A three-stage optimization framework for unlocking demand-side flexibility in highly renewable electricity grids

被引:0
|
作者
Bagheritabar, Mahmoud [1 ,2 ]
Hakimi, Seyed Mehdi [1 ,2 ]
Derakhshan, Ghasem [1 ,2 ]
Jordehi, Ahmad Rezaee [3 ]
机构
[1] Islamic Azad Univ, Dept Elect Engn, Damavand Branch, Damavand, Iran
[2] Islamic Azad Univ, Renewable Energy Res Ctr, Damavand Branch, Damavand, Iran
[3] Islamic Azad Univ, Dept Elect Engn, Rasht Branch, Rasht, Iran
关键词
Microgrids; Energy communities; Flexibility markets; Electric vehicles; Battery storage systems;
D O I
10.1016/j.energy.2025.135158
中图分类号
O414.1 [热力学];
学科分类号
摘要
The integration of renewable resources into distribution systems has significantly increased the uncertainties associated with real-time operations, thereby necessitating more flexibility services compared to those required in traditional distribution systems. Demand-side resources have substantial potential to contribute to this flexibility, making it crucial to develop new mechanisms for harnessing this potential. This paper presents a comprehensive three-stage framework for releasing flexibility capacities within energy communities and microgrids in balancing markets, aimed at eliminating real-time imbalances between energy production and consumption. In the first stage, a risk-averse estimation mechanism is introduced, allowing for the estimation of flexible capacities within energy communities. These capacities are then communicated to the microgrids before the balancing market is initiated. At the second stage, the microgrids address the balancing needs within their area considering the flexible capacities received from the energy communities. Finally, at the third stage, surplus flexibility capacities are offered to the upstream market managed by the Distribution System Operator (DSO). This model is implemented using the GUROBI solver in GAMS on a 69-bus distribution system that includes four microgrids. The simulation results demonstrate the model's effectiveness in extracting maximum capacities from the demand side. Notably, by unlocking the flexible capacities of Thermostatically Controlled Loads (TCLs), battery storage systems, and fleets of Electric Vehicles (EVs), the model meets 79.61 % of the microgrids' required balancing capacities locally, while also reducing their daily costs by 27.74 %.
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页数:20
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