Modeling Local Energy Markets Transactions for Multi-Energy Systems in Low-Voltage Unbalanced Distribution Networks

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2023
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Institute of Electrical and Electronics Engineers Inc.
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Local energy markets (LEMs) for multi-energy systems have emerged as promising solutions to facilitate energy sharing within local communities, potentially reducing energy costs, promoting renewable energy generation, and increasing energy efficiency. In this regard, analyzing the energy traded among users in local communities is crucial, as well as the characteristics of the electrical network where they are connected. In the residential sector, the low-voltage (LV) distribution network plays a vital role due to its unbalanced nature, where loads and distributed energy resources are unevenly distributed per phase, leading to conditions such as single-phase generators serving users with three-phase connections. Thus, to accurately model user transactions and capture the interaction between buyers and sellers on the LV network, this article proposes a deterministic mixed-integer second-order cone programming model for LEMs in an unbalanced active distribution network, considering both electricity and gas as energy vectors. The unbalanced model is compared with the balanced single-phase formulation using a modified version of a real LV feeder, showing that balanced models could overestimate the energy traded in LEM and have a more stable voltage pattern, which could underestimate the real voltage limits and affect the network safety.
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Publisher Copyright: © 2023 IEEE.
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Garcia-Munoz , F , Borray , A F C & Gonzalez-Garrido , A 2023 , Modeling Local Energy Markets Transactions for Multi-Energy Systems in Low-Voltage Unbalanced Distribution Networks . in Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023 . Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023 , Institute of Electrical and Electronics Engineers Inc. , 9th IEEE International Smart Cities Conference, ISC2 2023 , Bucharest , Romania , 24/09/23 . https://doi.org/10.1109/ISC257844.2023.10293331
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