期刊
ENERGY REPORTS
卷 9, 期 -, 页码 2839-2851出版社
ELSEVIER
DOI: 10.1016/j.egyr.2023.01.115
关键词
Wholesale and retail markets; Energy hub; DisCo; Two -level optimization; Energy management; Flexibility
This paper proposes the formulation of energy markets in wholesale and retail models for different energy networks, including electric, gas, and thermal networks. A two-layer energy management system is presented, considering the coordination of resources and ALs with operator of EHs in the first layer, and the coordination of EHs operator with ENOs in the second layer. The proposed design involves private distribution companies participating in the wholesale market and buying energy, sharing it in the retail market between consumers and EHs connected to themselves. This design is expressed as a two-level optimization problem, aiming to minimize the expected energy cost and losses of the networks.
In this paper, the formulation of the energy market in two wholesale and retail models for different energy networks such as electric, gas and thermal networks in the presence of energy hubs according to the two-layer energy management system is presented. In the first layer of EMS, the coordination of resources and ALs with the operator of EHs is considered, and in the second layer of EMS, the coordination of the operator of EHs with ENOs is considered. In the proposed design, the mentioned networks have participated in the wholesale market as private distribution companies or DisCo and then buy energy from it. These companies have shared the purchased energy in the retail energy market environment between consumers and EHs connected to itself. This design is expressed in the form of two-level optimization, the upper level of which is the minimization of the expected energy cost of ENs in the mentioned markets, and the other level is the minimization of the expected energy losses of ENs in the retail market. In the following, the Karush-Kuhn-Tucker (KKT) method and Pareto optimization technique based on epsilon constraint method were used to derive the single-level and single-objective problem. Then, the unscented transformation (UT) method was used to model the uncertainties of load, energy price, renewable power and EV energy demand. Finally, based on the numerical results, it was observed that the proposed plan achieves the highest profit for EHs in proportion to the time-varying energy price. Also, with the optimal energy management of EHs, it has been able to reduce the energy cost of ENs by about 12% compared to load flow studies.(c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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