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Joint energy and flexiramp market equilibrium model for regional‐integrated electricity‐heat systems considering flexibility exploitation of district heating networks
Author(s) -
Wang Xuechun,
Chen Hongkun,
Chen Lei,
Wu Jun,
Ding Tong
Publication year - 2022
Publication title -
energy science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 29
ISSN - 2050-0505
DOI - 10.1002/ese3.1026
Subject(s) - flexibility (engineering) , renewable energy , bidding , computer science , mathematical optimization , energy supply , electricity market , electricity , economics , energy (signal processing) , microeconomics , engineering , statistics , mathematics , management , electrical engineering
The increasing penetration of renewable energy resources into regional‐integrated energy systems (RIES) holds higher standards on operational flexibility. To alleviate the negative effects of insufficient operational flexibility, this paper proposes a joint market equilibrium model to obtain flexible resources in microgrids (MGs) and district heating networks (DHNs) through economic incentives. Based on the incorporation of the flexiramp (FRP) into the energy markets, a joint market mechanism is first established. Through multi‐energy synergy, the FRP provisions on the supply and demand sides in MGs are then introduced. Considering the flexibility exploitation of DHNs, a collaborative FRP supply method is developed to formulate the optimal bidding strategy for MGs. Moreover, a hierarchical model is designed to achieve joint market equilibrium, where MGs strategically bid in the external layer and the RIES operator optimally clears the market in the internal layer. The combined utilization of the Q‐learning algorithm and path‐tracking interior point method is applied to solve the hierarchical model efficiently. The performance of the proposed approach is verified by case studies. The results demonstrate the efficacy of the proposed approach for operational flexibility improvement through minimizing renewable energy curtailment, the overall cost, and the average energy prices.

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