable energy curtailment by 17.3% and 27.0% respectively.
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